OpenAI’s new study mode for ChatGPT throws questions back at students, but the learning feature doesn’t address generative AI’s underlying disruption of education.

Last year, [Deep Tronix] wished to teach colors to his nephew. Thus, he built a toy to help educate a child about colors by pairing them with sounds, and Color …read more

IntroductionHello! My name is Denys. I was born and raised in Nigeria, where I'm currently based. I began my journey into 3D art in March 2022, teaching myself through online resources, starting, of course, with the iconic donut tutorial on YouTube. Since then, I've continued to grow my skills independently, and now I'm working toward a career in 3D generalism, with a particular interest in environment art.I originally got into Blender because SketchUp wasn't free, and I could not keep up with the subscriptions. While searching for alternatives, I came across Blender. That's when I realized I had installed it once years ago, but back then, the interface completely intimidated me, and I gave up on it. This time, though, I decided to stick with it – and I'm glad I did.I started out creating simple models. One of my first big projects was modeling the entire SpongeBob crew. That led to my first animation, and eventually, the first four episodes of a short animated series (though it's still incomplete). As I grew more confident, I began participating in online 3D competitions, like cgandwe, where I focused on designing realistic environments. Those experiences have played a huge role in getting me to where I am today.Getting Started Before starting any scene, I always look for references. It might not be the most original approach, but it's what works best for me. One piece that inspired me was a beautiful artwork by Calder Moore. I bookmarked it as soon as I saw it back in 2023, and luckily, I finally found the time to bring it to life last month.BlockoutThe goal was to match the original camera angle and roughly model the main frame of the structures. It wasn't perfect, but modeling and placing the lower docks helped me get the perspective right. Then I moved on to modeling and positioning the major structures in the scene.I gave myself two weeks to complete this project. And as much as I enjoy modeling, I also enjoy not modeling, so I turned to asset kits and free models to help speed things up. I came across an awesome paid kit by Bigmediumsmall and instantly knew it would fit perfectly into my scene.I also downloaded a few models from Sketchfab, including a lamp, desk console, freighter controls, and a robotic arm, which I later took apart to add extra detail. Another incredibly helpful tool was the Random Flow add-on by BlenderGuppy, which made adding sci-fi elements much easier. Lastly, I pulled in some models from my older sci-fi and cyberpunk projects to round things out.Kitbashing Once I had the overall shape I was aiming for, I moved on to kitbashing to pack in as much detail as possible. There wasn't any strict method to the madness; I simply picked assets I liked, whether it was a set of pipes, vents, or even a random shape that just worked in the sci-fi context. I focused first on kitbashing the front structure, and used the Random Flow add-on to fill in areas where I didn't kitbash manually. Then I moved on to the other collections, following the same process.The freighter was the final piece of the puzzle, and I knew it was going to be a challenge. Part of me wanted to model it entirely from scratch, but the more practical side knew I could save a lot of time by sticking with my usual method. So I modeled the main shapes myself, then kitbashed the details to bring it to life. I also grabbed some crates from Sketchfab to fill out the scene.Texturing This part was easily my favorite, and there was no shortcut here. I had to meticulously create each material myself. Well, I did use PBR materials downloaded from CGAmbient as a base, but I spent a lot of time tweaking and editing them to get everything just right.Texturing has always been my favorite stage when building scenes like this. Many artists prefer external tools like Substance 3D Painter (which I did use for some of the models), but I've learned so much about procedural texturing, especially from RyanKingArt, that I couldn't let it go. It's such a flexible and rewarding approach, and I love pushing it as far as I can.I wanted most of the colors in the scene to be dark, but I did keep the original color of the pipes and the pillars, just to add a little bit of vibrance to the scene. I also wanted the overall texture to be very rough and grungy. One of the biggest helps in achieving this was using the Grunge Maps from Substance 3D Painter. I found a way to extract them into Blender, and it helped.A major tool during the texturing phase was Jsplacement, which I used to procedurally generate sci-fi grids and plates. This was the icing on the cake for adding intricate details. Whenever an area felt too flat, I applied bump maps with these grids and panels to bring the materials to life. For example, both the lamp pole and the entire black metal material feature these Jsplacement Maps.Lighting For this, I didn't do anything fancy. I knew the scene was in a high altitude, so I looked for HDRI with a cloudless sky, and I boosted the saturation up a little to give it that high altitude look.Post-Production The rendering phase was challenging since I was working on a low-end laptop. I couldn't render the entire scene all at once, so I broke it down by collections and rendered them as separate layers. Then, I composited the layers together in post-production. I'm not big on heavy post-work, so I kept it simple, mostly tweaking brightness and saturation on my phone. That's about it for the post-production process.Conclusion The entire project took me 10 days to complete, working at least four hours each day. Although I've expressed my love for texturing, my favorite part of this project was the detailing and kitbashing. I really enjoyed piecing all the small details together. The most challenging part was deciding which assets to use and where to place them. I had a lot of greebles to choose from, but I'm happy with the ones I selected; they felt like a perfect fit for the scene.I know kitbashing sometimes gets a negative reputation in the 3D community, but I found it incredibly relieving. Honestly, this project wouldn't have come together without it, so I fully embraced the process.I'm excited to keep making projects like this. The world of 3D art is truly an endless and vast realm, and I encourage every artist like me to keep exploring it, one project at a time.Denys Molokwu, 3D Artist

Posted on : June 13, 2025 By Tech World Times Uncategorized  Rate this post Sorting is important in programming. It helps organize data. Sorting improves performance in searching, analysis, and reporting. There are many sorting algorithms. One of the simplest is Insertion Sort. In this article, we will learn how to implement Insertion Sort in Java. We will explain each step in simple words. You will see examples and understand how it works. What Is Insertion Sort? Insertion Sort is a simple sorting algorithm. It works like how you sort playing cards. You take one card at a time and place it in the right position. It compares the current element with those before it. If needed, it shifts elements to the right. Then, it inserts the current element at the correct place. How Insertion Sort Works Let’s understand with a small list: Example List: [8, 3, 5, 1] Steps: First element (8) is already sorted. Compare 3 with 8. Move 8 right. Insert 3 before it → [3, 8, 5, 1] Compare 5 with 8. Move 8 right. Insert 5 after 3 → [3, 5, 8, 1] Compare 1 with 8, 5, 3. Move them right. Insert 1 at start → [1, 3, 5, 8] Now the list is sorted! Why Use Insertion Sort? Insertion Sort is simple and easy to code. It works well for: Small datasets Nearly sorted lists Educational purposes and practice However, it is not good for large datasets. It has a time complexity of O(n²). Time Complexity of Insertion Sort Best Case (already sorted): O(n) Average Case: O(n²) Worst Case (reversed list): O(n²) It performs fewer steps in nearly sorted data. How to Implement Insertion Sort in Java Now let’s write the code for Insertion Sort in Java. We will explain each part. Step 1: Define a Class javaCopyEditpublic class InsertionSortExample { // Code goes here } We create a class named InsertionSortExample. Step 2: Create the Sorting Method javaCopyEditpublic static void insertionSort(int[] arr) { int n = arr.length; for (int i = 1; i < n; i++) { int key = arr[i]; int j = i - 1; while (j >= 0 && arr[j] > key) { arr[j + 1] = arr[j]; j = j - 1; } arr[j + 1] = key; } } Let’s break it down: arr[i] is the current value (called key). j starts from the previous index. While arr[j] > key, shift arr[j] to the right. Insert the key at the correct position. This logic sorts the array step by step. Step 3: Create the Main Method Now we test the code. javaCopyEditpublic static void main(String[] args) { int[] numbers = {9, 5, 1, 4, 3}; System.out.println("Before sorting:"); printArray(numbers); insertionSort(numbers); System.out.println("After sorting:"); printArray(numbers); } This method: Creates an array of numbers Prints the array before sorting Calls the sort method Prints the array after sorting Step 4: Print the Array Let’s add a helper method to print the array. javaCopyEditpublic static void printArray(int[] arr) { for (int number : arr) { System.out.print(number + " "); } System.out.println(); } Now you can see how the array changes before and after sorting. Full Code Example javaCopyEditpublic class InsertionSortExample { public static void insertionSort(int[] arr) { int n = arr.length; for (int i = 1; i < n; i++) { int key = arr[i]; int j = i - 1; while (j >= 0 && arr[j] > key) { arr[j + 1] = arr[j]; j = j - 1; } arr[j + 1] = key; } } public static void printArray(int[] arr) { for (int number : arr) { System.out.print(number + " "); } System.out.println(); } public static void main(String[] args) { int[] numbers = {9, 5, 1, 4, 3}; System.out.println("Before sorting:"); printArray(numbers); insertionSort(numbers); System.out.println("After sorting:"); printArray(numbers); } } Sample Output yamlCopyEditBefore sorting: 9 5 1 4 3 After sorting: 1 3 4 5 9 This confirms that the sorting works correctly. Advantages of Insertion Sort in Java Easy to implement Works well with small inputs Stable sort (keeps equal items in order) Good for educational use When Not to Use Insertion Sort Avoid Insertion Sort when: The dataset is large Performance is critical Better algorithms like Merge Sort or Quick Sort are available Real-World Uses Sorting small records in a database Teaching algorithm basics Handling partially sorted arrays Even though it is not the fastest, it is useful in many simple tasks. Final Tips Practice with different inputs Add print statements to see how it works Try sorting strings or objects Use Java’s built-in sort methods for large arrays Conclusion Insertion Sort in Java is a great way to learn sorting. It is simple and easy to understand. In this guide, we showed how to implement it step-by-step. We covered the logic, code, and output. We also explained when to use it. Now you can try it yourself. Understanding sorting helps in coding interviews and software development. Keep practicing and exploring other sorting methods too. The more you practice, the better you understand algorithms. Tech World TimesTech World Times (TWT), a global collective focusing on the latest tech news and trends in blockchain, Fintech, Development & Testing, AI and Startups. If you are looking for the guest post then contact at techworldtimes@gmail.com

Germany and NVIDIA are building possibly the most ambitious European tech project of the decade: the continent’s first industrial AI cloud.NVIDIA has been on a European tour over the past month with CEO Jensen Huang charming audiences at London Tech Week before dazzling the crowds at Paris’s VivaTech. But it was his meeting with German Chancellor Friedrich Merz that might prove the most consequential stop.The resulting partnership between NVIDIA and Deutsche Telekom isn’t just another corporate handshake; it’s potentially a turning point for European technological sovereignty.An “AI factory” (as they’re calling it) will be created with a focus on manufacturing, which is hardly surprising given Germany’s renowned industrial heritage. The facility aims to give European industrial players the computational firepower to revolutionise everything from design to robotics.“In the era of AI, every manufacturer needs two factories: one for making things, and one for creating the intelligence that powers them,” said Huang. “By building Europe’s first industrial AI infrastructure, we’re enabling the region’s leading industrial companies to advance simulation-first, AI-driven manufacturing.”It’s rare to hear such urgency from a telecoms CEO, but Deutsche Telekom’s Timotheus Höttges added: “Europe’s technological future needs a sprint, not a stroll. We must seize the opportunities of artificial intelligence now, revolutionise our industry, and secure a leading position in the global technology competition. Our economic success depends on quick decisions and collaborative innovations.”The first phase alone will deploy 10,000 NVIDIA Blackwell GPUs spread across various high-performance systems. That makes this Germany’s largest AI deployment ever; a statement the country isn’t content to watch from the sidelines as AI transforms global industry.A Deloitte study recently highlighted the critical importance of AI technology development to Germany’s future competitiveness, particularly noting the need for expanded data centre capacity. When you consider that demand is expected to triple within just five years, this investment seems less like ambition and more like necessity.Robots teaching robotsOne of the early adopters is NEURA Robotics, a German firm that specialises in cognitive robotics. They’re using this computational muscle to power something called the Neuraverse which is essentially a connected network where robots can learn from each other.Think of it as a robotic hive mind for skills ranging from precision welding to household ironing, with each machine contributing its learnings to a collective intelligence.“Physical AI is the electricity of the future—it will power every machine on the planet,” said David Reger, Founder and CEO of NEURA Robotics. “Through this initiative, we’re helping build the sovereign infrastructure Europe needs to lead in intelligent robotics and stay in control of its future.”The implications of this AI project for manufacturing in Germany could be profound. This isn’t just about making existing factories slightly more efficient; it’s about reimagining what manufacturing can be in an age of intelligent machines.AI for more than just Germany’s industrial titansWhat’s particularly promising about this project is its potential reach beyond Germany’s industrial titans. The famed Mittelstand – the network of specialised small and medium-sized businesses that forms the backbone of the German economy – stands to benefit.These companies often lack the resources to build their own AI infrastructure but possess the specialised knowledge that makes them perfect candidates for AI-enhanced innovation. Democratising access to cutting-edge AI could help preserve their competitive edge in a challenging global market.Academic and research institutions will also gain access, potentially accelerating innovation across numerous fields. The approximately 900 Germany-based startups in NVIDIA’s Inception program will be eligible to use these resources, potentially unleashing a wave of entrepreneurial AI applications.However impressive this massive project is, it’s viewed merely as a stepping stone towards something even more ambitious: Europe’s AI gigafactory. This planned 100,000 GPU-powered initiative backed by the EU and Germany won’t come online until 2027, but it represents Europe’s determination to carve out its own technological future.As other European telecom providers follow suit with their own AI infrastructure projects, we may be witnessing the beginning of a concerted effort to establish technological sovereignty across the continent.For a region that has often found itself caught between American tech dominance and Chinese ambitions, building indigenous AI capability represents more than economic opportunity. Whether this bold project in Germany will succeed remains to be seen, but one thing is clear: Europe is no longer content to be a passive consumer of AI technology developed elsewhere.(Photo by Maheshkumar Painam)Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.Explore other upcoming enterprise technology events and webinars powered by TechForge here.

Transcript [MUSIC]      [BOOK PASSAGE]   PETER LEE: “In ‘The Little Black Bag,’ a classic science fiction story, a high-tech doctor’s kit of the future is accidentally transported back to the 1950s, into the shaky hands of a washed-up, alcoholic doctor. The ultimate medical tool, it redeems the doctor wielding it, allowing him to practice gratifyingly heroic medicine. … The tale ends badly for the doctor and his treacherous assistant, but it offered a picture of how advanced technology could transform medicine—powerful when it was written nearly 75 years ago and still so today. What would be the Al equivalent of that little black bag? At this moment when new capabilities are emerging, how do we imagine them into medicine?”   [END OF BOOK PASSAGE]     [THEME MUSIC]     This is The AI Revolution in Medicine, Revisited. I’m your host, Peter Lee.    Shortly after OpenAI’s GPT-4 was publicly released, Carey Goldberg, Dr. Zak Kohane, and I published The AI Revolution in Medicine to help educate the world of healthcare and medical research about the transformative impact this new generative AI technology could have. But because we wrote the book when GPT-4 was still a secret, we had to speculate. Now, two years later, what did we get right, and what did we get wrong?     In this series, we’ll talk to clinicians, patients, hospital administrators, and others to understand the reality of AI in the field and where we go from here.   [THEME MUSIC FADES] The book passage I read at the top is from “Chapter 10: The Big Black Bag.”  In imagining AI in medicine, Carey, Zak, and I included in our book two fictional accounts. In the first, a medical resident consults GPT-4 on her personal phone as the patient in front of her crashes. Within seconds, it offers an alternate response based on recent literature. In the second account, a 90-year-old woman with several chronic conditions is living independently and receiving near-constant medical support from an AI aide.    In our conversations with the guests we’ve spoken to so far, we’ve caught a glimpse of these predicted futures, seeing how clinicians and patients are actually using AI today and how developers are leveraging the technology in the healthcare products and services they’re creating. In fact, that first fictional account isn’t so fictional after all, as most of the doctors in the real world actually appear to be using AI at least occasionally—and sometimes much more than occasionally—to help in their daily clinical work. And as for the second fictional account, which is more of a science fiction account, it seems we are indeed on the verge of a new way of delivering and receiving healthcare, though the future is still very much open.  As we continue to examine the current state of AI in healthcare and its potential to transform the field, I’m pleased to welcome Bill Gates and Sébastien Bubeck.   Bill may be best known as the co-founder of Microsoft, having created the company with his childhood friend Paul Allen in 1975. He’s now the founder of Breakthrough Energy, which aims to advance clean energy innovation, and TerraPower, a company developing groundbreaking nuclear energy and science technologies. He also chairs the world’s largest philanthropic organization, the Gates Foundation, and focuses on solving a variety of health challenges around the globe and here at home.  Sébastien is a research lead at OpenAI. He was previously a distinguished scientist, vice president of AI, and a colleague of mine here at Microsoft, where his work included spearheading the development of the family of small language models known as Phi. While at Microsoft, he also coauthored the discussion-provoking 2023 paper “Sparks of Artificial General Intelligence,” which presented the results of early experiments with GPT-4 conducted by a small team from Microsoft Research.    [TRANSITION MUSIC]   Here’s my conversation with Bill Gates and Sébastien Bubeck.  LEE: Bill, welcome.  BILL GATES: Thank you.  LEE: Seb …  SÉBASTIEN BUBECK: Yeah. Hi, hi, Peter. Nice to be here.  LEE: You know, one of the things that I’ve been doing just to get the conversation warmed up is to talk about origin stories, and what I mean about origin stories is, you know, what was the first contact that you had with large language models or the concept of generative AI that convinced you or made you think that something really important was happening?  And so, Bill, I think I’ve heard the story about, you know, the time when the OpenAI folks—Sam Altman, Greg Brockman, and others—showed you something, but could we hear from you what those early encounters were like and what was going through your mind?   GATES: Well, I’d been visiting OpenAI soon after it was created to see things like GPT-2 and to see the little arm they had that was trying to match human manipulation and, you know, looking at their games like Dota that they were trying to get as good as human play. And honestly, I didn’t think the language model stuff they were doing, even when they got to GPT-3, would show the ability to learn, you know, in the same sense that a human reads a biology book and is able to take that knowledge and access it not only to pass a test but also to create new medicines.  And so my challenge to them was that if their LLM could get a five on the advanced placement biology test, then I would say, OK, it took biologic knowledge and encoded it in an accessible way and that I didn’t expect them to do that very quickly but it would be profound.   And it was only about six months after I challenged them to do that, that an early version of GPT-4 they brought up to a dinner at my house, and in fact, it answered most of the questions that night very well. The one it got totally wrong, we were … because it was so good, we kept thinking, Oh, we must be wrong. It turned out it was a math weakness [LAUGHTER] that, you know, we later understood that that was an area of, weirdly, of incredible weakness of those early models. But, you know, that was when I realized, OK, the age of cheap intelligence was at its beginning.  LEE: Yeah. So I guess it seems like you had something similar to me in that my first encounters, I actually harbored some skepticism. Is it fair to say you were skeptical before that?  GATES: Well, the idea that we’ve figured out how to encode and access knowledge in this very deep sense without even understanding the nature of the encoding, …  LEE: Right.   GATES: … that is a bit weird.   LEE: Yeah.  GATES: We have an algorithm that creates the computation, but even say, OK, where is the president’s birthday stored in there? Where is this fact stored in there? The fact that even now when we’re playing around, getting a little bit more sense of it, it’s opaque to us what the semantic encoding is, it’s, kind of, amazing to me. I thought the invention of knowledge storage would be an explicit way of encoding knowledge, not an implicit statistical training.  LEE: Yeah, yeah. All right. So, Seb, you know, on this same topic, you know, I got—as we say at Microsoft—I got pulled into the tent. [LAUGHS]  BUBECK: Yes.   LEE: Because this was a very secret project. And then, um, I had the opportunity to select a small number of researchers in MSR [Microsoft Research] to join and start investigating this thing seriously. And the first person I pulled in was you.  BUBECK: Yeah.  LEE: And so what were your first encounters? Because I actually don’t remember what happened then.  BUBECK: Oh, I remember it very well. [LAUGHS] My first encounter with GPT-4 was in a meeting with the two of you, actually. But my kind of first contact, the first moment where I realized that something was happening with generative AI, was before that. And I agree with Bill that I also wasn’t too impressed by GPT-3.  I though that it was kind of, you know, very naturally mimicking the web, sort of parroting what was written there in a nice way. Still in a way which seemed very impressive. But it wasn’t really intelligent in any way. But shortly after GPT-3, there was a model before GPT-4 that really shocked me, and this was the first image generation model, DALL-E 1.  So that was in 2021. And I will forever remember the press release of OpenAI where they had this prompt of an avocado chair and then you had this image of the avocado chair. [LAUGHTER] And what really shocked me is that clearly the model kind of “understood” what is a chair, what is an avocado, and was able to merge those concepts.  So this was really, to me, the first moment where I saw some understanding in those models.   LEE: So this was, just to get the timing right, that was before I pulled you into the tent.  BUBECK: That was before. That was like a year before.  LEE: Right.   BUBECK: And now I will tell you how, you know, we went from that moment to the meeting with the two of you and GPT-4.  So once I saw this kind of understanding, I thought, OK, fine. It understands concept, but it’s still not able to reason. It cannot—as, you know, Bill was saying—it cannot learn from your document. It cannot reason.   So I set out to try to prove that. You know, this is what I was in the business of at the time, trying to prove things in mathematics. So I was trying to prove that basically autoregressive transformers could never reason. So I was trying to prove this. And after a year of work, I had something reasonable to show. And so I had the meeting with the two of you, and I had this example where I wanted to say, there is no way that an LLM is going to be able to do x.  And then as soon as I … I don’t know if you remember, Bill. But as soon as I said that, you said, oh, but wait a second. I had, you know, the OpenAI crew at my house recently, and they showed me a new model. Why don’t we ask this new model this question?   LEE: Yeah. BUBECK: And we did, and it solved it on the spot. And that really, honestly, just changed my life. Like, you know, I had been working for a year trying to say that this was impossible. And just right there, it was shown to be possible.   LEE: [LAUGHS] One of the very first things I got interested in—because I was really thinking a lot about healthcare—was healthcare and medicine.  And I don’t know if the two of you remember, but I ended up doing a lot of tests. I ran through, you know, step one and step two of the US Medical Licensing Exam. Did a whole bunch of other things. I wrote this big report. It was, you know, I can’t remember … a couple hundred pages.   And I needed to share this with someone. I didn’t … there weren’t too many people I could share it with. So I sent, I think, a copy to you, Bill. Sent a copy to you, Seb.   I hardly slept for about a week putting that report together. And, yeah, and I kept working on it. But I was far from alone. I think everyone who was in the tent, so to speak, in those early days was going through something pretty similar. All right. So I think … of course, a lot of what I put in the report also ended up being examples that made it into the book.  But the main purpose of this conversation isn’t to reminisce about [LAUGHS] or indulge in those reminiscences but to talk about what’s happening in healthcare and medicine. And, you know, as I said, we wrote this book. We did it very, very quickly. Seb, you helped. Bill, you know, you provided a review and some endorsements.  But, you know, honestly, we didn’t know what we were talking about because no one had access to this thing. And so we just made a bunch of guesses. So really, the whole thing I wanted to probe with the two of you is, now with two years of experience out in the world, what, you know, what do we think is happening today?  You know, is AI actually having an impact, positive or negative, on healthcare and medicine? And what do we now think is going to happen in the next two years, five years, or 10 years? And so I realize it’s a little bit too abstract to just ask it that way. So let me just try to narrow the discussion and guide us a little bit.   Um, the kind of administrative and clerical work, paperwork, around healthcare—and we made a lot of guesses about that—that appears to be going well, but, you know, Bill, I know we’ve discussed that sometimes that you think there ought to be a lot more going on. Do you have a viewpoint on how AI is actually finding its way into reducing paperwork?  GATES: Well, I’m stunned … I don’t think there should be a patient-doctor meeting where the AI is not sitting in and both transcribing, offering to help with the paperwork, and even making suggestions, although the doctor will be the one, you know, who makes the final decision about the diagnosis and whatever prescription gets done.   It’s so helpful. You know, when that patient goes home and their, you know, son who wants to understand what happened has some questions, that AI should be available to continue that conversation. And the way you can improve that experience and streamline things and, you know, involve the people who advise you. I don’t understand why that’s not more adopted, because there you still have the human in the loop making that final decision.  But even for, like, follow-up calls to make sure the patient did things, to understand if they have concerns and knowing when to escalate back to the doctor, the benefit is incredible. And, you know, that thing is ready for prime time. That paradigm is ready for prime time, in my view.  LEE: Yeah, there are some good products, but it seems like the number one use right now—and we kind of got this from some of the previous guests in previous episodes—is the use of AI just to respond to emails from patients. [LAUGHTER] Does that make sense to you?  BUBECK: Yeah. So maybe I want to second what Bill was saying but maybe take a step back first. You know, two years ago, like, the concept of clinical scribes, which is one of the things that we’re talking about right now, it would have sounded, in fact, it sounded two years ago, borderline dangerous. Because everybody was worried about hallucinations. What happened if you have this AI listening in and then it transcribes, you know, something wrong?  Now, two years later, I think it’s mostly working. And in fact, it is not yet, you know, fully adopted. You’re right. But it is in production. It is used, you know, in many, many places. So this rate of progress is astounding because it wasn’t obvious that we would be able to overcome those obstacles of hallucination. It’s not to say that hallucinations are fully solved. In the case of the closed system, they are.   Now, I think more generally what’s going on in the background is that there is something that we, that certainly I, underestimated, which is this management overhead. So I think the reason why this is not adopted everywhere is really a training and teaching aspect. People need to be taught, like, those systems, how to interact with them.  And one example that I really like, a study that recently appeared where they tried to use ChatGPT for diagnosis and they were comparing doctors without and with ChatGPT (opens in new tab). And the amazing thing … so this was a set of cases where the accuracy of the doctors alone was around 75%. ChatGPT alone was 90%. So that’s already kind of mind blowing. But then the kicker is that doctors with ChatGPT was 80%.   Intelligence alone is not enough. It’s also how it’s presented, how you interact with it. And ChatGPT, it’s an amazing tool. Obviously, I absolutely love it. But it’s not … you don’t want a doctor to have to type in, you know, prompts and use it that way.  It should be, as Bill was saying, kind of running continuously in the background, sending you notifications. And you have to be really careful of the rate at which those notifications are being sent. Because if they are too frequent, then the doctor will learn to ignore them. So you have to … all of those things matter, in fact, at least as much as the level of intelligence of the machine.  LEE: One of the things I think about, Bill, in that scenario that you described, doctors do some thinking about the patient when they write the note. So, you know, I’m always a little uncertain whether it’s actually … you know, you wouldn’t necessarily want to fully automate this, I don’t think. Or at least there needs to be some prompt to the doctor to make sure that the doctor puts some thought into what happened in the encounter with the patient. Does that make sense to you at all?  GATES: At this stage, you know, I’d still put the onus on the doctor to write the conclusions and the summary and not delegate that.  The tradeoffs you make a little bit are somewhat dependent on the situation you’re in. If you’re in Africa, So, yes, the doctor’s still going to have to do a lot of work, but just the quality of letting the patient and the people around them interact and ask questions and have things explained, that alone is such a quality improvement. It’s mind blowing.   LEE: So since you mentioned, you know, Africa—and, of course, this touches on the mission and some of the priorities of the Gates Foundation and this idea of democratization of access to expert medical care—what’s the most interesting stuff going on right now? Are there people and organizations or technologies that are impressing you or that you’re tracking?  GATES: Yeah. So the Gates Foundation has given out a lot of grants to people in Africa doing education, agriculture but more healthcare examples than anything. And the way these things start off, they often start out either being patient-centric in a narrow situation, like, OK, I’m a pregnant woman; talk to me. Or, I have infectious disease symptoms; talk to me. Or they’re connected to a health worker where they’re helping that worker get their job done. And we have lots of pilots out, you know, in both of those cases.   The dream would be eventually to have the thing the patient consults be so broad that it’s like having a doctor available who understands the local things.   LEE: Right.   GATES: We’re not there yet. But over the next two or three years, you know, particularly given the worsening financial constraints against African health systems, where the withdrawal of money has been dramatic, you know, figuring out how to take this—what I sometimes call “free intelligence”—and build a quality health system around that, we will have to be more radical in low-income countries than any rich country is ever going to be.   LEE: Also, there’s maybe a different regulatory environment, so some of those things maybe are easier? Because right now, I think the world hasn’t figured out how to and whether to regulate, let’s say, an AI that might give a medical diagnosis or write a prescription for a medication.  BUBECK: Yeah. I think one issue with this, and it’s also slowing down the deployment of AI in healthcare more generally, is a lack of proper benchmark. Because, you know, you were mentioning the USMLE [United States Medical Licensing Examination], for example. That’s a great test to test human beings and their knowledge of healthcare and medicine. But it’s not a great test to give to an AI.  It’s not asking the right questions. So finding what are the right questions to test whether an AI system is ready to give diagnosis in a constrained setting, that’s a very, very important direction, which to my surprise, is not yet accelerating at the rate that I was hoping for.  LEE: OK, so that gives me an excuse to get more now into the core AI tech because something I’ve discussed with both of you is this issue of what are the right tests. And you both know the very first test I give to any new spin of an LLM is I present a patient, the results—a mythical patient—the results of my physical exam, my mythical physical exam. Maybe some results of some initial labs. And then I present or propose a differential diagnosis. And if you’re not in medicine, a differential diagnosis you can just think of as a prioritized list of the possible diagnoses that fit with all that data. And in that proposed differential, I always intentionally make two mistakes.  I make a textbook technical error in one of the possible elements of the differential diagnosis, and I have an error of omission. And, you know, I just want to know, does the LLM understand what I’m talking about? And all the good ones out there do now. But then I want to know, can it spot the errors? And then most importantly, is it willing to tell me I’m wrong, that I’ve made a mistake?   That last piece seems really hard for AI today. And so let me ask you first, Seb, because at the time of this taping, of course, there was a new spin of GPT-4o last week that became overly sycophantic. In other words, it was actually prone in that test of mine not only to not tell me I’m wrong, but it actually praised me for the creativity of my differential. [LAUGHTER] What’s up with that?  BUBECK: Yeah, I guess it’s a testament to the fact that training those models is still more of an art than a science. So it’s a difficult job. Just to be clear with the audience, we have rolled back that [LAUGHS] version of GPT-4o, so now we don’t have the sycophant version out there.  Yeah, no, it’s a really difficult question. It has to do … as you said, it’s very technical. It has to do with the post-training and how, like, where do you nudge the model? So, you know, there is this very classical by now technique called RLHF [reinforcement learning from human feedback], where you push the model in the direction of a certain reward model. So the reward model is just telling the model, you know, what behavior is good, what behavior is bad.  But this reward model is itself an LLM, and, you know, Bill was saying at the very beginning of the conversation that we don’t really understand how those LLMs deal with concepts like, you know, where is the capital of France located? Things like that. It is the same thing for this reward model. We don’t know why it says that it prefers one output to another, and whether this is correlated with some sycophancy is, you know, something that we discovered basically just now. That if you push too hard in optimization on this reward model, you will get a sycophant model.  So it’s kind of … what I’m trying to say is we became too good at what we were doing, and we ended up, in fact, in a trap of the reward model.  LEE: I mean, you do want … it’s a difficult balance because you do want models to follow your desires and …  BUBECK: It’s a very difficult, very difficult balance.  LEE: So this brings up then the following question for me, which is the extent to which we think we’ll need to have specially trained models for things. So let me start with you, Bill. Do you have a point of view on whether we will need to, you know, quote-unquote take AI models to med school? Have them specially trained? Like, if you were going to deploy something to give medical care in underserved parts of the world, do we need to do something special to create those models?  GATES: We certainly need to teach them the African languages and the unique dialects so that the multimedia interactions are very high quality. We certainly need to teach them the disease prevalence and unique disease patterns like, you know, neglected tropical diseases and malaria. So we need to gather a set of facts that somebody trying to go for a US customer base, you know, wouldn’t necessarily have that in there.  Those two things are actually very straightforward because the additional training time is small. I’d say for the next few years, we’ll also need to do reinforcement learning about the context of being a doctor and how important certain behaviors are. Humans learn over the course of their life to some degree that, I’m in a different context and the way I behave in terms of being willing to criticize or be nice, you know, how important is it? Who’s here? What’s my relationship to them?   Right now, these machines don’t have that broad social experience. And so if you know it’s going to be used for health things, a lot of reinforcement learning of the very best humans in that context would still be valuable. Eventually, the models will, having read all the literature of the world about good doctors, bad doctors, it’ll understand as soon as you say, “I want you to be a doctor diagnosing somebody.” All of the implicit reinforcement that fits that situation, you know, will be there. LEE: Yeah. GATES: And so I hope three years from now, we don’t have to do that reinforcement learning. But today, for any medical context, you would want a lot of data to reinforce tone, willingness to say things when, you know, there might be something significant at stake.  LEE: Yeah. So, you know, something Bill said, kind of, reminds me of another thing that I think we missed, which is, the context also … and the specialization also pertains to different, I guess, what we still call “modes,” although I don’t know if the idea of multimodal is the same as it was two years ago. But, you know, what do you make of all of the hubbub around—in fact, within Microsoft Research, this is a big deal, but I think we’re far from alone—you know, medical images and vision, video, proteins and molecules, cell, you know, cellular data and so on.  BUBECK: Yeah. OK. So there is a lot to say to everything … to the last, you know, couple of minutes. Maybe on the specialization aspect, you know, I think there is, hiding behind this, a really fundamental scientific question of whether eventually we have a singular AGI [artificial general intelligence] that kind of knows everything and you can just put, you know, explain your own context and it will just get it and understand everything.  That’s one vision. I have to say, I don’t particularly believe in this vision. In fact, we humans are not like that at all. I think, hopefully, we are general intelligences, yet we have to specialize a lot. And, you know, I did myself a lot of RL, reinforcement learning, on mathematics. Like, that’s what I did, you know, spent a lot of time doing that. And I didn’t improve on other aspects. You know, in fact, I probably degraded in other aspects. [LAUGHTER] So it’s … I think it’s an important example to have in mind.  LEE: I think I might disagree with you on that, though, because, like, doesn’t a model have to see both good science and bad science in order to be able to gain the ability to discern between the two?  BUBECK: Yeah, no, that absolutely. I think there is value in seeing the generality, in having a very broad base. But then you, kind of, specialize on verticals. And this is where also, you know, open-weights model, which we haven’t talked about yet, are really important because they allow you to provide this broad base to everyone. And then you can specialize on top of it.  LEE: So we have about three hours of stuff to talk about, but our time is actually running low. BUBECK: Yes, yes, yes.   LEE: So I think I want … there’s a more provocative question. It’s almost a silly question, but I need to ask it of the two of you, which is, is there a future, you know, where AI replaces doctors or replaces, you know, medical specialties that we have today? So what does the world look like, say, five years from now?  GATES: Well, it’s important to distinguish healthcare discovery activity from healthcare delivery activity. We focused mostly on delivery. I think it’s very much within the realm of possibility that the AI is not only accelerating healthcare discovery but substituting for a lot of the roles of, you know, I’m an organic chemist, or I run various types of assays. I can see those, which are, you know, testable-output-type jobs but with still very high value, I can see, you know, some replacement in those areas before the doctor.   The doctor, still understanding the human condition and long-term dialogues, you know, they’ve had a lifetime of reinforcement of that, particularly when you get into areas like mental health. So I wouldn’t say in five years, either people will choose to adopt it, but it will be profound that there’ll be this nearly free intelligence that can do follow-up, that can help you, you know, make sure you went through different possibilities.  And so I’d say, yes, we’ll have doctors, but I’d say healthcare will be massively transformed in its quality and in efficiency by AI in that time period.  LEE: Is there a comparison, useful comparison, say, between doctors and, say, programmers, computer programmers, or doctors and, I don’t know, lawyers?  GATES: Programming is another one that has, kind of, a mathematical correctness to it, you know, and so the objective function that you’re trying to reinforce to, as soon as you can understand the state machines, you can have something that’s “checkable”; that’s correct. So I think programming, you know, which is weird to say, that the machine will beat us at most programming tasks before we let it take over roles that have deep empathy, you know, physical presence and social understanding in them.  LEE: Yeah. By the way, you know, I fully expect in five years that AI will produce mathematical proofs that are checkable for validity, easily checkable, because they’ll be written in a proof-checking language like Lean or something but will be so complex that no human mathematician can understand them. I expect that to happen.   I can imagine in some fields, like cellular biology, we could have the same situation in the future because the molecular pathways, the chemistry, biochemistry of human cells or living cells is as complex as any mathematics, and so it seems possible that we may be in a state where in wet lab, we see, Oh yeah, this actually works, but no one can understand why.  BUBECK: Yeah, absolutely. I mean, I think I really agree with Bill’s distinction of the discovery and the delivery, and indeed, the discovery’s when you can check things, and at the end, there is an artifact that you can verify. You know, you can run the protocol in the wet lab and see [if you have] produced what you wanted. So I absolutely agree with that.   And in fact, you know, we don’t have to talk five years from now. I don’t know if you know, but just recently, there was a paper that was published on a scientific discovery using o3- mini (opens in new tab). So this is really amazing. And, you know, just very quickly, just so people know, it was about this statistical physics model, the frustrated Potts model, which has to do with coloring, and basically, the case of three colors, like, more than two colors was open for a long time, and o3 was able to reduce the case of three colors to two colors.   LEE: Yeah.  BUBECK: Which is just, like, astounding. And this is not … this is now. This is happening right now. So this is something that I personally didn’t expect it would happen so quickly, and it’s due to those reasoning models.   Now, on the delivery side, I would add something more to it for the reason why doctors and, in fact, lawyers and coders will remain for a long time, and it’s because we still don’t understand how those models generalize. Like, at the end of the day, we are not able to tell you when they are confronted with a really new, novel situation, whether they will work or not.  Nobody is able to give you that guarantee. And I think until we understand this generalization better, we’re not going to be willing to just let the system in the wild without human supervision.  LEE: But don’t human doctors, human specialists … so, for example, a cardiologist sees a patient in a certain way that a nephrologist …  BUBECK: Yeah. LEE: … or an endocrinologist might not. BUBECK: That’s right. But another cardiologist will understand and, kind of, expect a certain level of generalization from their peer. And this, we just don’t have it with AI models. Now, of course, you’re exactly right. That generalization is also hard for humans. Like, if you have a human trained for one task and you put them into another task, then you don’t … you often don’t know. LEE: OK. You know, the podcast is focused on what’s happened over the last two years. But now, I’d like one provocative prediction about what you think the world of AI and medicine is going to be at some point in the future. You pick your timeframe. I don’t care if it’s two years or 20 years from now, but, you know, what do you think will be different about AI in medicine in that future than today?  BUBECK: Yeah, I think the deployment is going to accelerate soon. Like, we’re really not missing very much. There is this enormous capability overhang. Like, even if progress completely stopped, with current systems, we can do a lot more than what we’re doing right now. So I think this will … this has to be realized, you know, sooner rather than later.  And I think it’s probably dependent on these benchmarks and proper evaluation and tying this with regulation. So these are things that take time in human society and for good reason. But now we already are at two years; you know, give it another two years and it should be really …   LEE: Will AI prescribe your medicines? Write your prescriptions?  BUBECK: I think yes. I think yes.  LEE: OK. Bill?  GATES: Well, I think the next two years, we’ll have massive pilots, and so the amount of use of the AI, still in a copilot-type mode, you know, we should get millions of patient visits, you know, both in general medicine and in the mental health side, as well. And I think that’s going to build up both the data and the confidence to give the AI some additional autonomy. You know, are you going to let it talk to you at night when you’re panicked about your mental health with some ability to escalate? And, you know, I’ve gone so far as to tell politicians with national health systems that if they deploy AI appropriately, that the quality of care, the overload of the doctors, the improvement in the economics will be enough that their voters will be stunned because they just don’t expect this, and, you know, they could be reelected [LAUGHTER] just on this one thing of fixing what is a very overloaded and economically challenged health system in these rich countries.  You know, my personal role is going to be to make sure that in the poorer countries, there isn’t some lag; in fact, in many cases, that we’ll be more aggressive because, you know, we’re comparing to having no access to doctors at all. And, you know, so I think whether it’s India or Africa, there’ll be lessons that are globally valuable because we need medical intelligence. And, you know, thank god AI is going to provide a lot of that.  LEE: Well, on that optimistic note, I think that’s a good way to end. Bill, Seb, really appreciate all of this.   I think the most fundamental prediction we made in the book is that AI would actually find its way into the practice of medicine, and I think that that at least has come true, maybe in different ways than we expected, but it’s come true, and I think it’ll only accelerate from here. So thanks again, both of you.  [TRANSITION MUSIC]  GATES: Yeah. Thanks, you guys.  BUBECK: Thank you, Peter. Thanks, Bill.  LEE: I just always feel such a sense of privilege to have a chance to interact and actually work with people like Bill and Sébastien.    With Bill, I’m always amazed at how practically minded he is. He’s really thinking about the nuts and bolts of what AI might be able to do for people, and his thoughts about underserved parts of the world, the idea that we might actually be able to empower people with access to expert medical knowledge, I think is both inspiring and amazing.   And then, Seb, Sébastien Bubeck, he’s just absolutely a brilliant mind. He has a really firm grip on the deep mathematics of artificial intelligence and brings that to bear in his research and development work. And where that mathematics takes him isn’t just into the nuts and bolts of algorithms but into philosophical questions about the nature of intelligence.   One of the things that Sébastien brought up was the state of evaluation of AI systems. And indeed, he was fairly critical in our conversation. But of course, the world of AI research and development is just moving so fast, and indeed, since we recorded our conversation, OpenAI, in fact, released a new evaluation metric that is directly relevant to medical applications, and that is something called HealthBench. And Microsoft Research also released a new evaluation approach or process called ADeLe.   HealthBench and ADeLe are examples of new approaches to evaluating AI models that are less about testing their knowledge and ability to pass multiple-choice exams and instead are evaluation approaches designed to assess how well AI models are able to complete tasks that actually arise every day in typical healthcare or biomedical research settings. These are examples of really important good work that speak to how well AI models work in the real world of healthcare and biomedical research and how well they can collaborate with human beings in those settings.  You know, I asked Bill and Seb to make some predictions about the future. You know, my own answer, I expect that we’re going to be able to use AI to change how we diagnose patients, change how we decide treatment options.   If you’re a doctor or a nurse and you encounter a patient, you’ll ask questions, do a physical exam, you know, call out for labs just like you do today, but then you’ll be able to engage with AI based on all of that data and just ask, you know, based on all the other people who have gone through the same experience, who have similar data, how were they diagnosed? How were they treated? What were their outcomes? And what does that mean for the patient I have right now? Some people call it the “patients like me” paradigm. And I think that’s going to become real because of AI within our lifetimes. That idea of really grounding the delivery in healthcare and medical practice through data and intelligence, I actually now don’t see any barriers to that future becoming real.  [THEME MUSIC]  I’d like to extend another big thank you to Bill and Sébastien for their time. And to our listeners, as always, it’s a pleasure to have you along for the ride. I hope you’ll join us for our remaining conversations, as well as a second coauthor roundtable with Carey and Zak.   Until next time.   [MUSIC FADES]

Last year, MACK Books published Architecture from Below, which anthologized writings by the French Brazilian architect, theorist, and painter Sérgio Ferro. (Douglas Spencer reviewed it for AN.) Now, MACK follows with Design and the Building Site and Complementary Essays, the second in the trilogy of books dedicated to Ferro’s scholarship. The following excerpt of the author’s 2023 preface to the English edition, which preserves its British phrasing, captures Ferro’s realization about the working conditions of construction sites in Brasília. The sentiment is likely relatable even today for young architects as they discover how drawings become buildings. Design and the Building Site and Complementary Essays will be released on May 22. If I remember correctly, it was in 1958 or 1959, when Rodrigo and I were second- or third year architecture students at FAUUSP, that my father, the real estate developer Armando Simone Pereira, commissioned us to design two large office buildings and eleven shops in Brasilia, which was then under construction. Of course, we were not adequately prepared for such an undertaking. Fortunately, Oscar Niemeyer and his team, who were responsible for overseeing the construction of the capital, had drawn up a detailed document determining the essential characteristics of all the private sector buildings. We followed these prescriptions to the letter, which saved us from disaster. Nowadays, it is hard to imagine the degree to which the construction of Brasilia inspired enthusiasm and professional pride in the country’s architects. And in the national imagination, the city’s establishment in the supposedly unpopulated hinterland evoked a re-founding of Brazil. Up until that point, the occupation of our immense territory had been reduced to a collection of arborescent communication routes, generally converging upon some river, following it up to the Atlantic Ocean. Through its ports, agricultural or extractive commodities produced by enslaved peoples or their substitutes passed towards the metropolises; goods were exchanged in the metropolises for more elaborate products, which took the opposite route. Our national identity was summed up in a few symbols, such as the anthem or the flag, and this scattering of paths pointing overseas. Brasilia would radically change this situation, or so we believed. It would create a central hub where the internal communication routes could converge, linking together hithertoseparate junctions, stimulating trade and economic progress in the country’s interior. It was as if, for the first time, we were taking care of ourselves. At the nucleus of this centripetal movement, architecture would embody the renaissance. And at the naval of the nucleus, the symbolic mandala of this utopia: the cathedral. Rodrigo and I got caught up in the euphoria. And perhaps more so than our colleagues, because we were taking part in the adventure with ‘our’ designs. The reality was very different — but we did not know that yet. At that time, architects in Brazil were responsible for verifying that the construction was in line with the design. We had already monitored some of our first building sites. But the construction company in charge of them, Osmar Souza e Silva’s CENPLA, specialized in the building sites of modernist architects from the so-called Escola Paulista led by Vilanova Artigas (which we aspired to be a part of, like the pretentious students we were). Osmar was very attentive to his clients and his workers, who formed a supportive and helpful team. He was even more careful with us, because he knew how inexperienced we were. I believe that the CENPLA was particularly important in São Paulo modernism: with its congeniality, it facilitated experimentation, but for the same reason, it deceived novices like us about the reality of other building sites. Consequently, Rodrigo and I travelled to Brasilia several times to check that the constructions followed ‘our’ designs and to resolve any issues. From the very first trip, our little bubble burst. Our building sites, like all the others in the future capital, bore no relation to Osmar’s. They were more like a branch of hell. A huge, muddy wasteland, in which a few cranes, pile drivers, tractors, and excavators dotted the mound of scaffolding occupied by thousands of skinny, seemingly exhausted wretches, who were nevertheless driven on by the shouts of master builders and foremen, in turn pressured by the imminence of the fateful inauguration date. Surrounding or huddled underneath the marquees of buildings under construction, entire families, equally skeletal and ragged, were waiting for some accident or death to open up a vacancy. In contact only with the master builders, and under close surveillance so we would not speak to the workers, we were not allowed to see what comrades who had worked on these sites later told us in prison: suicide abounded; escape was known to be futile in the unpopulated surroundings with no viable roads; fatal accidents were often caused by weakness due to chronic diarrhoea, brought on by rotten food that came from far away; outright theft took place in the calculation of wages and expenses in the contractor’s grocery store; camps were surrounded by law enforcement. I repeat this anecdote yet again not to invoke the benevolence of potential readers, but rather to point out the conditions that, in my opinion, allowed two students (Flávio Império joined us a little later) still in their professional infancy to quickly adopt positions that were contrary to the usual stance of architects. As the project was more Oscar Niemeyer’s than it was our own, we did not have the same emotional attachment that is understandably engendered between real authors and their designs. We had not yet been imbued with the charm and aura of the métier. And the only building sites we had visited thus far, Osmar’s, were incomparable to those we discovered in Brasilia. In short, our youthfulness and unpreparedness up against an unbearable situation made us react almost immediately to the profession’s satisfied doxa. Unprepared and young perhaps, but already with Marx by our side. Rodrigo and I joined the student cell of the Brazilian Communist Party during our first year at university. In itself, this did not help us much: the Party’s Marxism, revised in the interests of the USSR, was pitiful. Even high-level leaders rarely went beyond the first chapter of Capital. But at the end of the 1950s, the effervescence of the years to come was already nascent:  […] this extraordinary revival […] the rediscovery of Marxism and the great dialectical texts and traditions in the 1960s: an excitement that identifies a forgotten or repressed moment of the past as the new and subversive, and learns the dialectical grammar of a Hegel or an Adorno, a Marx or a Lukács, like a foreign language that has resources unavailable in our own. And what is more: the Chinese and Cuban revolutions, the war in Vietnam, guerrilla warfare of all kinds, national liberation movements, and a rare libertarian disposition in contemporary history, totally averse to fanaticism and respect for ideological apparatuses of (any) state or institution. Going against the grain was almost the norm. We were of course no more than contemporaries of our time. We were soon able to position ourselves from chapters 13, 14, and 15 of Capital, but only because we could constantly cross-reference Marx with our observations from well-contrasted building sites and do our own experimenting. As soon as we identified construction as manufacture, for example, thanks to the willingness and even encouragement of two friends and clients, Boris Fausto and Bernardo Issler, I was able to test both types of manufacture — organic and heterogeneous — on similar-sized projects taking place simultaneously, in order to find out which would be most convenient for the situation in Brazil, particularly in São Paulo. Despite the scientific shortcomings of these tests, they sufficed for us to select organic manufacture. Arquitetura Nova had defined its line of practice, studies, and research. There were other sources that were central to our theory and practice. Flávio Império was one of the founders of the Teatro de Arena, undoubtedly the vanguard of popular, militant theatre in Brazil. He won practically every set design award. He brought us his marvelous findings in spatial condensation and malleability, and in the creative diversion of techniques and material—appropriate devices for an underdeveloped country. This is what helped us pave the way to reformulating the reigning design paradigms.  We had to do what Flávio had done in the theatre: thoroughly rethink how to be an architect. Upend the perspective. The way we were taught was to start from a desired result; then others would take care of getting there, no matter how. We, on the other hand, set out to go down to the building site and accompany those carrying out the labor itself, those who actually build, the formally subsumed workers in manufacture who are increasingly deprived of the knowledge and know-how presupposed by this kind of subsumption. We should have been fostering the reconstitution of this knowledge and know-how—not so as to fulfil this assumption, but in order to reinvigorate the other side of this assumption according to Marx: the historical rebellion of the manufacture worker, especially the construction worker. We had to rekindle the demand that fueled this rebellion: total self-determination, and not just that of the manual operation as such. Our aim was above all political and ethical. Aesthetics only mattered by way of what it included—ethics. Instead of estética, we wrote est ética [this is ethics]. We wanted to make building sites into nests for the return of revolutionary syndicalism, which we ourselves had yet to discover. Sérgio Ferro, born in Brazil in 1938, studied architecture at FAUUSP, São Paulo. In the 1960s, he joined the Brazilian communist party and started, along with Rodrigo Lefevre and Flávio Império, the collective known as Arquitetura Nova. After being arrested by the military dictatorship that took power in Brazil in 1964, he moved to France as an exile. As a painter and a professor at the École Nationale Supérieure d’Architecture de Grenoble, where he founded the Dessin/Chantier laboratory, he engaged in extensive research which resulted in several publications, exhibitions, and awards in Brazil and in France, including the title of Chevalier des Arts et des Lettres in 1992. Following his retirement from teaching, Ferro continues to research, write, and paint.

Greg Touhill, director of the Software Engineering’s Institute’s (SEI’s) Computer Emergency Response Team (CERT) division is an atypical technology leader. For one thing, he’s been in tech and other leadership positions that span the US Air Force, the US government, the private sector and now SEI’s CERT. More importantly, he’s been a major force in the cybersecurity realm, making the world a safer place and even saving lives. Touhill earned a bachelor’s degree from the Pennsylvania State University, a master’s degree from the University of Southern California, a master’s degree from the Air War College, was a senior executive fellow at the Harvard University Kennedy School of Government and completed executive education studies at the University of North Carolina. “I was a student intern at Carnegie Mellon, but I was going to college at Penn State and studying chemical engineering. As an Air Force ROTC scholarship recipient, I knew I was going to become an Air Force officer but soon realized that I didn’t necessarily want to be a chemical engineer in the Air Force,” says Touhill. “Because I passed all the mathematics, physics, and engineering courses, I ended up becoming a communications, electronics, and computer systems officer in the Air Force. I spent 30 years, one month and three days on active duty in the United States Air Force, eventually retiring as a brigadier general and having done many different types of jobs that were available to me within and even beyond my career field.” Related:Specifically, he was an operational commander at the squadron, group, and wing levels. For example, as a colonel, Touhill served as director of command, control, communications and computers (C4) for the United States Central Command Forces, then he was appointed chief information officer and director, communications and information at Air Mobility Command. Later, he served as commander, 81st Training Wing at Kessler Air Force Base where he was promoted to brigadier general and commanded over 12,500 personnel. After that, he served as the senior defense officer and US defense attaché at the US Embassy in Kuwait, before concluding his military career as the chief information officer and director, C4 systems at the US Transportation Command, one of 10 US combatant commands, where he and his team were awarded the NSA Rowlett Award for the best cybersecurity program in the government. While in the Air Force, Touhill received numerous awards and decorations including the Bronze Star medal and the Air Force Science and Engineering Award. He is the only three-time recipient of the USAF C4 Professionalism Award. Related:Greg Touhill“I got to serve at major combatant commands, work with coalition partners from many different countries and represented the US as part of a diplomatic mission to Kuwait for two years as the senior defense official at a time when America was withdrawing forces out of Iraq. I also led the negotiation of a new bilateral defense agreement with the Kuwaitis,” says Touhill. “Then I was recruited to continue my service and was asked to serve as the deputy assistant secretary of cybersecurity and communications at the Department of Homeland Security, where I ran the operations of what is now known as the Cybersecurity and Infrastructure Security Agency. I was there at a pivotal moment because we were building up the capacity of that organization and setting the stage for it to become its own agency.” While at DHS, there were many noteworthy breaches including the infamous US Office of People Management (OPM) breach. Those events led to Obama’s visit to the National Cybersecurity and Communications Integration Center.  “I got to brief the president on the state of cybersecurity, what we had seen with the OPM breach and some other deficiencies,” says Touhill. “I was on the federal CIO council as the cybersecurity advisor to that since I’d been a federal CIO before and I got to conclude my federal career by being the first United States government chief information security officer. From there, I pivoted to industry, but I also got to return to Carnegie Mellon as a faculty member at Carnegie Mellon’s Heinz College, where I've been teaching since January 2017.” Related:Touhill has been involved in three startups, two of which were successfully acquired. He also served on three Fortune 100 advisory boards and on the Information Systems Audit and Control Association board, eventually becoming its chair for a term during the seven years he served there. Touhill just celebrated his fourth year at CERT, which he considers the pinnacle of the cybersecurity profession and everything he’s done to date. “Over my career I've led teams that have done major software builds in the national security space. I've also been the guy who's pulled cables and set up routers, hubs and switches, and I've been a system administrator. I've done everything that I could do from the keyboard up all the way up to the White House,” says Touhill. “For 40 years, the Software Engineering Institute has been leading the world in secure by design, cybersecurity, software engineering, artificial intelligence and engineering, pioneering best practices, and figuring out how to make the world a safer more secure and trustworthy place. I’ve had a hand in the making of today’s modern military and government information technology environment, beginning as a 22-year-old lieutenant, and hope to inspire the next generation to do even better.” What ‘Success’ Means Many people would be satisfied with their careers as a brigadier general, a tech leader, the White House’s first anything, or working at CERT, let alone running it. Touhill has spent his entire career making the world a safer place, so it’s not surprising that he considers his greatest achievement saving lives. “In the Middle East and Iraq, convoys were being attacked with improvised explosive devices. There were also ‘direct fire’ attacks where people are firing weapons at you and indirect fire attacks where you could be in the line of fire,” says Touhill. “The convoys were using SINCGARS line-of-site walkie-talkies for communications that are most effective when the ground is flat, and Iraq is not flat. As a result, our troops were at risk of not having reliable communications while under attack. As my team brainstormed options to remedy the situation, one of my guys found some technology, about the size of an iPhone, that could covert a radio signal, which is basically a waveform, into a digital pulse I could put on a dedicated network to support the convoy missions.” For $11 million, Touhill and his team quickly architected, tested, and fielded the Radio over IP network (aka “Ripper Net”) that had a 99% reliability rate anywhere in Iraq. Better still, convoys could communicate over the network using any radios. That solution saved a minimum of six lives. In one case, the hospital doctor said if the patient had arrived five minutes later, he would have died. Sage Advice Anyone who has ever spent time in the military or in a military family knows that soldiers are very well disciplined, or they wash out. Other traits include being physically fit, mentally fit, and achieving balance in life, though that’s difficult to achieve in combat. Still, it’s a necessity. “I served three and a half years down range in combat operations. My experience taught me you could be doing 20-hour days for a year or two on end. If you haven’t built a good foundation of being disciplined and fit, it impacts your ability to maintain presence in times of stress, and CISOs work in stressful situations,” says Touhill. “Staying fit also fortifies you for the long haul, so you don’t get burned out as fast.” Another necessary skill is the ability to work well with others.  “Cybersecurity is an interdisciplinary practice. One of the great joys I have as CERT director is the wide range of experts in many different fields that include software engineers, computer engineers, computer scientists, data scientists, mathematicians and physicists,” says Touhill. “I have folks who have business degrees and others who have philosophy degrees. It's really a rich community of interests all coming together towards that common goal of making the world a safer, more secure and more trusted place in the cyber domain. We’re are kind of like the cyber neighborhood watch for the whole world.” He also says that money isn’t everything, having taken a pay cut to go from being an Air Force brigadier general to the deputy assistant secretary of the Department of Homeland Security . “You’ll always do well if you pick the job that matters most. That’s what I did, and I’ve been rewarded every step,” says Touhill.  The biggest challenge he sees is the complexity of cyber systems and software, which can have second, third, and fourth order effects.  “Complexity raises the cost of the attack surface, increases the attack surface, raises the number of vulnerabilities and exploits human weaknesses,” says Touhill. “The No. 1 thing we need to be paying attention to is privacy when it comes to AI because AI can unearth and discover knowledge from data we already have. While it gives us greater insights at greater velocities, we need to be careful that we take precautions to better protect our privacy, civil rights and civil liberties.” 

These annual rankings were last updated on June 13, 2025. Want to see your firm on next year’s list? Continue reading for more on how you can improve your studio’s ranking. New Zealand is a one-of-a-kind island in the Pacific, famous for its indigenous Maori architecture. The country has managed to preserve an array of historical aboriginal ruins, such as marae (meeting grounds) and wharenui (meeting houses), despite its European colonization during the 19th century. Apart from the country’s ancient ruins, New Zealand is also home to several notable architectural landmarks like the famous Sky Tower piercing the Auckland skyline to the organic forms of the Te Papa Tongarewa Museum in Wellington. Renowned architects like Sir Ian Athfield, whose works blend modernist principles with a deep respect for the natural landscape, have left an indelible mark on the country’s architectural legacy. Being home to a stunning tropical landscape, New Zealand architects have developed eco-friendly residential designs that harness the power of renewable energy as well as visionary urban developments prioritizing livability and connectivity. A notable example is Turanga Central Library in Christchurch, a project that exceeds all eco-friendly design standards and benchmark emissions. Finally, concepts like passive design are increasingly becoming standard practice in architectural circles. With so many architecture firms to choose from, it’s challenging for clients to identify the industry leaders that will be an ideal fit for their project needs. Fortunately, Architizer is able to provide guidance on the top design firms in New Zealand based on more than a decade of data and industry knowledge. How are these architecture firms ranked? The following ranking has been created according to key statistics that demonstrate each firm’s level of architectural excellence. The following metrics have been accumulated to establish each architecture firm’s ranking, in order of priority: The number of A+Awards won (2013 to 2025) The number of A+Awards finalists (2013 to 2025) The number of projects selected as “Project of the Day” (2009 to 2025) The number of projects selected as “Featured Project” (2009 to 2025) The number of projects uploaded to Architizer (2009 to 2025) Each of these metrics is explained in more detail at the foot of this article. This ranking list will be updated annually, taking into account new achievements of New Zealand architecture firms throughout the year. Without further ado, here are the 30 best architecture firms in New Zealand: 30. CoLab Architecture © CoLab Architecture Ltd CoLab Architecture is a small practice of two directors, Tobin Smith and Blair Paterson, based in Christchurch New Zealand. Tobin is a creative designer with a wealth of experience in the building industry. Blair is a registered architect and graduate from the University of Auckland. “We like architecture to be visually powerful, intellectually elegant, and above all timeless. For us, timeless design is achieved through simplicity and strength of concept — in other words, a single idea executed beautifully with a dedication to the details. We strive to create architecture that is conscious of local climate (hunker down in the winter and open up in summer) and the environment (scale and relationship to other buildings and the natural environment).” Some of CoLab Architecture’s most prominent projects include: Urban Cottage, Christchurch, New Zealand The following statistics helped CoLab Architecture Ltd achieve 30th place in the 30 Best Architecture Firms in New Zealand: Featured Projects 1 Total Projects 1 29. Paul Whittaker © Paul Whittaker Paul Whittaker is an architecture firm based in New Zealand. Its work revolves around residential architecture. Some of Paul Whittaker’s most prominent projects include: Whittaker Cube, Kakanui, New Zealand The following statistics helped Paul Whittaker achieve 29th place in the 30 Best Architecture Firms in New Zealand: Featured Projects 1 Total Projects 1 28. Space Division © Simon Devitt Photographer Space Division is a boutique architectural practice that aims to positively impact the lives and environment of its clients and their communities by purposefully producing quality space. We believe our name reflects both the essence of what we do, but also how we strive to do it – succinctly and simply. Our design process is inclusive and client focused with their desires, physical constraints, budgets, time frames, compliance and construction processes all carefully considered and incorporated into our designs. Space Division has successfully applied this approach to a broad range of project types within the field of architecture, ranging from commercial developments, urban infrastructure to baches, playhouses and residential homes. Space Divisions team is committed to delivering a very personal and complete service to each of their clients, at each stage of the process. To assist in achieving this Space Division collaborates with a range of trusted technical specialists, based on the specific needs of our client. Which ensures we stay focussed, passionate agile and easily scalable. Some of Space Division’s most prominent projects include: Stradwick House, Auckland, New Zealand The following statistics helped Space Division achieve 28th place in the 30 Best Architecture Firms in New Zealand: Featured Projects 1 Total Projects 1 27. Sumich Chaplin Architects © Sumich Chaplin Architects Sumich Chaplin Architects undertake to provide creative, enduring architectural design based on a clear understanding and interpretation of a client’s brief. We work with an appreciation and respect for the surrounding landscape and environment. Some of Sumich Chaplin Architects’ most prominent projects include: Millbrook House, Arrowtown, New Zealand The following statistics helped Sumich Chaplin Architects achieve 27th place in the 30 Best Architecture Firms in New Zealand: Featured Projects 1 Total Projects 1 26. Daniel Marshall Architects © Simon Devitt Photographer Daniel Marshall Architects (DMA) is an Auckland based practice who are passionate about designing high quality and award winning New Zealand architecture. Our work has been published in periodicals and books internationally as well as numerous digital publications. Daniel leads a core team of four individually accomplished designers who skillfully collaborate to resolve architectural projects from their conception through to their occupation. DMA believe architecture is a ‘generalist’ profession which engages with all components of an architectural project; during conceptual design, documentation and construction phases.  We pride ourselves on being able to holistically engage with a complex of architectural issues to arrive at a design solution equally appropriate to its context (site and surrounds) and the unique ways our clients prefer to live. Some of Daniel Marshall Architects’ most prominent projects include: Lucerne, Auckland, New Zealand House in Herne Bay, Herne Bay, Auckland, New Zealand The following statistics helped Daniel Marshall Architects achieve 26th place in the 30 Best Architecture Firms in New Zealand: Featured Projects 1 Total Projects 2 25. AW Architects © AW Architects Creative studio based in Christchurch, New Zealand. AW-ARCH is committed to an inclusive culture where everyone is encouraged to share their perspectives – our partners, our colleagues and our clients. Our team comes from all over the globe, bringing with them a variety of experiences. We embrace the differences that shape people’s lives, including race, ethnicity, identity and ability. We come together around the drawing board, the monitor, and the lunch table, immersed in the free exchange of ideas and synthesizing the diverse viewpoints of creative people, which stimulates innovative design and makes our work possible. Mentorship is key to engagement within AW-ARCH, energizing our studio and feeding invention. It’s our social and professional responsibility and helps us develop and retain a dedicated team. This includes offering internships that introduce young people to our profession, as well as supporting opportunities for our people outside the office — teaching, volunteering and exploring. Some of AW Architects’ most prominent projects include: OCEAN VIEW TERRACE HOUSE, Christchurch, New Zealand 212 CASHEL STREET, Christchurch, New Zealand LAKE HOUSE, Queenstown, New Zealand RIVER HOUSE, Christchurch, New Zealand HE PUNA TAIMOANA, Christchurch, New Zealand The following statistics helped AW Architects achieve 25th place in the 30 Best Architecture Firms in New Zealand: A+Awards Finalist 1 Total Projects 9 24. Archimedia © Patrick Reynolds Archimedia is a New Zealand architecture practice with NZRAB and green star accredited staff, offering design services in the disciplines of architecture, interiors and ecology. Delivering architecture involves intervention in both natural eco-systems and the built environment — the context within which human beings live their lives. Archimedia uses the word “ecology” to extend the concept of sustainability to urban design and master planning and integrates this holistic strategy into every project. Archimedia prioritizes client project requirements, functionality, operational efficiency, feasibility and programme. Some of Archimedia’s most prominent projects include: Te Oro, Auckland, New Zealand Auckland Art Gallery Toi o Tamaki, Auckland, New Zealand Hekerua Bay Residence, New Zealand Eye Institute , Remuera, Auckland, New Zealand University of Auckland Business School, Auckland, New Zealand The following statistics helped Archimedia achieve 24th place in the 30 Best Architecture Firms in New Zealand: Featured Projects 1 Total Projects 25 23. MC Architecture Studio © MC Architecture Studio Ltd The studio’s work, questioning the boundary between art and architecture, provides engaging and innovative living space with the highest sustainability standard. Design solutions are tailored on client needs and site’s characteristics. Hence the final product will be unique and strongly related to the context and wider environment. On a specific-project basis, the studio, maintaining the leadership of the whole process, works in a network with local and international practices to achieve the best operational efficiency and local knowledge worldwide to accommodate the needs of a big scale project or specific requirements. Some of MC Architecture Studio’s most prominent projects include: Cass Bay House, Cass Bay, Lyttelton, New Zealand Ashburton Alteration, Ashburton, New Zealand restaurant/cafe, Ovindoli, Italy Private Residence, Christchurch, New Zealand Private Residence, Christchurch, New Zealand The following statistics helped MC Architecture Studio Ltd achieve 23rd place in the 30 Best Architecture Firms in New Zealand: Featured Projects 2 Total Projects 19 22. Architecture van Brandenburg © Architecture van Brandenburg Van Brandenburg is a design focused studio for architecture, landscape architecture, urbanism, and product design with studios in Queenstown and Dunedin, New Zealand. With global reach Van Brandenburg conducts themselves internationally, where the team of architects, designers and innovators create organic built form, inspired by nature, and captured by curvilinear design. Some of Architecture van Brandenburg’s most prominent projects include: Marisfrolg Fashion Campus, Shenzhen, China The following statistics helped Architecture van Brandenburg achieve 22nd place in the 30 Best Architecture Firms in New Zealand: A+Awards Winner 1 Featured Projects 1 Total Projects 1 21. MacKayCurtis © MacKayCurtis MacKay Curtis is a design led practice with a mission to create functional architecture of lasting beauty that enhances peoples lives. Some of MacKayCurtis’ most prominent projects include: Mawhitipana House, Auckland, New Zealand The following statistics helped MacKayCurtis achieve 21st place in the 30 Best Architecture Firms in New Zealand: A+Awards Winner 1 Featured Projects 1 Total Projects 1 20. Gerrad Hall Architects © Gerrad Hall Architects We aspire to create houses that are a joyful sensory experience. Some of Gerrad Hall Architects’ most prominent projects include: Inland House, Mangawhai, New Zealand Herne Bay Villa Alteration, Auckland, New Zealand The following statistics helped Gerrad Hall Architects achieve 20th place in the 30 Best Architecture Firms in New Zealand: Featured Projects 2 Total Projects 2 19. Dorrington Atcheson Architects © Dorrington Atcheson Architects Dorrington Atcheson Architects was founded as Dorrington Architects & Associates was formed in 2010, resulting in a combined 20 years of experience in the New Zealand architectural market. We’re a boutique architecture firm working on a range of projects and budgets. We love our work, we pride ourselves on the work we do and we enjoy working with our clients to achieve a result that resolves their brief. The design process is a collaborative effort, working with the client, budget, site and brief, to find unique solutions that solve the project at hand. The style of our projects are determined by the site and the budget, with a leaning towards contemporary modernist design, utilizing a rich natural material palette, creating clean and tranquil spaces. Some of Dorrington Atcheson Architects’ most prominent projects include: Lynch Street Coopers Beach House, Coopers Beach, New Zealand Rutherford House, Tauranga Taupo, New Zealand Winsomere Cres Kathryn Wilson Shoebox, Auckland, New Zealand The following statistics helped Dorrington Atcheson Architects achieve 19th place in the 30 Best Architecture Firms in New Zealand: Featured Projects 2 Total Projects 14 18. Andrew Barre Lab © Marcela Grassi Andrew Barrie Lab is an architectural practice that undertakes a diverse range of projects. We make buildings, books, maps, classes, exhibitions and research. Some of Andrew Barre Lab’s most prominent projects include: Learning from Trees, Venice, Italy The following statistics helped Andrew Barre Lab achieve 18th place in the 30 Best Architecture Firms in New Zealand: A+Awards Finalist 2 Featured Projects 1 Total Projects 1 17. Warren and Mahoney © Simon Devitt Photographer Warren and Mahoney is an insight led multidisciplinary architectural practice with six locations functioning as a single office. Our clients and projects span New Zealand, Australia and the Pacific Rim. The practice has over 190 people, comprising of specialists working across the disciplines of architecture, workplace, masterplanning, urban design and sustainable design. We draw from the wider group for skills and experience on every project, regardless of the location. Some of Warren and Mahoney’s most prominent projects include: MIT Manukau & Transport Interchange, Auckland, New Zealand Carlaw Park Student Accommodation, Auckland, New Zealand Pt Resolution Footbridge, Auckland, New Zealand Isaac Theatre Royal, Christchurch, New Zealand University of Auckland Recreation and Wellness Centre, Auckland, New Zealand The following statistics helped Warren and Mahoney achieve 17th place in the 30 Best Architecture Firms in New Zealand: Featured Projects 2 Total Projects 5 16. South Architects Limited © South Architects Limited Led by Craig South, our friendly professional team is dedicated to crafting for uniqueness and producing carefully considered architecture that will endure and be loved. At South Architects, every project has a unique story. This story starts and ends with our clients, whose values and aspirations fundamentally empower and inspire our whole design process. Working together with our clients is pivotal to how we operate and we share a passion for innovation in design. We invite you to meet us and explore what we can do for you. As you will discover, our client focussed process is thorough, robust and responsive. We see architecture as the culmination of a journey with you. Some of South Architects Limited’s most prominent projects include: Three Gables, Christchurch, New Zealand Concrete Copper Home, Christchurch, New Zealand Driftwood Home, Christchurch, New Zealand Half Gable Townhouses, Christchurch, New Zealand Kilmore Street, Christchurch, New Zealand The following statistics helped South Architects Limited achieve 16th place in the 30 Best Architecture Firms in New Zealand: Featured Projects 3 Total Projects 6 15. Pac Studio © Pac Studio Pac Studio is an ideas-driven design office, committed to intellectual and artistic rigor and fueled by a strong commitment to realizing ideas in the world. We believe a thoughtful and inclusive approach to design, which puts people at the heart of any potential solution, is the key to compelling and positive architecture. Through our relationships with inter-related disciplines — furniture, art, landscape and academia — we can create a whole that is greater than the sum of its parts. We are open to unconventional propositions. We are architects and designers with substantial experience delivering highly awarded architectural projects on multiple scales. Some of Pac Studio’s most prominent projects include: Space Invader, Auckland, New Zealand Split House, Auckland, New Zealand Yolk House, Auckland, New Zealand Wanaka Crib, Wanaka, New Zealand Pahi House, Pahi, New Zealand The following statistics helped Pac Studio achieve 15th place in the 30 Best Architecture Firms in New Zealand: Featured Projects 3 Total Projects 8 14. Jasmax © Jasmax Jasmax is one of New Zealand’s largest and longest established architecture and design practices. With over 250 staff nationwide, the practice has delivered some of the country’s most well known projects, from the Museum of New Zealand Te Papa Tongarewa to major infrastructure and masterplanning projects such as Auckland’s Britomart Station. From our four regional offices, the practice works with clients, stakeholders and communities across the following sectors: commercial, cultural and civic, education, infrastructure, health, hospitality, retail, residential, sports and recreation, and urban design. Environmentally sustainable design is part of everything we do, and we were proud to work with Ngāi Tūhoe to design one of New Zealand’s most advanced sustainable buildings, Te Uru Taumatua; which has been designed to the stringent criteria of the International Living Future Institute’s Living Building Challenge. Some of Jasmax’s most prominent projects include: The Surf Club at Muriwai, Muriwai, New Zealand Auckland University Mana Hauora Building, Auckland, New Zealand The Fonterra Centre, Auckland, New Zealand Auckland University of Technology Sir Paul Reeves Building , Auckland, New Zealand NZI Centre, Auckland, New Zealand The following statistics helped Jasmax achieve 14th place in the 30 Best Architecture Firms in New Zealand: Featured Projects 3 Total Projects 21 13. Condon Scott Architects © Condon Scott Architects Condon Scott Architects is a boutique, award-winning NZIA registered architectural practice based in Wānaka, New Zealand. Since inception 35 years ago, Condon Scott Architects has been involved in a wide range of high end residential and commercial architectural projects throughout Queenstown, Wānaka, the Central Otago region and further afield. Director Barry Condon (ANZIA) and principal Sarah Scott (FNZIA) – both registered architects – work alongside a highly skilled architectural team to deliver a full design and construction management service. This spans from initial concept design right through to tender management and interior design. Condon Scott Architect’s approach is to view each commission as a bespoke and site specific project, capitalizing on the unique environmental conditions and natural surroundings that are so often evident in this beautiful part of the world. Some of Condon Scott Architects’ most prominent projects include: Sugi House, Wānaka, New Zealand Wanaka Catholic Church, Wanaka, New Zealand Mount Iron Barn, Wanaka, New Zealand Bendigo Terrace House, New Zealand Bargour Residence, Wanaka, New Zealand The following statistics helped Condon Scott Architects achieve 13th place in the 30 Best Architecture Firms in New Zealand: Featured Projects 4 Total Projects 17 12. Glamuzina Paterson Architects © Glamuzina Paterson Architects Glamuzina Architects is an Auckland based practice established in 2014. We strive to produce architecture that is crafted, contextual and clever. Rather than seeking a particular outcome we value a design process that is rigorous and collaborative. When designing we look to the context of a project beyond just its immediate physical location to the social, political, historical and economic conditions of place. This results in architecture that is uniquely tailored to the context it sits within. We work on many different types of projects across a range of scales; from small interiors to large public buildings. Regardless of a project’s budget we always prefer to work smart, using a creative mix of materials, light and volume in preference to elaborate finishes or complex detailing. Some of Glamuzina Paterson Architects’ most prominent projects include: Lake Hawea Courtyard House, Otago, New Zealand Blackpool House, Auckland, New Zealand Brick Bay House, Auckland, New Zealand Giraffe House, Auckland, New Zealand Giraffe House, Auckland, New Zealand The following statistics helped Glamuzina Paterson Architects achieve 12th place in the 30 Best Architecture Firms in New Zealand: Featured Projects 4 Total Projects 5 11. Cheshire Architects © Patrick Reynolds Cheshire Architects does special projects, irrespective of discipline, scale or type. The firm moves fluidly from luxury retreat to city master plan to basement cocktail den, shaping every aspect of an environment in pursuit of the extraordinary. Some of Cheshire Architects’ most prominent projects include: Rore kahu, Te Tii, New Zealand Eyrie, New Zealand Milse, Takanini, New Zealand The following statistics helped Cheshire Architects achieve 11th place in the 30 Best Architecture Firms in New Zealand: Featured Projects 3 Total Projects 3 10. Patterson Associates © Patterson Associates Pattersons Associates Architects began its creative story with architect Andrew Patterson in 1986 whose early work on New Zealand’s unspoiled coasts, explores relationships between people and landscape to create a sense of belonging. The architecture studio started based on a very simple idea; if a building can feel like it naturally ‘belongs,’ or fits logically in a place, to an environment, a time and culture, then the people that inhabit the building will likely feel a sense of belonging there as well. This methodology connects theories of beauty, confidence, economy and comfort. In 2004 Davor Popadich and Andrew Mitchell joined the firm as directors, taking it to another level of creative exploration and helping it grow into an architecture studio with an international reputation. Some of Patterson Associates’ most prominent projects include: Seascape Retreat, Canterbury, New Zealand The Len Lye Centre, New Plymouth, New Zealand Country House in the City, Auckland, New Zealand Scrubby Bay House, Canterbury, New Zealand Parihoa House, Auckland, New Zealand The following statistics helped Patterson Associates achieve 10th place in the 30 Best Architecture Firms in New Zealand: Featured Projects 5 Total Projects 5 9. Team Green Architects © Team Green Architects Established in 2013 by Sian Taylor and Mark Read, Team Green Architects is a young committed practice focused on designing energy efficient buildings. Some of Team Green Architects’ most prominent projects include: Dalefield Guest House, Queenstown, New Zealand Olive Grove House, Cromwell, New Zealand Hawthorn House, Queenstown, New Zealand Frankton House, Queenstown, New Zealand Contemporary Sleepout, Arthurs Point, New Zealand The following statistics helped Team Green Architects achieve 9th place in the 30 Best Architecture Firms in New Zealand: Featured Projects 5 Total Projects 7 8. Creative Arch © Creative Arch Creative Arch is an award-winning, multi-disciplined architectural design practice, founded in 1998 by architectural designer and director Mark McLeay. The range of work at Creative Arch is as diverse as our clients, encompassing residential homes, alterations and renovations, coastal developments, sub-division developments, to commercial projects. The team at Creative Arch are an enthusiastic group of talented professional architects and architectural designers, with a depth of experience, from a range of different backgrounds and cultures. Creative Arch is a client-focused firm committed to providing excellence in service, culture and project outcomes. Some of Creative Arch’s most prominent projects include: Rothesay Bay House, North Shore, New Zealand Best Pacific Institute of Education, Auckland, New Zealand Sumar Holiday Home, Whangapoua, New Zealand Cook Holiday Home, Omaha, New Zealand Arkles Bay Residence, Whangaparaoa, New Zealand The following statistics helped Creative Arch achieve 8th place in the 30 Best Architecture Firms in New Zealand: Featured Projects 5 Total Projects 18 7. Crosson Architects © Crosson Architects At Crosson Architects we are constantly striving to understand what is motivating the world around us. Some of Crosson Architects’ most prominent projects include: Hut on Sleds, Whangapoua, New Zealand Te Pae North Piha Surf Lifesaving Tower, Auckland, New Zealand Coromandel Bach, Coromandel, New Zealand Tutukaka House, Tutukaka, New Zealand St Heliers House, Saint Heliers, Auckland, New Zealand The following statistics helped Crosson Architects achieve 7th place in the 30 Best Architecture Firms in New Zealand: A+Awards Winner 1 A+Awards Finalist 2 Featured Projects 4 Total Projects 6 6. Bossley Architects © Bossley Architects Bossley Architects is an architectural and interior design practice with the express purpose of providing intense input into a deliberately limited number of projects. The practice is based on the belief that innovative yet practical design is essential for the production of good buildings, and that the best buildings spring from an open and enthusiastic collaboration between architect, client and consultants. We have designed a wide range of projects including commercial, institutional and residential, and have amassed special expertise in the field of art galleries and museums, residential and the restaurant/entertainment sector. Whilst being very much design focused, the practice has an overriding interest in the pragmatics and feasibility of construction. Some of Bossley Architects’ most prominent projects include: Ngā Hau Māngere -Old Māngere Bridge Replacement, Auckland, New Zealand Arruba, Waiuku, New Zealand Brown Vujcich House Voyager NZ Maritime Museum Omana Luxury Villas, Auckland, New Zealand The following statistics helped Bossley Architects achieve 6th place in the 30 Best Architecture Firms in New Zealand: Featured Projects 6 Total Projects 21 5. Smith Architects © Simon Devitt Photographer Smith Architects is an award-winning international architectural practice creating beautiful human spaces that are unique, innovative and sustainable through creativity, refinement and care. Phil and Tiffany Smith established the practice in 2007. We have spent more than two decades striving to understand what makes some buildings more attractive than others, in the anticipation that it can help us design better buildings. Some of Smith Architects’ most prominent projects include: Kakapo Creek Children’s Garden, Mairangi Bay, Auckland, New Zealand New Shoots Children’s Centre, Kerikeri, Kerikeri, New Zealand Gaia (Earth) Forest Preschool, Manurewa, Auckland, New Zealand Chrysalis Childcare, Auckland, New Zealand House of Wonder, Cambridge, Cambridge, New Zealand The following statistics helped Smith Architects achieve 5th place in the 30 Best Architecture Firms in New Zealand: A+Awards Finalist 1 Featured Projects 6 Total Projects 23 4. Monk Mackenzie © Monk Mackenzie Monk Mackenzie is an architecture and design firm based in New Zealand. Monk Mackenzie’s design portfolio includes a variety of architectural projects, such as transport and infrastructure, hospitality and sport, residential, cultural and more. Some of Monk Mackenzie’s most prominent projects include: X HOUSE, Queenstown, New Zealand TURANGANUI BRIDGE, Gisborne, New Zealand VIVEKANANDA BRIDGE EDITION Canada Street Bridge, Auckland, New Zealand The following statistics helped Monk Mackenzie achieve 4th place in the 30 Best Architecture Firms in New Zealand: A+Awards Winner 2 A+Awards Finalist 4 Featured Projects 4 Total Projects 17 3. Irving Smith Architects © Irving Smith Architects Irving Smith Jack (ISJ) has been developed as a niche architecture practice based in Nelson, but working in a variety of sensitive environments and contexts throughout New Zealand. ISJ demonstrates an ongoing commitment to innovative, sustainable and researched based design , backed up by national and international award and publication recognition, ongoing research with both the Universities of Canterbury and Auckland, and regular invitations to lecture on their work. Timber Awards include NZ’s highest residential, commercial and engineering timber designs. Key experience, ongoing research and work includes developing structural timber design solutions in the aftermath of the Canterbury earthquakes. Current projects include cultural, urban, civic and residential projects spread throughout New Zealand, and recently in the United States and France. Some of Irving Smith Architects’ most prominent projects include: SCION Innovation Hub – Te Whare Nui o Tuteata, Rotorua, New Zealand Mountain Range House, Brightwater, New Zealand Alexandra Tent House, Wellington, New Zealand Te Koputu a te Whanga a Toi : Whakatane Library & Exhibition Centre, Whakatane, New Zealand offSET Shed House, Gisborne, New Zealand The following statistics helped Irving Smith Architects achieve 3rd place in the 30 Best Architecture Firms in New Zealand: A+Awards Winner 2 A+Awards Finalist 1 Featured Projects 6 Total Projects 13 2. Fearon Hay Architects © Fearon Hay Architects Fearon Hay is a design-led studio undertaking a broad range of projects in diverse environments, the firm is engaged in projects on sites around the world. Tim Hay and Jeff Fearon founded the practice in 1993 as a way to enable their combined involvement in the design and delivery of each project. Together, they lead an international team of experienced professionals. The studio approached every project with a commitment to design excellence, a thoughtful consideration of site and place, and an inventive sense of creativity. Fearon Hay enjoys responding to a range of briefs: Commercial projects for office and workplace, complex heritage environments, public work within the urban realm or wider landscape, private dwellings and detailed bespoke work for hospitality and interior environments. Some of Fearon Hay Architects’ most prominent projects include: Bishop Hill The Camp, Tawharanui Peninsula, New Zealand Matagouri, Queenstown, New Zealand Alpine Terrace House, Queenstown, New Zealand Island Retreat, Auckland, New Zealand Bishop Selwyn Chapel, Auckland, New Zealand The following statistics helped Fearon Hay Architects achieve 2nd place in the 30 Best Architecture Firms in New Zealand: A+Awards Winner 2 A+Awards Finalist 3 Featured Projects 8 Total Projects 17 1. RTA Studio © RTA Studio Richard Naish founded RTA Studio in 1999 after a successful career with top practices in London and Auckland. We are a practice that focuses on delivering exceptional design with a considered and personal service. Our work aims to make a lasting contribution to the urban and natural context by challenging, provoking and delighting. Our studio is constantly working within the realms of public, commercial and urban design as well as sensitive residential projects. We are committed to a sustainable built environment and are at the forefront developing carbon neutral buildings. RTA Studio has received more than 100 New Zealand and international awards, including Home of The Year, a World Architecture Festival category win and the New Zealand Architecture Medal. Some of RTA Studio’s most prominent projects include: SCION Innovation Hub – Te Whare Nui o Tuteata, Rotorua, New Zealand OBJECTSPACE, Auckland, New Zealand C3 House, New Zealand Freemans Bay School, Freemans Bay, Auckland, New Zealand ARROWTOWN HOUSE, Arrowtown, New Zealand Featured image: E-Type House by RTA Studio, Auckland, New Zealand The following statistics helped RTA Studio achieve 1st place in the 30 Best Architecture Firms in New Zealand: A+Awards Winner 2 A+Awards Finalist 6 Featured Projects 6 Total Projects 16 Why Should I Trust Architizer’s Ranking? With more than 30,000 architecture firms and over 130,000 projects within its database, Architizer is proud to host the world’s largest online community of architects and building product manufacturers. Its celebrated A+Awards program is also the largest celebration of architecture and building products, with more than 400 jurors and hundreds of thousands of public votes helping to recognize the world’s best architecture each year. Architizer also powers firm directories for a number of AIA (American Institute of Architects) Chapters nationwide, including the official directory of architecture firms for AIA New York. An example of a project page on Architizer with Project Award Badges highlighted A Guide to Project Awards The blue “+” badge denotes that a project has won a prestigious A+Award as described above. Hovering over the badge reveals details of the award, including award category, year, and whether the project won the jury or popular choice award. The orange Project of the Day and yellow Featured Project badges are awarded by Architizer’s Editorial team, and are selected based on a number of factors. The following factors increase a project’s likelihood of being featured or awarded Project of the Day status: Project completed within the last 3 years A well written, concise project description of at least 3 paragraphs Architectural design with a high level of both functional and aesthetic value High quality, in focus photographs At least 8 photographs of both the interior and exterior of the building Inclusion of architectural drawings and renderings Inclusion of construction photographs There are 7 Projects of the Day each week and a further 31 Featured Projects. Each Project of the Day is published on Facebook, Twitter and Instagram Stories, while each Featured Project is published on Facebook. Each Project of the Day also features in Architizer’s Weekly Projects Newsletter and shared with 170,000 subscribers.     We’re constantly look for the world’s best architects to join our community. If you would like to understand more about this ranking list and learn how your firm can achieve a presence on it, please don’t hesitate to reach out to us at editorial@architizer.com. The post 30 Best Architecture and Design Firms in New Zealand appeared first on Journal.