These days, job titles like data scientist, machine learning engineer, and Ai Engineer are everywhere — and if you were anything like me, it can be hard to understand what each of them actually does if you are not working within the field. And then there are titles that sound even more confusing — like quantum blockchain LLM robotic engineer (okay, I made that one up, but you get the point). The job market is full of buzzwords and overlapping roles, which can make it difficult to know where to start if you’re interested in a career in machine learning. In this article, I’ll break down the top machine learning roles and explain what each one involves — plus what you need to do to prepare for them. Data Scientist What is it? A data scientist is the most well-known role, but has the largest range of job responsibilities. In general, there are two types of data scientists: Analytics and experiment-focused. Machine learning and modelling focused. The former includes things like running A/B tests, conducting deep dives to determine where the business could improve, and suggesting improvements to machine learning models by identifying their blind spots. A lot of this work is called explanatory data analysis or EDA for short. The latter is mainly about building PoC machine learning models and decision systems that benefit the business. Then, working with software and machine learning engineers, to deploy those models to production and monitor their performance. Many of the machine learning algorithms will typically be on the simpler side and be regular supervised and unsupervised learning models, like: XGBoost Linear and logistic regression Random forest K-means clustering I was a data scientist at my old company, but I mainly built machine learning models and didn’t run many A/B tests or experiments. That was work that was carried out by data analysts and product analysts. However, at my current company, data scientists don’t build machine learning models but mainly do deep-dive analysis and measure experiments. Model development is mainly done by machine learning engineers. It all really comes down to the company. Therefore, it is really important that you read the job description to make sure it’s the right job for you. What do they use? As a data scientist, these are generally the things you need to know (it’s not exhaustive and will vary by role): Python and SQL Git and GitHub Command Line (Bash and Zsh) Statistics and maths knowledge Basic machine learning skills A bit of cloud systems (AWS, Azure, GCP) I have roadmaps on becoming a data scientist that you can check out below if this role interests you. How I’d Become a Data Scientist (If I Had to Start Over) Machine Learning Engineer What is it? As the title suggests, a machine learning engineer is all about building machine learning models and deploying them into production systems.  It originally came from software engineering, but is now its own job/title. The significant distinction between machine learning engineers and data scientists is that machine learning engineers deploy the algorithms. As leading AI/ML practitioner Chip Huyen puts it: The goal of data science is to generate business insights, whereas the goal of ML engineering is to turn data into products. You will find that data scientists often come from a strong maths, statistics, or economics background, and machine learning engineers come more from science and engineering backgrounds. However, there is a big overlap in this role, and some companies may bundle the data scientist and machine learning engineer positions into a single job, frequently with the data scientist title. The machine learning engineer job is typically found in more established tech companies; however, it is slowly becoming more popular over time. There also exist further specialisms within the machine learning engineer role, like: ML platform engineer ML hardware engineer ML solutions architect Don’t worry about these if you are a beginner, as they are pretty niche and only relevant after a few years of experience in the field. I just wanted to add these so you know the various options out there. What do they use? The tech stack is quite similar for machine learning engineers as for data scientists, but has more software engineering elements: Python and SQL, however, some companies may require other languages. For example, in my current role, Rust is needed. Git and GitHub Bash and Zsh AWS, Azure or GCP Software engineering fundamentals like CI/CD, MLOps and Docker. Excellent machine learning knowledge, ideally a specialism in an area. AI Engineer What is it? This is a new title that cropped up with all the AI hype going on now, and to be honest, I think it’s an odd title and not really needed. Often, a machine learning engineer will do the role of an AI engineer at most companies. Most AI engineer roles are actually about GenAI, not AI as a whole. This distinction normally makes no sense to people outside of the industry.  However, AI encompasses almost any decision-making algorithm and is larger than the machine learning field. Image by author. The current definition of an AI engineer is someone who works mainly with LLM and GenAI tools to help the business. They don’t necessarily develop the underlying algorithms from scratch, mainly because it’s hard to do unless you’re in a research lab, and many of the top models are open-sourced, so you don’t need to reinvent the wheel. Instead, they focus on adapting and building the product first, then worrying about the model fine-tuning afterwards. So, they wu It is a lot closer to traditional software engineering than the machine learning engineer role as it currently stands. Although many machine learning engineers will operate as AI engineers, the job is new and not fully fleshed out yet. What do they use? This role is evolving quite a bit, but in general, you need good knowledge of all the latest GenAI and LLM trends: Solid software engineering skills Python, SQL and backend langauges like Java or GO are useful CI/CD Git LLMs and transformers RAG Prompt engineering Foundational models Fine tuning I also recommend you check out Datacamp’s associates AI engineer for data scientist track, that will also set you up nicely for a career as a data scientist. This is linked in the description below. Research Scientist/Engineer What is it? The previous roles were mainly industry positions, but these next two will be research-based. Industry roles are mainly associated with business and are all about generating business value. Whether you use linear regression or a transformer model, what matters is the impact, not necessarily the method. Research aims to expand the current knowledge capabilities theoretically and practically. This approach revolves around the scientific method and deep experiments in a niche field. The difference between what’s research and industry is vague and often overlaps. For example, a lot of the top research labs are actually big tech companies: Meta Research Google AI Microsoft AI These companies initially started to solve business problems, but now have dedicated research sectors, so you may work on industry and research problems. Where one begins and the other ends is not always clear. If you are interested in exploring the differences between research and industry more deeply, I recommend you read this document. It’s the first lecture of Stanford’s CS 329S, lecture 1: Understanding machine learning production. In general, there are more industry positions than research, as only the large companies can afford the data and computing costs. Anyway, as a research engineer or scientist, you will essentially be working on cutting-edge research, pushing the boundaries of machine learning knowledge. There is a slight distinction between the two the jobs. As a research scientist, you will need a Phd, but this is not necessarily true for a research engineer. A research engineer typically implements the theoretical details and ideas of the research scientist. This role is usually at large, established research companies; in most situations, the research engineer and scientist jobs are the same though. Companies may offer the research scientist title as it gives you more “clout” and makes you more likely to take the job. What do they use? This one is similar to machine learning engineering, but the depth of knowledge and qualifications is often greater. Python and SQL Git and GitHub Bash and Zsh AWS, Azure or GCP Software engineering fundamentals like CI/CD, MLOps and Docker. Excellent machine learning knowledge and a specialism in a cutting-edge area like computer vision, reinforcement learning, LLM, etc. PhD or at least a master’s in a relevant discipline. Research experience. This article has just scratched the surface of machine learning roles, and there are many more niche jobs and specialisms within these four or five I mentioned. I always recommend starting your career by getting your foot in the door and then pivoting to the direction you want to go. This strategy is much more effective than tunnel vision for only one role. Another thing! I offer 1:1 coaching calls where we can chat about whatever you need — whether it’s projects, Career Advice, or just figuring out your next step. I’m here to help you move forward! 1:1 Mentoring Call with Egor HowellCareer guidance, job advice, project help, resume reviewtopmate.io Connect with me YouTube LinkedIn Instagram Website The post Top Machine Learning Jobs and How to Prepare For Them appeared first on Towards Data Science.

L’un des avantages d’être sur place pour la conférence I/O de Google, c’est de pouvoir essayer les technologies et produits qui viennent d’être...

Most people think of urban open spaces in terms of grand parks—Chicago’s Millennium Park or New York’s Central Park or San Francisco’s Golden Gate Park. These are our iconic parks—our sublime spaces. They serve as the “lungs” of our cities, and they certainly steal our hearts. These spaces are not locked behind gates but are stages where our own lives play out and memories are created, full of movement and reflection and joy.  There are more modest spaces in our cities, though, that are just as important to our lives—the thresholds and courtyards and pocket parks. They’re the places where we bump into our neighbors to walk our dogs or read on a bench in an environment where nature takes over. They are often unheralded like a great Olmsted Park, but always full of potential for true placemaking to begin.   My father, Edwin Smith was director of parks and recreation for the City of Eugene, Oregon and he knew this. He served for more than 30 years and was responsible for the design and development of 41 parks and greenways in and around the city. His work had a profound impact on me as a future architect. More to the point, his work and vision quietly enhanced the lives of so many people in the community as their access to parks was interwoven into their lives.   Westmoreland Park is one of Eugene’s centerpiece parks and is a great example. Its gentle slopes and lush lawns support stands of mature cedars and redwoods, not to mention Douglas firs, hemlocks, spruces, and the Oregon white oak. Even if you don’t know all those trees by sight, you know Westmoreland Park if you live in Eugene, and you know that it offers something for almost every active resident. I think that’s the importance of a well-designed space—it invites and it responds.   Living ribbon of connection  Responsiveness is a word worth pausing on for a moment. It’s the entire reason for design—architectural, urban, or otherwise—and it’s one of the hallmarks of placemaking.  My firm, MG2, recently envisioned design for an attainable housing project in Irvine, California, that was meant to respond to a specific housing challenge in a rapidly changing part of the state. It isn’t a monolith. It is, instead, what we think of as a living ribbon of connection—a continuous path that links breezeways, community gardens, play areas, and shared courtyards woven throughout the residential units. It is not simply a circulation route. It is a spine, and just like our spines, everything it touches depends upon it for structure. But more importantly, this isn’t just a collection of amenities. It is a social ecosystem. The layout fosters degrees of interaction—private balconies that open into semi-private courtyards, which in turn flow into cooperative gardens and fully public gathering spaces. Residents can choose solitude, casual interaction, or spirited communal activity—each space encouraging a different rhythm of human engagement. Children play while parents share meals. Strangers become neighbors over garden beds. This is architecture as social infrastructure.  To reimagine open space is not to think bigger—it is to think deeper. To look between, beneath, beyond. It is to ask: How do we shape space to be responsive? How do we design for encounter, for joy, for the unplanned but meaningful moments of connection?  Let us not treat the spaces between buildings as voids. Let us see them as vessels—of life, of community, of possibility. Let us design not just for shelter, but for spirit. Let us reimagine open spaces.  Mitch Smith AIA, LEED AP is the CEO and chairman of MG2, an affiliate of Colliers Engineering & Design. 

A 10TB secure cloud storage lifetime subscription is now only $280. Credit: Internxt Deal pricing and availability subject to change after time of publication. TL;DR: Replace your monthly Dropbox subscription with a 10TB Internxt Cloud Storage Lifetime Plan on sale for £208.51 with code STORAGE20. Opens in a new window Credit: Internxt Internxt Cloud Storage Lifetime Subscription: 10TB Plan £208.51 £2,233.42 Save £2,024.91 with code STORAGE20 Cloud storage subscriptions are expensive, even if they don't seem like it at first. Dropbox's cheapest plan is $9.99 per month for 2TB of cloud storage. It seems cheap, but that's a little under $120 every year, and you're never actually done paying for it. If you want a cheaper alternative to Dropbox, Internxt just dropped the price for a 10TB cloud storage lifetime subscription. Now it's only £208.51 with code STORAGE20. Pay once for a lifetime of cloud storageSpace isn't the only thing this cloud storage has going for it. Internxt is committed to keeping your data safe. That's why they use end-to-end encryption to secure files during transfer and at rest. Its zero-knowledge architecture means that files are encrypted in a way that Internxt itself cannot access. You're the only one who has access to your files.You don't even have to manually upload. You can sync all your files and photos across platforms, even Linux. This focus on privacy even extends to its open-source design, so users can inspect the code for transparency and security.This subscription lasts for life with no recurring payments of any kind. You can access your cloud storage on unlimited devices, too.  Mashable Deals Want more hand-picked deals from our shopping experts? Sign up for the Mashable Deals newsletter. By clicking Sign Me Up, you confirm you are 16+ and agree to our Terms of Use and Privacy Policy. Thanks for signing up! Use code STORAGE20 to get an Internxt 10TB Cloud Storage Lifetime Subscription on sale for £208.51.StackSocial prices subject to change. Topics Apps & Software

Gen Z is big into retro cameras. It's something that took me by surprise when the youth movement toward old Coolpix, Cyber-shot, and PowerShot pocket cameras gained enough traction to warrant reports from NPR and The New York Times. Young creators want small cameras that give a different aesthetic than smartphones, with digital noise and the distinctive look of direct flash you won't get from an iPhone snapshot. The problem? You're left scouring eBay or used shops to get a good-quality pocket camera because the few made today cost a bundle and are frequently sold out at stores.So when Fujifilm briefed me on the features of its latest digital camera, the X Half, just about everything seemed perfect for Gen Z photogs. The Half is pocket-sized, has an optical viewfinder, snaps pics in a social-friendly vertical 3:4 aspect ratio, and includes a baker's dozen Film Simulation profiles to give pictures an analog look. Plus, the Half looks great—Fuji's designers are experts at making new cameras with vintage flair.But instead of using a Xenon flash like an old compact, its built-in flash is LED, like a smartphone, and it doesn't work with external flashes. It seems like a missed opportunity for a camera otherwise catered to an over-connected generation that's looking for a disconnected device to use for photography.(Credit: Fujifilm)For instance, you can set the Half to Film Camera mode, in which you'll pick a film simulation and a number of images (36, 54, or 72), and snap a virtual roll with just the optical viewfinder and no option to play back photos in camera. When you finish the roll, you'll need to send it to a smartphone app to develop into individual photos, plus a simulated contact sheet showing the whole roll.Recommended by Our EditorsOf course, you can also use the X Half to take individual photos. It has an optical viewfinder and two rear LCDs. One shows a preview of your photo (or playback) and serves as the main menu, while the second shows a graphic with the current film setting and lets you swipe between options. It has one more neat feature: a film advance lever that lets you create two-shot diptychs in camera. Take a picture, advance the lever, and your next photo will complete the pair.I'm looking forward to trying the X Half and seeing how it works for myself. I'll be sure to try the LED flash for some snapshots to see if it's able to get close to achieving the direct flash look that's all the rage. But I can't help but think that a proper Xenon flash or a hot shoe would have made this one an instant hit with younger creators. Heck, I'd be happy with a center-pin hot shoe, as there are loads of small, inexpensive add-on flashes like the Godox Lux Elf that would have paired well with this camera were it compatible. Time will tell if it's as in-demand as Fuji's most recent TikTok darling, the X100VI, an upscale alternative with a proper Xenon flash tube built-in, plus a hot shoe for an add-on. The X100VI is a hot item that's been on backorder since launch, leaving impatient photographers to pay inflated aftermarket prices to get one without a wait.The X Half will be available in late June for $849.99. Stay tuned for my full review.

TNW Backstage returns this week to explore one of tech’s most fascinating frontiers: brain-computer interfaces (BCIs). The capabilities of these neural devices are rapidly expanding. They’ve been implanted in skulls and worn as headbands. They’ve measured focus, treated Parkinson’s disease, and enabled paralysed people to control computers with their minds. A range of research labs and tech firms are developing BCIs. Yet the spotlight has been dominated by one company: Elon Musk’s Neuralink. The startup has put brain implants in monkeys so they can play Pong with their minds. Musk also has big plans for humans, from giving us “superpowers” to downloading our memories. But shockingly, not everyone is keen on the idea of Elon controlling their brains. Thankfully, there are other options. One of them comes from Dutch healthtech company MindAffect. The company uses BCIs primarily for hearing and visual tests. Worn as headbands, the devices analyse the brain’s responses to stimulation, which reveals what the user saw or heard. It’s completely non-invasive, affordable, and requires little staff support. MindAffect’s CEO, Jennifer Goodall, discusses the system on this week’s episode of TNW Backstage. We revisit her session from TNW Conference 2024 and discuss the healthtech trends shaping this year’s event. You can listen to the show on Spotify, at our dedicated website, or via the media player at the bottom of this article. Once you’re done, check out our previous episodes of the podcast, which goes behind the scenes of TNW Conference and the tech shaping our world. In our debut show, we explored the data security landscape — and Meta’s controversial “pay or consent” model — with Ron de Jesus, the world’s first Field Chief Privacy Officer. In our second episode, comedy content creator Derek Mitchell and TNW co-founder Boris discussed the value of humour in tech businesses. To celebrate the podcast’s launch, we’re also offering an exclusive discount on tickets for TNW Conference, which takes place in Amsterdam on June 19 and 20. You’ll find the offer hidden in each episode of TNW Backstage. Thanks for reading — and now, for listening too. Story by Thomas Macaulay Managing editor Thomas is the managing editor of TNW. He leads our coverage of European tech and oversees our talented team of writers. Away from work, he e (show all) Thomas is the managing editor of TNW. He leads our coverage of European tech and oversees our talented team of writers. Away from work, he enjoys playing chess (badly) and the guitar (even worse). Get the TNW newsletter Get the most important tech news in your inbox each week. Also tagged with

Huawei just shattered our expectations of what a laptop can be. The new MateBook Fold Ultimate Design doesn’t just push boundaries. It obliterates them. Designer: Huawei Unveiled on May 19, this groundbreaking device introduces the world’s first 18-inch foldable display in a laptop form factor. But calling it merely a laptop feels almost reductive. When unfolded, you’re looking at a stunning 18-inch canvas that somehow weighs less than many 13-inch ultrabooks. When folded, it transforms into a compact 13-inch device that slides effortlessly into a bag. What makes this design achievement particularly impressive isn’t just the folding display itself. It’s how Huawei solved the countless engineering challenges that have prevented others from creating something this ambitious. The innovation extends beyond mere technical specifications. Huawei has reimagined the fundamental relationship between users and their computing devices, creating something that adapts to various workflows rather than forcing users to adapt to rigid form factors. Engineering Marvel: The Hinge The hinge deserves special attention. Stretching 285mm across the device, Huawei calls it the “world’s largest basalt water drop hinge.” This isn’t marketing hyperbole. The three-stage shaft with mortise and tenon structure delivers a 400% increase in hovering torque compared to standard designs. What does this mean for users? Exceptional stability at viewing angles between 30° and 150°, while maintaining smooth operation at shallow angles between 0-20 degrees. When unfolded, the MateBook measures a mere 7.3mm thick. For perspective, that’s thinner than many smartphones. Even when folded, it maintains a relatively svelte 14.9mm profile while weighing just 1.16kg. The exterior combines premium leather and metal elements, available in Black, Blue, and White colorways. The integrated kickstand on the rear panel adds another dimension of versatility. Position the device in landscape or portrait orientation at various angles for different use cases. Present to clients, watch content, sketch ideas, or type documents. The physical form adapts to your needs rather than forcing you to adapt to it. This level of engineering precision didn’t happen overnight. Huawei claims thousands of prototypes were tested before arriving at this final design, with particular attention paid to the durability of the folding mechanism. The company promises the hinge will maintain structural integrity through thousands of folding cycles. Display Technology But the true star is undoubtedly the display itself. The dual-layer LTPO OLED panel delivers an immersive visual experience with a 92% screen-to-body ratio. When fully expanded, you’re looking at an 18-inch canvas with 4:3 aspect ratio and 3.3K resolution (3296 × 2472 pixels). Fold it, and you have a more conventional 13-inch display with 3:2 aspect ratio (2472 × 1648 pixels). This isn’t just any OLED panel. Huawei implemented the first commercial laptop application of LTPO (Low-Temperature Polycrystalline Oxide) technology, reducing power consumption by 30% while enabling adaptive refresh rates. The 2,000,000:1 contrast ratio ensures deep blacks and vibrant colors across the P3 wide color gamut, while peak brightness reaches an impressive 1600 nits. For those concerned about eye strain during extended use, the screen incorporates 1440Hz high-frequency PWM dimming and carries TÜV Rheinland Eye Comfort 3.0 certification. Color accuracy hasn’t been overlooked either. Huawei claims each display is factory calibrated to achieve a Delta E of less than 1, making it suitable for professional creative work. The anti-reflective coating helps maintain visibility even in challenging lighting conditions. Thermal Innovation The revolutionary design extends beyond the visible elements. Cooling such powerful components in an ultra-thin chassis required innovative solutions. Huawei engineered diamond aluminum dual fans and an ultra-thin antigravity vapor chamber heat sink. The copper-steel composite 3D vapor chamber and distributed component layout optimize thermal performance without excessive fan noise. Traditional cooling systems simply wouldn’t work in a device this thin. Huawei’s approach involves separating heat-generating components across the chassis to prevent hotspots. The vapor chamber technology efficiently transfers heat away from critical components to maintain performance during intensive tasks. Fan noise has been carefully tuned to remain below 28dB during typical usage scenarios. This makes the MateBook Fold Ultimate suitable for quiet environments like libraries and meeting rooms where traditional laptop fans might prove distracting. Performance and Connectivity Despite its slim profile, performance hasn’t been compromised. The MateBook Fold Ultimate comes equipped with 32GB of RAM and storage options of either 1TB or 2TB SSD. While Huawei hasn’t explicitly confirmed the processor in all materials, some sources indicate it uses their own Kirin X90 chipset, a fully Chinese-manufactured ARM processor. A 74.69Wh battery powers the device, with support for fast charging through the included 140W USB-C charger. Connectivity includes strategically placed USB-C ports, one on top and one on the side, along with dual-band Wi-Fi 6 and Bluetooth 5.2. The decision to position USB-C ports on different edges of the device shows thoughtful design consideration. This arrangement allows for convenient charging regardless of how the device is positioned or folded. The absence of legacy ports might disappoint some users, but reflects the forward-looking design philosophy behind the entire product. Audio-Visual Experience The audio experience matches the visual excellence with six speakers in total. Three 2W speakers work alongside three 1W speakers, enhanced by Huawei Sound technology. For video conferencing, an 8MP front-facing camera works alongside four microphones to ensure clear communication. Speaker placement has been carefully considered to maintain audio quality regardless of the device’s orientation. Whether used as a tablet, laptop, or in presentation mode, the sound remains clear and directional. The multi-microphone array uses AI-powered noise cancellation to isolate voices from background noise during calls. The camera quality represents a significant upgrade from typical laptop webcams. The 8MP sensor captures more detail than the standard 720p cameras found in most laptops, while the wide-angle lens ensures you stay in frame even when moving during calls. HarmonyOS 5: A New Computing Paradigm Perhaps the most intriguing aspect beyond the hardware is the software. The MateBook Fold Ultimate runs HarmonyOS 5, marking the first time this operating system appears on a Huawei laptop. This represents a significant departure from Windows, offering users a third major OS option alongside Windows and macOS. HarmonyOS 5 is designed specifically for this unique form factor. Intuitive gestures include three-finger swipes to move windows across screens and five-finger spreads to maximize applications. When positioned at a 90-degree angle like a traditional laptop, the bottom half can function as a virtual keyboard with customizable skins, adjustable key spacing, and haptic feedback through a linear motor. The operating system adapts intelligently to different usage scenarios. When folded, it automatically adjusts the interface for a more traditional laptop experience. When fully opened, it transforms into a tablet-like environment optimized for touch interaction. This contextual awareness extends to connected peripherals as well, with the interface changing based on whether the physical keyboard is attached. Input Options For those who prefer physical keys, Huawei includes an ultra-thin 5mm wireless keyboard weighing just 290g. This keyboard features 1.5mm key travel, lasts up to 24 days on a single charge, and magnetically attaches to the back of the device when not in use. The keyboard design deserves special mention. Despite its ultra-thin profile, Huawei has managed to deliver a surprisingly satisfying typing experience. The keys offer tactile feedback that rivals much thicker keyboards, while the full-size layout prevents the cramped feeling often associated with portable keyboards. Touch input has been optimized as well. The display supports 10-point multi-touch with pressure sensitivity, making it suitable for digital art and note-taking. Palm rejection technology works remarkably well, allowing users to rest their hand on the screen while writing or drawing without causing unwanted input. Versatility and Use Cases The versatility of the MateBook Fold Ultimate is perhaps its greatest strength. It transitions seamlessly between tablet mode, laptop configuration, and presentation setup. The built-in kickstand allows positioning at various angles in both portrait and landscape orientations. Creative professionals will appreciate the large canvas for digital art and design work. The 18-inch display provides ample space for complex projects, while the foldable nature means you can still take this capability on the road. Business users can leverage the presentation mode for client meetings, with the large screen eliminating the need for external displays in many scenarios. Students might find the combination of note-taking capabilities and full-size keyboard particularly appealing. The ability to fold the device partially creates a natural reading angle for digital textbooks, while the performance specifications handle research and productivity applications with ease. Market Position Priced at CNY 23,999 (approximately $3,300) for the 1TB model and CNY 26,999 (roughly $3,700) for the 2TB variant, the MateBook Fold Ultimate Design positions itself firmly in the premium market. It will initially launch in China on June 6, with international availability planned for later dates. While foldable laptops aren’t entirely new, Lenovo pioneered the concept years ago, Huawei’s implementation represents a significant leap forward. The larger screen, thinner profile, innovative hinge mechanism, and comprehensive ecosystem integration through HarmonyOS demonstrate what’s possible when design and engineering excellence converge. The pricing strategy places this device in competition with high-end laptops and creative workstations rather than mainstream consumer devices. Huawei is clearly targeting professionals and enthusiasts who value cutting-edge technology and are willing to invest in unique capabilities not found elsewhere. Future Implications The MateBook Fold Ultimate Design doesn’t just represent another iterative step in laptop evolution. It reimagines what portable computing can be. Whether this specific implementation becomes the new standard remains to be seen, but Huawei has undoubtedly expanded our understanding of what’s possible in mobile computing design. As with most breakthrough technologies, we can expect the concepts pioneered here to eventually trickle down to more affordable devices. The engineering solutions developed for this premium device will likely inform future products across various price points, potentially making foldable displays a common feature in laptops within the next few years. The introduction of HarmonyOS to the laptop form factor also signals Huawei’s ambitions beyond smartphones and tablets. Creating a cohesive ecosystem across all computing devices could position the company as a more comprehensive alternative to established players in the personal computing space.The post Huawei’s MateBook Fold Ultimate Design Redefines Mobile Computing with World’s First 18-inch Foldable Display first appeared on Yanko Design.

Sick of warmed-over nostalgia? Here's how Disney could fix it.

When you purchase through links on our site, we may earn an affiliate commission. Here’s how it works. Vercel releases first AI model for v0, now in beta David Uzondu Neowin · May 22, 2025 02:18 EDT Google recently showered us with AI goodies, including Gemma 3n, an AI model that's designed to run on low-end devices, like smartphones. Now, Vercel has stepped further into the ring with its own generative UI system, v0, by releasing its very first dedicated model. If you do not know what v0 is, it is a sort of competitor to tools like the recently announced Google Stitch, which also aims to let you describe a user interface and have AI generate the design. The tool first saw the light of day back in 2023 as an invite-only beta, promising to turn natural language into front-end code. The newly available model is dubbed v0-1.0-md, and Vercel states it is specifically designed for building modern web applications. This multimodal model supports both text and image inputs, offers a 128,000-token context window with a 32,000-token output limit, and is priced at $3 per million input tokens and $15 per million output tokens. It offers features like 'auto-fix' for common coding blunders and 'quick edit' for streaming inline changes as they are generated. Crucially, v0-1.0-md uses an OpenAI-compatible API, meaning you can plug it into existing tools like Cursor, Codex, or your own custom applications that already speak OpenAI's language, including Vercel's own AI SDK. It even supports function and tool calls, and promises low-latency streaming responses. Developers can poke around with this new model in the Vercel AI Playground to see how it handles different prompts. Currently, access to the v0 API, and thus the v0-1.0-md model, is in beta, and you will need a Premium or Team plan on Vercel with usage-based billing enabled. To get started, you would grab an API key from v0.dev and then send requests to its POST api.v0.dev/v1/chat/completions endpoint, authenticating with a bearer token. While there are daily message limits around 200 messages and context size constraints that mirror its advertised capabilities, Vercel notes you can request higher limits if you hit those ceilings. If you want to dig into the details or see how to set it up, the official v0 docs on Vercel's site have everything you need, including examples. Tags Report a problem with article Follow @NeowinFeed

Three teenagers nearly escaped prosecution for a 2020 house fire that killed five people until Denver police discovered a novel investigative technique: requesting Google search histories for specific terms. Kevin Bui, Gavin Seymour, and Dillon Siebert had burned down a house in Green Valley Ranch, mistakenly targeting innocent Senegalese immigrants after Bui used Apple's Find My feature to track his stolen phone to the wrong address. The August 2020 arson killed a family of five, including a toddler and infant. For months, detectives Neil Baker and Ernest Sandoval had no viable leads despite security footage showing three masked figures. Traditional methods -- cell tower data, geofence warrants, and hundreds of tips -- yielded nothing concrete. The breakthrough came when another detective suggested Google might have records of anyone searching the address beforehand. Police obtained a reverse keyword search warrant requesting all users who had searched variations of "5312 Truckee Street" in the 15 days before the fire. Google provided 61 matching devices. Cross-referencing with earlier cell tower data revealed the three suspects, who had collectively searched the address dozens of times, including floor plans on Zillow. Read more of this story at Slashdot.