✨🎨 Are you ready to unleash your creativity in a whole new way? Let’s dive into the magical world of ASCII ART in Blender! 🌟 With a simple method shared by Baeac, you can transform your vibrant Blender scenes into nostalgic ASCII masterpieces! 🎉 Imagine capturing the charm of the eighties by calculating the brightness of squares and matching them with stunning bitmaps! This technique opens the door to endless artistic possibilities, allowing you to express yourself in a fun and unique manner. So why wait? Grab your Blender and start creating your ASCII art today! 🚀💖 Stay inspired, keep creating, and remember: every masterpiece begins with a single square! 💪✨ #ASCIIArt #Blender #CreativeJourney

Garry Elmendorf isn’t just a special effects supervisor, he’s a master of controlled chaos. With over 50 years in the business, from Logan’s Run in the ’70s to the high-octane worlds of Yellowstone, 1883, 1923, and Landman. Elmendorf has shaped the visual DNA of Taylor Sheridan’s TV empire with a mix of old-school craft and jaw-dropping spectacle. In the latest fxpodcast, Garry joins us to break down the physical effects work behind some of the most explosive moments in Landman. As regular listeners know, we occasionally conduct interviews with individuals working in SFX, rather than with VFX. Garry’s work is not the kind of work that’s built in post and his approach is grounded in real-world physics, practical fabrication, and deeply collaborative on-set discipline. Take the aircraft crash in Landman’s premiere: there was no CGI here, other than comp cleanup. It was shot with just a Frankenstein plane built from scrap, rigged with trip triggers and detonated in real time. Or the massive oil rig explosion, which involved custom pump jacks, 2,000 gallons of burning diesel and gasoline, propane cannons, and tightly timed pyro rigs. The scale is cinematic. Safety, Garry insists, is always his first concern, but what keeps him up at night is timing. One mistimed trigger, one failed ignition, and the shot is ruined. In our conversation, Garry shares incredible behind-the-scenes insights into how these sequences are devised, tested, and executed, whether it’s launching a van skyward via an air cannon or walking Billy Bob Thornton within 40 feet of a roaring fireball. There’s a tactile intensity to his work, and a trust among his crew that only comes from decades of working under pressure. From assembling a crashable aircraft out of mismatched parts to rigging oil rig explosions with precise control over flame size, duration, and safety, his work is rooted in mechanical problem-solving and coordination across departments. In Landman, whether coordinating multiple fuel types to achieve specific smoke density or calculating safe clearances for actors and crew around high-temperature pyrotechnics, Elmendorf’s contribution reflects a commitment to realism and repeatability on set. The result is a series where the physicality of explosions, crashes, and fire-driven action carries weight, both in terms of production logistics and visual impact. Listen to the full interview on the fxpodcast. #fxpodcast #landmans #special #effects #explosions

© Henrique Ferreira via Unsplash Finding property lines can be tricky, especially for individuals who are looking to purchase or list a home for sale. Conventional techniques, including engaging surveyors, are costly and labor-intensive. As an alternate solution, technology provides apps that profess to show property lines. This raises the question: How precise are these digital resources at demarcating boundary lines? The emergence of an app that shows property lines has revolutionized how property owners, buyers, and real estate professionals interact with land boundaries. These digital tools leverage advanced mapping technologies to provide visual representations of property boundaries, offering a more accessible alternative to traditional surveying methods while raising important questions about their accuracy and reliability. What Are Property Line Apps? Apps that display property lines use Geographic Information Systemsand satellite imagery. They offer users a visual display of land boundaries, most commonly available on smartphones or tablets. These apps are meant to help make property borders easier to identify and are a helpful tool for property owners, real estate agents, and buyers. These applications typically draw information from public records, county assessor data, and other official sources to create digital representations of property boundaries. Many also incorporate user-friendly features like measurement tools, parcel information displays, and the ability to save or share property data with others. How Various Factors Affect Accuracy Several factors impact the reliability of property line apps. First, the source of the data is significant. Apps usually have access to government databases and public records that vary in accuracy based on when the data was last refreshed. Second, GPS technology limitations impact accuracy. Although GPS technology is becoming more advanced, apps might still have discrepancies where tree cover or high buildings block signals from satellites and influence tracking accuracy. The resolution of satellite imagery also plays a crucial role in determining how precisely property lines can be displayed. Higher-resolution images allow for more detailed and accurate boundary placements, while lower-quality imagery may result in less precise representations. Additionally, the frequency of data updates affects whether the app reflects recent property divisions, consolidations, or boundary adjustments. Comparing Traditional Surveying and Apps Professional surveyors approach property line determination using high-precision equipment and established methodologies. This traditional approach yields highly accurate results with precise and legally enforceable boundaries. Apps offer more general information on property lines compared to professional surveys. While they are fast and convenient, they provide no substitute for the precision of a professional survey. App-generated boundaries should not be relied upon as definitive indications of legal property lines. Traditional surveys involve physical measurements taken directly on the property, considering historical markers, neighboring properties, and legal descriptions. In contrast, apps rely on digital interpretations of existing records, which may not account for all the nuances that a professional surveyor would observe in person. Advantages of property line applications App-Generated Property Lines Property line apps may have their limitations, but they do have valuable uses. They are useful for general assessments where an immediate overview of boundaries may be required. The applications also have user-friendly interfaces that allow a wider audience to use these applications and learn technical skills. Additionally, they are often enhanced with more functionalities, such as calculating areas and providing land parcel information, thus expanding their usefulness for users. According to the U.S. Bureau of Land Management, these digital tools have significantly increased public access to property information that was previously difficult to obtain without professional assistance. This democratization of property data allows property owners to be more informed about their land assets and helps potential buyers better understand properties of interest before making major decisions. Potential Limitations and Risks Property line apps may be convenient, but they have clear limitations. Since the data relies heavily on public records, data errors are common. It can be outdated or incomplete, which can lead to misunderstandings or disputes. In addition, these apps are incapable of recognizing legal nuances, such as easements or encroachments, which can significantly impact property rights and boundaries. There is also a risk that users might place too much confidence in app-generated boundaries when making important decisions. While these tools can provide helpful guidance, they should not be the sole basis for resolving boundary disputes, building structures near property lines, or making purchase decisions without professional verification. Best Practices for Users Users should follow a few best practices to make the best and most effective use of a property line app. Cross-referencing results with official records verifies data accuracy, minimizing potential inaccuracies. Moreover, when app data is paired with physical inspections, it provides a fuller picture of property lines. Advice from professionals, including surveyors or real estate agents, can also be beneficial, especially for legal transactions. For important matters such as property purchases, boundary disputes, or construction projects near property lines, it’s advisable to use apps as preliminary tools only, following up with professional surveys before making final decisions. Understanding the limitations of these digital tools helps users utilize them appropriately within a broader strategy for property boundary determination. Conclusion Instead, property line apps provide a convenient and accessible way to determine where your land ends and where your neighbor’s begins. Yet, the precision of these tools is contingent on multiple factors such as data sources and technological limitations. Although useful as an initial step, these tools should not be used, and they should not be used for legal purposes, instead of professional surveys. Users can properly contextualize property boundary information by understanding what these applications can and cannot do. Technology continues to shape how we deal with real estate by digitalizing and providing easy access to tools that simplify complex processes. These apps will likely improve accuracy over time and become increasingly integral to property transactions. Until then, users must balance convenience with reliability, ensuring that the information they obtain is helpful and accurate. Smart Technologytechnology by ArchEyes Team Leave a comment #how #accurate #are #apps #that

If, like me, you’re slightly addicted to your astrology app and love checking your daily horoscope, you may have wondered just how much stock you should put into it. Allow me to tell you that it may be more revealing than you think. Sure, your zodiac sign can give you guidance on when to make a big move or when to save a certain conversation for a better, star-blessed date. But, did you know it can also help you decorate? That’s right. Your astrological sign can give you insight into what no-regret color you should choose for your kitchen, living room, bedroom or if you *actually* should go all in on maximalism. To answer all your decorating questions, we sat down with astrologer Sam Manzella to chat about the impact astrology can have on how you decorate your home and to find out what she thinks are the best paint colors for each astrology sign.Want even more astrology content? Check out these stories.Meet Our AstrologerSam Manzella is a Brooklyn-based astrologer and multi-award winning journalist. She practices a Hellenistic tradition, working from ancient frameworks, including the Whole Sign house system, sect, and traditional rulerships. Additionally, her practice is based around the planetary rulers that were visible to the naked eye in the age before telescopes, also called the seven core planets, meaning that the outer planets of Uranus, Neptune, and Pluto won't be making an appearance in this article. The Signs, Their Rulers, and Their Color FamiliesLet’s start with the basics: There are 12 signs in Western astrology. You’ve probably heard of them—think Aries, Cancer, Libra, etc. While most modern mainstream astrology focuses heavily on the signs, it’s actually their relationship to the planets that has the biggest impact on your day-to-day. “In astrology, planets, not zodiac signs, are the main players,” says Sam. This more nuanced and wholistic approach to astrology uses planets to determine what will happen, while signs only dictate the how. “Pop astrology often relies too heavily on zodiac sign archetypes, in my opinion,” says Sam. “Place a planet in a specific sign? Now we’re cooking, baby.”When it comes to matching up planets and colors, millennia of traditional associations guide the way. Sam’s color coordination is based on two works: The Complete Picatrix, a Medieval text on astrological magic, and Hellenistic Astrology: The Study of Fate and Fortune, a traditional astrology manual written by storied astrologer Chris Brennan. Below, we’ll break down the seven core planets, the signs that correspond with them, and their traditional color associations.MarsSigns: Aries, ScorpioColor Associations: Strong, aged shades of red and rust. VenusSigns: Taurus, LibraColor Associations: Sumptuous natural shades, such as greens, pinks, whites, and pastels.MercurySigns: Gemini, VirgoColor Associations: Orange is a good color for Mercury, but mixes of patterns and colors also works well for these Mercurial signs. SunSigns: LeoColor Associations: Classic sunny shades, such as golds and yellows. MoonSigns: CancerColor Associations: Silvery shades and crisp whites. JupiterSigns: Sagittarius, Pisces. Color Associations: A mix of royally influenced shades, such as purples, blues, and yellows. SaturnSigns: Capricorn, AquariusColor Associations: Dark and moody shades, such as browns, blacks, and grays. How Can You Use Astrology to Help You Decorate? The best place to start is at the very beginning. Sam’s advice? Call your mom. “I highly recommend calculating your full birth chart—to do so, you’ll need the exact date, time, and location of your birth.” This will give you the proper framework from which you can build your astrologically inspired home. Once you have your complete birth chart, look at your various planetary alignments. While your sun sign can tell you a lot about who you are, it’s actually your Venus placement that Sam recommends consulting. “This planet governs art, beauty, and romance—if it’s sweet, enjoyable, or aesthetically pleasing, then it probably falls under Venus’s purview. Whatever zodiac sign this planet occupies in your birth chart can tell you a lot about the vibes, color palettes, and visual aesthetics you gravitate toward.” Not sure you have all the information you need for a full birth chart? No worries, we’ve pulled together the best paint color for you based on your zodiac sign and planetary ruler below. If you want to dive a little deeper, Sam recommends checking out the planetary placement in your Fourth House. “The Fourth House represents our home and family life. Whatever planet rules this house, and its placement by zodiac sign, reflects the energy that feels like home to you.”The Best Paint Colors for Every Zodiac Sign: #best #paint #colors #every #zodiac

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. What’s next for AI and math The modern world is built on mathematics. Math lets us model complex systems such as the way air flows around an aircraft, the way financial markets fluctuate, and the way blood flows through the heart. Mathematicians have used computers for decades, but the new vision is that AI might help them crack problems that were previously uncrackable.   However, there’s a huge difference between AI that can solve the kinds of problems set in high school—math that the latest generation of models has already mastered—and AI that couldsolve the kinds of problems that professional mathematicians spend careers chipping away at. Here are three ways to understand that gulf.  —Will Douglas HeavenThis story is from our What’s Next series, which looks across industries, trends, and technologies to give you a first look at the future. You can read the rest of them here. Inside the effort to tally AI’s energy appetite —James O’Donnell After working on it for months, my colleague Casey Crownhart and I finally saw our story on AI’s energy and emissions burden go live last week.  The initial goal sounded simple: Calculate how much energy is used when we interact with a chatbot, then tally that up to understand why leaders in tech and politics are so keen to harness unprecedented levels of electricity to power AI and reshape our energy grids in the process.It was, of course, not so simple. After speaking with dozens of researchers, we realized that the common understanding of AI’s energy appetite is full of holes. I encourage you to read the full story, which has some incredible graphics to help you understand this topic. But here are three takeaways I have after the project. This story originally appeared in The Algorithm, our weekly newsletter on AI. To get it in your inbox first, sign up here, and check out the rest of our Power Hungry package about AI here. The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 Elon Musk has turned on Trump He called Trump’s domestic policy agenda a “disgusting abomination.”+ House Speaker Mike Johnson has, naturally, hit back. 2 NASA is in crisisIts budget has been cut by a quarter, and now its new leader has had his nomination revoked.+ What’s next for NASA’s giant moon rocket? 3 Here’s how Big Tech plans to wield AITo build ‘everything apps’ that keep you inside their ecosystem, forever.+ The trouble is, the experience isn’t always slick enough, as Google has discovered with its ‘Ask Photos’ feature.+ How to fight your instinct to blindly trust AI. 4 Meta has signed a 20-year deal to buy nuclear power It’s the latest in a race to try to keep up with AI’s surging energy demands.+ Can nuclear power really fuel the rise of AI?  5 Extreme heat takes a huge toll on people’s mental healthIt’s yet another issue we’re failing to prepare for, as summers get hotter and hotter.+ The quest to protect farmworkers from extreme heat. 6 China’s robotaxi companies are planning to expand in the Middle East And they’re getting a warmer welcome than in the US or Europe.+ China’s EV giants are also betting big on humanoid robots. 7 AI will supercharge hackersThe full impact of new AI techniques is yet to be felt, but experts say it’s only a matter of time.+ Five ways criminals are using AI. 8 It’s an exciting time to be working on Alzheimer’s treatments 12 of them are moving to the final phase of clinical trials this year.+ The innovation that gets an Alzheimer’s drug through the blood-brain barrier. 9 Workers are being subjected to more and more surveillanceNot just in the gig economy either—’bossware’ is increasingly appearing in offices too.10 Noughties nostalgia is rife on TikTokIt was a pretty fun decade, to be fair.Quote of the day  “This is scientific heaven. Or it used to be.” —Tom Rapoport, a 77-year-old Harvard Medical School professor from Germany, expresses his sadness about Trump’s cuts to US science funding to the New York Times.  One more thing OLCF What’s next for the world’s fastest supercomputers When the Frontier supercomputer came online in 2022, it marked the dawn of so-called exascale computing, with machines that can execute an exaflop—or a quintillionfloating point operations a second.Since then, scientists have geared up to make more of these blazingly fast computers: several exascale machines are due to come online in the US and Europe.But speed itself isn’t the endgame. Researchers hope to pursue previously unanswerable questions about nature—and to design new technologies in areas from transportation to medicine. Read the full story. —Sophia Chen We can still have nice things A place for comfort, fun and distraction to brighten up your day.+ If tracking tube trains in London is your thing, you’ll love this live map.+ Take a truly bonkers trip down memory lane, courtesy of these FBI artifacts.+ Netflix’s Frankenstein looks pretty intense.+ Why landlines are so darn spooky #download #ais #role #math #calculating

Author Hi, I've downloaded a recent android app called NCM - Next Chess Move and it states that it uses stockfish on the device. I've did some digging up and it seems it's true, it's calculating moves even when the internet is off,Being interested in chess and studies this in the past I though then , because of the licensing for Stockfish, the source code for this app must be public right ? And if that is the case, any way I could find the source code for this app ?The license for Stockfish is GPLv3.  Author I'm  interested in this since I've been toying with the idea of creating a closed source 3D chess game and would be so much better to use Stockfish locally than on a server. Can anyone point in the right direction, please ?  Advertisement The author of NCM should be able to point you in the right direction Note that GPL affects all software around it. If you combine it with other software, the other software then carries the GPL license as well.In other words you cannot leverage GPL software and wrap it in closed source without also publishing the code of the closed source. It's tricky. There are ways to mix GPL and non-GPL software, but it needs a good lawyer who is comfortable with software generally and the nuance of the GPL specifically.It is tricky but possible to build up non-free tools and software that rely heavily on F/OSS systems, including GPL systems. For example, they might build a standalone chess engine and release the engine portions and interface under the terms of the GPL, and also have their UI and front-end that interfaces with it which they sell. There would need to be a clear, clean break between them, but it is possible to do and has been done on a few projects.I don't see them under an LGPL license, but those are similarly able to co-exist with proper lawyer involvement. Companies like EA have a page where they distribute the libraries with source and the implementation changes they made. Author Is it possible then to use Stockfish: 1. On a server and distribute the server code ?2. Build a binary framework, link to that and only distribute the binary framework if building an app with it ? Advertisement I am not a lawyer and cannot answer if any specific way is sufficient to avoid a lawsuit.The license is trying very hard to make it impossible to use the software in a non-free/open source context.  If you want to do it anyway and be legally safe, talk to a lawyer.Alternatively, don't go there. Yup, it's generally best to be 100% in or 100% out unless you have careful legal reviews by experienced lawyers. Working with GPL, release it all GPL and you are safe. Not touching anything with GPL, release it without source as a proprietary system and you are safe. It is possible to mix them, but only when you have lawyers involved asking difficult questions about the details. No lawyers, don't mix it.  GPL does not demand you reveal source code when the program is only interacted with over the internet. It only demands you publish the entire source code to the person whose machine it is running on, basically. Also, as soon as you use a GPL component in a project, the entire project needs to be GPL, but you may use sub-components in the parent project that are non-GPL. But the overall parent project must be under a GPL license.If you want a GPL license that also enforces the open-sourcing when interacted with over the network, choose AGPL. You can use GPL dependencies in an AGPL parent project, but you cannot use AGPL dependencies in a GPL parent project. There is also the LGPL which is a bit less ideologically strict. #stockfish #gplv3 #commercial #apps

Estimating the time required to complete a task is riddled with pitfalls.Let’s start with two key concepts you must understand — after managing and designing projects for over 20 years, I’ve seen these patterns play out again and again.Hofstadter’s lawHofstadter’s law is a self-referential adage about time that goes like this:“It always takes longer than you expect, even when you take into account Hofstadter’s law.”This law highlights how difficult it is to accurately estimate the time required to complete complex tasks. Its recursive nature reflects the widespread experience that, no matter how complex a task appears, calculating the time needed is hard, even with our best efforts.Why is that?Optimism biasThe main reason stems from the tendency known as optimism bias — the inclination to be overly optimistic and thus overestimate favorable outcomes. In fact, we tend to overestimate our own abilities as well.It’s worth noting that this bias is actually quite necessary for humans: without it, we wouldn’t take risks, start businesses, or grow. However, when it comes to estimation, it can seriously backfire. This phenomenon naturally leads to…Planning fallacyOverly optimistic forecasts about the outcomes of plans are almost everywhere. Daniel Kahneman and Amos Tversky introduced the term planning fallacy to describe how we consistently underestimate the necessary resourceswhen planning complex projects. This phenomenon pushes us toward optimistic planning. Unsurprisingly, we’re much more realistic when reviewing someone else’s plan.In short:We overestimate favorable outcomes and our abilities, and we underestimate the required resources and constraints.What can we do?As I mentioned earlier, I’ll share how I personally handle this. The phenomenon is not new, and there are countless methods available.2x + 15 ruleFor smaller tasks, I use this technique. I look at the task, estimate the number of hours, double it, and add 15 minutes. The extra 15 minutes is to get started and immerse yourself in the task. Most of the time, it works quite well and is incredibly simple.Hofstadter multiplierMy teammates track and record the actual time spent on tasks, which is useful for several reasons. First, it helps everyone gain experience with how long typical tasks take, which they can then compare to their own estimates, improving their estimation skills. Second, you can determine your own — or a particular person’s — so-called Hofstadter multiplier. We’re all different, so this is a more advanced, personalized version of the 2x + 15 rule.Complex projectsThe earlier solutions work well for simpler tasks, but complex projects require additional considerations. But first, it’s important to clarify one question:How much energy can you, or do you want to, invest in the estimate/proposal?From there, more questions arise:Is it a rough indicative proposal or a detailed, itemized one?What inputs, expertise, and professionals are needed for the estimate?Is all necessary information available?How much capacity do you havefor the estimation and/or execution?Do you realistically have a chance of winning the work? :)Your answers to these questions will influence the path you choose.Going back to the planning fallacy for a moment: it can be mitigated by involving a third party or by relying on real data from similar past projects.That’s why it’s crucial to keep precise records of the time spent on every task so that the data is available later.You will log the time for every task. — Obi-Wan KenobiMoving on…In an ideal world, the best approach is for the team that will actually execute the project to estimate it together. But consider how much it costs if a 4–5 person team individually reviews and interprets the materials, discusses them together, collects missing information, breaks down the project into items, and estimates each one using some method. It’s incredibly time-consuming and expensive.Therefore, as a substitute, it’s good to have an experienced person who’s seen many projects and/or to rely on actual hours from similar past projects. In this case, you only need to account for the differences and unknownsat the time of the proposal. Estimation becomes much simpler, faster, and cheaper.For indicative proposals, I almost always use this latter method, with one important addition: always assume a ±20% variation.Whoa, be careful!It may seem like you’ve done something similar before, but hidden behind the scenes are major differences. This can lead to nasty surprises if you rely on data from nearly similar projects. In such cases, it’s wise to consult multiple external teams to benchmark the work. This helps refine the estimate and creates a healthy competitive environment.And when a detailed, itemized proposal is necessary… There’s no shortcut: you’ll need to apply a methodology. I won’t even attempt to cover this topic here, as there are entire books written about the relevant methodologies.FinallyI’ve been in the product design profession for over 20 years, and I often play the game where, after hearing the requirements, I throw out a number almost off the top of my head. It works surprisingly often, but of course, I wouldn’t even call it indicative. Still, it’s fun.Estimating time for complex projects was originally published in UX Collective on Medium, where people are continuing the conversation by highlighting and responding to this story. #estimating #time #complex #projects

AI could soon surpass Bitcoin mining in energy consumption, according to a new analysis that concludes artificial intelligence could use close to half of all the electricity consumed by data centers globally by the end of 2025.The estimates come from Alex de Vries-Gao, a PhD candidate at Vrije Universiteit Amsterdam Institute for Environmental Studies who has tracked cryptocurrencies’ electricity consumption and environmental impact in previous research and on his website Digiconomist. He published his latest commentary on AI’s growing electricity demand last week in the journal Joule. AI already accounts for up to a fifth of the electricity that data centers use, according to de Vries-Gao. It’s a tricky number to pin down without big tech companies sharing data specifically on how much energy their AI models consume. De Vries-Gao had to make projections based on the supply chain for specialized computer chips used for AI. He and other researchers trying to understand AI’s energy consumption have found, however, that its appetite is growing despite efficiency gains — and at a fast enough clip to warrant more scrutiny.“Oh boy, here we go.”With alternative cryptocurrencies to Bitcoin — namely Ethereum — moving to less energy-intensive technologies, de Vries-Gao says he figured he was about to hang up his hat. And then “ChatGPT happened,” he tells The Verge. “I was like, Oh boy, here we go. This is another usually energy-intensive technology, especially in extremely competitive markets.” There are a couple key parallels he sees. First is a mindset of “bigger is better.” “We see these big techconstantly boosting the size of their models, trying to have the very best model out there, but in the meanwhile, of course, also boosting the resource demands of those models,” he says. That chase has led to a boom in new data centers for AI, particularly in the US, where there are more data centers than in any other country. Energy companies plan to build out new gas-fired power plants and nuclear reactors to meet growing electricity demand from AI. Sudden spikes in electricity demand can stress power grids and derail efforts to switch to cleaner sources of energy, problems similarly posed by new crypto mines that are essentially like data centers used to validate blockchain transactions. The other parallel de Vries-Gao sees with his previous work on crypto mining is how hard it can be to suss out how much energy these technologies are actually using and their environmental impact. To be sure, many major tech companies developing AI tools have set climate goals and include their greenhouse gas emissions in annual sustainability reports. That’s how we know that both Google’s and Microsoft’s carbon footprints have grown in recent years as they focus on AI. But companies usually don’t break down the data to show what’s attributable to AI specifically.To figure this out, de Vries-Gao used what he calls a “triangulation” technique. He turned to publicly available device details, analyst estimates, and companies’ earnings calls to estimate hardware production for AI and how much energy that hardware will likely use. Taiwan Semiconductor Manufacturing Company, which fabricates AI chips for other companies including Nvidia and AMD, saw its production capacity for packaged chips used for AI more than double between 2023 and 2024. After calculating how much specialized AI equipment can be produced, de Vries-Gao compared that to information about how much electricity these devices consume. Last year, they likely burned through as much electricity as de Vries-Gao’s home country of the Netherlands, he found. He expects that number to grow closer to a country as large as the UK by the end of 2025, with power demand for AI reaching 23GW. Last week, a separate report from consulting firm ICF forecast a 25 percent rise in electricity demand in the US by the end of the decade thanks in large part to AI, traditional data centers, and Bitcoin mining. It’s still really hard to make blanket predictions about AI’s energy consumption and the resulting environmental impact — a point laid out clearly in a deeply reported article published in MIT Technology Review last week with support from the Tarbell Center for AI Journalism. A person using AI tools to promote a fundraiser might create nearly twice as much carbon pollution if their queries were answered by data centers in West Virginia than in California, as an example. Energy intensity and emissions depend on a range of factors including the types of queries made, the size of the models answering those queries, and the share of renewables and fossil fuels on the local power grid feeding the data center. It’s a mystery that could be solved if tech companies were more transparentIt’s a mystery that could be solved if tech companies were more transparent about AI in their sustainability reporting. “The crazy amount of steps that you have to go through to be able to put any number at all on this, I think this is really absurd,” de Vries-Gao says. “It shouldn’t be this ridiculously hard. But sadly, it is.”Looking further into the future, there’s even more uncertainty when it comes to whether energy efficiency gains will eventually flatten out electricity demand. DeepSeek made a splash earlier this year when it said that its AI model could use a fraction of the electricity that Meta’s Llama 3.1 model does — raising questions about whether tech companies really need to be such energy hogs in order to make advances in AI. The question is whether they’ll prioritize building more efficient models and abandon the “bigger is better” approach of simply throwing more data and computing power at their AI ambitions. When Ethereum transitioned to a far more energy efficient strategy for validating transactions than Bitcoin mining, its electricity consumption suddenly dropped by 99.988 percent. Environmental advocates have pressured other blockchain networks to follow suit. But others — namely Bitcoin miners — are reluctant to abandon investments they’ve already made in existing hardware. There’s also the risk of Jevons paradox with AI, that more efficient models will still gobble up increasing amounts of electricity because people just start to use the technology more. Either way, it’ll be hard to manage the issue without measuring it first. See More: #could #consume #more #power #than

If the adoption of AI feels different from any tech revolution you may have experienced before — mobile, social, cloud computing — it actually is. Venture capitalist Mary Meeker just dropped a 340-page slideshow report — which used the word “unprecedented” on 51 of those pages — to describe the speed at which AI is being developed, adopted, spent on, and used, backed up with chart after chart. “The pace and scope of change related to the artificial intelligence technology evolution is indeed unprecedented, as supported by the data,” she writes in the report, called “Trends — Artificial Intelligence.” There’s a certain poetic history to this person writing this kind of report. Meeker is the founder and general partner at VC firm Bond and was once known as Queen of the Internet for her previous annual Internet Trends reports. Before founding Bond, she ran Kleiner Perkins’ growth practice, from 2010-2019, where she backed companies like Facebook, Spotify, Ring, and Block.  She hasn’t released a trends report since 2019. But she dusted off her skills to document, in laser detail, how AI adoption has outpaced any other tech in human history.  ChatGPT reaching 800 million users in 17 months: unprecedented. The number of companies and the rate at which so many others are hitting high annual recurring revenue rates: also unprecedented. The speed at which costs of usage are dropping: unprecedented. While the costs of training a modelis up to billion, inference costs — for example, those paying to use the tech — has already dropped 99% over two years, when calculating cost per 1 million tokens, she writes, citing research from Stanford.  Techcrunch event now through June 4 for TechCrunch Sessions: AI on your ticket to TC Sessions: AI—and get 50% off a second. Hear from leaders at OpenAI, Anthropic, Khosla Ventures, and more during a full day of expert insights, hands-on workshops, and high-impact networking. These low-rate deals disappear when the doors open on June 5. Exhibit at TechCrunch Sessions: AI Secure your spot at TC Sessions: AI and show 1,200+ decision-makers what you’ve built — without the big spend. Available through May 9 or while tables last. Berkeley, CA | June 5 REGISTER NOW The pace at which competitors are matching each other’s features, at a fraction of the cost, including open source options, particularly Chinese models: unprecedented. For example, she points out that Nvidia’s 2024 Blackwell GPU uses 105,000x less energy per token than the company’s 2014 Kepler GPU predecessor.  Meanwhile, chips from Google, like its TPU, and Amazon’s Trainium, are being developed at scale for their clouds — that’s moving quickly, too. “These aren’t side projects — they’re foundational bets,” she writes. The one area where AI hasn’t outpaced every other tech revolution is in financial returns. While VCs are pouring money on the AI fire as fast as they can, AI companies and cloud service providers are also burning through cash. AI requires massive investments in infrastructure.  That’s good for consumers and enterprises, the beneficiaries of fast improvements, while competition lowers costs, Meeker points out. But the jury is still out over which of the current crop of companies will become long-term, profitable, next-generation tech giants. “Only time will tell which side of the money-making equation the current AI aspirants will land,” she writes. As for the rest of us: Just hold on to your hats. #its #not #your #imagination #speeding