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The Hard Part of AI Hardware - Is It Really That Hard?😟 ✅Watch Now: https://lnkd.in/gbwsugne At the CES 2024 Panel Talk, DEEPX's CEO, Lokwon Kim, is discussing the challenges of developing AI hardware and why it is a complex task. "AI itself is critically limited by semiconductor technology" You can watch the full version here! https://lnkd.in/gju8uQRh #AI #Hardware #Software #CES #PanelTalk #DEEPX #Semiconductors

A friendly tip if you're evaluating different methods to collect 13-bin classification data: don't tie yourself down into a single tech ecosystem. The AI detection software used to process that information should be agnostic to the cameras utilizes (granted, they need to provide more than potato-quality video), and vice-versa. Tech companies aren't exactly known for long-term hardware and product support. They have an incentive to move you on to the next round of products once they stop making enough money from their current line. Don't get lured in by something that looks shiny today and leave the next round of engineers and leadership holding the bag.

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What's New to The Street... 🚀📉 Dell’s AI margin slip is just a speed bump! Their strong position in the AI server market ensures solid pricing power, and the potential inclusion in the S&P 500 adds new momentum to the stock. How do you think Dell's focus on AI will shape its future? Share your insights below! ⬇️🤖💬 👉🏻Follow New To The Street for more! #Dell #ArtificialIntelligence #StockMarket #TechNews #businessnews #business #news #newtothestreet

Three elements of hardware to make it easier for Federal agencies to leverage #AI: 1️⃣Processing power 2️⃣Storage 3️⃣Communications More from Dell Technologies Ken Rollins and Art Villanueva: https://dell.to/3VxRURb #iwork4dell #Fed #Federal #iwork4dell

The fourth post in the Rational Reflections series is now up. Give it a read and let me know what you think! In the business world, an effective strategy can be to commoditize your complements, which can result in higher demand for your products while simultaneously lowering input costs. This month’s Rational Reflections explores how this concept is currently taking place in the artificial intelligence market, with NVIDIA attempting to lock in customers while the hyperscalers attempt to undo its moat. This fight will determine who controls the future of AI hardware and software. https://lnkd.in/dawiKMEz

I'm glad the Financial Times (Tim Bradshaw) is reporting on the breakdown of the so-called scaling law https://lnkd.in/e5kG6A3q; it’s about time the mainstream press called this out. The scaling law is this belief (if I’m being generous) or marketing gimmick (if I’m being more realistic) promoted by some AI figures like #Altman, which claims that more compute will inevitably lead to better AI accuracy and outcomes. This has been used as a justification for securing more capital for compute, with the notion that such extravagant investment will enable Altman and others to achieve AGI. There are two flaws in this logic: 1) Lack of #FormalLogic: Apple has already demonstrated that even o1 does not produce formal-logic results, a point discussed at length, including in my post here: https://lnkd.in/dQqcQnKW. Without additional techniques to improve AI models, brute force alone may not be sufficient. 2) #Exponential nature of the #ScalingLaw: The scaling law requires exponentially more compute and resources. To achieve the next level of AI output (on a linear scale) requires 10x more capital, resources, and energy. At some point, this would demand all the energy on Earth, or even in our solar system or galaxy, and current #LLM techniques may still not achieve AGI. Below, I transformed the famous “scaling law” graph from the o1 release into a linear scale; the limitations are quite clear. Current progress on #GenAI is phenomenal. There’s at least a decade’s worth of technology and applications to develop on top of what we already have. Let’s focus on putting the existing tools into production (there are still many kinks to iron out) while also in parallel making smarter bets on alternative paths to achieving #AGI." #ArtificialIntelligence #AIResearch #MachineLearning #ComputeLimits #AGI #TechInnovation #AIModels #LLM #EnergyEfficiency #AIProgress #GenAI #FutureOfAI #AIOptimization #TechSustainability Sirion Eigen Technologies

Three elements of hardware to make it easier for Federal agencies to leverage #AI: 1️⃣Processing power 2️⃣Storage 3️⃣Communications More from Dell Technologies Ken Rollins and Art Villanueva: https://dell.to/3VxRURb #iwork4dell #Fed #Federal #iwork4dell

What's New to The Street... 🚀📉 Dell’s AI margin slip is just a speed bump! Their strong position in the AI server market ensures solid pricing power, and the potential inclusion in the S&P 500 adds new momentum to the stock. How do you think Dell's focus on AI will shape its future? Share your insights below! ⬇️🤖💬 👉🏻Follow New To The Street for more! #Dell #ArtificialIntelligence #StockMarket #TechNews #businessnews #business #news #newtothestreet

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