Exponential View

Exciting news! 🚀 I'm thrilled to share the joint research on the future of computing power I've conducted with Azeem Azhar and Nathan Warren from Exponential View, and Riccarda Joas and David Zuluaga Martínez from the BCG Henderson Institute. Many people worry that GenAI adoption will result in a computing power crunch. We ran the numbers and here’s what we found: - We're more likely heading towards compute abundance, not scarcity - By 2028, GenAI workloads will likely use only ~34% of the global AI computing supply - Energy and not hardware is more likely to constrain computing power supply Our analysis (read it here: https://lnkd.in/eVVdmSaH) shows that it is crucial for business leaders to understand that they need to plan for a future of orders-of-magnitude more compute, a future wherein AI will be able to conquer increasingly complex tasks. Stay tuned for Part 2 next week, where we'll explore strategies to capitalize on this compute abundance! What's your take on compute abundance? How might it reshape your industry? #AICompute #FutureOfTech #StrategicForesight #GenerativeAI #GenAI #ArtificalIntelligence

The world's computers consume vast amounts of energy, and this consumption is expected to triple by 2030. This comes on top of existing pressures on the grid. We know that energy efficiency gains in compute are reaching an impasse within the current computing paradigm, but what is the way forward? One potential solution can be found in reversible computing. I'll try to explain it simply: computers we use today perform operations that are irreversible, meaning once they compute something, you can't easily go back to the previous state. This irreversibility is what causes heat and energy loss. In contrast, reversible computing allows operations to be undone. Think of it like having a movie where you can watch scenes both forward and backward without losing any detail. By making operations reversible, computers can significantly reduce the amount of energy wasted as heat. This is because reversible operations can, in theory, recover and reuse energy that would otherwise be lost. The idea ties back to basic physics principles. The second law of thermodynamics says that systems naturally become more disordered over time (entropy increases), which typically results in energy loss as heat. Reversible computing tries to minimise this disorder and energy loss. With reversible computing, computers would generate much less heat. This is important because too much heat can interfere with computer performance. And as computers become more efficient, the demand for electricity to power them would decrease, which is crucial given the growing global energy needs. So, how could this all work out? David Galbraith wrote an essay explaining the science and history behind reversible computing in great detail for Exponential View. It is a must-read if you want to understand what alternative computing paradigms could look like in the near future. I'll link David's piece in comments. Image via DALL-E

"Breaking the energy barrier with reversible computing" an Exponential View guest post by David Galbraith ♻️ https://lnkd.in/emuE6EPE

I spoke with Azeem Azhar of Exponential View about: - How he thinks about the speed of progress in AI - Inevitability narratives, cultural affordances, centralization/decentralization - Future outlooks

Our 30 days of Charter 30 continues with Azeem Azhar, founder of Exponential View. Azhar's ability to distill complex topics into understandable concepts makes him a must-follow for anyone interested in technology and the future of work. His Substack, Exponential View, helps readers make sense of the latest updates in AI through great analyses and interviews with top-tier researchers and technology leaders. Read more about Azhar, and view our full list of Charter 30 honorees:

Do you distrust AI? Tech expert Azeem Azhar explains why you're not alone. Azhar is a member of the Global Future Council on the Future of Technology Policy, which brings together experts from various sectors to foster responsible technology governance and regulation. Learn more about it here: https://ow.ly/k9Po50QKI0a Azeem Azhari Exponential View

👏  𝐆𝐫𝐞𝐚𝐭 𝐬𝐞𝐬𝐬𝐢𝐨𝐧 𝐲𝐞𝐬𝐭𝐞𝐫𝐝𝐚𝐲 - (𝘧𝘪𝘳𝘦𝘤𝘩𝘢𝘵) 𝐖𝐡𝐞𝐫𝐞’𝐬 𝐭𝐡𝐞 𝐌𝐨𝐧𝐞𝐲 𝐢𝐧 𝐀𝐈? 👏 🙏 Thanks Azeem Azhar, Exponential View Founder & Gregory Shove, Section CEO Key Takeaways (from 🤖): 💡 𝙇𝙖𝙧𝙜𝙚 𝙘𝙤𝙢𝙥𝙖𝙣𝙞𝙚𝙨 𝙖𝙧𝙚 𝙪𝙨𝙞𝙣𝙜 𝘼𝙄 𝙩𝙤𝙤𝙡𝙨 𝙞𝙣𝙩𝙚𝙧𝙣𝙖𝙡𝙡𝙮 𝘵𝘩𝘳𝘰𝘶𝘨𝘩 𝘱𝘳𝘰𝘰𝘧𝘴 𝘰𝘧 𝘤𝘰𝘯𝘤𝘦𝘱𝘵𝘴 𝘣𝘶𝘵 𝘧𝘶𝘭𝘭 𝘪𝘮𝘱𝘭𝘦𝘮𝘦𝘯𝘵𝘢𝘵𝘪𝘰𝘯 𝘪𝘴 𝘤𝘩𝘢𝘭𝘭𝘦𝘯𝘨𝘪𝘯𝘨 𝘥𝘶𝘦 𝘵𝘰 𝘴𝘤𝘢𝘭𝘦, 𝘤𝘩𝘢𝘯𝘨𝘦 𝘮𝘢𝘯𝘢𝘨𝘦𝘮𝘦𝘯𝘵 𝘯𝘦𝘦𝘥𝘴, 𝘢𝘯𝘥 𝘰𝘵𝘩𝘦𝘳 𝘴𝘺𝘴𝘵𝘦𝘮𝘴 𝘪𝘯𝘵𝘦𝘨𝘳𝘢𝘵𝘪𝘰𝘯 💡 𝙋𝙧𝙤𝙙𝙪𝙘𝙩𝙞𝙫𝙞𝙩𝙮 𝙜𝙖𝙞𝙣𝙨 𝙤𝙛 𝙖𝙧𝙤𝙪𝙣𝙙 10-20% 𝘩𝘢𝘷𝘦 𝘣𝘦𝘦𝘯 𝘴𝘦𝘦𝘯 𝘪𝘯𝘵𝘦𝘳𝘯𝘢𝘭𝘭𝘺 𝘢𝘵 𝘤𝘰𝘮𝘱𝘢𝘯𝘪𝘦𝘴 𝘧𝘳𝘰𝘮 𝘶𝘴𝘪𝘯𝘨 𝘈𝘐 𝘵𝘰𝘰𝘭𝘴. 𝘏𝘰𝘸𝘦𝘷𝘦𝘳, 𝘮𝘦𝘢𝘴𝘶𝘳𝘪𝘯𝘨 𝘵𝘩𝘦𝘴𝘦 𝘨𝘢𝘪𝘯𝘴 𝘲𝘶𝘢𝘯𝘵𝘪𝘵𝘢𝘵𝘪𝘷𝘦𝘭𝘺 𝘤𝘢𝘯 𝘣𝘦 𝘥𝘪𝘧𝘧𝘪𝘤𝘶𝘭𝘵 𝘢𝘯𝘥 𝘪𝘴 𝘰𝘧𝘵𝘦𝘯 𝘢𝘯𝘦𝘤𝘥𝘰𝘵𝘢𝘭. 💡 𝙄𝙣𝙙𝙪𝙨𝙩𝙧𝙞𝙚𝙨 𝙡𝙞𝙠𝙚 𝙝𝙚𝙖𝙡𝙩𝙝𝙘𝙖𝙧𝙚, 𝙛𝙞𝙣𝙖𝙣𝙘𝙞𝙖𝙡 𝙨𝙚𝙧𝙫𝙞𝙘𝙚𝙨, 𝙖𝙣𝙙 𝙡𝙖𝙬 𝙖𝙧𝙚 𝙨𝙚𝙚𝙣 𝙖𝙨 𝙝𝙖𝙫𝙞𝙣𝙜 𝙜𝙤𝙤𝙙 𝙥𝙤𝙩𝙚𝙣𝙩𝙞𝙖𝙡 𝙛𝙤𝙧 𝙍𝙊𝙄 𝘧𝘳𝘰𝘮 𝘈𝘐 𝘥𝘶𝘦 𝘵𝘰 𝘭𝘢𝘳𝘨𝘦 𝘢𝘮𝘰𝘶𝘯𝘵𝘴 𝘰𝘧 𝘥𝘢𝘵𝘢, 𝘥𝘰𝘤𝘶𝘮𝘦𝘯𝘵𝘢𝘵𝘪𝘰𝘯 𝘸𝘰𝘳𝘬, 𝘢𝘯𝘥 𝘴𝘵𝘢𝘯𝘥𝘢𝘳𝘥𝘪𝘻𝘦𝘥 𝘱𝘳𝘰𝘤𝘦𝘴𝘴𝘦𝘴/𝘤𝘰𝘯𝘵𝘳𝘢𝘤𝘵𝘴. 𝘏𝘰𝘸𝘦𝘷𝘦𝘳, 𝘩𝘦𝘢𝘭𝘵𝘩𝘤𝘢𝘳𝘦 𝘪𝘴 𝘷𝘦𝘳𝘺 𝘳𝘦𝘨𝘶𝘭𝘢𝘵𝘦𝘥. 💡 𝙁𝙤𝙧 𝙨𝙩𝙖𝙧𝙩𝙪𝙥𝙨, 𝙛𝙤𝙘𝙪𝙨𝙞𝙣𝙜 𝙤𝙣 𝙨𝙤𝙡𝙫𝙞𝙣𝙜 𝙞𝙢𝙥𝙤𝙧𝙩𝙖𝙣𝙩 𝙥𝙧𝙤𝙗𝙡𝙚𝙢𝙨 𝘧𝘰𝘳 𝘸𝘦𝘭𝘭-𝘥𝘦𝘧𝘪𝘯𝘦𝘥 𝘤𝘶𝘴𝘵𝘰𝘮𝘦𝘳 𝘴𝘦𝘨𝘮𝘦𝘯𝘵𝘴 𝘢𝘯𝘥 𝘭𝘦𝘷𝘦𝘳𝘢𝘨𝘪𝘯𝘨 𝘈𝘐 𝘧𝘰𝘳 𝘪𝘯𝘯𝘰𝘷𝘢𝘵𝘪𝘰𝘯/𝘥𝘪𝘴𝘳𝘶𝘱𝘵𝘪𝘰𝘯 𝘳𝘢𝘵𝘩𝘦𝘳 𝘵𝘩𝘢𝘯 𝘴𝘵𝘢𝘳𝘵𝘪𝘯𝘨 𝘸𝘪𝘵𝘩 𝘵𝘩𝘦 𝘵𝘦𝘤𝘩𝘯𝘰𝘭𝘰𝘨𝘺 𝘪𝘵𝘴𝘦𝘭𝘧 𝘪𝘴 𝘢𝘥𝘷𝘪𝘴𝘦𝘥. 𝙑𝙚𝙧𝙩𝙞𝙘𝙖𝙡 𝙖𝙥𝙥𝙡𝙞𝙘𝙖𝙩𝙞𝙤𝙣𝙨 𝙞𝙣 𝙡𝙖𝙧𝙜𝙚 𝙞𝙣𝙙𝙪𝙨𝙩𝙧𝙞𝙚𝙨 𝙢𝙖𝙮 𝙥𝙧𝙤𝙫𝙞𝙙𝙚 𝙤𝙥𝙥𝙤𝙧𝙩𝙪𝙣𝙞𝙩𝙞𝙚𝙨. 💡 𝙏𝙝𝙚 "𝙂𝙋𝙏 𝘼𝙥𝙥 𝙎𝙩𝙤𝙧𝙚" 𝙢𝙤𝙙𝙚𝙡 𝙞𝙨 𝙨𝙩𝙞𝙡𝙡 𝙫𝙚𝙧𝙮 𝙣𝙚𝙬 𝘢𝘯𝘥 𝘪𝘵 𝘳𝘦𝘮𝘢𝘪𝘯𝘴 𝘵𝘰 𝘣𝘦 𝘴𝘦𝘦𝘯 𝘸𝘩𝘢𝘵 𝘵𝘺𝘱𝘦𝘴 𝘰𝘧 𝘢𝘱𝘱𝘭𝘪𝘤𝘢𝘵𝘪𝘰𝘯𝘴 𝘸𝘪𝘭𝘭 𝘣𝘦 𝘮𝘰𝘴𝘵 𝘴𝘶𝘤𝘤𝘦𝘴𝘴𝘧𝘶𝘭/𝘷𝘢𝘭𝘶𝘢𝘣𝘭𝘦 𝘪𝘯 𝘵𝘩𝘦 𝘭𝘰𝘯𝘨 𝘳𝘶𝘯 𝘰𝘯 𝘵𝘩𝘦 𝘮𝘰𝘥𝘦𝘭. 🅲🅷🅴🅲🅺 🅾🆄🆃 𝐒𝐞𝐜𝐭𝐢𝐨𝐧'𝐬 𝐀𝐈 🄲🄰🄻🄴🄽🄳🄰🅁 👉 https://buff.ly/3SHHc8Y 🙏 Last but not least, thank you to the rest of the #𝐒𝐞𝐜𝐭𝐢𝐨𝐧 team including Alex Maxwell, Ph.D. for organizing it! 🎟️  #lifelonglearning #personaldevelopment #AI #digitaltransformation #saas #startups #business

AI chip startup Groq (not to be confused with Musk’s Grok!) has put all its chips on the table. The team released a demo demonstrating Mixtral, an open-source LLM, running through their API, generating responses four times faster than other servicesat highly competitive rates. Unlike NVIDIA, which produces GPUs with versatile capabilities across various tasks, Groq’s processors are tailored for specific, high-performance AI computations, potentially offering more specialised efficiency in these areas. https://lnkd.in/d8mYKGHf

How many trillions of dollars does the chip industry need? Probably less than Sam Altman is looking to raise. Here is why. https://lnkd.in/gXSkvCsj #ai