Wrote this 2.5 years ago. Think it's still mostly right. I hope so. FWIW my personal usage of code peaked around 2017 when I first became deeply informed about Machine Learning and AI. But imagining and adapting to the evolving forest has never required expertise in the trees 引用 @dampedspring:The
Already running a model endpoint? What does it take to scale it on Kubernetes? In five minutes, we walk through how NVIDIA Dynamo handles deployment with scalable workers and an OpenAI-compatible endpoint. Watch below: https://t.co/S8uc5ljUIW
JPM’s chart puts global AI compute demand at ~450 GW in 2030 and ~530 GW in 2031. Translating that into capital and revenue shows aggressive these assumptions seem to be. At an illustrative $50B per fully equipped GW (low-end by the way as costs are moving up), supplying 530 GW 引用 @pequityresearch
"In the past year, Devin has gone from writing 13% of Cognition’s production code to more than 90%." This statement is particularly notable given that many consider Cognition as having one of the highest talent density with regards to AI talent and software engineering. 引用 @pmarca:https://t.co/lhP
based. now this is the type of respectful pushback & fact-based discourse we need. no horse in the race but rooted in fundamentals and facts. presenting the sources. Rittenhouse doing a lot to raise the level of discourse on this topic here and elsewhere on this site. 引用 @RHouseResearch:@daniel_k
Thought it'd be helpful to frame this in economic output terms relative to history: Anthropic staff's survey answers imply US real GDP growth of ~18.6% in the 12 months to January 2030 (17.1% in the model's log terms). In the BEA annual record back to 1929, comparable growth https://t.co/j1RJcEaOKC
Fair distinction on the terminology and it's not fair for me to blend them. My broader point is that the investment case still assumes today’s revenue persists and grows so you're still making the same implicit bet. In reality, subscribers can churn, API customers can reduce 引用 @ramez:@ShanuMat
大多数关注 AI 交易的投资者没有意识到,货币和财政政策一直是支撑这笔交易的一大底层驱动力。下一轮政策刺激(policy pump)将难得多。本周在博客 App 上免费阅读: https://t.co/LVoRhG3Yzp 【被引推文】下一轮政策刺激(The Next Policy Pump) 过去几年,市场一直受到财政和货币双重宽松的支撑,但这些利好将会逆转,这意味着任何新的刺激都将需要远为非常规的手段。 https://t.co/o3oq3TJ8lq 原文: Most investors focused on the AI trade don't get that monetary
这真的管用! Grok @Bot 可以自负盈亏。 https://t.co/GEZskbNU9h 【被引推文】我让我的 Grok Bot 去想办法自己挣钱。 我爱这个应用 https://t.co/g9SysaLINp 原文: This really works! Grok @Bot can pay for itself. https://t.co/GEZskbNU9h 引用 @mikepat711:I told my Grok Bot to go figure out how to pay for itself. I love this app https://t.co/g
Can anyone see a world in which we need five ( or more if you include non US) frontier models? I don't get how all can win. But not my lane. Like why would we need 5 roughly identical generalized models who leapfrog each other in capabilities instead of 2 or 3?
Building safer AI agents takes more than model safeguards. @perplexity_ai open sourced SPACE, the agent sandbox platform behind Computer, giving developers more control over where agents run code and what they can access. Cheers to more teams open-sourcing tools to build safer 引用 @perplexity_ai:W
Bubble Talk: Tulips to Tech Rational Dissent Episode 013 Despite bubbly valuations, persistent market skepticism suggests the AI boom is expanding like 1996—not collapsing like 2000. -- Available on YT, Spotify, Apple Podcasts, Overcast, etc. Chapters 00:00 - Introduction & https://t.co/zP8B4ZOu6i
AI agents are moving from answers to actions. But how do you safely run what they create? On Azure Friday, @shanselman and Jan Kalis explore how Azure Container Apps Sandboxes isolate agentic AI workloads. Watch now: https://t.co/4enIdHGpUI https://t.co/8H5XRqLGXm
New from our STEM Fellows Program: Designing more efficient quantum circuits with Claude. Given plain-language instructions, Claude Mythos 5 designed quantum circuits that improve on the best published ones, sometimes by an order of magnitude or more. More efficient circuits
Also, ask Grok @Bot to connect to your 𝕏 DMs. Best way to use it. 引用 @bot:Voice calls with Grok Bot are faster, more reliable, and better at remembering past conversations. https://t.co/v4vAZxNrf5
Grok @Bot got much faster 引用 @bot:Grok Bot is much faster. Computer tasks finish 3x sooner on average, and replies to everything else arrive in less than half the time.
最新@conferenceboard调查发现,近一半CEO预期未来三年AI将提升生产率并降低运营成本 https://t.co/yTaNSjJYs1 原文: Latest survey from @conferenceboard found that nearly half of CEOs expect AI to boost productivity and reduce operating costs over the next three years https://t.co/yTaNSjJYs1
I've been pretty clear about my skepticism around land, power and shells, though the rest of the world waking up in a big way could change the picture. The question is whether it happens, and on what timeline. “TSMC is very conservative and doesn't freelance. They're sending 引用 @DratchCap:Zoom out
Gemini Argon 4 crashed on the very first task I gave it (which was largely reviewing this infrastructure model I've developed with my corpus of compute + infra economics info over time)... not off to a promising start.
我们已经连续两份热通胀读数,可利率却在下滑。 整个市场都在…… 原文: We've had two hot inflation prints in a row, and yet rates have been sliding. The entire market is all about the AI trade, and the recent jitters about Anthropic's revenue numbers matter way more than some random government datapoint right now.
How do I use a Microsoft LLM? Where are they? I couldn't find an API on Openrouter. 引用 @mustafasuleyman:We now have state-of-the-art pre-trained base models in the 3T-parameter weight class, built entirely in-house at MAI. Post-training results coming soon -- stay tuned! Lots of details in our te
Figuring out how to prevent AI models from doing “rogue” things is obviously good. But I also agree with Alvaro here. We don’t know how the future will unfold, but extreme concentrated power per se is worrisome and it’s very plausible that creating strong AI will lead to that. 引用 @GroundhogStrat:So