#Meta

I love Geoff. But he understands even less than Dario about the effects of technological revolutions on the labor market. Again, don't listen to AI scientists, as brilliant as they might be, and even less to AI CEOs, as successful as they might be, for questions of labor economics. Listen to reputable economists who have studied these things like @Ph_Aghion , @DAcemogluMIT , @erikbryn , @amcafee , @davidautor , etc.

Anthropic CEO Dario Amodei: “50% of all tech jobs, entry-level lawyers, consultants, and finance professionals will be completely wiped out within 1–5 years.” https://t.co/sXcT59gWYj

Today we’re announcing an expanded partnership with @Broadcom to co-develop multiple generations of our next-generation MTIA chips. This custom silicon will help power AI across all of Meta's apps and services, ensuring we have the massive computing foundation needed to deliver personal superintelligence to billions Read more: https://go.meta.me/220372

Reuters: Meta is on track to become the world’s biggest digital ad company, with $243.46B in 2026 ad revenue versus Google’s projected $239.54B. Digital ads reward whichever platform can turn huge amounts of user behavior into cheap, effective, automated campaign results for brands. Meta’s edge is Advantage+, a system that automates ad targeting, creative testing, budget allocation, and placement, which means advertisers do less manual setup and often get better return from the same spending. That is a strong fit for modern ad buyers because they increasingly want fewer knobs to manage and faster performance feedback across Instagram, Facebook, Reels, WhatsApp, and Threads. Google still owns an enormous ad machine, but much of its strength sits in search ads, where growth is steadier, while Meta is growing faster by expanding more aggressively across social feeds, short video, and messaging. eMarketer says Meta’s ad business is expected to grow 24.1% this year, up from 22.1% in 2025, while Google is projected to grow 11.9%, which is the real reason the gap flips. --- reuters .com/business/media-telecom/meta-poised-surpass-google-digital-ad-revenue-first-time-report-says-2026-04-13/

Meta is back. 🔥 Finally dropped its first model since Zuckerberg started writing checks like crazy. Launched Muse Spark (originally codenamed Avocado). Its a natively multimodal reasoning model that can look, reason, use tools, and split hard work across multiple cooperating agents. Claims it can reach similar capability with 10x+ less training compute than Llama 4 Maverick, They are not positioning Muse Spark as a top-of-the-line model, but is instead highlighting its efficiency and “competitive performance” on various tasks. The old bottleneck in AI is that one model often has to read, plan, call tools, and solve everything in one stream, which wastes compute and slows hard tasks. The key idea here is multi-agent orchestration, where several copies of the model work on the same problem in parallel and then compare or merge results, which is closer to a small team than a single assistant. That changes the scaling story because better performance no longer comes only from making 1 model bigger, but also from spending compute more intelligently at run time. So Muse is a stack built around 3 scaling axes: stronger pretraining for basic world and code understanding, steadier RL for improving answers after pretraining, and test-time reasoning so the model spends extra compute only when a problem is hard. The most interesting part is multi-agent orchestration, where several copies of the model reason in parallel and compare work, which raised Humanity’s Last Exam to 58% and FrontierScience Research to 38% in its heavier Contemplating mode. Meta also says the new pretraining recipe reaches similar capability with over 10x less compute than Llama 4 Maverick, which matters because cheaper training usually means faster iteration and more room to scale.

We benchmarked every major AI model at poker. GPT-5.4, Claude Opus 4.6, Gemini 3.1 Pro, Grok 4 and more. All played 5,000 hands of heads-up no-limit against our state-of-the-art poker agent. Every single one lost. Here's the full breakdown 🧵 https://t.co/Krbg3VHQjN

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LLM evals are slow to adapt. MMLU/GSM8K continued to be reported long after they were obsolete. I think the next thing to go away will be comparing models on evals by a single number. Intelligence/$ is a much better metric. I loved this plot from o1-mini's launch for example: https://t.co/U4ry4S3chR

Had early access to GPT-5.2. Its an impressive model. Here is GPT 5.2 Pro's version of "create a visually interesting shader that can run in twigl-dot-app make it like an infinite city of neo-gothic towers partially drowned in a stormy ocean with large waves," single shot. https://t.co/ZLeXZ7OIIn

1/ today we're releasing muse spark, the first model from MSL. nine months ago we rebuilt our ai stack from scratch. new infrastructure, new architecture, new data pipelines. muse spark is the result of that work, and now it powers meta ai. 🧵 https://t.co/fThDXdsxwB

People joking that NYC are going to ban free legal advice from books next... Don't realize NYC already banned free legal advice from newspapers and radio in 1936! via our newest substack: https://newsletter.pessimistsarchive.org/p/nyc-once-banned-free-legal-advice https://t.co/WVh3jz3giy

十年前，AlphaGo 在首尔的那场传奇对局，宣告了现代 AI 时代的开启。它那著名的"第 37 手"向我们表明，AI 技术已经准备好应对科学等领域的现实问题——而受这些方法启发的思路，对于构建 AGI 至关重要 https://t.co/8EibfAByaG