David Smith

That does it. I am officially switching back to “Statistician”.

Always remember that when an LLM prints the beginning of a text, it has no idea what the end will be. Therefore, when it says "The answer is yes, and this is why:" the text after "why" would most likely be a very elaborate lie combined with gaslighting in case "yes" was the wrong answer.

Okay here's my argument for exactly how I think the "AI uses a bottle of water" statistic looks like it was miscalculated. It's a little in the weeds. Link below

Is there way on iOS to automatically hide notifications that begin with “A gunman”…?

What happens when you post a real Monet and say it’s AI? The coolest art social experiment I’ve seen in a while. Thank you @SHL0MS

@Mark_Graph That seems like an invocation of the No True Scotsman fallacy to me. Nonetheless the right measure to chart would be retail dollars spent per KWh consumed at home. I’d be interested to see those data if it existed (which I doubt, since all-home consumption isn’t tracked AFAIK)

The CPI electricity series measures retail prices paid by households on the grid. It doesn't capture the implicit savings of households who've gone solar. But that cuts both ways: the households who can't afford rooftop solar, who rent, or who live in apartments are the ones actually paying these retail prices, and the chart shows what's happened to them. There's a bigger structural point. Retail electricity prices reflect generation, transmission, distribution, and retail margins. Even if wholesale generation costs have fallen due to renewables, network costs and the costs of integrating intermittent generation (firming, transmission upgrades, capacity payments) flow through to the retail bill. The "cheap green electricity" promise was generally pitched as a retail outcome for consumers, not a wholesale-only metric or an "if you can afford panels" metric.

Remember the promise of cheap green electricity.

I have not laughed this hard in a very long time. Hang up your meeting and listen to this 🤣🤣🤣 “DIRECTIONALLY DIRECTIONALLY VERY BAD” 🎵

@AndyMasley Solar radiation of course. It’s right there in the name!

Learning via my comments that a ton of people are under the impression that solar panels pollute the land they are on. This seems to be completely fake but a lot of people believe it anyway. Like where would the pollution even come from?

This is a must-read for anyone concerned about the expanding lawlessness of the USA. (Gift link.) nytimes.com/2026/05/01/opi…

It’s been a tough stretch with GitHub availability. The feedback isn’t wrong. People depend on us, and we haven’t met that bar. Just know there are humans on the other side of this, reading all your comments and working as hard as we can to improve it. github.blog/news-insights/…

@holtbt Great to have you back!

I'm back at Microsoft after 4 years away! 🎉 I'm joining the Databases org as a Principal PM on Azure Postgres — VS Code extension, DX, and the agent experience. Also moving the family back to Seattle! Missed Microsoft. Missed Seattle. Excited for both!

Why the weird discontinuities at the :00 and :30 times? Physiology doesn’t care about clocks, so is it an artefact of training?

Four photos of Wimbledon’s Centre Court show how tennis has shifted: from grass worn across the whole court (serve-and-volley era) to damage almost only at the baseline today. A slower, power-driven game played from the back. The 1970 picture (top left) shows the grass played to a pulp all over the court, from baseline to net. In 1980 (top right), turf damage is visible in a T-shaped zone beyond the baseline. This damage to “volley valley” largely evaporates by 2005 (bottom left). By 2023 (bottom right), the service boxes appear entirely untouched, with only the baseline area showing wear and tear. Source: bigthink.com/strange-maps/d…

Excited to announce the new preview for Microsoft Foundry Agents 🎉! You can now build, run, and deploy your agent using any model, any framework, any harness in the cloud 🧑‍💻 - check out the demo below This is not just any cloud compute environment; it's an agent-optimized platform with: 🖥️ Persistent microVMs - securely scale up and down without losing context 🛠️ Built-in tools (1000+) 👀 Observability and evaluations 👷 Guardrails 🔐 Private networking... and more

Got 4th on the video game leaderboard and won this light cube. @slace didn’t even make 10th. #githubSydney

This is so good. The art of talking to people you disagree with —>

Funny how “God” worked it out for the octopus but not humans. Huh.

Rebooting my iPhone to make it connect to my AirPods like it’s fuckin Windows 95

Saw the EML paper blowing up yesterday so I thought: “What if I build a full LLM inference engine with it?” So I did. Meet emilio — an end-to-end inference engine where every single multiplication is replaced by the EML primitive: eml(x, y) = exp(x) - ln(y) No *. No +. Just this one wild operator (plus the constant 1) powering all the math: linear layers, attention, everything. It runs Qwen2.5-0.5B-Instruct (494M params) completely in EML and actually generates coherent text. → ~5.5 tok/s on CPU → ~30 tok/s on Apple Silicon GPU Not competing with llama.cpp on speed. This is pure proof-of-concept: showing the math actually works at transformer scale. A celebration of mathematical minimalism in the LLM era. Repo: github.com/videlalvaro/em… My paper (how I built + optimized it): github.com/videlalvaro/em… If you like weird math, extreme minimalism, or just watching someone go “hold my beer” after reading a paper… star it ✨ #LLM #MachineLearning #Math #Rust

The New York Times falls victim to the No True Scotsman fallacy. nytimes.com/2026/04/14/us/…