there's something genuinely beautiful about topology optimization you give it a load case, a boundary, and a material budget and it just… removes everything that doesn't need to be there no aesthetic intent no design language no human bias toward familiar shapes just physics deciding what stays the results look organic because nature runs the same algorithm stress flows material remains where it must everything else disappears engineers spent centuries adding material for confidence topology optimization asks a different question entirely: what's the minimum structure that doesn't fail? and the answer is always something that looks alive

Mathematician Terence Tao: "one thing this whole era of AI is teaching us is that our idea of intelligence is not really accurate" The history of AI has been: 'here’s a task only humans can do', and then one by one, an algorithm does it too Maybe we're not quite as smart as we think

The people saying "people don't know difference btw genAI and algorithmic AI" don't know the difference themselves This is gen AI, it literally takes in data, and generates drawings. But it gets it's data locally &ethically Please if you disagree tell me why this is not gen ai

Hi, I'm Felix. I'm an eng lead working on Claude. I love watching people take flight and do things they never thought possible. We often describe that as "being more ambitious" when using AI, which is tricky advice to follow. I wrote a tutorial: felixrieseberg.com/how-to-be…

I mean yeah this is a pretty accurate trajectory of a cannonball

This is a slide from Terence Tao's 'Math 2.0' public lecture yesterday evening at Caltech. I am highly confident that, if the cure actually worked, almost any Stage 4 cancer patient would tell you that human comprehension of its mechanism is completely irrelevant to them.

If you think AI is conscious, you should take a 3 to 6 month leave, stop using AI, uninstall social media, stop reading AI news, and touch grass. Seriously. I'm guessing the vast majority of high-level researchers haven't disconnected for longer than a week in the past decade.

An AI system is not a concrete thing. It’s an abstract, mathematical object. Saying that a sufficiently complex AI system might be conscious is like thinking that the number pi might be conscious

No it doesn’t. Statistically guessing solutions is not economically competitive in a large, high variance environment. There are no games you can play to make it so.

Everyone says Opus 5.5 is crazy. Best model. Massive jump. Blah blah. I still don’t think it’s better than Astra. Frontier LLM coding capability has plateaued after Opus 4.8.

Antigravity 2.0 now features a dedicated planning mode, just like the Antigravity CLI. Type /plan and the agent steps back to think through the task, and conduct extensive research, before generating an implementation plan for your review. The agent will ask for your approval before it begins executing on the task. You can also ask for a plan naturally in your prompt, for a lighter version of a plan.

it’s a shame to see someone like @NateSilver538 does not understand a basic, fundamental technical distinction. (@tristanharris and Kevin Roose missed it the other day, too.) pure LLMs were (very roughly and certainly not exactly) like stochastic parrots. harnesses, tools, code interpreters heralded the spread of neurosymbolic AI. the new systems are hybrids; they work differently. the somewhat weak metaphor is much weaker with them. but the fact that they are less like stochastic parrots doesn’t mean the original systems weren’t, nor that pure scaling worked. it means that neurosymbolic AI was an important next step. this still doesn’t mean we have AGI; most of the progress works best in verifiable domains; truly reliable general intelligence has certainly not yet arrived. (my 2020 article Next Decade in AI foresaw all of this, and what’s still missing, including world models, which i called cognitive models there.)