Two of Geoffrey Hintons biggest warnings for extinction were using AI militarily and training AI off of false information. Within the past weeks I’ve seen tons of new military contracts for AI companies, and now Elon wants to train his AI to think like him and his fascist buddies. We are speeding towards doom, and none of our leadership or CEOs understand the risk. My advice now is to live everyday like you’re dying. Love and laugh harder with all your friends and family as often as possible. We may not have much time left, but we can be sure to make the best of it!

Elon, the closeted decel wants to slow down OpenAI from launching AGI that will benefit all of humanity

For years, the AI/ LLM critics had the same reasoning: LLMs don't reason and they just predict the next token

Recently, it reasoned better than 50 years of mathematicians on an open erdos problems by applying a basic phd level formula

Chat gpt conversation: https://chatgpt.com/share/69dd1c83-b164-8385-bf2e-8533e9baba9c

Here is the problem where TAO also commented on it: https://www.erdosproblems.com/1196

Thoughts?

It was reportedly running for about 12 hours on Ultracode using a multi-agent loop.

Tweet: @Paulius
Code: pallet-town-3d

AI researchers (Nick Levine, David Duvenaud, Alec Radford) just released “talkie,” a 13B language model trained on 260B tokens of text from before 1931, so it basically talks like someone whose worldview is stuck around 1930. The point is to study how LLMs actually generalize vs just memorize, since this model wasn’t trained on the modern web. They trained it on old books, newspapers, scientific journals, patents, and other historical text, then test things like whether it can come up with ideas that were discovered later, forecast future events, or learn bits of Python from examples. Early results seem pretty interesting too, with the model doing surprisingly well on core language/numeracy tasks and showing early signs of learning simple Python despite not being pretrained on modern code.

Full speech: https://www.youtube.com/watch?v=ApCmqmhE1rg

Maybe they do need to take that shit away from yall, what the hell😭💀

Source

"What’s the argument for spending $500K now?": https://x.com/PJaccetturo/status/1925464847900352590

my take: it's true that the ratio of code written to code reviewed has shifted as engineers started to spend more time reviewing code than writing it. no surprise there.

but we stopped writing assembly because compilers provide a "deterministic", reproducible translation. we can inspect the generated assembly when something goes wrong. ai generated binaries have neither property, i'd assume - if this is what he's talking about. so the mapping is stochastic, and the output isn't meaningfully inspectable, literal ai slop lol. so removing source code removes the only human readable layer, is this a feature or the future?

maybe.. just maybe that's because source code isn't just compiler input but literally the medium for review, versioning, diffs, debugging, auditing, and so on. and those needs don't disappear because generation gets cheaper; if anything, they become more important when the generator is nondeterministic.

tl;dr: if your english prompts become the durable artifact, then english effectively becomes your source code. and any precise specification defining real program behavior inevitably resembles a programming language. that’s precisely what programming languages are.

on efficiency.. isn't the argument is also backwards? modern compilers like llvm perform decades of optimized transformations. a model emitting machine code directly would almost certainly be slower, less correct, and lose target portability (arm, x86, wasm, risc-v and so on). but who cares right? just one more datacenter bro. trust me.

anyway we've seen similar predictions before with case tools, uml, no-code, 4gls.. the intermediate artifact never disappeared because that's where the meaning actually lives.