Apple outsourcing its chatbot to OpenAI is like IBM outsourcing its PC operating system to Microsoft.

As an engineer, I have nothing but respect and admiration for the human brain.

AI is a revolution, not a product.

We'll have AGI long before we figure out how the brain works. The brain is just very, very complicated. In fact, developing AGI is likely a prerequisite in order to make progress on understanding the brain.

Sitting neglected between memorization and hallucination is what LLMs do that really matters: generalization.

Saying that what LLMs do is compress the Web is like saying that what TVs do is generate heat.

Nature is pre-training. Nurture is fine-tuning.

i used to post some good stuff to the blue app

We stopped chasing money a while ago.

Far El From a 2016 talk: ('sufficient' here means sufficient for an AI's world model)

Google's claim of quantum supremacy has been completely smashed newscientist.com/article/243788…

The main benefit of having extensive programming experience isn't the ability to write software (which is a bit of a commodity -- you could hire someone to do it), it's how it changes the way you think.

A Japanese research team has developed a drug that uses RNA to target the USAG-1 protein to help regrow teeth. Creds aijamayrock via Reddit

We replicated the DeepSeek-R1-Zero and DeepSeek-R1 training on 7B model with only 8K examples, the results are surprisingly strong. 🚀 Starting from Qwen2.5-Math-7B (base model), we perform RL on it directly. No SFT, no reward model, just 8K MATH examples for verification, the

Jeremy, you know, 99% of the people who are talking about AI or LLMs on the internet don't know what they are talking about.

In 120 days, the global AI ecosystem will converge in Singapore. 7,000+ attendees, 150+ speakers, 2 unparalleled days to connect and co-create. Step into the future at Asia's Largest AI Event, 18-19 June 2025. superai.com

This is what flying in dreams feels like

Rich's slogans for AI research (revised 2006): 1. Approximate the solution, not the problem (no special cases) 2. Drive from the problem 3. Take the agent’s point of view 4. Don’t ask the agent to achieve what it can’t measure 5. Don't ask the agent to know what it can't verify

RL wisdom: be optimistic under uncertainty. It applies to life as well.