Has anyone developed a method for (a) determining if the reasoning chain of thought is actually reasoning or if the model is pretending and - about half the time responses are incorrect because the model pretended to reason - feel like this would be useful for scaling RL
openai should buy xai, they get the infrastructure and xai ain’t gonna make it…. But you couldn’t pick two ceos less likely to make a deal so xai will putter out until they go bankrupt and xai will loose billions paying providers a premium on gpus
Prediction: Yann lecun’s days are numbered at Facebook ~ if he hasn’t been sidelined already
It’s a fundamental misalignment to have a leader push the narrative that AI isn’t cutting edge & changing the world, your either on the train, or pushing in the wrong direction
I love patterns that repeat over various periods.
One I just noticed:
Early Computer Era: founders working at night on mainframes that were unavailable/swamped during the day
AI Era: working at night, so you don’t get quantized llms
Innovators always identify ways to optimize
This ain’t it folks, R1 is way overhyped, it can generate human like ramblings that sound like your pal thinking through a problem, but 01 does a much better job at identifying the actual problem in large code chunks and actually provides solutions, no one hyping it has used it
I’m getting to the point of being comfortable in js, and by comfortable i mean that I’m getting used to my skin crawling and my brain slowly going into a coma atrophying while I type
Woke up today and realized Claude has fallen off the map, I use gemini and 01 exclusively now, the only time I touch Claude is for Frontend design, @AnthropicAI what happened guys? You fell off so hard, your sonnet is conversation and over complicates everything, what happened?
🚀 We have exciting news 🚀
We have acquired @codesandbox, a pioneer in code execution environments, and are joining forces to launch Together Code Interpreter—giving LLMs the ability to seamlessly execute the code they write.
Here’s why this is a big deal for AI developers 👇
How does nobody see the past week of product releases by anthropic and openai as the clear desperate cries for new data that they are - give me your files (mtcs) and give me all websites (browser) wink wink
Ever feel like GPT-4o has a metaphorical gun to its head, ready to shoot if it gets too chatty? It’s like coaxing your quietest friend into conversation, while GPT-3.5 and 4-turbo play it cool. But GPT-4o? I said ‘good morning,’ and 30 minutes later, it’s still going!
New paper where we explore using a small LM’s perplexity to prune the pretraining data for larger LMs.
We find that small LMs can prune data for up to 30x larger LMs, data pruning works in the overtrained and data-constrained regimes, and more!
arxiv.org/abs/2405.20541
💵 $1,000,000 and a Free Car: Join round two of the @Google Gemini Hackathon!
Remember the Gen AI hackathon I judged? Well, we're doing it again, but this time we're giving away $1,000,000 and a custom made car to people who build the most creative ideas using Google Gemini.…
🚨 Data is King in the LLM world! 👑 I am starting a thread of short, essential and actionable data advice. Here's Part 1: Improving Annotation 👇
Human annotators are vital for creating data & evaluating models. But annotation artifacts can lead to different types of spurious…
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