@srush_nlp Double descent! Due to early stopping, transformers are massively overparametrized. No bias variance tradeoff in this regime - sgd seems to have an inductive bias for “simple” solutions (literally min norm in case of linear regression)
Here's a letter we sent to Governor Newsom about SB 1047. This isn't an endorsement but rather a view of the costs and benefits of the bill. https://t.co/HhOTsdk7ui
Enjoying Claude Artifacts? Want to build the next generation of Human-AI Interfaces?
We're hiring an ML Lead for Artifacts.
This is a unique full-stack role where you'll help co-develop new user interfaces along with the model capabilities which support them. You'll work as closely with our Finetuning teams as our UX and design teams.
Strong front-end/design intuitions + decent ML Engineering experience. Come build:
https://t.co/5AnW1hC3jN
Many have said this already, but worth repeating: this is not correct.
We take security seriously and that's why we end-to-end encrypt your messages. They don't get sent to us every night or exported to us.
If you do want to backup your messages, you can use your cloud provider and you can even use end-to-end encryption for that too. Turn it on here: https://t.co/dxDkM9vn3H
I’m hiring ambitious Research Scientists at @AnthropicAI to measure and prepare for models acting autonomously in the world. This is one of the most novel and difficult capabilities to measure, and critical for safety.
Join the Frontier Red Team at Anthropic: https://t.co/5WT7xprWhA
We’re hiring for the adversarial robustness team @AnthropicAI!
As an Alignment subteam, we're making a big effort on red-teaming, test-time monitoring, and adversarial training. If you’re interested in these areas, let us know! (emails in 🧵)
Claude 3 Opus is great at following multiple complex instructions.
To test it, @ErikSchluntz and I had it take on @karpathy's challenge to transform his 2h13m tokenizer video into a blog post, in ONE prompt, and it just... did it
Here are some details:
How can we check LLM outputs in domains where we are not experts?
We find that non-expert humans answer questions better after reading debates between expert LLMs.
Moreover, human judges are more accurate as experts get more persuasive. 📈
https://t.co/jgyfCEQvfw