.@OpenAI seems to be echoing Ajeya Cotra's view that predicting scaling capability is key to managing AI safety. We can predict 10,000x ahead by extrapolating from smaller models. On that respect GPT4 has been a near-complete success using the now-familiar Azure supercluster.
@OpenAI In the generative AI era, it's very very good to be an OpenAI partner.
GPT4's image capability is launch exclusive to one nonprofit.
Khan Academy launched today with GPT-4 powered personal tutoring.
Whoop i just got let in to the ChatGPT4 beta!
This is going to get completely lost in the noise but @AnthropicAI launched Claude/Claude+ (with @notionhq and @poe_platform launch partner) and Google launched their PaLM API today as well
1. OpenAI's longest ever Context length: 128k 2. Better JSON/function calling 3. Knowledge: built in RAG and April 2023 cutoff 4. Dalle3, GPT4-V, and TTS model all in API today!!!
4b. Whisper V3 open sourced (coming to API) 5. Customization: GPT3 16k, GPT4 finetuning, Custom Models services 6. Higher Rate Limits - 2x tokens per minute, request raises in account settings - plus: Copyright Shield!
"GPT4 Turbo is a smarter model than GPT4" (GPT4.5 confirmed!)
@latentspacepod @thursdai_pod Friendship resumed with Satya senpai
it’s official - I think GitHub Copilot is the first* generative AI product to publicly claim they’ve passed $100m ARR — enough to stand alone as a publicly listed company
Whenever people ask me “is AI a fad” the biggest thing I point to is “follow the money”:
- revenue, not just funding
- RECURRING, not tcosts on hype
- people publicly saying they’d pay 5x the cost
(*there’s likely a few others but none confirmed officially - see Anatomy of Autonomy post on @latentspacepod)
next up is @DedyKredo LIVE CODING a full test suite, making code changes, and automating commit and PR review, all assisted by @CodiumAI . audible “what the fuck” from @eugeneyan.
Builders need a place to talk turpentine. This is why i'm teaming up with @benghamine to produce @aiDotEngineer, the definitive place to talk AI UX, devtools, infra, and all things AI Engineering.
since MoE is So Hot Right Now, GLaM might be the paper to pay attention to. Google already has a 1.2T model with 64 experts, while Microsoft Bing’s modes are different mixes accordingly
this is a trend I'm calling "Code is all you need"
Comparing Bard vs @OpenAI ChatGPT vs @AnthropicAI Claude on Google's own reasoning/math prompts shows the stark contrast once you make your model write and eval code to answer questions. Reminds me of @amasad and @goodside's… twitter.com/i/web/status/1…