Since a diagram is worth a 1000 words, and public is confused about what developments in #AI mean for robotics, I took some time to draw this. Feedback welcomed.
This. And with a few lines of code, you can search on 10s of millions of embeddings on your laptop CPU. With a GPU, that can be in the billions. I haven't yet figured out why people pay for vector search unless it's the same crowd that does "npm install stringreverse".
I think current GPT “agents” are very limited in capacity (you can try using them to see what I mean). Often getting lost the deeper the task goes or just outright failing to make any progress
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Introducing "🤖 Task-driven Autonomous Agent"
An agent that leverages @openai's GPT-4, @pinecone vector search, and @langchain framework to autonomously create and perform tasks based on an objective.
"Paper": https://t.co/MT5WxB0Ebo
[More 🔽]
@StefanKarpinski This doesn't need to be the case per se, Haskell is getting better support for unboxed types for example.
Also there are languages such as gibbon and sixten (https://t.co/KMQOkxh6xf) which are exploring new approaches to this problem!
I am sooooooo excited for this paper. We've spent years developing a super fast program induction library. We use it to learn key pieces of language structure.
So much of what Chomskyan linguists say about learnability is totally wrong.
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https://t.co/JVZQ56OVhb
Some folks find this movie hard to fathom.
This is not a rendering it is humanity seeing our largest planet in the solar system.
This is Cassini passing by Jupiter’s great red spot and moons Io and Europa in the foreground.
Magical moments.
I love working with JavaScript, and I’m grateful for the people who make the tools without which I couldn’t work.
Still, I find myself puzzled every time I have to spend hours on plumbing instead of code, and reminds me of the fragility of the ecosystem.
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