Very cool graphic 🔥

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I think AI agentic workflows will drive massive AI progress this year — perhaps even more than the next generation of foundation models. This is an important trend, and I urge everyone who works in AI to pay attention to it. Today, we mostly use LLMs in zero-shot mode, prompting

Study hard what interests you the most in the most undisciplined, irreverent and original manner possible.

Our acceleration towards AGI is much faster than many anticipate. And by AGI I mean God-level AI that can literally do anything, not just profit from stocks. The biggest and foremost risk of this is that we might not even realise when it's here because we don't know how it

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The beginning of memory is the end of childhood.

Wow! That’s a hell of a statistic. via Berber Jin The Wall Street Journal

Honoured to have been accepted in the Microsoft for Startups Founders Hub. Looking forward to building our upcoming tools and AI agents on the Microsoft Azure stack! Thank you Microsoft!

We still don’t know why LLMs work so well or how to internally control their outputs! But a recent landmark paper from Anthropic on ‘Mapping the Mind of a Large Language Model‘ attempts to make the inner workings of LLMs more transparent and interpretable. Why is this such a

Meanwhile, inside the box, Schrödinger's cat plans its revenge.

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NVIDIA's Rapids cuDF library is now available by default on Colab. It can accelerate pandas code by up to 50x on Colab with zero code changes. ⚡🐼 Try acceleration on pandas workloads with this 10-minute guide: colab.research.google.com/drive/12tCzP94…

All you need to know about Sam Altman.

One the the biggest disadvantages of using proprietary models is that if the host organisation changes the model (which they frequently do), your entire product falls apart. GPT-4o mini replacing GPT-3.5 Turbo is an example. Here's a great case for the bright future of open