From transformers to open-source LLM chatbots, generative AI has come a long way.
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Greetings,

 

According to the pioneers of generative AI, we’re still just seeing the aftermath, or “tech overhang”, of their foundational 2017 paper that introduced the Transformer architecture. It’s amazing how a small group of dedicated people can change the world with just one idea.

  • AI expert Santiago Valdarrama is moved to question whether software developers will still have jobs in a few years after using Gorilla, an open-source LLM trained to write API calls. - X thread, Gorilla page

  • “Attention is All You Need” was the formative paper that made generative AI possible – this is the story of how it came to be, who made it, and how it changed the industry. - Financial Times, alternative link: archive.today

  • A small team from Mozilla’s innovation group ran a hackathon to build an open-source LLM chatbot – here’s what they learned, invaluable information in case you want to build one too. - Mozilla

  • “As soon as it works, no one calls it AI anymore” – on the AI Effect, the broader Frontier Paradox, and why it might have been better if we’d never used the term AI. - Sequoia
     
  • Fascinating breakdown of 5 big AI risks based on lessons from self-driving systems – which, as the author notes, are based on the same principles as Large Language Models. - IEEE Spectrum

  • This offline-first, self-hosted (with a cloud version in the works), desktop AI assistant lets you search for and chat with notes, docs, images, even GitHub repositories. - Khoj

  • By using AI to cross-analyze data from modern humans, neanderthals, and denisovans, researchers are “bringing back molecules from the past” – an interesting new avenue for drug discovery. - Nature

 

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    kuba filipowski
    Kuba Filipowski
    CEO and Co-founder at Netguru
    LinkedIn
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