Find new artists and inspiration. With Runway Watch.
— Runway (@runwayml) 18 août 2023
Available now in browser and iOS. pic.twitter.com/0SYmFuYA7t
Find new artists and inspiration. With Runway Watch. Available now in browser and iOS.

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Find new artists and inspiration. With Runway Watch.
— Runway (@runwayml) 18 août 2023
Available now in browser and iOS. pic.twitter.com/0SYmFuYA7t
Find new artists and inspiration. With Runway Watch. Available now in browser and iOS.
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While the open LLM leaderboard provided (and still provides) a good starting point for a lot of companies exploring integrating LLMs into their products, the one-upmanship of it seems to be less and less of an indicator of whether a model is "good" for a specific product.
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We are demonstrating the AI initiatives of @MoHFW_INDIA @g20org Health Ministers' Meeting in Gandhinagar. We have developed advanced and sustainable AI technology to enhance current surveillance systems aiming to improve response effectiveness and health coverage. #G20India
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In particular, they "evaluate" by twisting the knobs, so to speak, until they land on a good user experience. If you've worked in data science or ML, that should sound like a very familiar experience.

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For the past several months developers have been obsessing over performance scores whenever a new LLM comes out. That may be changing, though, as some developers increasingly look for alternate ways to evaluate the success of products powered by AI.
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Saying UMAP is slower than PCA is "the glass is half-empty" view haha.
The more positive take is: UMAP is much faster than T-SNE!
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OpenAI acquires @illdotinc I guess the pressure is ON to raise more funds and survive in 2024 ( when their burn rate collapses) oh the joy of startups

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Only 15% of tech startup founders are female https://
bit.ly/3O1Fz5h via @VentureBeat #leadership #WomeninTech

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A free foundational course on machine learning by #ManaranjanPradhan. With 20 hours of recorded videos on YouTube, as well as numerous notebooks and exercises, it's useful for anyone looking to start learning about the basics of machine learning. https://
manaranjanp.com/docs/ML-Founda
tion
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The NeurIPS 2023 LLM efficiency challenge of course 🙂 https://
llm-efficiency-challenge.github.io Just recommend your Ulmfit paper with @seb_ruder to the students I am collaborating with the other day. Would be looking forward to the solutions you come up with for this one