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Here is what you missed:

💸 The accidental leak that sparked the LLM space

🙌 TechCrunch on YC Demo Day

🎮 Segmentation comes to AI

🙋 Being Polite is Key 🙋 

🪙 Nuggets of News 🪙

News snacks for the time-starved: grab a quick bite to stay up-to-date

1. Move Over GPT-3, Llama is Here to Steal the Show

   Well, well, well, the open source versus API-based distribution debate is rearing its head in the generative AI ecosystem. It's no secret that the biggest breakthroughs in language models like GPT-4 and Cohere are only available via APIs, leaving open source alternatives struggling to keep up. The release of Meta AI's Llama is shaking things up. Though not initially open-sourced, Llama's recent leak on 4chan has ignited a wildfire of innovation in the LLM space. Who knew an accidental leak could be such a blessing? With projects like Alpaca, Vicuna, and Koala popping up left and right, it's clear that Llama is the spark that the open source LLM space needed. 

   👉️ (Read More)👈️ 

2. YC AI can do that…Maybe

   So, there were a ton of startups presenting at YC Demo Days, and they all seemed to have one thing in common: "AI can do that, probably! Maybe." For the most part, most of the startups were throwing together a prefab UI and cherry-picking good examples to make it seem like their AI is amazing. Overall, a lot of these AI startups seem more like they're trying to fit into the trend of AI than actually creating something innovative.

   👉️(Read More)👈️

3. Segmentation comes to AI

   Introducing SegGPT, a jack-of-all-trades tool for figuring out what's in pictures and videos. It can handle all kinds of different segmentation tasks, from objects to text, just by looking at the context. SegGPT was trained to be a master of in-context coloring, so it can handle any color scheme you throw at it. We tested it on a bunch of different tasks, and it rocked 'em all, whether they were in its wheelhouse or not.

   👉️(Read More)👈️

📙The Daily AI Lexicon 📙

Boltzmann Machines

A type of neural network that is used for unsupervised learning

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