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NimbleBox Who? Say Hello to Tune AI

Hello Tuners,

In today’s edition:

  • NimbleBox Who?

  • Meta's Custom Chips: A Game-Changer in the Making?

  • Google Maps Gets an AI Makeover: Yay or Nay?

  • Apple's MGIE AI: The Future of Image Editing?

Introducing Tune AI: The New Face of NimbleBox

We're more than just a pretty new name; we're reppin' the future of AI, fine-tuning & deploying generative models for enterprises.

Remember ChatNBX, our LLM playground? it's been a hit with over 145,000 users since last July. We're multiplying like AI generations, and we're only getting started. Tune Now 

Meta's Custom Chips: A Game-Changer in the Making?

Meta's unleashing their second-gen custom chips in their data centers this year, and guess who's in their sights? None other than Nvidia.

They're trying to cut down on those hefty AI-running costs.

Mark Zuck himself let the cat outta the bag – by the end of 2022, they're aiming to replace 350,000 Nvidia processors with their own custom chips, which is A LOT.

Google Maps Gets an AI Makeover: Yay or Nay?

Google's about to give Maps a serious glow-up.They're teaming up with generative AI to help you discover even more rad spots in your 'hood.

So, how does it work? Think of it like this: you're hungry for some bomb tacos, but you've been to all the same spots. Instead of settling for Taco Bell (again 😭), you can type "places with a vintage vibe in SF" in Maps and boom!

Google's AI wizards will analyze EVERYTHING – from reviews and pics to the vibe of the place – and spit out some hidden gem taco spots that'll have you.

Apple's MGIE AI: The Future of Image Editing?

Apple just dropped a lit AI tool called MGIE (MLLM-Guided Image Editing) that's gonna change the game for editing pics.

Get this, it's open-source, so you can grab the code, data, and pre-trained models from GitHub or even test it out on Hugging Face spaces' web demo.

LLM Of The Week

BiLLM is a new method that makes big AI models like LLaMA-70B much smaller while keeping their accuracy very high.

For example, it makes models like the 70 billion parameter LLaMA-70B as small as 9.8GB, which is much smaller than other similar models like IQ3-XXS (27.5GB) or 4_K_KM (43.9GB).

Today's Goal : Try new things 🧪

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