Of course, Apple frameworks are far from optimized for ML model development. They're actually pretty bad! But the bar is ridiculously low for Apple here to improve on, and it seems like it's starting to do a lot of foundational work here to own those workflows.
AI
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Open Source AI Models Enabling New Development Workflows
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In that future, that's a workflow it actually has a shot at owning! And as OSS models continue to improve—particularly with the open sourcing of Falcon 40B last week—there will be much more development happening on top of those models rather than building from scratch.
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Apple Abandons Foundation Models, Focuses on Developer Ecosystem
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So here Apple has basically said, screw it, let's focus on the long tail of developers and leave the huge foundation model development to Nvidia. But that was really how it was always going to play out given the big Cuda dependency most large model training has.
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Trending AI News Stories and Papers
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Trending AI news stories + papers https://
open.substack.com/pub/akhaliq/p/
trending-ai-news-stories-papers-5d4
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Apple’s ML Strategy: Fine-tuning and Quantizing Models for Production
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Based on the announcements, as well as some descriptions from WWDC sessions, we can see a potential ML development route Apple is targeting: fine-tuning and quantizing ML models to put into prod.
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Apple Uses Transformers for Autocorrect, Positions Mac Studio for ML
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There were two essentially throwaway lines from WWDC yesterday. First, it's using a transformers-based approach for autocorrect, of all things. And the second was it wanted to semi-position its new Mac Studio with a comically large level of memory for ML training workflows.
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Apple’s AI Strategy: Speculation on Model Development Plans
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Okay! Today's issue of Supervised is about over-speculating on Apple's AI plans, as is the time-honored tradition with all Apple launches and product releases. For this we're looking specifically at what type of model development Apple wants to own.
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Meta’s MTIA AI Inference Accelerator: Key Problems Solved
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3️⃣ Important problems that MTIA, our first-generation AI inference accelerator solves. A closer look from Mahesh Maddury, Roman Levenstein & Linda Cheng; part of the team behind this work.
— AI at Meta (@AIatMeta) 6 juin 2023
Details on Meta Training and Inference Accelerators ➡️ https://t.co/9A4I1iwNGp pic.twitter.com/aQmJ4wqwN4Important problems that MTIA, our first-generation AI inference accelerator solves. A closer look from Mahesh Maddury, Roman Levenstein & Linda Cheng; part of the team behind this work. Details on Meta Training and Inference Accelerators https://
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Jensen Huang ServiceNow Partnership AI Generative Models Enterprise
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Watch our Founder and CEO Jensen Huang and @ServiceNow President and COO CJ Desai talk about the recent partnership, the future of #AI as an industry, and how #generativeAI models will transform enterprise #IT operations. Watch the entire video: https://t.co/UYfPJiA8Sf pic.twitter.com/Eh3U9ZlWHh
— NVIDIA (@nvidia) 6 juin 2023Watch our Founder and CEO Jensen Huang and @ServiceNow President and COO CJ Desai talk about the recent partnership, the future of #AI as an industry, and how #generativeAI models will transform enterprise #IT operations. Watch the entire video: https://
nvda.ws/43LyZEY -
Apple’s AR Strategy: Meta’s Failed Opportunity and Industry Dynamics
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This is why I told Meron Gribitz he was screwed. He started the Meta AR company, before it was sold for pennies on the dollar, and long before Mark Zuckerberg renamed his company to Meta. Apple gets billions in free PR. This is priceless. Inside the industry we call