a sunny day with blue skies. a computer chip orchard. crates full of computer chips sit in the grass. a wooden sign says “Chips” –ar 4:3 –style raw –personalize 9zxyhz8
“I wonder how many Apple users know that iCloud isn’t fully managed by Apple? 🤔 Surprise! It’s actually a ‘hybrid cloud’ that leans heavily on Google Cloud and Amazon Web Services. Rivals in the streets. Lovers in the sheets. That’s just how it goes in Silicon Valley.
“Immersive video got a huge boost today with a new Blackmagic 3D camera + Resolve editing support. Insane specs: > 8K per eye @ 90 fps > That’s 235 megapixels! > 16 stops of dynamic range > Immersive RAW format w/ lens calibration metadata > Live preview on Apple Vision Pro 😎
How to Build an AI Data Center – by Brian Potter
Giant Chips Give Supercomputers a Run for Their Money – IEEE Spectrum
China Is Losing the Chip War – The Atlantic
AMD
AMD launches new AI chips to take on leader Nvidia | Reuters
NVIDIA
“1/ one of the biggest questions in AI today is: since GPT-4 was trained in fall 2022, we’ve collectively spent ~$100B on NVIDIA GPUs will the next generation of AI models’ capabilities live up to that aggregate investment level? NVIDIA qtrly datacenter rev, by @Thomas_Woodside
US agencies to probe AI dominance of Nvidia, Microsoft, and OpenAI | Ars Technica
Nemotron-4 340B | Research
We release the Nemotron-4 340B model family, including Nemotron-4-340B-Base, Nemotron-4-340B-Instruct, and Nemotron-4-340B-Reward. Our models are open access under the NVIDIA Open Model License Agreement, a permissive model license that allows the distribution, modification, and use of the models and their outputs.
NVIDIA Releases Open Synthetic Data Generation Pipeline for Training Large Language Models | NVIDIA Blog
“Nemotron-4-340B is released today! * Base, Instruct, Reward models * Permissive license * Great for Synthetic Data Generation * Designed to help others build their own models * Sized for inference on 8 NVIDIA H100 GPUs * Competitive across many tasks” / X
“Nemotron -4-340B-Reward: * Best reward model currently available *
“Nemotron-4-340B-Base: * Trained for 9T tokens on 6144 H100 GPUs * Using Megatron-Core at 41% MFU * 96 layers, 18432 hidden state * GQA, Squared ReLU
“Nvidia presents HelpSteer2 Open-source dataset for training top-performing reward models High-quality preference datasets are essential for training reward models that can effectively guide large language models (LLMs) in generating high-quality responses aligned with human
“1/ one of the biggest questions in AI today is: since GPT-4 was trained in fall 2022, we’ve collectively spent ~$100B on NVIDIA GPUs will the next generation of AI models’ capabilities live up to that aggregate investment level? NVIDIA qtrly datacenter rev, by @Thomas_Woodside
Nvidia Conquers Latest AI Tests – IEEE Spectrum
Nvidia’s New Sales Booster: The Global Push for National AI Champions – WSJ
Heads up! You’ve scrolled to the end of this category. There may have been just one or two links (above), so go back up and double check to be sure you didn’t quickly scroll down past it.
Be Sure To Read This Week’s Main Post:
This week’s executive overview and top links are here:
AI News #37: Week Ending 06/14/2024 with Executive Summary and Top 7 Must-Read Links
The post you just read is an deep dive extension of my weekly newsletter, This Week In AI, an executive summary of the top things to know in AI. Each week, I create an accessible overview for laypeople to feel confident they are conversant with the week’s AI developments. I include a curated list of must-click links of the week, to offer everyone a hands-on opportunity to explore the most intriguing updates in artificial intelligence across various categories, including robotics, imagery, video, AR/VR, science, ethics, and more. Beyond the overview, I post these topic-based deeper dives (below). If you haven’t read this week’s overview, I recommend starting there.
- Agents/Copilots
- Amazon
- Apple
- Artificial General Intelligence (AGI)
- Augmented and Virtual Reality (AR/VR)
- Autonomous Vehicles
- AI Audio
- Business and Enterprise AI
- Chips and Hardware
- Consumer Products
- Education
- Ethics/Legal Security
- Images/Photos
- International AI News
- Locally Run AI Models
- Mobile
- Meta
- Microsoft
- OpenAI
- Open Source
- Podcasts/YouTube
- Publishing and News
- Retrieval-Augmented Generation (RAG) News
- Robots and Embodiment
- Science and Medicine
- Video
- Vision/Multimodality
- X/Twitter/Grok
- Tech and Development
Credits/Sources
Most of these weekly links come from just a few prolific oversharing sources. Please follow them, as they work hard to find the news each week and they make it a lot easier for me to compile.
- Robert Scoble: https://x.com/Scobleizer
- Ethan Mollick: https://www.linkedin.com/in/emollick/
- Alan Thompson: https://lifearchitect.ai/
- Theoretically Media: https://www.youtube.com/@TheoreticallyMedia
- The Rundown: https://www.therundown.ai/
- Bilawal Sidhu: https://twitter.com/bilawalsidhu/
- TLDR: https://tldr.tech/ai
- Jeremiah Owyang: https://twitter.com/jowyang
- Nick St. Pierre: https://twitter.com/nickfloats
- Dr. Jim Fan: https://twitter.com/DrJimFan
- All About AI: https://www.youtube.com/@AllAboutAI
- Marshall Kirkpatrick: https://aitimetoimpact.com/
- AI News (Smol Talk): https://buttondown.email/ainews/archive/
- Andrej Karpathy: https://x.com/karpathy
- Brett Adcock: https://x.com/adcock_brett
- Florent Daudens: https://x.com/fdaudens
- Ate-a-Pi: https://x.com/8teAPi
- Francesco Marconi: https://x.com/fpmarconi
- Charlie Beckett: https://x.com/CharlieBeckett
For previous issues, please visit the archives!
Thanks for reading!
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