AI HARDWARE - AI Dynamics

Neuromorphic Computing And The Potential For Hyper-Realistic AI

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04 July 2023 20h01

Neuromorphic Computing And The Potential For Hyper-Realistic AI
#AI #AIio #BigData #ML #NLU #Futureofwork http://
ow.ly/NVwM30svSfj

→ View original post on X — @terence_mills

4 July 2023

Neuromorphic Computing: Advancing Hyper-Realistic Artificial Intelligence

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@terence_mills

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04 July 2023 20h01

Neuromorphic Computing And The Potential For Hyper-Realistic AI
#AI #AIio #BigData #ML #NLU #Futureofwork @gp_pulipaka @stratorob @PetiotEric @EvanKirstel @Fgraillot @HaroldSinnott @HeinzVHoenen @helene_wpli http://
ow.ly/xuQE30svStE

→ View original post on X — @terence_mills

4 July 2023

China’s dominance in gallium production raises semiconductor concerns

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@katecrawford

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04 July 2023 12h57

Gallium, of course, is a critical material for semiconductors. And China produces 80% of it. If you listen closely, you can hear the emergency meetings in session.

→ View original post on X — @katecrawford

4 July 2023

Computer Vision and Edge AI Innovation Events Announced

By

@axeleraai

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04 July 2023 9h38

An amazing semester filled with unforgettable events, connecting with individuals who share our passion for pushing the boundaries of #computervision in #edge AI! The excitement continues with upcoming events. Join us https://t.co/lcJNc4QEKq #ArtificialIntelligence #EdgeComputing pic.twitter.com/KfEOagPJBm
— Axelera AI (@AxeleraAI) 4 juillet 2023

An amazing semester filled with unforgettable events, connecting with individuals who share our passion for pushing the boundaries of #computervision in #edge AI! The excitement continues with upcoming events. Join us https://
axelera.ai/events/ #ArtificialIntelligence #EdgeComputing

→ View original post on X — @axeleraai

4 July 2023

Production capacity constraints limit AI hardware manufacturing

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@scobleizer

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04 July 2023 5h25

I have said for months they can’t make enough.

→ View original post on X — @scobleizer

4 July 2023

GPU Advances Enable Bigger, Wider LLM Model Architectures

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@replit

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03 July 2023 22h00

With newer GPU technologies, the shape of our LLM models will begin to change. Bigger, wider, models are now a possibility.

To learn more watch the full AI panel with @MosaicML’s Chief Scientist @jefrankle in conversation with Replit’s @amasad and @pirroh pic.twitter.com/A4g56a5Ztj
— Replit ⠕ (@Replit) 3 juillet 2023

With newer GPU technologies, the shape of our LLM models will begin to change. Bigger, wider, models are now a possibility. To learn more watch the full AI panel with @MosaicML
’s Chief Scientist @jefrankle in conversation with Replit’s @amasad and @pirroh

→ View original post on X — @replit

3 July 2023

Jensen-Shannon Divergence: DNN Training Reproducibility Issues on Nvidia GPUs

By

@rasbt

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03 July 2023 21h11

Haha good one . Jensen-Shannon divergence: Training DNNs on Nvidia GPUs is not reproducible due to randomly selected code

→ View original post on X — @rasbt

3 July 2023

Question about TPU and Nvidia GPU compatibility for suggestion

By

@rasbt

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03 July 2023 19h18

Thanks for the suggestion! That's only for TPUs, or would it also work on Nvidia GPUs?

→ View original post on X — @rasbt

3 July 2023

Reducing GPU Memory for LLMs and Vision Transformers in PyTorch

By

@rasbt

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03 July 2023 17h08

One of the big bottlenecks with LLMs & Vision Transformers is GPU memory on consumer devices. Wrote about my favorite techniques for reducing peak memory in PyTorch: https://
lightning.ai/pages/communit
y/tutorial/pytorch-memory-vit-llm/
… Focused on techniques that don't require architecture changes! Suggestions welcome!

→ View original post on X — @rasbt

3 July 2023