3. Building AI Applications on Jetson Nano https://
learn.nvidia.com/courses/course
-detail?course_id=course-v1:DLI+S-IV-02+V2
…
AI HARDWARE
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Building Video AI Applications on Jetson Nano Course
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CPU GPU TPU support evolution in machine learning framework
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(Initial version supported CPUs. Later versions added support for GPUs and TPUs).
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Tactile Glove Devices: Data Collection Design and Feasibility
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The new efforts to collect touch data with gloves are very exciting, e.g. https://
manus-meta.com and https://
pressureprofile.com/body-pressure-
mapping/tactile-glove
… How hard is it to design and build these devices? It feels that once they become cheap enough, humans (NOT robots) can be paid to collect enough data to -
AI Wearables: Future Adoption and LLM Startup Viability
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The likely future. How long before everyone is using AI assistants via wearables? Does it represent an exit direction for LLM startups desperate to make money? How hard or costly is it to replicate the tech? Would love to hear serious thoughts on this.
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EU Digital Ambassadors Discuss AI, Chips, and Quantum Innovation
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When 23 digital EU ambassadors meet in Brussels, what do they talk about? #ArtificialIntelligence #chips #semiconductor #quantum #innovation #technology #digitaleu @DigitalEU @ArturHabant @elaniaz @PawlowskiMario @JolaBurnett @BetaMoroney @CurieuxExplorer @Shi4Tech @enilev… pic.twitter.com/uI9SNFncRH
— Nicolas Babin (@Nicochan33) 4 mai 2024When 23 digital EU ambassadors meet in Brussels, what do they talk about? #ArtificialIntelligence #chips #semiconductor #quantum #innovation #technology #digitaleu @DigitalEU @ArturHabant @elaniaz @PawlowskiMario @JolaBurnett @BetaMoroney @CurieuxExplorer @Shi4Tech @enilev
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GPU and Disk Constraints: Need for Smaller Dataset Variants
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I'm not only GPU poor but disk poor too. 350GB?
(And ofc doing so wouldn't be representative of the full data distribution)
Also while replying, ideally there could be a "dataset miniseries", e.g. 1B, 10B, 100B, and then full. I think would be very helpful and bandwidth saving. -
Cerebras AI Innovation Solutions for Enterprise
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Work with winners! Learn how Cerebras can bring AI innovation into your company. Contact us here: https://
cerebras.net/contact-us/ -
UAI’s Automotive AI Accelerator: EV and ADAS Integration
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UAI's @beach66 joined @sallywf on @eetimes
' "AI with Sally" podcast to discuss our automotive #AI #accelerator plans: Collab with @Arm for efficient #EVs Flexible architecture for #ADAS & voice AI Timeline for #vehicle platform integration https://
eetimes.com/podcasts/autom
otive-ai-adas-functional-safety-and-chiplets/
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llm.c Day 24: Multi-GPU Training in C/CUDA Outperforms PyTorch
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Day 24 of llm.c: we now do multi-GPU training, in bfloat16, with flash attention, directly in ~3000 lines of C/CUDA, and it is FAST! We're running ~7% faster than PyTorch nightly, with no asterisks, i.e. this baseline includes all modern & standard bells-and-whistles: mixed
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Rodney Brooks visits Matic Robots and praises their engineering
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Thanks @mehul and @navneetdalal for showing me around your company @maticrobots and sharing your passion for exquisitely well engineered solutions to hard problems using clever mixtures of mechanical design and just enough silicon compute.