The fact that they are rebuilding every Apple Store to demo it shows Apple has a long term plan in action.
HARDWARE
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Vision Pro Apps Represent Long-Term Investment Opportunity
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That's awesome. Apps for Vision Pro will have a long future, so good on you on investing there.
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Version 3 lightweight glasses mainstream excitement potential
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Version 3 is lightweight glasses. That's what will excite the mainstream.
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Apple Strategy: Drawing Fans Into Retail Stores
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The target audience is the Apple fan. Get them into a store to try it.
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Spatial Computing Demos Drive Mass Adoption Strategy
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That said, they all will go get a demo. Which is really the goal here. Just get people used to the idea of spatial computing. That said, I can't wait to get mine.
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AWS Claims Largest Best-Performing GPU Clusters Cloud
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'We have the largest GPU clusters anywhere in the cloud. We have the best-performing GPU clusters in the cloud.' -Matt Garman, AWS SVP of sales and marketing https://
siliconangle.com/2023/06/28/exc
lusive-aws-sales-chief-matt-garman-amazon-aims-lead-generative-ai/
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Velox Robot Moves Seamlessly Across Water and Terrain
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Biomimicry at its best The Velox #robot can move through the water and over sand, pebbles, snow, ice, and other solid ground Cdt: Pliant Energy v/ @pascal_bornet #innovation #creativity #tech #Robotics #robots #AI #ML #Drone #Drones #AutonomousVehicles #ElectricVehicles
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SambaNovaAI DataScale SN30 Training at Argonne Testbed
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Join us for a 2-day training that will introduce users to the @SambaNovaAI DataScale SN30 system architecture and software stack, SambaFlow. The session will provide hands-on training to get started on the SN30 in the @argonne_lcf AI testbed. The event will be virtual and the
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Groq and BittWare Collaborate on Ultra-Low Latency ML Inference Chip
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@GroqInc and @BittWareInc are collaborating on a deterministic #ML #inference chip designed for ultra-low latency applications for real time #AI acceleration. For more information: http://
bittware.com/products/groq/. -
Memory-Lowering Techniques for PyTorch Hardware Optimization
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Depending on the hardware, and next to parameter-efficient finetuning, there are a bunch of memory-lowering techniques you can try. Summarized them here: https://
github.com/rasbt/pytorch-
memory-optim
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