Oh yes. I was trying to say you are right. The fleet only matters if it is connected. Communication technology.
SYSTEMS
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Tesla Autonomous Vehicle Powers Silicon Valley Daily Commutes
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My Tesla is in my garage and drives me everywhere in Silicon Valley. And the world.
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AndroidLab benchmark shows small fine-tuned models can power JARVIS
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> AndroidLab: First ever systematic benchmark for Android mobile agents shows that small, fine-tuned open models can power a JARVIS system on your smartphone A team from @Tsinghua_Uni just released AndroidLab, the first systematic framework to evaluate and train Android
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AI Platform Development Advances Announced
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New steps toward completing our AI platform – proud of the team!
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Google’s Jarvis AI Accidentally Revealed: Computer Control Capability
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Google accidentally leaked a preview of its Jarvis AI that can take over computers. In other words, Google’s new AI has the ability to take control of a computer to complete these simple tasks without manual human input.
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Six LLM Inference Modes Evolution and Future Trends
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The 6 "modes" of LLM inference, over time: – 2021: "large" models
– 2023: "turbo"/"mini" models
– Apr 2024: Batch API
– Sep 2024: Reasoning models
– Oct 2024: Realtime API
– Nov 2024: Speculative Decoding APIs seems pretty comprehensive. what else will be coming? -
Separating LLM Orchestration From Information Processing
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I agree, we should separate out when the LLM is used for orchestrating and when it is used for processing information. The more the two are tied together, the harder is it to debug.
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Google’s Gemini Inference Systems Expert Emanuel Shares Production Knowledge
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Don't miss this! Emanuel is one of my treasured colleagues for many, many years (I think we've made 20,000 cappuccinos together). He's got awesome knowledge of nearly every aspect of Google's production systems (including Gemini inference systems).
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Edge Computing Models: Necessity and Importance
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Its even necessary, to have models that run on the edge
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Benchmark Tests Complete Agent System Beyond Just Model
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The benchmark tests the entire "agent" system – not just the model, but also the software scaffolding around it that handles prompts, parses outputs, and manages the interaction loop.