Like neurons, individual brains are too small to make sense of the world by themselves, but they are big enough to learn how to move freely through the space of ideas instead of being locked down by them. Substrates allowing unfiltered resonance between strong minds are valuable.
SYSTEMS
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Digital Twins Drive Business Resilience and Risk Management
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Join us for a panel discussion on #digitaltwins and business resilience at #IIoTWorldDay! This session will explore the critical role of digital twins in risk management, strategic planning, & technology resilience. Register today! https://
ow.ly/B5fL50QOMh7 #sponsored #cirrus_iiot -
Active Inference as a Solution to Distribution Shift in Models
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There are essentially two main options to remedy this: 1. Find ways to perform active inference, so that the model adapts its learned program in contact with a new data distribution at test time. Would likely lead to some meaningful progress, but it isn't the ultimate solution,
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UAI joins SOAFEE for energy-efficient AI acceleration autonomous driving
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UAI proudly joins #SOAFEE to drive energy-efficient #AI acceleration for software-defined vehicles. Our expertise will enable high-performance, low-latency solutions for #autonomous driving at the #edge & #cloud as centralized car platforms create demand. https://
tinyurl.com/untetherai-soa
fee
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Crowdsourced GPU Cluster Ratings and TPU Comparison
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Great post by Yi.
It's time for crowd-sourced ratings for GPU clusters. Maybe an AirBnB for GPU Clusters. I also tried to explain some of the differences between TPU clusters and most public GPU clusters; as well as made some practical recommendations here: -
GPU Cluster Ratings System: Reliability and Performance Comparison
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Great post Yi! We definitely need a Ratings mechanism for GPU Clusters (ala Airbnb for GPU Clusters). You are correct that large-scale GPU clusters that we carefully build are way more reliable and performant. I also want to point out some differences compared to TPU clusters
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AI, 5G, and Cloud: Transforming Connected Devices into Intelligent Systems
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We can envision a world where devices do more than connect—they learn and evolve. #AI is the driving force behind this transformation, with #5G providing the necessary speed, #IoT supplying abundant data, and #Cloud technology ensuring accessibility. #MWC24 @MWCHub @GSMA
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OpenAI vs Apple: Different AI Model Deployment Strategies
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Feels like OpenAI is going for the first model. I suspect Apple might do the second (your local Siri on your phone connects to SIRIAC when it can’t help you).
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Two Competing Visions for AI Agent Organization Architecture
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I see two competing visions of the future of organizing AI agents: In one, you talk to the smartest AI model first, and it decides what to delegate to dumber (but cheaper) models. In the other you start with a dumb local model & it calls for help from bigger models when needed.
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Grounding LLMs with Context: Does Sensory Data Change Arguments?
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If you ground the LLM consistently in a context (for instance by constrained them with sensory data, a personality model and memories of all previous interactions), does your argument change?