Soon, LLMs will know when they don’t know. They’ll know when to say IDK, or instead ask another ai, or ask a human, or use a different tool, or different knowledge base. This will be a hugely transformative moment.
SYSTEMS
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Measuring AI Systems with Proper Evaluation Metrics
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Life becomes much better if you measure things with their proper measuring tools.
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Modal Logic in AI: Reasoning About Possibilities and Uncertainties
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Modal logic in AI extends classical logic to reason about possibilities and uncertainties. It includes artificial intelligence, database theory, distributed systems, programme testing, and cryptography theory. Read more about this concept here: https://
rb.gy/xoe8i -
Language Models and Semantic Layers Transform the Analyst Role
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Or, more specifically, what happens to the analyst role at some intersection of the emergence of the semantic layer and a language model to interact with it.
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End-to-End Learning Limitations: The Unspoken Assumption of Hardware
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EndToEnd learning is a fetish, even with pre-training. Why not include the computer, along with the software, and have that learned? Why the distinction? BECAUSE it won't work. The innate computing machine is assumed. Y'all are playing an intellectual game, but don't discuss it.
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30 MLOps Requirements for Building Machine Learning Systems
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Building Machine Learning Systems is hard. Here are 30 requirements for an MLOps environment. At @abacusai
, we worry about this for you. You bring the data; we do the rest. (Source: "Requirements and Reference Architecture for MLOps: Insights from Industry") -
Why Can’t We Simulate Mapped Brain Connectomes Computationally?
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There are many projects that have mapped whole-brain connectome of various creatures, from C. elegans (302 neurons) to Drosophila fruit fly (~100k neurons). With our current compute, why can’t we create accurate computer simulations of these creatures in a virtual 3D environment? https://t.co/PXCsnIaYAJ
— hardmaru (@hardmaru) 2 juillet 2023There are many projects that have mapped whole-brain connectome of various creatures, from C. elegans (302 neurons) to Drosophila fruit fly (~100k neurons). With our current compute, why can’t we create accurate computer simulations of these creatures in a virtual 3D environment?
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AGI Nodes: Silent Titans of Intellectual Renaissance
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[ A G I N o d e s ] AGI Nodes – the silent titans powering an intellectual renaissance. As we navigate the dawn of the AGI Era, let's remember: our future is shaped by our collective stewardship. #AGINodes #AGI #AGIFirst
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IoT AI Digital Twins at Collision Conference Toronto
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A year ago I attended the @CollisionHQ in Toronto, Canada, invited by @Siemens https://
linkedin.com/posts/marcusbo
rba_tbt-ai-iot-activity-7080281017533513728-16YJ
… #IoT #AI #DigitalTwins @JAdP @YvesMulkers @gvalan @mvollmer1 @anijov @CatherineAdenle @enilev @Damien_CABADI @avrohomg @Shi4Tech @fernandolofrano @Fabriziobustama @FmFrancois -
Qualification Problem in AI: Testing Machine Intelligence
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'Qualification problem' in AI refers to the challenge of testing a machine's intelligence. With varying ideas of what defines intelligence, specifically in cases of autonomous systems, can result in this problem. Explore its history & implications here: https://
rb.gy/w9g2o