Join us for a panel with @argonne on programming new AI accelerators for scientific computing. Hear from Victoria Godsoe, Manager of CX Engineering, about recent advances at @GroqInc
. @Supercomputing #HPC #AI #SuperComputing #HPCaccelerates #SCinet #SCInclusivity
INNOVATION
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Groq and Argonne Panel on AI Accelerators for Scientific Computing
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Databricks AI-Powered Holiday Recipe Finder App
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Did someone say…pie? Meet the Databricks Holiday Recipe Finder, an #AI-powered app that leverages text and image-based search to help you easily find the best recipes to add to your holiday table! What new recipes will be trying? https://
dbricks.co/3Ej5foT -
Automation Transforms Food Logistics With Robotic Solutions
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Food on the Move Means New Ways to Move Food https://
machinedesign.com/automation-iio
t/article/21253000/food-on-the-move-means-new-ways-to-move-food
… @ASMEdotorg @3DSNorthAmerica @Dassault3DS @cyngn @MargaretSiegien @Cindybolt61 @fogoros @DrFerdowsi @CRudinschi @PawlowskiMario @IIoT_World @MEngineeringMag #Engineering #Industry40 #Robots #AI #Manufacturing -
AI-Equipped Drones Track Endangered Black Rhinos in Namibia
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Check out our AI podcast and discover how a team of researchers has proposed harnessing high-flying AI-equipped drones powered to track the endangered black rhino through the wilds of Namibia: https://
nvda.ws/3Um1N2z -
How Insilico Medicine Uses AI to Accelerate Drug Development
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How Insilico Medicine Uses #AI To Accelerate Drug Development https://
forbes.com/sites/calumcha
ce/2022/11/09/how-insilico-medicine-uses-ai-to-accelerate-drug-development/
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Minting NFT copies of digital images on blockchain
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Until I mint my own NFT with a copy of the same image
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Brad Smith on Going Carbon-Negative with AI Technology
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Brad Smith explains why the world needs to go carbon-negative — and how to get there https://
buff.ly/3Tz7Mjn
#cop27 @microsoft #ai #ArtificialIntelligence #MachineLearning #DeepLearning -
New Algorithm Reduces AI Curiosity Problem With Intrinsic Rewards
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New algorithm overcomes the problem of AI being too “curious,” utilizing intrinsic rewards when they are helpful to save practitioners' time on deciding which algorithm to use on any new task: http://
bit.ly/3fStdhe -
Data Moats Overrated: UX and Distribution Win GenAI
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Many investors seem to think a data moat is what will lead generative AI companies to win in the coming years. Wrong. In a lot of cases, a small set of highly curated examples is all you need. Differentiate on UX, network effects, positioning, distribution, etc.
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Dataset Curation Strategy for AI Use Cases
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My rule of thumb: If the use-case doesn’t have a ‘right answer’, or is creative, curate small datasets. If the use-case has a ‘right answer’, lots of data is helpful and a moat will persist for a couple of years until models are ridiculously smart. Applies often but not always