A breakout year for artificial intelligence
#RuleoftheRobots #AI
MACHINE LEARNING
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Artificial Intelligence Marks Breakout Year in Technology
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NLP and Quantum Computing Drive Financial Innovation
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#NLP & #quantum computing could drive years of new financial innovation, says @NVIDIAAI
's Mark J. Bennet. Could 2023 be the first year for you? Find out how in the Finance and Insurance #DataScience Innovator's Playbook https://
domino.buzz/3X8GNgH #MLOps -
Chinchilla’s implications: Dataset size over model size in LLMs
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Great post (5mo ago) "chinchilla's wild implications" giving context to LLM goldrush shifting from model size to dataset size following Chinchilla https://
lesswrong.com/posts/6Fpvch8R
R29qLEWNH/chinchilla-s-wild-implications
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Subtle important detail: analysis assumes 1 epoch. Recent work (e.g. Galactica) gives hope for 1+ regime. -
Top Digital Skills for Product Delivery in 2026
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6 of the top #digital-age skills for product delivery >>> @PMInstitute via @MikeQuindazzi >>> #AI #IoT #DataAnalytics #DataScience #CloudComputing #CyberSecurity >>> Global #Megatrends Report: http://
shorturl.at/lJP17 -
Abacus AI: End-to-End MLOps Platform for Scalable Solutions
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If you have made it here, Check out this end-to-end MLOps platform by @abacusai that lets you build scalable ML solutions out-of-the-box https://
abacus.ai -
Five things to consider before choosing MLOps tools
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Five things to keep in mind before finalizing the MLOps tool for your team. (A thread) cc: @abacusai
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Bring Your Own Model Platforms: MLOps in a Box
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The future of machine learning for many out there: "Bring Your Own Model" platforms. Upload a trained model and get: • A RESTful interface
• Versioning
• Monitoring
• Scalability MLOps in a box. @abacusai is a great example of this. -
Tracing GPT-3.5’s Emergent Abilities to Their Sources
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GPT-3.5 is technically all of the following, but I meant it as just the first three:
– code-davinci-002
– text-davinci-002
– text-davinci-003
– ChatGPT See here: https://
yaofu.notion.site/How-does-GPT-O
btain-its-Ability-Tracing-Emergent-Abilities-of-Language-Models-to-their-Sources-b9a57ac0fcf74f30a1ab9e3e36fa1dc1
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MIT Student Creates AI-Powered Real-Time Hologram Technology
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Tensor Holography MIT Student creates #AI learning, advancing #Holograms created by your iPhone w/ headsets >>> What could real-time holograms do for you? >>> Beyond Mythos via @MikeQuindazzi pic.twitter.com/sLUPr0pLBz
— Mike Quindazzi (@MikeQuindazzi) 4 janvier 2023Tensor Holography MIT Student creates #AI learning, advancing #Holograms created by your iPhone w/ headsets >>> What could real-time holograms do for you? >>> Beyond Mythos via @MikeQuindazzi
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Language Models and Mathematical Accuracy: Parameters vs Hard Numbers
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Parameters are great. Absolutely agree. For hard numbers, though, the language model doesn't do math in the way you'd expect. Often it'll be off on those, but they will get it closer to the goal you're seeking.