Building & Deploying Enterprise #MachineLearning Systems is hard. Here are 30 requirements for an #MLOps environment. @AbacusAI handles all that for you. You bring the data and the use case. Abacus delivers the #ML environment: https://
abacus.ai/mlops #DataScience #AI #ML
MACHINE LEARNING
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Enterprise Machine Learning Systems: 30 MLOps Requirements and Solutions
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Data-Centric AI Production at Scale with Matei Zaharia
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We've got something that might interest you. Matei Zaharia, Stanford Professor and Chief Technologist at Databricks, shares insights on making data-centric AI easy to use at scale in production. Check it out here https://
youtube.com/watch?v=NCktwY
7KcQ4
… #datacentricai #mlngineering -
Stanford Professor Studies Robot Learning and Intelligent Behavior Development
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Assistant prof. @chelseabfinn studies the capability of robots and other agents to develop broadly intelligent behavior through learning and interaction. She runs the IRIS lab @Stanford whose work was featured in the @nytimes
: https://
nytimes.com/2021/07/20/tec
hnology/ai-education-neural-networks.html
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Vision-Language-Action Learning in Robotics: Progress Discussion
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TY David for a very fun discussion about the state of the art in robotics, including new developments in robot vision-language-action learning, and why progress is not exponential!
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Predictive Analytics Revolutionizing Patient Outcomes in Healthcare
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Improving Patient Outcomes with Predictive Analytics: A Revolution in Healthcare https://
linkedin.com/pulse/improvin
g-patient-outcomes-predictive-analytics-revolution-babin-vneje
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#healthcare #ArtificialIntelligence #predictive #innovation #technology @jblefevre60 @kalydeoo @Ym78200 @pierrepinna @CurieuxExplorer @Shi4Tech @smaksked @AkwyZ @enilev -
ODSC AI Mini-Bootcamp: Master Data Science Theory and Practical Skills
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Dive deep into #DataScience (both theory and practical skills) at the @_odsc #AI Mini-Bootcamp. Register now—30% OFF ends soon: https://
bit.ly/3RJDP2e —————
#ODSC #DataScientists #ML #MachineLearning #DeepLearning -
AI Companies Neglect Language and Reasoning Benchmarks for Software Optimization
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There are so few benchmarks the AI companies compete on outside of software and general knowledge benchmarks. They also fine tune obsessively to optimize software. Language, turn-taking, logical reasoning, lack of hallucinations, and other critical issues get less clear focus.
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Rise of LLMs: Vector Embeddings and Vector Databases in AI
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The rise of #LLMs has made vector embeddings and #VectorDB immensely popular and useful, particularly in #AI, #GenerativeAI, and #LLMOps applications. @bindureddy from @abacusai explains in this “RAG – Vector Retrieval – Comprehensive Study”…
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Consciousness-Inspired Abstractions Improve RL Generalization
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Consciousness-Inspired Spatio-Temporal Abstractions for Better Generalization in Reinforcement Learning Zhao et al.: https://
arxiv.org/abs/2310.00229 #ArtificialIntelligence #DeepLearning #MachineLearning -
Linear Neural Networks for Regression with Practical Projects and Code
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Linear #NeuralNetworks for Regression Simplified with implemented projects — by @NainaChaturved8 Projects, code, and implementations: https://
naina0405.substack.com/p/monday-and-t
uesday-bytes-linear-neural
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#DataScience #MachineLearning #AI #Algorithms #Mathematics #DataScientists