Here is a cheat sheet listing the key components of an end-to-end MLOps platform. The main advantage of a platform like @abacusai
: You can get most of these components out of the box in an integrated solution.
MACHINE LEARNING
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Key Components of End-to-End MLOps Platform Solutions
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Jacobian Chaining Lifts 2D Diffusion Models for 3D Generation
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Score Jacobian Chaining: Lifting Pretrained 2D Diffusion Models for 3D Generation Wang et al.: https://
arxiv.org/abs/2212.00774 #ArtificialIntelligence #DeepLearning #MachineLearning -
Groq Accelerates HPC and AI Computing at NYC AI Summit
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Learn how @GroqInc accelerates #HPC from scalable, ultra low-latency systems to generalized software, and meet some of our Groqstars at #AISummit next week in NYC. Request a one-on-one by contacting jpeckham@groq.com and learn more at http://
groq.link/aisummitnyc. #ML #AI #computing -
Consciousness: Self-Awareness and Environmental Awareness in AI Systems
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Consciousness is a combination of self and environmental awareness. I see environmental awareness in Minedojo as tractable but self-awareness is a different story. For that, you need uncertainty quantification is key: unknown unknowns is tricky.
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MineDojo: Open-ended Agents for Minecraft Task Solving
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Thank you @davidchalmers42 for featuring https://
minedojo.org in your talk. We build open-ended agents that can solve any task in Minecraft. This requires the agent to have awareness of the Minecraft world. Foundation models provide the agent with priors (e.g. reward function) -
MLflow 2.0 Simplifies Data Science Workloads and MLOps
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#MLflow 2.0 has entered the chat By simplifying #data science workloads and delivering innovative, first-class tools for #MLOps, MLflow is now better than ever. See the latest updates https://
dbricks.co/3tAv3qy -
MLOps: Implementing Procedures and Best Practices for AI Production
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Adopting MLOps means putting in place procedures and best practices to maintain models for executing artificial intelligence inferences in production formally and efficiently. The name mimics the DevOps nomenclature model. Microblog and social design by @antgrasso #MLOps #AI
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4 CEO Actions to Become AI-First Companies
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4 actions #CEOs can take to follow the #AI Achievers’ playbook and become AI-first companies
Via @ingliguori #DataSecurity #dataScientist #DataAnalytics #TensorFlow #Cloud #coding #BigData #5G #MachineLearning #fintech #blockchain #DataScience #100DaysOfCode #Python #leadership -
RoentGen: Vision-Language Model for Chest X-rays
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A later work, "RoentGen: Vision-Language Foundation Model for Chest X-ray Generation", was also conducted by Stanford's Department of Radiology, in collaboration with Tanishq Abraham (@iScienceLuvr) at @StabilityAI. https://stanfordmimi.github.io/RoentGen/
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Stanford researchers generate synthetic chest X-rays with Stable Diffusion
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Stanford researchers create synthetic yet realistic chest X-rays using #StableDiffusion SD is typically used for art, not for science. In this case, the “radiographs” might be high quality enough to complement real image datasets. https://
arxiv.org/abs/2210.04133