Artificial Intelligence in Health Grand Rounds to share expertise and build community
#AI #AIio #BigData #ML #NLU #Futureofwork @TopCyberNews @SpirosMargaris @MarshaCollier @MHiesboeck
@MHcommunicate @Fisher85M @MikeQuindazzi @NealSchaffer
MACHINE LEARNING
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AI in Health Grand Rounds: Expertise Sharing and Community Building
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Discussion on fine-tuning Llama-based models
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Yes it's a finetune of llama, thus I hesitated to include it, but they do build great models
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DataRobot Tackles AI Production Challenges With Unified Platform
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Businesses are investing heavily in AI, yet 90% of AI projects fail to move from prototype to production. We’re addressing this head-on. From unifying predictive and generative AI to introducing agentic workflows and advanced observability, DataRobot delivers AI that makes
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Deploy Real-Time AI and Machine Learning Models at Scale with Abacus
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Easily deploy real-time #AI #DeepLearning and #MachineLearning models at scale with the @AbacusAI enterprise-class #ML FEATURE STORE that provides security, governance, and high SLAs: https://
abacus.ai/featurestore
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#DataScience #EnterpriseAI #MLOps #SQL #BigData #DataStrategy #CDO -
Autonomous Business Systems: Exponential Learning AI
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I don't know of one. It's like building an autonomous car. It's an exponentially-learning system. An autonomous business. One that works better and better every day.
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Designing Machine Learning Systems for Production-Ready Applications
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Designing #MachineLearning Systems — An Iterative Process for Production-Ready Applications: http://
amzn.to/46epLSi by @chipro (formerly @ClaypotAI
, now @VoltronData
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#DataScience #AI #ML #MLOps #DataScientist
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Topics covered: Engineering data and choosing the right -
Fine-tuning Reduces Hallucinations in AI Models
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E.g. Fine-tuning improved hallucinating
Try it today for free! https://
predibase.com/free-trial -
Predibase Launches Visual Language Models Fine-tuning and Serving Beta
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Big news: Predibase now supports fine-tuning & serving Visual Language Models (#VLMs) [beta]! Combine visual + text inputs for reasoning, captioning, VQA, multimodal gen, & image search. Fine-tune easily, deploy faster, and outperform OOTB models. Docs
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Linear Attention: Scaling LLMs Beyond Transformer Limitations
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LLMs rely heavily on transformers, which make use of an "attention mechanism" for modeling interactions among inputs. But this attention mechanism is inefficient and thus difficult to scale to longer contexts. Because of this, researchers have been experimenting w/"linear
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CSAIL Proposes Efficient Training Algorithm for Linear Transformers
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Linear transformers have their own downsides, and there have been ongoing efforts in the community on improving their performance while maintaining training efficiency. Recently, CSAIL researchers have proposed a novel parallel algorithm for efficiently training an expressive