Remove AI Development Remove AI Modeling Remove Hybrid AI
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AI Learns from AI: The Emergence of Social Learning Among Large Language Models

Unite.AI

Saving Resources: This approach allows for more efficient use of resources, as models learn from each other's experiences without needing direct access to large datasets. Decentralized Learning : The idea of AI models learning from each other across a decentralized network presents a novel way to scale up knowledge sharing.

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Give AI a Look: Any Industry Can Now Search and Summarize Vast Volumes of Visual Data

NVIDIA

NVIDIA AI Blueprint Harnesses Vision Language Models Visual AI agents are powered by vision language models (VLMs) , a class of generative AI models that combine computer vision and language understanding to interpret the physical world and perform reasoning tasks.

professionals

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Graph Viz with Gephi and ChatGPT, Google’s Bard AI, and Reverse Engineering Image Prompts

ODSC - Open Data Science

Over 1,000 Technology Leaders and Researchers Call for Pause in AI Development A massive group of technology leaders and researchers are calling to pause AI development citing “profound risks to society and humanity.” But, be sure to act fast before passes run out! Register by Friday for 40% off.

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Understanding the Core Limitations of Large Language Models: Insights from Gary Marcus

ODSC - Open Data Science

This blog explores Marcus’s insights, addressing LLMs’ inherent limitations, the need for hybrid AI approaches, and the societal implications of current AI practices. The Case for Hybrid AI Models A significant portion of Gary Marcus’s discussion revolves around hybrid AI as a necessary evolution.