NEWS IN BRIEF: AI/ML FRESH UPDATES

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Optimizing ML Models: The Power of Chaining

ML metamorphosis, a process chaining different models together, can significantly improve model quality beyond traditional training methods. Knowledge distillation transfers knowledge from a large model to a smaller, more efficient one, resulting in faster and lighter models with improved performance.

Supercharge Your LLMs on RTX with LM Studio

Large language models (LLMs) are transforming productivity with tasks like drafting documents and answering questions. NVIDIA RTX GPUs enable local running of LLMs, optimizing AI acceleration and performance with GPU offloading and LM Studio.

Yorke, Moore, and Creators Unite Against AI Threat

Abba’s Björn Ulvaeus, Julianne Moore, and Thom Yorke join 10,500 signatories warning AI companies against unlicensed use of creative work. Legal battles escalate over use of intellectual property to train AI models like ChatGPT.

The Power of Agentic AI

AI chatbots use generative AI for responses. Agentic AI autonomously solves complex problems, improving productivity across industries.

Revolutionizing ML: Relational Deep Learning

Engage in Relational Deep Learning (RDL) by directly training on your relational database, transforming tables into a graph for efficient ML tasks. RDL eliminates feature engineering steps by learning from raw relational data, enhancing model performance and granularity.

Streamlining AI Verification

MIT researchers developed SymGen to help human fact-checkers quickly verify responses from large language models by providing citations that directly link to the source document, speeding up verification time by about 20%. SymGen allows users to selectively focus on specific parts of the text to ensure accuracy, potentially increasing confidence in model responses in high-stakes settings like h...

Mastering Generative AI with Amazon Bedrock Agents

Amazon Bedrock Agents streamline generative AI app development by orchestrating multistep tasks with foundation models and Retrieval Augmented Generation. Architectural considerations and IaC frameworks enhance robust, scalable, and secure agent development for conversational AI applications.