Building Agentic AI Systems with Microsoft’s Agent Framework

A practical guide to modern type annotations in Python for data science The post The Joy of Typing appeared first on Towards Data Science.

Feature engineering is the foundation of strong machine learning systems, but the traditional process is often manual, time-consuming, and dependent on domain expertise. While effective, it can miss deeper signals hidden in unstructured data such as text, logs, and user interactions. Large Language Models change this by helping machines understand language, extract meaning, and generate […] The post Feature Engineering with LLMs: Techniques & Python Examples appeared first on Analytics Vidhya.

MRC (Multipath Reliable Connection) is a new open networking protocol developed by OpenAI in partnership with AMD, Broadcom, Intel, Microsoft, and NVIDIA that improves GPU networking performance and resilience in large-scale AI training clusters by spreading packets across hundreds of paths simultaneously, recovering from network failures in microseconds, and enabling supercomputers with over 100,000 GPUs to be built using only two tiers of Ethernet switches. The post OpenAI Introduces MRC (Multipath Reliable Connection): A New Open Networking Protocol for Large-Scale AI Supercomputer Training Clusters appeared first on MarkTechPost.

The Center for AI Standards and Innovation (CAISI), a division of the US Department of Commerce, has signed agreements with Google DeepMind, Microsoft, and xAI that would give the agency the ability to vet AI models from these organizations and others prior to their being made publicly available. According to a release from CAISI, which is part of the department’s National Institute of Standards and Technology (NIST), it will “conduct pre-deployment evaluations and targeted research to better assess frontier AI capabilities and advance the state of AI security.” The three join Anthropic and OpenAI, which signed similar agreements almost two years ago during the Biden administration, when CAISI was known as the US Artificial Intelligence Safety Institute. An August 2024 release about those agreements indicated that the institute planned to provide feedback to both companies on “potential safety improvements to their models, in close collaboration with its partners at the UK AI Safety In

Deal follows others with Microsoft, Amazon, and more.

Stop shifting elements in lists! Discover why collections.deque is the secret to high-performance sliding windows, thread-safe queues, and efficient data streams in your next Python project. The post Beyond Lists: Using Python Deque for Real-Time Sliding Windows appeared first on Towards Data Science.

Building a RAG system just got much easier. Google’s File Search tool for the Gemini API now handles the heavy lifting of connecting LLMs to your data. Chunking, embedding, indexing are all managed for you. And with the latest update, it’s gone multimodal. You can now search through both text and images in a single […] The post Gemini API File Search: The Easy Way to Build RAG appeared first on Analytics Vidhya.

The US administration has added four more AI companies to its roster of favoured suppliers, with the Pentagon signing agreements with Microsoft, Reflection AI (which has yet to release a publicly-available model), Amazon, and Nvidia that mean their products can be used on classified operations. The companies join OpenAI, xAI, and Google as companies that […] The post US government increases AI suppliers and rethinks Anthropic’s role appeared first on AI News.