Anthropic has released a detailed best-practice guide for using Claude Code, a command-line interface designed for agentic software development workflows.…
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LLMs Still Struggle to Cite Medical Sources Reliably: Stanford Researchers Introduce SourceCheckup to Audit Factual Support in AI-Generated Responses
As LLMs become more prominent in healthcare settings, ensuring that credible sources back their outputs is increasingly important. Although no…
Lees meerServerless MCP Brings AI-Assisted Debugging to AWS Workflows Within Modern IDEs
Serverless computing has significantly streamlined how developers build and deploy applications on cloud platforms like AWS. However, debugging and managing…
Lees meerA Step-by-Step Coding Guide to Defining Custom Model Context Protocol (MCP) Server and Client Tools with FastMCP and Integrating Them into Google Gemini 2.0’s Function‑Calling Workflow
In this Colab‑ready tutorial, we demonstrate how to integrate Google’s Gemini 2.0 generative AI with an in‑process Model Context Protocol…
Lees meerStanford Researchers Propose FramePack: A Compression-based AI Framework to Tackle Drifting and Forgetting in Long-Sequence Video Generation Using Efficient Context Management and Sampling
Video generation, a branch of computer vision and machine learning, focuses on creating sequences of images that simulate motion and…
Lees meerByteDance Releases UI-TARS-1.5: An Open-Source Multimodal AI Agent Built upon a Powerful Vision-Language Model
ByteDance has released UI-TARS-1.5, an updated version of its multimodal agent framework focused on graphical user interface (GUI) interaction and…
Lees meerOpenAI Releases a Practical Guide to Identifying and Scaling AI Use Cases in Enterprise Workflows
As the deployment of artificial intelligence accelerates across industries, a recurring challenge for enterprises is determining how to operationalize AI…
Lees meerReTool: A Tool-Augmented Reinforcement Learning Framework for Optimizing LLM Reasoning with Computational Tools
Reinforcement learning (RL) is a powerful technique for enhancing the reasoning capabilities of LLMs, enabling them to develop and refine…
Lees meerLLMs Can Think While Idle: Researchers from Letta and UC Berkeley Introduce ‘Sleep-Time Compute’ to Slash Inference Costs and Boost Accuracy Without Sacrificing Latency
Large language models (LLMs) have gained prominence for their ability to handle complex reasoning tasks, transforming applications from chatbots to…
Lees meerLLMs Can Be Misled by Surprising Data: Google DeepMind Introduces New Techniques to Predict and Reduce Unintended Knowledge Contamination
Large language models (LLMs) are continually evolving by ingesting vast quantities of text data, enabling them to become more accurate…
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