AI has advanced in language processing, mathematics, and code generation, but extending these capabilities to physical environments remains challenging. Physical AI seeks to close this gap by ...

At Google I/O 2025, Google introduced MedGemma, an open suite of models designed for multimodal medical text and image comprehension. Built on the Gemma 3 architecture, MedGemma aims to provide ...

Chain-of-thought (CoT) prompting has become a popular method for improving and interpreting the reasoning processes of large language models (LLMs). The idea is simple: if a model explains its answer ...

Meta has introduced KernelLLM, an 8-billion-parameter language model fine-tuned from Llama 3.1 Instruct, aimed at automating the translation of PyTorch modules into efficient Triton GPU kernels. This ...

The ability to search high-dimensional vector representations has become a core requirement for modern data systems. These vector representations, generated by deep ...

LLM-based agents are increasingly used across various applications because they handle complex tasks and assume multiple roles. A key component of these agents is memory, which stores and recalls ...

Generative models traditionally rely on large, high-quality datasets to produce samples that replicate the underlying data distribution. However, in fields like molecular modeling or physics-based ...

The Model Context Protocol (MCP) represents a powerful paradigm shift in how large language models interact with tools, services, and external data sources. Designed to enable dynamic tool invocation, ...

Google has officially rolled out the NotebookLM mobile app, extending its AI-powered research assistant to Android devices. The app aims to bring personalized learning and content synthesis directly ...

As autonomous AI agents move from theory into implementation, their impact on the financial services sector is becoming tangible. A recent whitepaper from IBM Consulting, titled “Agentic AI in ...

While RAG enables responses without extensive model retraining, current evaluation frameworks focus on accuracy and relevance for answerable questions, neglecting the crucial ability to reject ...

Fine-tuning LLMs often requires extensive resources, time, and memory, challenges that can hinder rapid experimentation and deployment. Unsloth AI revolutionizes this process by enabling fast, ...