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 ...

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 ...

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

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 ...

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 ...

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 ...

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 ...

In this tutorial, we demonstrate how to build a powerful and intelligent question-answering system by combining the strengths of Tavily Search API, Chroma, Google Gemini LLMs, and the LangChain ...

Recent developments have shown that RL can significantly enhance the reasoning abilities of LLMs. Building on this progress, the study aims to improve Audio LLMs—models that process audio and text to ...

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, ...

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, ...