How far can we push large language model speed by reusing “free” GPU compute, without giving up autoregressive level output quality? NVIDIA researchers propose TiDAR, a sequence level hybrid language ...

Vector Tiered vector (MemGPT-style virtual context) Working set + vector archive Better reuse of important info, bounded context size Paging policy errors, per-agent divergence Graph Temporal KG ...

Every time you prompt an LLM, it doesn’t generate a complete answer all at once — it builds the response one word (or token) at a time. At each step, the model predicts the probability of what the ...

Code-oriented large language models moved from autocomplete to software engineering systems. In 2025, leading models must fix real GitHub issues, refactor multi-repo backends, write tests, and run as ...

Optical character recognition has moved from plain text extraction to document intelligence. Modern systems must read scanned and digital PDFs in one pass, preserve layout, detect tables, extract key ...

In this tutorial, we develop a comprehensive benchmarking framework to evaluate various types of agentic AI systems on real-world enterprise software tasks. We design a suite of diverse challenges, ...

In this article we will analyze how Google, OpenAI, and Anthropic are productizing ‘agentic’ capabilities across computer-use control, tool/function calling, orchestration, governance, and enterprise ...

In this tutorial, we explore the Advanced Model Context Protocol (MCP) and demonstrate how to use it to address one of the most unique challenges in modern AI systems: enabling real-time interaction ...

Orchestration Host routes across many servers/tools App-local chaining Agent/toolkit routes intents → operations ...

TUMIX runs a group of heterogeneous agents—text-only Chain-of-Thought, code-executing, web-searching, and guided variants—in parallel, then iterates a small number of refinement rounds where each ...

Neuphonic frames the model for on-device privacy (no audio/text leaves the machine without user’s approval) and notes that all generated audio includes a Perth (Perceptual Threshold) watermarker to ...

An open-source framework that couples LLM-driven program mutations with evolutionary search to automate algorithm discovery and optimization. Code and report are public. 2) How does it achieve higher ...