Large language model serving often wastes GPU memory because engines pre-reserve large static KV cache regions per model, even when […]
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5 Common LLM Parameters Explained with Examples
Large language models (LLMs) offer several parameters that let you fine-tune their behavior and control how they generate responses. If […]
A New AI Research from Anthropic and Thinking Machines Lab Stress Tests Model Specs and Reveal Character Differences among Language Models
AI companies use model specifications to define target behaviors during training and evaluation. Do current specs state the intended behaviors […]
How to Build a Fully Functional Computer-Use Agent that Thinks, Plans, and Executes Virtual Actions Using Local AI Models
In this tutorial, we build an advanced computer-use agent from scratch that can reason, plan, and perform virtual actions using […]
Google vs OpenAI vs Anthropic: The Agentic AI Arms Race Breakdown
Table of contents OpenAI: CUA for GUI Autonomy, Responses as Agent Surface, and AgentKit for Lifecycle Google: Gemini 2.0 and […]
Liquid AI’s LFM2-VL-3B Brings a 3B Parameter Vision Language Model (VLM) to Edge-Class Devices
Liquid AI released LFM2-VL-3B, a 3B parameter vision language model for image text to text tasks. It extends the LFM2-VL […]
An Implementation on Building Advanced Multi-Endpoint Machine Learning APIs with LitServe: Batching, Streaming, Caching, and Local Inference
In this tutorial, we explore LitServe, a lightweight and powerful serving framework that allows us to deploy machine learning models […]
Google AI Introduces FLAME Approach: A One-Step Active Learning that Selects the Most Informative Samples for Training and Makes a Model Specialization Super Fast
Open vocabulary object detectors answer text queries with boxes. In remote sensing, zero shot performance drops because classes are fine […]
UltraCUA: A Foundation Computer-Use Agents Model that Bridges the Gap between General-Purpose GUI Agents and Specialized API-based Agents
Computer-use agents have been limited to primitives. They click, they type, they scroll. Long action chains amplify grounding errors and […]
Anthrogen Introduces Odyssey: A 102B Parameter Protein Language Model that Replaces Attention with Consensus and Trains with Discrete Diffusion
Anthrogen has introduced Odyssey, a family of protein language models for sequence and structure generation, protein editing, and conditional design. […]