Results for “agents”

…(STT) models designed to be fast and affordable for voice agents @krandiash. Sakana AI Labs introduced Text-to-LoRA, a hypernetwork that generates task-specific LLM adapters (LoRAs) from a text description of the task, offering significant …

Every Agent Needs a Box Enterprise agents need useful context, bounded access, a workspace, and human oversight. Making those pieces fit an organization is as much a workflow problem as a model problem.

…for AI applications, alongside high-compute search and research agents.

…approach by Sakana AI Labs, was introduced to develop LLM agents with niche capabilities using quality diversity techniques.

…evolved from specialized software-development workflows into agents and coordinated software factories.

…LangChain introduced the concept of Context Engineering for AI agents. Reinforcement learning on LLMs shows transformative potential, and the community values AI evals and data work. Sakana AI released Text-to-LoRA, a hypernetwork method…

…into prompt-to-app creation, design context for coding agents, and AI editing on its shared canvas.

…Neo4j/Pfizer's presentation, and OpenAI's first definition of Agents. Speakers announced $930 million in funding. On AI Twitter, discussions focused on Grok-3 and o3-mini models, with debates on performance and benchmarking, including…

Florent Crivello Lindy founder whose work on AI agents combines constrained workflows, model capabilities and software integrations.

…inference/self-verification), and reactions by @cloneofsimo. UI agents via reinforcement fine-tuning: Ant Group’s UI-Venus (built on Qwen2.5-VL) uses Group Relative Policy Optimization with tailored rewards to ground and navigate from…

…network restrictions and human control of code-executing agents.

…hooks, dynamic capabilities and a built-in harness to AI agents.