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OpenAI on Thursday launched GPT-5.3-Codex-Spark, a stripped-down coding model engineered for near-instantaneous response times, marking the company's first significant inference partnership outside its traditional Nvidia-dominated infrastructure. The model runs on hardware from Cerebras Systems, a Sunnyvale-based chipmaker whose wafer-scale processors specialize in low-latency AI workloads.The...
When an AI agent visits a website, it’s essentially a tourist who doesn’t speak the local language. Whether built on LangChain, Claude Code, or the increasingly popular OpenClaw framework, the agent is reduced to guessing which buttons to press: scraping raw HTML, firing off screenshots to multimodal models, and burning through thousands of tokens just to figure out where a search bar is.That era...
Lowering the cost of inference is typically a combination of hardware and software. A new analysis released Thursday by Nvidia details how four leading inference providers are reporting 4x to 10x reductions in cost per token.The dramatic cost reductions were achieved using Nvidia's Blackwell platform with open-source models. Production deployment data from Baseten, DeepInfra, Fireworks AI and...
Chinese AI startup Zhupai aka z.ai is back this week with an eye-popping new frontier large language model: GLM-5.The latest in z.ai's ongoing and continually impressive GLM series, it retains an open source MIT License — perfect for enterprise deployment – and, in one of several notable achievements, achieves a record-low hallucination rate on the independent Artificial Analysis Intelligence...
Anthropic released its Claude Cowork AI agent software for Windows on Monday, bringing the file management and task automation tool to roughly 70 percent of the desktop computing market and intensifying a remarkable corporate realignment that has seen Microsoft embrace a direct competitor to its longtime AI partner, OpenAI.The Windows launch arrives with what Anthropic calls "full feature parity...
When enterprises fine-tune LLMs for new tasks, they risk breaking everything the models already know. This forces companies to maintain separate models for every skill.Researchers at MIT, the Improbable AI Lab and ETH Zurich have developed a new technique that enables large language models to learn new skills and knowledge without forgetting their past capabilities.Their technique, called self-...
The rapid viral adoption of Austrian developer Peter Steinberger's open source AI assistant OpenClaw in recent weeks has sent enterprises and indie developers into a tizzy.It's easy to easy why: OpenClaw is freely available now and offers a powerful means of autonomously completing work and performing tasks across a user's entire computer, phone, or even business with natural language prompts...
Presented by Cisco AI agents are breaking traditional IT operations models, adding complexity, data silos, and fragmented workflows. DJ Sampath, Cisco's SVP of AI Software and Platform, believes that AgenticOps is the solution: a new operational paradigm where humans and AI collaborate in real time to create efficiency, boost security, and allow for innovative technological applications.In a...
Until recently, the practice of building AI agents has been a bit like training a long-distance runner with a thirty-second memory. Yes, you could give your AI models tools and instructions, but after a few dozen interactions — several laps around the track, to extend our running analogy — it would inevitably lose context and start hallucinating. With OpenAI's latest updates to its Responses API...
RAG isn't always fast enough or intelligent enough for modern agentic AI workflows. As teams move from short-lived chatbots to long-running, tool-heavy agents embedded in production systems, those limitations are becoming harder to work around.In response, teams are experimenting with alternative memory architectures — sometimes called contextual memory or agentic memory — that prioritize...