Category: AI News

[ad_1] Separating logic from inference improves AI agent scalability by decoupling core workflows from execution strategies. The transition from generative AI prototypes to production-grade agents introduces a specific engineering hurdle: reliability. LLMs are stochastic by nature. A prompt that works once may fail on the second attempt. To mitigate this, development teams often wrap core…

[ad_1] Anthropic has launched Claude Opus 4.6, its most capable model to date, focused on long-context reasoning, agentic coding, and high-value knowledge work. The model builds on Claude Opus 4.5 and is now available on claude.ai, the Claude API, and major cloud providers under the ID claude-opus-4-6. Model focus: agentic work, not single answers Opus…

[ad_1] Researchers from Stanford, Nvidia, and Together AI have developed a new technique that can discover new solutions to very complex problems. For example, they managed to optimize a critical GPU kernel to run 2x faster than the previous state-of-the-art written by human experts. Their technique, called “Test-Time Training to Discover” (TTT-Discover), challenges the current…

[ad_1] As OpenAI races toward its ambitious US$100 billion revenue target by 2027, the ChatGPT maker is reportedly building an army of AI consultants to bridge the gap between cutting-edge technology and enterprise boardrooms—a move that signals a fundamental shift in how AI companies are approaching the notoriously difficult challenge of enterprise adoption. According to…

[ad_1] Frontier multimodal models usually process an image in a single pass. If they miss a serial number on a chip or a small symbol on a building plan, they often guess. Google’s new Agentic Vision capability in Gemini 3 Flash changes this by turning image understanding into an active, tool using loop grounded in…

[ad_1] Chinese e-commerce giant Alibaba's Qwen team of AI researchers has emerged in the last year as one of the global leaders of open source AI development, releasing a host of powerful large language models and specialized multimodal models that approach, and in some cases, surpass the performance of the proprietary U.S. leaders such as…

[ad_1] Before you set sail on your AI journey, always check the state of your data – because if there is one thing likely to sink your ship, it is data quality. Gartner estimates that poor data quality costs organisations an average of $12.9 million each year in wasted resources and lost opportunities. That’s the…

[ad_1] In this tutorial, we build a robust, multi-layered safety filter designed to defend large language models against adaptive and paraphrased attacks. We combine semantic similarity analysis, rule-based pattern detection, LLM-driven intent classification, and anomaly detection to create a defense system that relies on no single point of failure. Also, we demonstrate how practical, production-style…

[ad_1] The key to successful AI agents within an enterprise? Shared memory and context.  This, according to Asana CPO Arnab Bose, provides detailed history and direct access from the get-go — with guardrail checkpoints and human oversight, of course.  This way, “when you assign a task, you're not having to go ahead and re-provide all…

[ad_1] If you are a data and analytics leader, then you know agentic AI is fuelling unprecedented speed of change right now. Knowing you need to do something and knowing what to do, however, are two different things. The good news is providers like ThoughtSpot are able to assist, with the company in its own…