Category: AI News

[ad_1] Test-time scaling (TTS) has emerged as a proven method to improve the performance of large language models in real-world applications by giving them extra compute cycles at inference time. However, TTS strategies have historically been handcrafted, relying heavily on human intuition to dictate the rules of the model’s reasoning.  To address this bottleneck, researchers…

[ad_1] Merck is using AI agents to cut drug discovery cycles by a third and ship compliant marketing materials up to 80% faster — but VP of Digital Platforms Sean Finnerty says the only reason it's working is because they built the infrastructure first. And the pharmaceutical manufacturer is seeing promising early results: AI is…

[ad_1] Over the past two decades, technical debt meant outdated architecture, messy code, and poorly maintained documentation. That definition is no longer sufficient in the AI era, where failure modes are more subtle and often non-linear. AI systems are introducing new layers of technical debt that live across prompts, models, and data dependencies — making…

[ad_1] There is a category of production incident that engineering teams are not tracking yet — because it doesn't fit any existing postmortem template. The agent initiated an action. The action was technically correct given the agent's context. The context was incomplete. The infrastructure cascaded. And, by the time the incident review happened, three teams…

[ad_1] Instruction-tuned language models refuse harmful requests. But which part of the model is actually responsible — and how does that mechanism get installed during training? A new research from Nous Research team takes a neuron-level look at this question. The Nous research team developed contrastive neuron attribution (CNA), a method that identifies the specific…

[ad_1] On May 19, 633 malicious npm package versions passed Sigstore provenance verification. They were cleared by the system because the attacker had generated valid signing certificates from a compromised maintainer account. Sigstore worked exactly as designed: it verified the package was built in a CI environment, confirmed a valid certificate was issued, and recorded…

[ad_1] For years, AI inside software meant a chat widget bolted onto the corner of an application. You typed, the model responded with text, and you manually translated that output into whatever you actually needed it to do. It was useful the way a calculator is useful: functional, but fundamentally passive. CopilotKit, a Seattle-based startup…

[ad_1] RAG architectures are good at one thing: surfacing semantically relevant documents. That's also where they stop. A framework called a decision context graph addresses that gap by giving agents structured memory, time-aware reasoning, and explicit decision logic. Rippletide, a startup in the Neo4j ecosystem, has built one. The key capability: agents that are non-regressive,…

[ad_1] Generative AI’s rapid transition from text-based chatbots to high-fidelity media—spanning images, video, spatial 3D, and audio—has exposed a glaring bottleneck in the modern tech stack: infrastructure. Rendering pixels in real-time requires a staggering amount of compute, and developers are increasingly struggling to manage fragmented GPU clusters just to keep their applications online. Enter fal,…

[ad_1] Four supply-chain incidents hit OpenAI, Anthropic and Meta in 50 days: three adversary-driven attacks and one self-inflicted packaging failure. None targeted the model, and all four exposed the same gap: release pipelines, dependency hooks, CI runners, and packaging gates that no system card, AISI evaluation, or Gray Swan red-team exercise has ever scoped. On…