Legacy R&D systems fragment data, limiting integration, collaboration and AI readiness across product development workflows.

Google’s going to the movies, as it invested $75 million in the hot indie studio A24, along with a pledge to provide AI to ...

Overview:  Large language models may dominate headlines, but modern NLP tools remain essential for text processing, ...

The ChromaToast vulnerability can be exploited by forcing the ChromaDB API server to fetch and load maliciously crafted AI models before authentication is checked. Researchers have published details ...

Objective: The study aims to (1) investigate how combining unsupervised natural language processing (NLP) and corpus linguistics can explore patient perspectives from a large unstructured dataset of ...

CEE takes raw, unstructured input — a question, a task, a half-formed thought — and runs it through a strict, auditable pipeline that produces a validated XML prompt structured for Claude's optimal ...

Deploying AI agents for repository-scale tasks like bug detection, patch verification, and code review requires overcoming significant technical hurdles. One major bottleneck: the need to set up ...

The proposed VLM-based human-guided mobile robot navigation approach aims to enable humans to use natural language instructions to guide the industrial robot to perform manufacturing tasks in an ...

Building a RAG system can be challenging. In addition to deployment and infrastructure challenges (eg, scaling up your vector db), there are many tradeoffs and decisions to make for each component of ...

Before public bodies connect AI tools to their estates, they need to know what data they hold, where it lives, who can access ...

The new managed functions will let enterprises apply LLM reasoning to structured and unstructured data directly in SQL, eliminating prompt tuning and external tools. Google has boosted its BigQuery ...