The hidden costs of traditional databases often force developers to create custom infrastructure for managing workflows. This is a critical resource conflict. Instead of focusing on building new products or advancing AI initiatives, the developers spend more time solving operational problems. As enterprises move deeper into AI, this issue is pushing data teams outside their…
Agentic AI has dominated industry conversations since 2025. Adoption across enterprises is on the rise, and investment plans remain aggressive. Use cases are expanding rapidly, from simple employee assistants to advanced agentic workflows for insurance renewals or support ticket triage, to name just a few. The shift has been undeniably fast. The momentum notwithstanding, a…
AI agents have become the primary driver of enterprise productivity. According to a recent report by Salesforce, organizations currently use an average of 12 agents, with that number expected to climb 67% within the next two years. Currently, 83% of organizations report that most or all teams and functions have adopted AI agents. However, business…
Until recently, most enterprises treated real-time data as something you reached for only when absolutely necessary. It sat at the edges of enterprise architecture. However, that has changed. If you have been following our coverage at BigDATAwire, you would have seen that real-time data and analytics has been a core theme for enterprise modernization efforts…
The aviation industry is already implementing AI solutions, but it is barely scratching the surface of the value AI can bring, according to Ali Pourshahid, Chief Engineering Officer and Alam Khan, Principal Architect, Solace. The industry is weighed down by diverse and siloed processes, preventing airlines from harnessing the full power of AI, in particular…
Researchers from the Allen Institute for AI (Ai2) and the University of Washington have developed a new open-source AI model named OpenScholar that they claim can synthesize scientific literature and verifiable citations at a level comparable to a human expert. With millions of scientific papers published every year, it’s challenging to keep up with the…
At its BUILD London event yesterday, Snowflake rolled out a new set of AI capabilities aimed at simplifying the development of agents and other advanced applications. The new capabilities include native integration of Snowflake Postgres, Semantic View Autopilot, and Cortex Code, among other tools. These new capabilities come only a couple of days after Snowflake…
When you think of the global AI race, what comes to mind? Models, benchmarks, and faster training? Well, those still matter, but the race depends more on infrastructure – think data centers and power grids. While many countries are investing heavily in this space and are slowly catching up in the AI race, the U.S….
DOE’s Argonne National Laboratory has teamed up with Fujitsu, RIKEN, and NVIDIA to help bring AI deeper into scientific computing. The goal is simple. Connect AI with high performance computing so researchers can work with simulation and experimental data in the same place, at the same time. AI is often thought of as a downstream…
Energy companies in the AI era are dealing with unprecedented volumes of operational data, all while being held back by legacy infrastructure. Many of the operations now depend on analytics including predictive maintenance, grid modernization, and renewal integration. However, these companies still struggle to bring everything together, slowing everyday decisions, complicating coordination across teams. Over…
