Traditionally, drug discovery relied heavily on trial and error, with long timelines and high costs. The introduction of ...

Srinivasa KalyanVangibhurathachhi is an experienced technology professional who has spent nearly two decades working in data ...

A predictive biophysical model that integrates protein-DNA structures and sequences to accurately determine genomic binding sites and affinities of DNA-binding proteins.

Chennai-based tech firm announces Zia LLM trained on business use cases, with focus on privacy and Indian compliance tools ...

Amy Carlisle, president of MSI, spoke with Digital Insurance about how the MGA has expanded in recent years through ...

The CMMC program is the DoD's answer to years of security gaps, cyber breaches and noncompliance with cyber requirements.

Drug discovery has long been criticized for its slow, costly, and failure-prone nature. Traditional approaches, particularly ...

But as more data centers are built to accommodate AI and other data-intensive processes, energy demand is expected to skyrocket. A single hyperscale data center can use the same amount of energy as a ...

Discover why S&P Global is rated 'Hold' for its strong growth in ESG data but limited upside. Learn key risks, insights, and ...

Explore the hidden challenges of context rot in AI and how input length affects large language models. Uncover the paradox of ...

As mentioned before, the major risk of Asana is its highly rigid and less modular project management software. Because this ...