As organizations embrace a paradigm of innovation centered on an explosion of richly structured data, they’re not just enabling better AI—they’re entirely redefining what software can achieve.

This not only affects AI and data science but also poses a challenge to scientific research. Different researchers may obtain varying data for the same phenomenon, and inappropriate averaging ...

further accelerating the journey towards meeting climate goals. Moreover, the exploitation of AI and data science in RE industries would yield opportunities for new economic growth with jobs in ...

London-based Orbital Materials is also using AI to try to build a MOF. The company has trained its own model from scratch, using supercomputer simulations to generate training data, says Jonathan ...

As such, three California lawmakers introduced bills last week aimed at encouraging AI data processing centers to work toward sustainable water use standards, and holding them accountable to new ...

Data quality issues in AIGC are very important. AI systems sometimes generate "hallucinations" — false or fabricated content — raising concerns about misinformation. A 2023 report by OpenAI ...