Joel Hans

NIST makes a strong argument for looking beyond data and even the ML processes to discover and destroy AI bias

Synthetic data can help train AI/ML applications in edge cases where it is difficult or dangerous to capture data in real life.

It is relatively common knowledge that AI systems can exhibit biases that stem from their programming and data sources.

Simpler software testing is needed as citizen developers using low-code development techniques aren’t willing to wait on IT’s sign-off.

Every department, from marketing to HR to product to IT, requires the heavily use of data for day-to-day tasks. As such, employees will need far more data training than what most organizations are doing right now.

The Alliance believes that by committing to open data standards, access, and integration between data platforms and applications, it can significantly accelerate business transformations and close the data to value gap.

The team uses digital twins and machine learning to monitor the health of its crops using automation, to eventually eliminate the need to send trained divers underwater.

Given the evolving global landscape, the State Department needs data-driven insights just as enterprises get with real-time analytics.

If your organization spends more time scratching its collective head about data quality or operational issues than it does asking unique and interesting questions, then you’re not just wasting time, you’re actively eroding your company’s future.

Graph databases and knowledge graphs have a number of built-in advantages when it comes to overcoming the challenges of data integration.

Researchers are studying how the functions of specific insect nervous systems resemble the functions performed by deterministic, probabilistic, volatile, and non-volatile memory and exploring how these functions could be recreated in high-performance, energy-efficient, silicon-based nanosystems for AI.

The largest AI models can take months to train on today’s computing platforms. NVIDIA’s new offerings aim to address that issue.