Machine learning, the most common foundation for building artificial intelligence algorithms, absolutely requires big data to identify patterns. That turns out to be one of the biggest hurdles for AI today.
Researchers often don't have enough data to give them a sample size large enough to draw conclusions. Combining multiple data stores to build a sufficiently large set can be a very expensive, time-consuming and labor-intensive process.
Montefiore Health Systems in New York seems to have overcome this tyranny of big data in the healthcare space. Their sophisticated PALM platform is able to blend multiple data stores and churn out life-saving AI algorithms with a speed and ease that few believed possible.
In cooperation with Intel, Montefiore embedded Mike Feibus, FeibusTech's Principal Analyst, into the healthcare system to learn more about this game-changing new platform, and how Intel Xeon Scalable processors are helping to drive the PALM team's success. Don't miss Embedded Analyst: AI Without Borders, FeibusTech's compelling new Research Brief.