On this episode of Data Driven, we explore the topic of distributed computing frameworks for AI and ML workloads.
Frank discusses the advancements of Ray, a new technology based on Python language, with performance enhancements that could range from 10-12 times faster to thousands of times faster in extreme cases.
We delve into the power of open source artificial intelligence and how it can aid data endeavors to accelerate these efforts. Along the way, we touch upon IBM and Red Hat’s partnership, the evolution of technology, the importance of problem-specific solutions, and more.
Stay tuned for a new episode of “Data Driven” and a special segment from our speaker on the potential AI holds for our future.
[00:01:50] Ray is a new computing framework for AI/ML, may replace Spark, based on Python, can free people from PySpark.
[00:03:49] Speaker has a MacBook M2 and prefers it over Windows. They enjoy stream-side streaming and wrote an article prompted by a question at work about a new technology claiming to be the next big data processing framework. They believe Ray still has an advantage.
[00:06:51] Webinar about power of IBM-Red Hat partnership in AI. Speaker mentions travel with family and introduces production assistant.
[00:11:34] Tech anticipated, surprised by speed of Chat GPT. Some dismiss as a fad, but it’s different from predictive text like comparing paper airplane to an Airbus A 380, based on same principles but very different in implementation and technology.
[00:13:30] Encourage attendance at AI webinar showcasing ethical concerns. Open source needed for transparency and risk-sharing. AI impact on all, even entry-level jobs and economy.