*DataPoint* Accelerating AI with Python-native Ray and the Importance of Open Source in AI
Podcast |
Data Driven
Publisher |
Data Driven
Media Type |
audio
Podknife tags |
Artificial Intelligence, 
Data Science, 
Interview, 
Machine Learning, 
Technology
Categories Via RSS |
Life Sciences, 
Mathematics, 
Science, 
Technology
Publication Date |
Jun 16, 2023
Episode Duration |
00:16:13

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.

Podcast Topics Summarized: 1. Ray - a new distributed computing framework for AI and ML workloads - Ray's potential to replace Spark and its Python-based architecture - Latest performance enhancements and potential benefits for big data processing - Speaker's off-topic mention of their need for a haircut and upcoming AI webinar 2. Open Source Technology - importance, transparency, innovation sharing, and societal risks - AI's impact on job economy and upcoming AI-focused webinars - Partnership between IBM and Red Hat to aid AI and data endeavors - Chat GPT and its technological advancements and differences from predictive text - Speaker's request for advice on platform usage and backlog of "Data Driven" shows 3. Speaker Excerpts - Importance of maturity, need for coffee, and discussions of coffee-preparation techniques - Reflection on the evolution of technology and human psychology of expectations - Comparison of Spark and Hadoop and the need for open-source projects to solve specific problems - Speaker's personal experience with MacBook M2, "stream side streaming," and article on new data-processing framework Key Takeaways: - Ray, an AI/ML distributed computing framework, and its potential improvements over Spark and potential for big data processing - Importance of open source mentality for innovation, transparency, and societal risks with AI - Technological advancements with Chat GPT and seeking suggestions on a platform for usage - Speaker's personal experiences and upcoming webinars and shows

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.

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