Episode

Surveying The Landscape Of AI and ML From An Investor's Perspective

Podcast
AI Engineering Podcast
Published
Oct 15, 2023
Duration seconds
3754
Processing state
failed
Canonical source
https://www.aiengineeringpodcast.com/mad-landscape-2023-ml-ai-episode-21
Audio
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JSON
/v1/public/podcasts/ai-engineering-podcast/episodes/surveying-the-landscape-of-ai-and-ml-from-an-investor-s-perspective
Markdown
/podcast/ai-engineering-podcast/surveying-the-landscape-of-ai-and-ml-from-an-investor-s-perspective.md

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Summary

Summary Artificial Intelligence is experiencing a renaissance in the wake of breakthrough natural language models. With new businesses sprouting up to address the various needs of ML and AI teams across the industry, it is a constant challenge to stay informed. Matt Turck has been compiling a report on the state of ML, AI, and Data for his work at FirstMark Capital. In this episode he shares his findings on the ML and AI landscape and the interesting trends that are developing. Announcements Hello and welcome to the Machine Learning Podcast, the podcast about machine learning and how to bring it from idea to delivery. As more people start using AI for projects, two things are clear: It’s a rapidly advancing field, but it’s tough to navigate. How can you get the best results for your use case? Instead of being subjected to a bunch of buzzword bingo, hear directly from pioneers in the developer and data science space on how they use graph tech to build AI-powered apps. . Attend the dev and ML talks at NODES 2023, a free online conference on October 26 featuring some of the brightest minds in tech. Check out the agenda and register today at Neo4j.com/NODES . Your host is Tobias Macey and today I'm interviewing Matt Turck about his work on the MAD (ML, AI, and Data) landscape and the insights he has gained on the ML ecosystem Interview Introduction How did you get involved in machine learning? Can you describe what the MAD landscape project is and the story behind it? What are the major changes in the ML ecosystem that you have seen since you first started compiling the landscape?  How have the developments in consumer-grade AI in recent years changed the business opportunities for ML/AI? What are the coarse divisions that you see as the boundaries that define the dif…