Chapter
The Origins of Weka, the First Open Source Machine Learning Toolkit
58:31 - 1:04:34 (06:03)
Researchers from Waikato University in New Zealand created Weka, the first open-source machine learning toolkit, which was launched in the early 90s. The funding for this project came from a government grant to study machine learning to predict the menstrual cycles of cows.
Clips
The advancement of self-driving car technology in Germany was pretty much independent of AI military advancements and has progressed further globally than most realize.
58:31 - 1:00:03 (01:31)
Summary
The advancement of self-driving car technology in Germany was pretty much independent of AI military advancements and has progressed further globally than most realize. The academic AI field in the past focused on rule-based expert systems and production systems, which seemed wrongheaded to our speaker.
ChapterThe Origins of Weka, the First Open Source Machine Learning Toolkit
Episode#103 – Ben Goertzel: Artificial General Intelligence
PodcastLex Fridman Podcast
The AI field should be focused on learning from experience rather than typing in knowledge for AI to think, according to a pioneer in the field.
1:00:03 - 1:00:47 (00:44)
Summary
The AI field should be focused on learning from experience rather than typing in knowledge for AI to think, according to a pioneer in the field. During the mid-80s, John Andreas discovered a book about a reinforcement learning system called PURPOSE, which was interested in learning from experience.
ChapterThe Origins of Weka, the First Open Source Machine Learning Toolkit
Episode#103 – Ben Goertzel: Artificial General Intelligence
PodcastLex Fridman Podcast
This episode explores the creation and evolution of Weka, the first open-source machine learning toolkit.
1:00:47 - 1:04:34 (03:46)
Summary
This episode explores the creation and evolution of Weka, the first open-source machine learning toolkit. It was launched in the early 90s by Ian Witten and his colleagues, and received early funding from a New Zealand government grant aimed at using machine learning to predict the menstrual cycles of cows.