Chris Re: How Machine Learning is Changing Software
Software has been "eating the world" for the last ten years. In the last few years, a new phenomenon has started to emerge: machine learning is eating software. That is, machine learning is radically changing how one builds, deploys, and maintains software — leading some to use the loosely defined phrase Software 2.0. Rather than conventional programming, Software 2.0 systems often accept high-level domain knowledge or are programmed by simply feeding them copious amounts of data.
In this Stanford HAI seminar, Stanford associate professor of computer science Chris Re describes the foundational challenges that these systems present including a theory of weak supervision, guiding self-supervised systems, and high-level abstractions to monitor these systems over time. This builds on his experience with systems including Snorkel, Overton, and Bootleg, which are in use in flagship products at Google, Apple, and many more.
This seminar took place on Jan. 27, 2021. Learn more about upcoming HAI events: https://hai.stanford.edu/events-hub
Видео Chris Re: How Machine Learning is Changing Software канала Stanford HAI
In this Stanford HAI seminar, Stanford associate professor of computer science Chris Re describes the foundational challenges that these systems present including a theory of weak supervision, guiding self-supervised systems, and high-level abstractions to monitor these systems over time. This builds on his experience with systems including Snorkel, Overton, and Bootleg, which are in use in flagship products at Google, Apple, and many more.
This seminar took place on Jan. 27, 2021. Learn more about upcoming HAI events: https://hai.stanford.edu/events-hub
Видео Chris Re: How Machine Learning is Changing Software канала Stanford HAI
Показать
Комментарии отсутствуют
Информация о видео
Другие видео канала
![Healthcare’s AI Future: A Conversation with Fei-Fei Li & Andrew Ng](https://i.ytimg.com/vi/Gbnep6RJinQ/default.jpg)
![Flexible systems are the next frontier of machine learning](https://i.ytimg.com/vi/Jnunp-EymJQ/default.jpg)
![Can Great Programmers Be Taught? - John Ousterhout - at #SoftGeeks](https://i.ytimg.com/vi/lgZ7Cxt5uIU/default.jpg)
![Light Years Ahead | The 1969 Apollo Guidance Computer](https://i.ytimg.com/vi/B1J2RMorJXM/default.jpg)
![How computers learn to recognize objects instantly | Joseph Redmon](https://i.ytimg.com/vi/Cgxsv1riJhI/default.jpg)
![The AI Hardware Problem](https://i.ytimg.com/vi/owe9cPEdm7k/default.jpg)
![Zack Witten: Extracting Structured Data from Legal Documents | PyData LA 2018](https://i.ytimg.com/vi/KrXJmaSHBJU/default.jpg)
![SambaNova Systems Solution Demo](https://i.ytimg.com/vi/QnziHqsOeXU/default.jpg)
![XLDB-2019: Snorkel - A System for Training Set Modeling](https://i.ytimg.com/vi/c_ZTjK5TaD0/default.jpg)
![PyTorch at Tesla - Andrej Karpathy, Tesla](https://i.ytimg.com/vi/oBklltKXtDE/default.jpg)
![Deep Learning: A Crash Course](https://i.ytimg.com/vi/r0Ogt-q956I/default.jpg)
![The E.U. AI Act: A Risk-Based Policy Approach to AI Applications](https://i.ytimg.com/vi/OhBsDIG8ioM/default.jpg)
![Stanford HAI 2019 Fall Conference - AI and the Economy](https://i.ytimg.com/vi/LIuUvSJoWMk/default.jpg)
![Why You Are Struggling To Learn Machine Learning.](https://i.ytimg.com/vi/k_2Wr0IcP-8/default.jpg)
![Machine Learning Zero to Hero (Google I/O'19)](https://i.ytimg.com/vi/VwVg9jCtqaU/default.jpg)
![Software 2.0 & Snorkel - Christopher Ré (Stanford University | Apple)](https://i.ytimg.com/vi/TWv5yb_0OEw/default.jpg)
![Natural Language Processing in Python](https://i.ytimg.com/vi/xvqsFTUsOmc/default.jpg)
![Why do people lie and how often are you lied to? | BBC Ideas](https://i.ytimg.com/vi/tjRP0FnoxN8/default.jpg)
![Snorkel: Dark Data and Machine Learning - Christopher Ré](https://i.ytimg.com/vi/yu15Nf5eJEE/default.jpg)
![Introducing the Stanford Institute for Human-Centered Artificial Intelligence](https://i.ytimg.com/vi/se4CQ5UZXaM/default.jpg)