The KUNGFU.AI team has the following recommendations�on where to start on getting up to speed on AI.
Interested in learning more about KUNGFU.AI?�Please visit our website at www.kungfu.ai�or email Stephen Straus, Managing Director, at stephen@kungfu.ai
AI Primer
AI-Related News
It’s a constant challenge to keep up with the fast-evolving world of AI. Here are several sources for AI-related news to help you stay up to speed. The last two items are aimed at the technical community.
This Week in Machine Learning (TWIML)
Set a daily or weekly Google Alert for “artificial intelligence” or “machine learning”
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Deep Learning, and Machine Learning: A Primer
This 45-minute video called AI. Deep Learning, and Machine Learning: A Primer is a good place to start your journey. It is an overview of the basics of AI and deep learning and provides historical context to the technology.
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AI/ML Explained
This 25 page report called Artificial Intelligence/Machine Learning Explained by Steve Blank at Stanford University explains what AI is, gives examples of use cases and implications for AI in business and national security, and provides a perspective on where AI is going next.
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When to Use Machine Learning
This module of a technical course from Full Stack Deep Learning is a good overview of when to use machine learning for non-practitioners (and we recommend the rest of the course for technical people).
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AI for Everyone
Andrew Ng is one of the most high-profile machine learning engineers in the world, having led AI at Google and Baidu. He is now teaching at Stanford and investing in AI as a VC.
Andrew teaches this free course on Coursera called AI for Everyone that is an accessible way to dig in deeper on AI. The course is six hours long but is broken into short videos, many only 10 to 15 minutes long, making it easy to get through.
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Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World by Marco Iansiti and Karim R. Lakhani
Notes from Stephen Straus: I had Marco Iansiti as a professor at Harvard Business School in 1996 for a course called Managing Product Development and thought he was excellent. I stumbled across this book when I noticed the author, and I highly recommend it. In fact, everyone at KUNGFU.AI has read the book, and we have all new team members read it as they join and everyone agrees it’s the best book any of us have found on AI strategy.
Let me give some context for why I am so excited about this book. Back in the late 1990s, I remember feeling that it was obvious that the Internet was going to change everything but found it very difficult to see exactly how given how early we were in the unfolding revolution. It felt like the future was cloudy and that I could only see a few feet in front of me. Yet, I also sensed that we’d see the path forward to profound changes when the fog finally lifted.
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Continued...
In similar ways, I find myself feeling the same today regarding AI. This book helped me clear the fog on how AI will transform how businesses will reorganize to optimize for AI. It provides a clear and compelling vision for building AI-First companies and how traditional businesses can transform into AI-Forward companies. It also provides great insight into the inner workings of companies that are leaders in utilizing AI as the basis of their operating models today, including Netflix and the vaccine developer Moderna. It also makes the argument for the need for strong leadership and ethics to manage in the age of AI, something we as a company strongly believe.
To get an overview of the book, you can read this article in HBR. But, I strongly suggest you not stop there as the book is much deeper and richer and the material so relevant to effectively competing in the age of AI.��Our KUNGFU.BookClub put together this reading guide for others who read the book.
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The Alignment Problem: Machine Learning and Human Values
by Brian Christian
This is a must-read book for everyone involved in AI, from business leaders to the most technical practitioners. It is a really well written and fascinating exploration of issues related to fairness and ethics and the key technical and moral questions related to AI. We liked it so much that we have asked everyone at KUNGFU.AI to read it.
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