What makes software intelligent?

Everyone, from journalists to investors, sees the growing impact of AI in our lives. But few know what’s under the hood. How do machine learning algorithms work, how did they arise, and where are they going? A detailed yet approachable explanation for the intelligent reader.

Length: 230 pages
Language: English
ISBN (Holloway.com):
Coming Soon
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Why read on Holloway?
Artificial Intelligence has become more important in society over time. Most of the software that people interact with has AI embedded in it. It is used broadly, from powering TikTok to helping predict cancer. These are still the early days of the development and impact of AI in different industries, and that will only increase. Making Things Think explains how these systems work in a simple way.Paul English(co-founder, Kayak)
About the Author
Giuliano Pezzolo Giacaglia
Giuliano has held several roles in technology and AI companies, from startups like Bluecore to Microsoft and Facebook. He has long been interested in the rise and applications of artificial intelligence. He holds two degrees from MIT, where he studied under Marvin Minsky, one of the founding fathers of artificial intelligence and founder of the MIT Media Lab. Giuliano also worked under Patrick Henry Winston, former director of the MIT Artificial Intelligence Laboratory, in the Genesis Group, helping to develop an account of human intelligence. This is his first book.
AI is going to be the engine of so much progress in the near-mid future across fields in tech, climate, medicine, retail and more. In this book, Giuliano goes over all the important developments in AI over the last decade, I'd recommend it to anyone who wants an overview of how these systems work.Ruchi Shangvi(former early engineer, Facebook and VP of Operations, Dropbox)

Table of Contents

A Brief History of AI
The Birth of Artificial Intelligence (1952–1956)
The Golden Years of AI (1956–1974)
The First AI Winter (1974–1980)
The AI Boom (1980–1987)
The Second AI Winter (1987–1993)
Probabilistic Reasoning (1993–2011)
IBM Watson
A Brief Overview of Deep Learning
Deep Neural Networks
Convolutional Neural Networks
Google Brain: The First Large-Scale Neural Network
DeepMind: Learning from Experience
AlphaGo: Defeating the Best Go Players
Software 2.0
Dueling Neural Networks
Data Is the New Oil
Data Privacy
Deep Learning Processors
What Can AI Learn from Animal Brains?
Learning to Learn Theory
Sleeping and Learning
Predicting the Future
Robots in the Industry
Machine Learning and Robotics
Self-Driving Cars
The Future of Self-Driving Cars
Industry Applications
Voice Assistants (Siri)
AI in Medicine
AI and Space
AI in E-Commerce
AI and the Law
AI and Real Estate
Risks and Impact of AI
Recommendation Algorithms
Interpretability of Neural Networks
Economic Impact of AI
Artificial General Intelligence
Landscape of Top AI Teams
Further Readings
Machine Learning Blogs
Courses and Programs
Year in Review Reports
Appendix: Short Biographies
Appendix: Select AI Tools and Efforts

Does this sound like you?

I see self-driving cars on the road and interact with different A.I. systems, like Siri. I want to learn how these systems work, and understand the likely developments in the area that will affect my life.
I’m deeply concerned about how my data is being harvested by tech companies and would like to understand how these companies can use A.I. to mine and analyze my data. How can my privacy be protected from unintended consequences? Aren’t data leaks inevitable?
From what I see AI doing now, I don’t understand how the technology could potentially achieve human intelligence. I would like to understand how close we are to Artificial General Intelligence.
I see news about artificial intelligence taking over the world, and I have seen some very impressive demos on the internet, with deepfakes and text generation. I would like to understand what the possible economic impacts of AI are, and more broadly how AI is going to impact the world in the near future.
I would like to know more about the history of AI, and how we got where we are now.

Learn more.

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