AIQ: How People and Machines Are Smarter Together

This book is excellent! In a very easy to absorb fashion, the book describes how artificial intelligence is used in our daily lives and what are the current limitations. It demystifies the term and makes it more concrete by explaining the algorithms and methodologies used by the modern AI systems. Most importantly this book shows that by knowing some basic math concepts one can come up with new applications of the AI algorithms. It reinsures that AI can be understood and applied by almost anyone. This book is great for anyone who is generally interested in the topic as well as for scientist, engineers, or businessmen who are interested in applying AI techniques in their work .

Great introduction to the topic, giving plenty of background and context to AI. The authors go quite far back into the history of computing which is great given a lot of the recent discussion is just about throwing around buzzwords. If you are already familiar with the basic concepts though, then this might not be the best book for you unless you want a recap.

As someone who has worked in the tech space for nearly 10 years but more so on the biz dev side, AI seemed like an abstract concept to me. The authors do a great job explaining this is simply probabilities and aside from some Bayesian equations and simple stats 101 material, the book is light on mathematical equations which makes it much more enjoyable to read. If you want to have a much stronger conceptual grasp of AI, Data science, et, this book is perfect

Great examples and analysis of what IA is and can become: a perfect tool for humans to use in the better development of our society. All this in a simple and astonishing way by introducing the historic origins of important use cases of AI.A book definitely not to miss!

This book does a fantastic job walking through the building blocks that have helped lead to the A.I. revolution.In addition to describing some of the fundamental elements that people should understand before diving into A.I. it has a very well written and interesting way of tying it back to historical episodes that help illustrate how these ideas were once used (or in one particularly interesting case should have been used) before layering on top of one another to become the systems we utilize today.

While a good read, there isn't anything here that you would not expect to find.

If you are interesting in what AI really means and are willing to wade through a little bit of math, this is a really helpful guide. I wish the authors did a little more when transitioning between topics to make it clearer how everything fits together.*How AI works in a nutshell*Start with algorithms, or step by step instructionsChain them together to do complicated thingsAI models train themselves using training data*Why is AI such a thing right now*Bigger models - able to have more prediction variables, the danger we over fit modelsFaster chips for processingAccumulation of much more data, powering smarter algorithmsCloud computing infrastructure makes it easy to get started*Conditional Probability*Conditional probability is the probability of a given bWe can learn a lot b carefully modeling missing dataBayes theory - treat prior information as a posterior probability so that you start with most likely and then apply lessons to rest of probability. Great example of this is a search for a nuclear submarine. Given what was known, researchers could calculate the probability of a sub being in a certain location. As searches were conducted, each observation helped improve the model. Best way to visualize this is showing 100 dots and saying "If a person gets a positive test result on a cancer test, what is the chance they actually have cancer" and breaking it down.*Latent Features*Latent features are underlying predictors of multiple variables. If you like Parks and Rev and like the Office, the latent feature is you like comedies.A pattern is a prediction rule that maps an input to an outputLearning a pattern means fitting a good prediction rule to a data setFeature engineering - converting inputs into numbers since that's how computers read info*How unsupervised learning works*Start with an initial guessFor each new data points, estimate standard errors and investigate how to make error smallerA deep neural network is simply multiple layersLet's take the the work required to understand using a series of pictures that stars are brightening and dimming periodically by breaking it down into 5 layers, each building upon the last as a representation for what happens in a neutral network:1. Bright parts of photo are bright parts of sky2. Stars are bright spots surrounded by darkness3. The brightness of a star is the size and intensity of the bright spot4. The brightness for a given star is pulsating, changing between photos.5. The period is the time from bright to dim to bright*Resources*Image net - millions of photos categorized for accuracy assessment*Story everyone should know*Grace Hopper - first person to use computers to run subroutines aka have computers run programs so that humans don't copy paste. Genius.

Great book, well written and explains how current AI works and what the societal issues are likely to be. It is done in a way that most educated people should find to be clear and sensible. The authors' goal is to give readers a background to be able to form intelligent views ot what the promise and potential problems of AI are. I think they have largely succeeded.

I believe, whoever want to know more about how AI really looks like and how you can understand how professionals in this area make things happens, I recommend this book, and particularly for me that I don't have so much time for reading, digital version is the best, perfect match, easy to follow, to search, to stop and comeback, etc

Excellent condition ! Such a good discount - a beautiful hard copy for the price of a paperback ! Really looking forward to the read :)

This book is a great read, whether you’re into data science professionally or just because you’re interested in knowing more. I found myself telling the same stories in this book helping others understand with context the point being made. My kids even enjoyed the stories, not even realising they were learning something.

Very absorbing book

Brilliantly explained in lucid prose with examples even for a Newcomer to the topic like me ( also not a pure science background) Covers both what and how AI works and also discusses the practical applications and benefits/risks and implications and likely future trajectory.