key concepts in review this section briefly synthesizes the key takeaways from this book if you ever need quick refresher to help you recall what you've learnedyou can read these few pages various approaches to ai first of alldeep learning isn' synonymous with ai or even with machine learning artificial intelligence is an ancientbroad field that can generally be defined as "all attempts to automate cognitive processes"--in other wordsthe automation of thought this can range from the very basicsuch as an excel spreadsheetto the very advancedlike humanoid robot that can walk and talk machine learning is specific subfield of ai that aims at automatically developing programs (called modelspurely from exposure to training data this process of turning data into program is called learning although machine learning has been around for long timeit only started to take off in the deep learning is one of many branches of machine learningwhere the models are long chains of geometric functionsapplied one after the other these operations are structured into modules called layersdeep-learning models are typically stacks of layers--ormore generallygraphs of layers these layers are parameterized by weightswhich are the parameters learned during training the knowledge of model is stored in its weightsand the process of learning consists of finding good values for these weights even though deep learning is just one among many approaches to machine learningit isn' on an equal footing with the others deep learning is breakout success here' why what makes deep learning special within the field of machine learning in the span of only few yearsdeep learning has achieved tremendous breakthroughs across wide range of tasks that have been historically perceived as extremely difficult for computersespecially in the area of machine perceptionextracting useful information from imagesvideossoundand more given sufficient training data (in particulartraining data appropriately labeled by humans)it' possible to extract from perceptual data almost anything that human could extract henceit' sometimes said that deep learning has solved perceptionalthough that' true only for fairly narrow definition of perception due to its unprecedented technical successesdeep learning has singlehandedly brought about the third and by far the largest ai summera period of intense interestinvestmentand hype in the field of ai as this book is being writtenwe're in the middle of it whether this period will end in the near futureand what happens after it endsare topics of debate one thing is certainin stark contrast with previous ai summersdeep learning has provided enormous business value to number of large technology companiesenabling human-level speech recognitionsmart assistantshuman-level licensed to