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The Self-Assembling Brain: How Neural Networks Grow Smarter PDF

384 Pages·2021·25.1984 MB·other
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A thought provoking book that makes us question whether we are taking the right approach with AI?

Reviewed in Germany on 8 August 2021 Verified Purchase

The book is a real pleasure to read. It provides the unusual mix of strong scientific evidence and alternating fictional arguments between a geneticist, a neurobiologist, an engineer, and an AI researcher. The book compares the approaches of these different fields to figure out what makes neural networks intelligent. In the biology part, the book explores in depth HOW genes make brains. The author uses algorithmic information theory and cellular automata to argue that the developmental outcome of a single gene mutation is not predictable. Basically, only evolution can program the genes based on selection of outcomes. How evolution itself plays an irreplaceable role in neural network formation and consequently in brain related behaviours is currently missing from engineering approaches to AI.
For me, the most impactful point was learning that AI can't reconstruct overnight what nature has been constructing and moulding through years and years of evolution. And realizing that each individual is unique and carries a special set of ancestral wisdom that has been genetically refining as part of the evolutionary process. How does the brain fit in the genes? Are younger generations smarter than our ancestors? How can we account for evolution with AI? Acknowledging the significance of developmental biology and evolution when tackling learning with AI. Definitely, a perplexing, controversial and thrilling concept that marks the beginning of new approach.

 A remarkable book from an accomplished neurobiologist.

Reviewed in the United States on 15 May 2021Verified Purchase

In this extremely scholarly but also quite accessible book, Robin Hiesinger systematically covers historical and conceptual landscape that forms the basis for today’s developmental neurobiology and artificial intelligence (AI) disciplines. The text relies on various narrative approaches to initiate the much-needed conversation between contemporary AI and neurobiology communities. This book has the potential to have the impact similar to Erwin Schrödinger’s famous “What is Life”, which fostered the molecular biology revolution, bringing disciplines together for true advances in understanding how brains are built and function.
Lisa Monteggia & Ege Kavalali, Neuroscientists

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