This book was published by CRC Press on 18 Sep 2024. The following is a brief description.
Although deep level neural networks, the models that drive the latest generative AI and large language models, have made impressive progress in real world applications, as well as captured the imagination of the public, they fall short of achieving anything near to HLAI. We explain these shortcomings and what is necessary to achieve HLAI at a high level. The speculations in this work are based on the evidence presented on neuroscience and AI research and are intended to stimulate thinking about how to build HLAI.
The foremost assumption made in this book is that it is possible for us to understand how the human brain works if we crack the neural code, i.e., how the human brain encodes the sensory information it receives, and moves information in the brain to perform cognitive tasks, such as thinking, learning, problem solving, internal visualization, internal dialogue, etc. A second key assumption is that in breaking through with such understanding we will then have the knowledge to create a human-level artificial intelligence (AI and HLAI): a machine that can perform cognitive tasks at the level that the best humans can achieve.
The readership this book aims for runs across anyone interested in the topic of where AI goes next: AI researchers, neuroscientists, students, research budget holders, venture capitalists, and the interested general reader. This book is divided into four parts:
- Part Zero provides a level setting for definitions of what I mean by AI, machine learning, deep learning etc. It provides a little history as well to put our current state of knowledge in AI into perspective so that the challenges ahead can be put into historical context.
- Part One pulls out of the neuroscience research literature useful pieces of information that should inform future AI models. It is all about facts, and is evidence based.
- Part Two covers the theories (perhaps more accurately called hypotheses) being pursued by first neuroscientists and then AI researchers on how the brain works.
- Part Three is speculative in nature, pulling bits from earlier chapters and trying to make sense of them holistically, in a logical manner, to guide research towards HLAI. For those AI researchers building HLAI systems I offer a series of test questions to compare with your model. This test is designed to follow more closely our knowledge of the human brain and what is likely to be needed in an HLAI model.
This book also touches on these questions:
- Do you need to be alive to have consciousness?
- Do you need consciousness to have intelligence?
- Do you need to be alive to have consciousness?
And presents an argument for why computer simulation of an intelligent system can create a virtual world in which HLAI can exist.