Brain Rush: How to Invest and Compete in the Real World of Generative AI
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- Дата: 5-07-2024, 02:06
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Автор: Peter Cohan
Издательство: Apress
Год: 2024
Страниц: 403
Язык: английский
Формат: pdf, epub
Размер: 10.1 MB
After decades of false starts, Artificial Intelligence (AI) is entering the mainstream of society. That is largely due to the rapid adoption of ChatGPT, a service that responds to almost any natural language question with cogent paragraphs. ChatGPT is the leading example of generative AI -- technology that creates original text, images, video and computer code based on uncovering patterns in training data.
The book will explain how generative AI works and how much economic value it could create and will map out the industry value network. For each value network stage, the book will define the industry, estimate its size, growth rate, and profit potential, identify the most successful participants, and explain how they have achieved their success and where they will compete in the future. The book will conclude with a section on what investors and business leaders should do to make an informed decision on where to place their bets.
Generative AI answers natural language questions with clearly written paragraphs, images, videos, or computer code. Through applications such as ChatGPT for text and DALL-E and Midjourney for images, Generative AI identifies “patterns in large quantities of training data, and then creates original material that has similar characteristics,” according to the New York Times. How do chatbots – generative AI applications for text – discover these patterns? Chatbots are large language models – computer systems that have processed large volumes of text – called training data. Through training, LLMs can predict the words most likely to follow any prompt the user supplies. LLMs are a type of neural network that seeks to replicate the way the human brain processes information. ChatGPT’s neural network is a transformer, which assigns numerical weights to the relationship between short bits of text, called tokens. Transformers use a technique called self-attention, which allows the model to focus on specific words that best elucidate the meaning of the sentence in which it appears.
What You Will Learn:
Insights on how best to assemble the resources – whether by hiring a consultant or bringing on board a generative AI expert -- to build, train, and operate company specific generative AI applications
How management can brainstorm, evaluate and execute the right opportunities
Concepts and processes to enable investors to place bets with the highest risk-adjusted returns
Who This Book is For:
Business and enterprises seeking to get value from generative AI, current or potential suppliers of technology and services to companies that build generative AI, and venture capitalists and public equity investors seeking to make profitable bets on generative AI companies.
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