Puzzling AI Trends 2025-26 Audiobook By H. Peter Alesso cover art

Puzzling AI Trends 2025-26

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Puzzling AI Trends 2025-26

By: H. Peter Alesso
Narrated by: Virtual Voice
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About this listen

 In November 2022, OpenAI quietly released ChatGPT to the public. Within five days, it had a million users. Within two months, one hundred million. This moment marked the beginning of the most rapid technological transformation in history—one that would fundamentally reshape not just the tech industry, but every aspect of how we work, learn, and interact with information.

"Puzzling AI Trends" traces the Large Language Model revolution through three distinct eras. The Pre-Cambrian Era (2022) saw AI locked within tech giants, with models costing tens of millions to train. The Cambrian Explosion (2023) brought ChatGPT's viral success and Meta's game-changing decision to open-source LLaMA, democratizing AI access. The Great Bifurcation (2024-2025) split the market between commoditized general intelligence and premium reasoning systems.

The book profiles major players reshaping AI: OpenAI's relentless capability push, Google's infrastructure dominance, Anthropic's safety focus, and Meta's disruptive open-source strategy. It reveals how Chinese companies like DeepSeek and the UAE's Falcon challenge Western dominance while specialized innovators find profitable niches.

The economic transformation is staggering. In two years, GPT-4-level intelligence costs dropped 90%. Models costing hundreds of millions to train now run on hardware costing thousands. The book analyzes true AI costs beyond API prices—infrastructure, expertise, and operations—helping organizations decide whether to build or buy capabilities.

A key contribution is examining the open-source versus proprietary divide. Through case studies and cost analyses, readers learn when "free" models save money, when APIs provide better value, and how to combine both effectively. Legal complexities, from licensing restrictions to IP implications, receive careful attention.

Looking ahead, the book projects AI's 2025-2026 impact across major sectors. Finance will see real-time risk modeling and hyper-personalized advisory. Medicine will witness AI diagnostics outperforming specialists and compressed drug discovery timelines. Engineering will adopt generative design and predictive maintenance as standards.

The book addresses crucial questions about measuring machine intelligence, revealing how benchmark convergence at ~90% performance forces new evaluation approaches. Specialized reasoning models that trade speed for accuracy represent a new frontier for applications requiring deep thought over quick patterns.

Essential reading for technology leaders, executives, investors, policymakers, and developers seeking to understand how AI will reshape business and society.
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