The book attempts to bridge the gap between algorithmic processes and practical decision-making in uncertain circumstances. It moves beyond mathematical solutions to acknowledge the complexity of real-world decisions. The author, Nicholas Mitsakos, argues that decision-making is essentially a form of statistical analysis that involves models or algorithms, and being thorough in this understanding confers a significant advantage. is a comprehensive text discussing decision-making under uncertainty and the algorithms that can enhance the decision-making process. It covers a wide range of topics, including applications in various fields such as air traffic control, drug discovery, autonomous driving, and more. The introduction sets the stage by discussing the importance of understanding and managing uncertainty in decision-making. It defines algorithms in the context of systematic thinking and approaches to problem-solving, emphasizing the significance of defining problems clearly to find obvious solutions.
Stunning capabilities are emerging from large language models like GPT 4 that, until very recently, were thought to be only theoretical. We could never have the data sets or the processing power to generate real and usable results. Well, all that has changed – rather suddenly.
But is it time for the torches and pitchforks? What are the serious risks that accompany this technology?
There will be good and bad, like every new era. Will it be the Middle Ages all over again and we’ll experience The Plague before the Renaissance, or will it be more balanced and reasonable? There are good, bad, and many things in between whenever humanity advances.
Let it happen. Put down the pitchforks.
Artificial intelligence is disrupting all software and services – when applied within narrow and specific parameters. It performs useful tasks and provides meaningful information for decision-makers but within well-defined data sets.AI still has significant limitations, and large language artificial general intelligence programs like ChatGPT (AGI) may not be the big leap forward many imagine. It is not the vanguard of a new era permeating every aspect of our professional, academic, and personal life. AGI’s usefulness is overstated, and it is not going to happen. Intelligence is not a lumbering statistical engine searching for patterns to generate a useful response. AGI is. The predictions of AGI are superficial and dubious. True intelligence is the ability to think and express improbable but insightful ideas (e.g., Einstein’s Theory of Relativity, Newton’s Laws of Motion, and many other improbable, insightful, and truly intelligent insights). Machine learning cannot do this. ChatGPT is a lumbering statistical engine searching for pattern recognition and feeding on incomprehensible terabytes of data and extrapolating the most probable answer. By contrast, the human mind is an efficient elegant system operating with small amounts of information. Human intelligence creates explanations. It does not infer conclusions by brute force and spurious correlations.
Our most intractable problems cannot be solved with behavior modification, conservation, or our existing technology, regardless of its advanced or widespread applications.
Only new knowledge creating innovative solutions can address our most intractable problems. This can only be achieved through basic scientific discoveries and then combining these discoveries with enterprise-based innovation, commercial discipline, and competition. Innovation, creativity, and competitive dynamics create the most effective innovations, the best solutions, and the most sustainable companies. Developing the best public policy as well as the best structure to enable innovative and creative solutions, as well as the economic incentive to scale these opportunities and make them economically sustainable.
Central planning, bureaucratic industrial policy, government-led economic management, and dictatorial focus have always failed, and always will.
Discovery, innovation, and practical application are never a straight line and, the best analogy is “the broken road.” Our greatest discoveries and advancements have confusing, uneven, and broken pathways that often lead somewhere astonishing – even though at the outset the initial steps could never envision this as a final destination. Artificial intelligence is the embodiment of this concept. A powerful tool that can lead anywhere given the imagination and unlimited creativity of its users. There may be nowhere more impactful, generating therapies for unmet medical needs in record time, than artificial intelligence’s ability to mimic evolution in minutes. The real outcomes are still unpredictable, but the potential is unfathomable. AI languages that produce pictures seem to be initially relegated toward a combination of Tik-Tok influencers, outraged artists, and those with limited imaginations and creative skills. But now, AI-generated pictures can use text to direct specific protein designs with properties of shape, size, and/or function that make it possible for these new proteins to perform specific tasks on demand. This breakthrough may lead to more efficient and effective drug development and, the discovery in minutes of what evolution would otherwise have taken millions of years to develop.
Most current innovations have yet to reach their potential, and new innovations are essential to address the most critical issues we confront, whether that is climate change, food scarcity, water shortages, or more effective distribution of innovation itself. Advanced technologies can be many things, but several areas, including artificial intelligence, life sciences, and software innovations provide the most potent platform for new opportunities, disruptive innovation, and value creation. Software will disrupt the most important industries in the world, especially finance, life sciences, and communications. These will be the fundamental innovations that will drive value creation over the course of the next year, and from now on.
This book explores the next decade’s more frequent and intense economic, geopolitical, fiscal, and market volatility, technological innovation, disruption, and hype.
Long-term opportunity exists, and this book uses a 10-year horizon as a surrogate for a long-term perspective. Some of the world’s most important industries are being disrupted, especially finance via digital assets and Blockchain-based businesses, life sciences via gene editing, DNA sequencing, and CRISPR, and communications via advanced wireless data networks, software technologies including artificial intelligence, and new interactive platforms such as the Metaverse.
The collapse of FTX shows how easily crypto is manipulated and the “crypto ecosystem” is fundamentally driven by centralized players and not any true form of decentralized or digital assets. Cryptocurrency is a sideshow and benefits no one other than speculators hoping for a greater fool. However, the combination of digital asset regulation, central-bank cooperation, and distributed assets via decentralized platforms still represents one of the most intriguing opportunities, and, with the potential disruption of global finance, one of the most exciting investment areas today.
A new vision for artificial intelligence is using smaller more relevant data sets for dynamic learning generating more effective outcomes and better predictions. This model uses cognitive architecture, learns, transfers learning, and retains knowledge – enabling more valuable and compelling artificial intelligence applications. This approach is more closely related to the brain’s actual structures and much more effective than “neural networks,” which is a catchy name but the similarity to the brain’s actual functioning is in name only. Real advancement in artificial intelligence must live in reality, not theoretical marketing. The current state of artificial intelligence shows the shortcomings of big data and trial-and-error approaches. A new AI vision can be a more effective solution. Smaller data sets, more relevant information, dynamic data, and algorithms will lead to more appropriate outcomes, better tools, and more effective applications.
The onslaught of market-making bad news seems almost a daily event. A gloomy picture of slowing economic growth, elevated inflation, and confusing fiscal and monetary policy has added a lethal mixture to the market’s performance. Fiscal stimulus is sidelined, and monetary policy is constricting economic growth and entrepreneurial innovation. It makes for a gloomy outlook and an even more depressing long-term perspective. The next 10 years look more like a lost decade. High-growth company valuations have been significantly discounted, and over time as discount rates drop, their valuations are likely to increase substantially. Higher-yielding fixed income securities will be a standout performer as interest rates are reduced, the higher-yielding BDCs, REITs, leveraged loan securities, and high cash flow instruments, along with high-dividend equities, will prove extremely attractive and are currently available at bargain prices. Providers of value and users of value will be the winners for the next decade. Those generating real cash flow and disruptive innovation will define the next decade.