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.
Cryptocurrencies soar in value, plunge, hit new highs, are written off, rebound, and hit new highs again, and the cycle repeats. We should be terrified. Over the last five years, cryptocurrencies such as Bitcoin and Ether have outperformed the overall market. However, can the general trend of outperformance last, or will these digital assets drop over 90% like some of its other crypto brethren? Is there a sustainable performance that creates the foundation for either a new currency or a valuable asset class? Probably not. Forces that drive these eye-watering returns seem to be the same as those that drove the social media-driven insanity behind meme stocks such as GameStop. We are seeing social media mobs controlling demand to a limited supply, creating price spikes that look attractive to any speculative investor. Unfortunately, demand can dry up quickly and the price subsequently falls through the floor. Financial markets ruthlessly sort nonsense from substance. Volatility and existential threats have been brutal and extreme for digital assets and the reckoning for crypto has been predicted for some time. However, digital assets are not on their way to history’s dustbin. Reality is more nuanced, and I try to provide a more detailed analysis since a broad brush hardly seems appropriate. The weakest and craziest portions of the crypto world have been exposed as nothing more than silliness. But some valuable components remain resilient and offer tremendous opportunity. I will explore these in detail. There is more cause for optimism than pessimism among the best and the brightest. We will explore these opportunities while harshly dismissing the hype and silliness – avoid the terror of a worthless market.
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.
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.
Predictions usually end up being nonsense. We simply draw a trajectory from what we know today. But innovation is a discontinuity. Things are unpredictable because innovation does not come from consensus thinking. It comes from small groups and individuals with a spark of entrepreneurship, intelligence, and vision.
One of the fundamental tenets of predicting technology is that most forecasters get things spectacularly wrong.
The rewards for innovative success have become enormous and unpalatable, especially among the five technological giants (Amazon, Apple, Facebook, Google, and Microsoft) forcing these firms to spend absurd amounts of money on lobbying in Washington DC. It’s an expensive and wasteful distraction, but essential in this brave new world. If nothing else, it clogs innovation. It is to our detriment – and the world is literally burning while politicians fiddle – and even more disastrously – impede innovative activity. Applying friction to free thinking and new ideas never ends well.