by Nicholas Mitsakos | Artificial Intelligence, Book Chapter, Globalization, Technology, Transformative businesses, Writing and Podcasts
Artificial intelligence is driving technological disruption and economic transformation. It is a unique opportunity and, like PCs, the Internet, mobile, and cloud computing before it, AI is driving a new supercycle. Unlike previous technological revolutions, the current transformation is exponential, creating new industries and markets and impacting existing economic structures, costs, distribution, and employment. While productivity and economic growth are expected to surge, the most significant opportunity arises for capital owners, and therefore, investors. AI will be the most significant economic catalyst of the 21st century, fundamentally altering how we work, innovate, and create value.
by Nicholas Mitsakos | Artificial Intelligence, Biotechnology, Book Chapter, Science, Technology, Transformative businesses, Writing and Podcasts
With better models, more effective benchmarks, and a framework for constant improvement, now is the time to focus AI on complex, innovative, and transformational tasks. Essentially, AI and models should focus on hard tech. Hard tech refers to businesses rooted in advanced engineering and scientific innovation, often involving the development of physical products or systems that address complex challenges. Beyond drones, robots, and AI-driven hardware, the following are prominent examples of hard tech opportunities across industries. AI-driven hard tech is creating new business models and industries, such as personalized medicine, autonomous logistics, smart infrastructure, and agentic AI platforms that autonomously manage complex operations, reshaping the competitive landscape and unlocking new avenues for value creation. As a result, businesses and professionals who embrace interdisciplinary skills and continuous learning will thrive in the hard tech ecosystem.
by Nicholas Mitsakos | Artificial Intelligence, Book Chapter, Technology, Transformative businesses, Writing and Podcasts
So far, we’ve attempted to answer that question through benchmarks. These give models a fixed set of questions to answer and grade them on how many they get right. But just like exams, these benchmarks don’t always reflect deeper abilities. Lately, it seems as if a new AI model is released every week, and each time a company introduces one, it comes with fresh scores showing it surpassing the capabilities of its predecessors. AI research is a hypercompetitive infinite game. An infinite game is open-ended—the goal is to keep playing. However, in AI, a dominant player often produces a significant result, triggering a wave of follow-up papers that chase the same narrow topic. This race-to-publish culture puts enormous pressure on researchers, rewarding speed over depth and short-term wins over long-term insight. If academia chooses to play a finite game, it will lose.
This “finite vs. infinite game” framework also applies to benchmarks. So, do we have a truly comprehensive scoreboard for evaluating the true quality of a model? Not really. Many dimensions—social, emotional, interdisciplinary—still evade assessment. But the wave of new benchmarks hints at a shift. As the field evolves, a bit of skepticism is probably healthy.
by Nicholas Mitsakos | Artificial Intelligence, Biotechnology, Book, Writing and Podcasts
Uncertainty and decisions. This book helps readers better understand a situation (What), determine why it’s important (So What), and decide what to do next (Now What).The world is uncertain, and all decisions are made in an uncertain environment with unpredictable outcomes. This challenge transcends disciplines, industries, and professions. An increasingly complex modern world shaped by artificial intelligence, geopolitical instability, data overload, and rapidly evolving technology can overwhelm decision-makers who rely on outdated ways of thinking. Uncertainty is unavoidable. It is not the enemy. It can be navigated with structure and discipline. Critical thinking, multiple perspectives, and decision tools help prioritize, forecast, and adapt decisions, but cannot dictate outcomes. “Decision Intelligence” is vital because it combines data, models, and human judgment, all augmented with new technologies, especially artificial intelligence. Better decisions come from clarity, not certainty. This is the foundation of resilience, agility, and better decision-making during volatile, unpredictable, and transformative environments. It’s not simply a matter of having a formula. Uncertain circumstances are not simple mathematical problems but require systematic and structured thinking. Understanding these structures and the motivations behind the various approaches will be essential. This approach is more of a way to think about thinking. As Einstein said, “Give me 60 minutes to solve a problem, and I will spend 55 minutes defining it. Then the solution will be obvious. ”This book is about those 55 minutes.
by Nicholas Mitsakos | Artificial Intelligence, Book Chapter, China, Economy, Globalization, Public Policy, Science, Taiwan, Technology, Transformative businesses, Writing and Podcasts
The convergence of volatile geopolitics fragmented and unpredictable markets, disruptive technologies, and unique opportunities. Understanding geopolitical issues, developing innovative and insightful investment strategies, and navigating political and economic volatility are now essential to achieving investment success.
by Nicholas Mitsakos | Artificial Intelligence, Book Chapter, China, commodities, Currency, Economy, Globalization, Innovation, Trade, Writing and Podcasts
The United States and China play global economic and political chess games. There are many moves and defensive and offensive strategies, not only for trade but also for energy and natural resources (rare earths among the most recent flavors of discord), geopolitics (Russia, Ukraine, Iran, the Middle East generally), technology (Taiwan and AI), and global economic supremacy. It’s a long list, but China and the US drive the outcomes. Instead of working for mutual benefit, regardless of fundamental cultural and political differences, we are now drawing bright lines demarking battle zones (Ukraine and Russia; Taiwan; AI and advanced technologies). The result will be economic and technical inefficiency and degradation in the quality of life, safety, and prosperity. China must acknowledge the outrage caused by its overreaching bids for control, and America must adjust to China’s presence without selling honor for profit. Competition is not us-or-them; reality is us-and-them. The U.S. semiconductor industry gets 30% of its revenue from China. China’s resulting products service the world, and China’s producers need the U.S. as well. If allowed, such examples of mutual benefit will proliferate. It is naïve to imagine wrestling China back to the past. The project, now, is to contest its moral vision of the future. Connected, collaborative engagement is the only practical way. China has come a long way, and its trajectory cannot be ignored or dismissed. The U.S. and China will be much better off from this more enlightened, realistic perspective. See the whole board.
by Nicholas Mitsakos | Artificial Intelligence, Book Chapter, China, Globalization, Innovation, Public Policy, Transformative businesses, Writing and Podcasts
Significant VC activity and AI development opportunities are emerging in China. DeepSeek is the Vanguard of innovation from the artificial intelligence “moonshot” encouraged by the Chinese government. Not only will we see ongoing developments from Alibaba and Tencent, but there will also be a layer of elite AI companies at the forefront of China’s AI sector. US sanctions and restrictions have only increased innovation and groundbreaking AI development activity in China. Those sanctions will amount to nothing and encourage accelerated advancement.
by Nicholas Mitsakos | Artificial Intelligence, China, Technology, Transformative businesses, Writing and Podcasts
The announcement of a $500 billion commitment to building AI infrastructure in the United States, is another major salvo in the AI wars. At this point, it’s hard to distinguish whether this is just hyperbole from hyperventilating technology executives or something with real substance.
But, more importantly, it indicates an agenda to “win” in artificial intelligence. OpenAI, Softbank, and others are pushing the narrative to “beat China” and align themselves with the Trump administration. Fundamental is a belief that such a race exists, the US can gain advantage by dedicating computer resources, and it’s worth winning at all costs – whatever that means.
Unfortunately, computer resources don’t define a sustainable advantage anymore. A decoupling of resources and cooperation between the United States and China have forced the Chinese to develop near-equivalent models while using only a fraction of resources. bigger data centers, substantial computing resources, and overwhelming numbers of GPU production won’t win this arms race.
It’s A Zero-Sum Game That Amounts to Nothing.
by Nicholas Mitsakos | Artificial Intelligence, Innovation, Podcast, Writing and Podcasts
This podcast discusses my article on the current state of artificial intelligence, focusing on the limitations of large language models and the unrealistic expectations surrounding the development of artificial general intelligence (AGI). I argue that AI systems are not on a trajectory to match or exceed human intelligence because LLMs lack common sense and rely on regurgitating information rather than understanding. Despite the hype surrounding AGI, it is decades away, and the current focus on LLMs is misguided. Instead, I advocate for a different approach to AI that incorporates real-world interactions and visual data.
by Nicholas Mitsakos | Artificial Intelligence, Writing and Podcasts
This is a new podcast based on my artificial intelligence research. I argue that the current approach to artificial intelligence, reliant on massive datasets and “neural networks” inspired by the brain, is fundamentally flawed. Instead, it advocates for a new vision that prioritizes cognitive architecture, mirroring the brain’s ability to process information dynamically and identify relevant data. This new approach would utilize smaller, more focused datasets, leading to more efficient, accurate, and scalable AI systems capable of true learning, knowledge transfer, and prediction.
by Nicholas Mitsakos | Artificial Intelligence, Digital Assets, Finance, Financial Technology, Innovation, Transformative businesses, Writing and Podcasts
Apple can disrupt global finance. Visa and MasterCard are now vulnerable. Previously, it was believed that the capital required for infrastructure, systems, and processing was an insurmountable obstacle to any new competitor. But things have changed. Innovation and disruption in the credit card business pose a threat to established players like Visa and MasterCard. Apple can leverage its ecosystem, user experience focus, brand trust, strategic partnerships, and innovative use of data to succeed in the credit card business. Over time, as it scales and innovates, it could challenge Visa and MasterCard’s market dominance.
by Nicholas Mitsakos | Artificial Intelligence, Book Chapter, Innovation, Science, Technology, Transformative businesses, Writing and Podcasts
AI is not a data problem; it is a cognitive architecture problem. Data and computing power will become insurmountable hurdles for transformer-based models. A new generation of AI models requires fundamental breakthroughs. Large data models can’t learn, transfer knowledge or understanding, understand the relevance, or use analogous learning to transfer that relevance and predict. Current AI models require massive and increasing data and learn from reinforcement. This cannot scale and is massively inefficient. Real learning based on cognitive architecture, focused dynamic data, and referential data sets is a better solution. This is closer to real human learning, more effective and efficient, and offers a significantly better solution. Understanding the natural learning process — referential and analogous data, categorization, transferring and building upon that data, and creating knowledge applicable to new situations — learning builds upon itself and is exponentially effective. That is the real AI solution.
