In The Line: AI and the Future of Personhood, James Boyle embarks on a thought-provoking exploration of the moral, philosophical, and legal challenges that artificial intelligence (AI) and other synthetic entities will bring to our understanding of what it means to be a person. Published by MIT Press, this book poses challenging questions about the boundaries of humanity and legal personhood at a time when AI and genetic engineering push those limits.

When we think of the giants on whose shoulders modern technology stands, names like Alan Turing and John von Neumann often come to mind. Edsger W. Dijkstra made incredibly significant contributions that have impacted computer science, programming, and operations research. His pioneering work established the foundation for the algorithms that drive today's technology and transformed our approach to programming and problem-solving.

In the ever-evolving landscape of modern organizations, the integration of Generative AI is transforming our approach to problem-solving, decision-making, and organizational design. Amid this technological revolution, it is essential to revisit the fundamental principles of systems thinking. Few individuals have made more significant contributions to this field than Russell Ackoff, a pioneer whose insights continue to guide us toward a holistic understanding of organizations.

Major tech companies now offer new bounties to secure their AI infrastructure in a significant shift within the cybersecurity landscape. With Apple recently announcing a $1 million bug bounty for their Private Cloud Compute servers and OpenAI offering up to $20,000 for critical vulnerabilities in ChatGPT, it's clear that securing AI infrastructure has become a top priority in the tech industry.

As artificial intelligence (AI) continues transforming industries, from customer service to healthcare, it becomes crucial to understand its capabilities and limitations. Recent insights from Apple’s AI study and Erik Larson’s arguments in The Myth of Artificial Intelligence provide a more nuanced perspective on what AI can and cannot do. Let’s explore these two perspectives and what they mean for the future of AI development.

In a world that often focuses on external rewards and incentives, we overlook one of the most potent forces driving human behavior—intrinsic motivation. This internal drive to engage in activities for their inherent satisfaction, enjoyment, or personal growth is crucial in fostering creativity, productivity, and long-term success.

Juergen Schmidhuber, often hailed as the original "father of AI," is a key figure in artificial intelligence, renowned for his pioneering work on neural networks and deep learning. His contributions have significantly shaped the landscape of AI, influencing both academic research and practical applications. However, beyond his well-documented achievements, Schmidhuber's career is peppered with intriguing and lesser-known stories offering more profound insight into his multifaceted persona.

Few names stand as tall in the annals of operations research and artificial intelligence as Allen Newell. Born in 1927, Newell's career was one of innovation and interdisciplinary brilliance that continues to influence operations research, cognitive science, and AI today.

In a groundbreaking and somewhat unexpected development, Geoffrey Hinton, renowned as a pioneer in artificial intelligence, has been awarded the 2024 Nobel Prize in Physics. Traditionally reserved for groundbreaking contributions to physical sciences, this accolade has sparked widespread intrigue and discussion across both scientific and public domains. Hinton, often called the "Godfather of AI," is celebrated for his seminal work in deep learning and neural networks, which have revolutionized the field of artificial intelligence and its applications across various sectors.

Today, I had the privilege of presenting at DevOpsCon NYC 2024 on a topic close to my heart: “Beyond Checkboxes: Embedding Resilience.” As the field of DevOps evolves, it’s critical to shift from superficial metrics to truly embedding resilience into every layer of our systems. My presentation focused on how we can think differently, learn from historical approaches, and adopt resilient frameworks that are built to withstand the challenges of modern infrastructures.

Generative AI (GenAI) offers companies transformative opportunities as the technology landscape rapidly evolves. However, with these advancements come significant risks. Pillar Security's latest report, "The State of Attacks on GenAI," sheds light on the vulnerabilities surrounding GenAI applications and provides critical insights from real-world data interactions. The findings from over 2,000 LLM-powered applications reveal the increasing frequency, complexity, and impact of security breaches. Here’s a breakdown of the report’s major takeaways:

During the weekend, my son and I took an Arthurian road trip through the south of England. Since I've been fascinated by the Arthurian legend for most of my life, I thought it would be fun to combine work and pleasure. This week, I cheated and asked GPT 01-preview to make up this story; however, the pictures are real.

We’ve all heard the buzz around AI reshaping industries and boosting productivity. Fortune 500 companies are taking action and integrating AI successfully. But as we stand on the edge of this new AI-driven world, we also know that with any technology, there are risks, and the most pressing ones with AI are technical debt and shadow AI. These hidden challenges are not unlike the early days of cloud and big data adoption, where the rush to innovate left businesses grappling with long-term consequences.

Few names have impacted operations research as profoundly as Merrill M. Flood. In this first installment of our series on great operations researchers, we honor Flood's pioneering work, especially his significant contributions to the Traveling Salesman Problem (TSP).

I recently visited the Toyota Material Handling Solutions (TMHS) facility in Columbus, Indiana, where I witnessed firsthand the precision and efficiency of their operations. Since 1973, TMHS has been a critical player in the material handling space, supplying a range of industry-leading brands like Toyota forklifts. The company stands as a model for lean practices—an approach deeply rooted not only in the philosophy of continuous improvement championed by Dr. W. Edwards Deming but also in the enduring core values established by Toyota's founders, Sakichi Toyoda and TPS founder Taiichi Ohno.

In recent conversations, I found myself reflecting on some fascinating ideas shared by Dr. Jabe Bloom during a podcast we recorded. We ventured deep into the realms of philosophy, Deming, DevOps, and artificial intelligence (AI), with particular emphasis on pragmatism and the role of abductive reasoning in complex systems.

As artificial intelligence continues to evolve, organizations are under increasing pressure to manage and scale their AI systems effectively. However, the broader issue confronting CIOs is the technical integration of AI models into existing systems and the entire approach to AI governance, scalability, and security.

Next week, I’m thrilled to be giving a presentation titled "Deming to DevOps" at a special 15th anniversary edition of devopsdays in Antwerp. For those who don't know, the first devopsdays was born, back in April 2009 at a CloudCamp in the Antwerp Zoo. That idea blossomed into the first conference later that year in Ghent, and now, 15 years later, they are bringing the DevOps community back together at the venue where it all began.

Ten years ago, I delivered an Ignite presentation titled "Deming to DevOps: The Science Behind DevOps," where I explored the historical events, philosophies, and influential figures that bridge Deming's work to the modern DevOps movement. On October 24th, I'll revisit this topic in a new presentation, examining how that history has evolved since my original talk. In this edition, I want to summarize my original presentation to set the stage for the upcoming discussion and highlight the connections between Deming's legacy and the continued growth of DevOps.

When exploring the origins of modern quality management and statistical process control, the name Dr. W. Edwards Deming inevitably comes to the forefront. Deming’s profound influence on manufacturing, especially in post-war Japan, and his development of the Plan-Do-Study-Act (PDSA) cycle are legendary. However, beneath the surface of Deming’s groundbreaking work, one might detect echoes of an earlier intellectual giant: Charles Sanders Peirce.