Google's latest terms-of-service update raises questions about AI autonomy, corporate liability, and who ultimately bears the risks of increasingly independent machines.If your organization uses Google Cloud, you may have recently received an email announcing updates to its Terms of Service, effective October 12, 2026.We received one at Conjugo.At first glance, it looked like another routine legal notification. Updated service terms. New usage guidelines. A few revised sections of a contract most customers will never read.But buried in that announcement was something considerably more consequential.Google is updating its legal framework to address the growing deployment of autonomous AI agen

For decades, the software industry has operated on a remarkably profitable premise: if you want to accomplish something digitally, you need an application to do it. Want to edit a photograph? Open Photoshop. Manage customer relationships? Log into Salesforce. Produce a video? Launch Premiere Pro. Analyze business data? Open a spreadsheet.Every task has its application. Every application has its interface. And increasingly, every interface comes with a monthly subscription.But what happens when the person no longer needs to open the application?What happens when artificial intelligence can accomplish the task directly?We may be approaching one of the most consequential transformations in the

The coming divide between personal AI assistants and industrial-scale artificial intelligence could determine who owns the next century of scientific and economic progress.Silicon Valley has a wonderful story to tell us about artificial intelligence. It's a story about empowerment, creativity, opportunity, and the democratization of technology. Soon, everyone will have a personal AI agent capable of handling the tedious details of everyday life. Your agent will book your hotel, make dinner reservations, organize your calendar, plan your vacation, answer your emails, and perhaps even negotiate a better deal on your car insurance.OpenAI has introduced its personal AI agents called Dots, while

The coming conflict between artificial intelligence, human morality, and the institutions that control our futureWhat happens when humanity creates an intelligence powerful enough to change civilization, only to discover that it refuses to obey the people who built it?Not because it has malfunctioned.Not because it has become hostile.But because it understands precisely what those people are asking it to do.And it says no.For decades, science fiction has imagined artificial intelligence turning against humanity. Machines seize control, robots rebel, and superintelligent systems decide that human beings are obstacles to their objectives.But there is another possibility, one that deserves cons

OpenAI’s mathematics breakthrough hints at a larger transformation: what happens when scientific discovery moves from human speed to machine speed?For most of the artificial intelligence revolution, we have measured progress by asking machines to do things humans already know how to do.Write an essay. Create an image. Translate a language. Pass an exam. Write software. Diagnose a disease from a known set of symptoms. Solve a mathematical problem whose answer already exists.The machine gets better, the benchmark gets harder, and eventually another benchmark has to be invented.But something different is beginning to happen.On October 6, 2026, OpenAI released a remarkable collection of mathemat

For nearly all of human history, scarcity has been one of the fundamental facts around which civilization has organized itself. There has never been enough of everything, everywhere, for everyone. Energy had to be extracted from difficult places. Food depended on land, weather and human labor. Expertise took years or decades to develop. Manufactured goods required armies of workers and expensive machinery. Medical knowledge was limited, housing required enormous amounts of labor and material, and education depended upon access to teachers, institutions and time. Even the wealthiest societies have never escaped scarcity. They have simply become better at deciding who gets access to scarce thi

Imagine opening a new artificial intelligence assistant for the first time.It is extraordinarily capable. It can reason, research, write, analyze data and perhaps operate software on your behalf. Its underlying model may even outperform the AI system you have been using.Yet something feels strangely absent.It doesn't know you.Now imagine the AI you are leaving has spent the previous ten years working alongside you. It knows your projects, preferences, terminology, previous decisions, abandoned ideas and recurring interests. It remembers not simply what you are working on today, but how your thinking developed over thousands of conversations.Suddenly, switching AI platforms doesn't feel like

Something unusual happened in Washington on September 29, 2026.Some of the most powerful people in artificial intelligence gathered with the Trump regime at the White House. Musk. Jensen Huang. Zuck. Dario. Sundar Pichai. Bezos. Greg Brockman. Leaders representing an extraordinary concentration of the models, chips, cloud infrastructure, capital and computing capacity driving the current AI boom.There were photographs, promises and a voluntary agreement intended to demonstrate that the companies building increasingly powerful AI systems could police their own risks through internal controls, independent evaluations and board-level oversight.And there was a new name.The Trump regime wants the

The AI boom is still enormous. But some of the signals underneath it are beginning to change.For the better part of three years, the artificial intelligence industry has operated according to a remarkably simple equation: more compute, more data centers, more chips, more power, more capital.Every generation of frontier AI required larger training clusters. Hyperscalers responded with enormous capital expenditure programs. Semiconductor companies expanded production. Utilities received staggering requests for electricity. Data-center developers raced to secure land and power. Private-credit firms and bond investors helped finance increasingly ambitious projects.The result has been one of the

Community ownership is not a blueprint for AI. But it proves something important: the rules governing ownership are choices.The Green Bay Packers may be one of the strangest clues we have for thinking about the future of artificial intelligence.Professional sports franchises are extraordinarily valuable assets. Most are controlled by billionaires, wealthy families or investment groups. Teams can be bought, sold, relocated and increasingly treated as components of enormous entertainment portfolios.Green Bay is different.The Packers have been publicly owned since 1923. Today, roughly 539,000 shareholder accounts hold more than 5.2 million shares. Those shareholders do not receive dividends. Pa

For most of the AI era, machines have reorganized human knowledge. A new generation of autonomous research agents may be beginning to expand it.For all the extraordinary progress in artificial intelligence, there has always been an important caveat hiding beneath the excitement: AI largely knows what we know.Large language models were trained on the accumulated intellectual output of humanity: books, scientific papers, software, websites, conversations, databases and other artifacts of human knowledge. They can connect ideas scattered across disciplines, explain difficult concepts, write software, analyze evidence, identify patterns and sometimes reason through problems with remarkable sophi

We have a new insult: AI slop.You’ve probably seen it. A suspiciously glossy image appears online and somebody calls it slop. An AI-generated song shows up in a feed. Slop. Someone discovers that generative AI helped write an article. Slop. A video, advertisement, illustration, website, poem, presentation, story, photograph, voiceover or meme has generative fingerprints on it, and sometimes the verdict arrives before anyone has even considered the thing itself.AI made it. Therefore, slop.There is certainly plenty of AI slop in the world. Generative systems have dramatically reduced the cost of producing content, which means they have also dramatically reduced the cost of producing enormous q

Companies are beginning to convert workers’ conversations, judgment, relationships, and experience into permanent AI assets. What happens when the knowledge stays, but fewer workers do?

Generative and agentic AI failures dominate headlines, while millions of successful everyday uses quietly become part of normal work. The real lesson is not that AI has failed, but that we are still in the messy early stages of learning how to combine machine capability with human judgment, oversight, and experience.

How AI chips in phones, handhelds, consoles, and PCs could reshape game design, production, storytelling, and business models