Singularity University

09/22/2026

Most established companies are asking the same AI question: where can we deploy pilots, automate processes, and cut costs? A different generation of companies is starting somewhere else entirely. Not "how do we add AI to what we already do?" but "if we built this business today, with AI from the start, what would it actually look like?"

That is a structurally different question. And it tends to produce structurally different companies.

The challenge for incumbents isn't access to AI tools. Most have them. The challenge is that the organizational logic built up over decades, the management layers, approval processes, budgeting cycles, and performance metrics, was designed for a different era. Those structures don't just slow down AI adoption. They actively resist the kind of experimentation that produces genuine transformation.

Singularity expert Jody Medich calls these forces corporate antibodies. They're not malicious. The organization is often doing exactly what it was designed to do. That's precisely what makes them hard to overcome.

What it actually takes to compete with a company designed around AI from day one is worth reading carefully.

Read the full story, link in comments.

09/21/2026

Developing a new drug can take years and cost hundreds of millions of dollars, and even then, most candidates ultimately fail. Now, researchers at Stanford have built a virtual biotech company with 37,000 AI agents that work together to analyze drug targets and design therapies.

The system, designed by Stanford researchers, identified which drugs are more likely to succeed in trials and even proposed a cancer treatment a major drugmaker later landed on too.

09/19/2026

The AI debate has been structured around a single unit of analysis: one model, one agent, one capability. How smart is it? What can it do? What happens if it gets smarter?

A researcher who has spent decades studying multi-agent systems says that framing is already becoming obsolete.

The meaningful frontier isn't individual agent intelligence. It's what emerges when millions of agents negotiate, compete, cooperate, and make decisions with each other at scale, across organizations, industries, and jurisdictions, with no single designer overseeing the whole.

Human societies have developed institutions, laws, norms, and accountability structures over centuries to manage the emergent behavior that arises when individuals with different interests interact at scale. Those systems still break down regularly.

AI societies will need equivalent infrastructure, built in years, for systems that operate at machine speed, across organizational boundaries, and with behavior that no single developer can fully predict or control.

The author's conclusion: the future of AI will not be determined by the intelligence of individual agents. It will be determined by the societies they create. And societies, as humans know, are much harder to govern than individuals.

For every leader deploying AI agents into operational environments, this is the layer of the challenge that most current governance frameworks are not yet built for.

Link in comments for the full story.

09/14/2026

Medical ethics took centuries to develop. It emerged from real catastrophes: experiments on prisoners, patients deceived without consent, vulnerable populations exploited in the name of progress. The rules that exist today were written in response to specific, documented harms.

AI ethics is being written in advance of most of those harms. And a growing number of researchers argue that borrowing medicine's framework to do it is a mistake.

The principles that guide medical practice, autonomy, beneficence, non-maleficence, justice, were designed for a specific relationship between a doctor and a patient. AI sits inside supply chains, policy systems, hiring pipelines, and social infrastructure. The stakeholders aren't patients. The harms aren't always traceable to a single decision. And the person harmed often has no relationship with the system that harmed them.

AI ethics may need to be built from different foundations entirely. Reaching for the nearest familiar framework may give the appearance of ethical seriousness without the substance.

What should those foundations should look like, and who should build them?

09/06/2026

Every parent goes to work carrying years of knowledge, and almost none of it ever reaches their kid's classroom. At the same time, schools are fighting a losing battle to keep curriculum current while the world changes faster than any textbook can be rewritten.

Our former VP of Community & Impact Darlene Damm makes the case for a fix: connect what kids learn in school to problems experts are solving right now. Kids build skills that matter today, and curriculum stays current because it's tied to real, live work.

Reimagine what's possible, starting with the future of education. What if your own job became part of your kid's classroom?

09/04/2026

Imagine you're the AI agent. Looking at your own organization's public data right now, would you fund it?

In a recent Meet the Expert conversation, SU faculty Karine Arama explains why financial institutions are turning to blockchain so AI agents can hold wallets and act on behalf of people and institutions directly. It's the same shift SU faculty Anne Connelly wrote about in philanthropy, where AI agents could become major donors in their own right by 2030.

Read the full article to prepare for the future of nonprofit marketing: https://hubs.li/Q04wBxwr0

And learn more about the future of finance: https://hubs.li/Q04wBxwM0

09/03/2026

One of the most common arguments for holding onto a gas car is that scrapping it early wastes the emissions already spent building it. A new study published in Science just dismantled that logic.

Researchers at UC Santa Cruz modeled more than 400 gas and electric vehicle models across varying efficiencies, battery sizes, mileage, and grid energy mixes. Their finding: scrapping a gas car just one year after purchase and replacing it with an electric vehicle reduced lifetime emissions in 92 percent of the scenarios they tested. For the average SUV switched after two years, cumulative emissions fell 44 percent.

The key insight is a simple accounting point the researchers make explicit. The emissions from building the gas car are a sunk cost. They're identical in every scenario. The only numbers that matter going forward are how much fuel the gas car will burn versus what it costs to build and charge the replacement.

There are real exceptions and the researchers are clear about them. There are also secondary effects that need more modeling. And the study has a pointed policy implication: without subsidies generous enough to make scrapping financially viable, even the most climate-conscious drivers won't do it.

Read the full story, link in comments.

09/02/2026

Here's the thing about waiting for technology to tell you what to do next: you'll always be a step behind.

The leaders who shape what's coming aren't the ones with the most technical knowledge. They're the ones who took the time to build a mindset for spotting change before it's obvious, and had the confidence to act on it.

That's what the Singularity Executive Program is built for. Over an intensive week, you'll get the mindset, skillset, and network to see what's coming and shape it in your favor, alongside a global cohort of leaders doing the same thing.

Applications for the final 2026 cohort close September 27th. Apply now, link in comments.

09/01/2026

One way we look at Exponential Thinking is through the lens of science fiction. Picture a future world. Give it future problems. Now picture how the people living there solve those problems, using technology that hasn't been invented yet.

Most people build forward from what already exists. Exponential thinkers build backward from what the future demands, then go invent it.

That's the difference between leading technology and being led by it. Imagination sets the destination, and technology is how we get there.

Our community has practiced this directly, working with alumni, faculty, and experts to imagine radically different futures, including a full graphic novel born out of one of these sessions. The habit of imagining is the first step.

What future are you building backward from?

08/28/2026

What happens when your biggest donor doesn't have a pulse?
Singularity University faculty member Anne Connelly says that question stops being hypothetical within five years.

Anne is a blockchain expert who spent years with Doctors Without Borders in Central Africa, and her latest piece argues AI agents will start holding and allocating real money by 2030. Most charities aren't built for a donor that can't be moved by a story.

She breaks down what it actually takes to become fundable to something that runs on data instead of emotion: machine readable impact reporting, verifiable outcomes, and real crypto infrastructure.

Read her full piece and get ahead of this shift, link in comments.