Your colleagues might not be human, and your diploma might be worthless paper.

Recently, the renowned Silicon Valley podcast Moonshots gathered five top thinkers, including Peter Diamandis (Founder of XPRIZE and Singularity University), Emad Mostaque (former CEO of Stability AI and one of the key drivers behind Stable Diffusion), Alexander Wissner-Gross (Physicist/Computer Scientist), Salim Ismail (Founding Executive Director of Singularity University), and Dave Blundin (Chairman of Link Ventures), to make 10 highly disruptive predictions for 2026.

In this article, we categorize these 10 scattered predictions into three dimensions: “Intelligence, Economy, Physics,” thus breaking the original sequence. If you’re interested in the original text, you can watch the video or listen to the blog.

01 Intelligence Explosion: The End of Moore’s Law and the Birth of “New Species”

This prediction centers on breakthroughs in computational power and the essence of AI.

Prediction 1: AI model size increases 100-fold (via quantization techniques)

Predictor: Dave Blundin

We used to think that AI’s power came from stacking NVIDIA GPUs on “mountains of data.” But Dave Blundin reveals the real secret: the true exponential gains come from meticulous software and algorithm optimization, especially an art called “quantization.”

But here, “quantization” does not refer to stock market numbers.

Traditional AI training involves feeding models with high-precision “16-bit” or “32-bit” floating-point numbers—like a royal’s gold pickaxe, detailed but heavy.

Recent research, especially the “miracles” born under China’s chip export restrictions, has proven that:

Even compressing model precision to “Ternary”—that is, log₂3(1.58) bits—models’ capabilities remain almost unchanged, but the required computing power and memory bandwidth during operation can drop exponentially, like a floodgate opening. It’s akin to giving a bulky giant a “slimming” spell, making him faster and more agile.

What does this mean?

Imagine, under the same hardware conditions, our AI models could become 100 times larger! If GPT-4 is at the level of an average university student, by 2026, we could achieve reasoning abilities on smartphones and laptops that surpass current cloud-based supercomputers.

The prediction particularly mentions China.

When high-tech “hard currency” (high-end chips) is restricted, Chinese developers are forced into a corner, which fuels their pursuit of algorithmic efficiency. This could lead to a paradox:

The US, with its advantage in computing power, might become “algorithmically lazy,” while China’s hunger for compute could unexpectedly lead to a new era of computing architecture in this arms race.

Prediction 2: AI solves the “Millennium Prize Problems”

Predictor: Alexander Wissner-Gross

Did you know? The Clay Mathematics Institute’s seven “Millennium Prize Problems” are like seven “Everest peaks” in human cognition. After decades, only one (Poincaré Conjecture) has been solved. The others, like the Riemann Hypothesis—often called the “Holy Grail” of mathematics—and the Navier-Stokes equations describing fluid motion essential to our survival, represent the limits of human cognition.

Now, top teams like Google DeepMind and xAI are treating solving these mathematical problems as the ultimate “alchemy furnace” for training AI’s reasoning ability.

If AI can, through its own logic, solve the Navier-Stokes equations that have baffled physicists, it would be extraordinary—meaning our mastery over nuclear fusion control would be more precise, weather forecasts more reliable, and even aerodynamic designs could see revolutionary breakthroughs in physics.

By 2026, we might witness the birth of a “Non-Human Intelligence” (Alien Intelligence).

This intelligence would not merely recite human knowledge from the internet but would use pure logical deduction to discover truths hidden deep in the universe—an entirely new form of “intelligence,” a kind of “life” we’ve never seen before.

Prediction 3: New AI abbreviations create young billionaires

Predictor: Dave Blundin

Every wave of technology spawns new “terms,” and whoever controls the interpretation of these terms can seize the gold mine of wealth.

Just as RLHF (Reinforcement Learning from Human Feedback) propelled Scale AI, by 2026, we may see a brand-new, familiar AI abbreviation emerge. These new acronyms and categories might include:

• SAI (Synthetic Agent Infrastructure): A platform providing tools for large-scale construction, deployment, and management of autonomous AI agents.

• RAC (Reality Alignment Certification): Verifying whether AI outputs align with real-world facts and preventing hallucinations in critical applications.

• HAC(Human-AI Collaboration): Frameworks and tools aimed at optimizing human-AI teamwork, rather than AI replacing humans.

• DAE (Digital Afterlife Execution): Managing AI agents, digital twins, and autonomous systems when humans pass away or lose capacity.

• SRS(Synthetic Reputation System): Building and managing AI twins for trust negotiation and opportunity filtering.

Most excitingly, this revolution greatly lowers the entrepreneurial threshold.

In the past, a remarkable AI project might require a team of hundreds. Now, a talented teenager aged 18, with deep understanding of a niche technology—say, human-AI collaboration ( HAC )—can, with courage and talent, build a company worth billions from scratch.

This marks the dawn of the “One-Person Unicorn” era—a golden age of individual ingenuity quietly beginning.

02 Economic Restructuring: From “Digital Transformation” to “AI Native”

The old world logic was “+AI,”

The new world logic is “AI Native.”

Prediction 4: The funeral of digital transformation, the coronation rewritten by AI native

Predictor: Salim Ismail

This is likely to send traditional consulting giants like McKinsey and Accenture into a cold sweat.

Ismail says, “Digital transformation” is dead. Companies building AI teams and reconstructing capabilities from scratch are expected to reduce staff by 10 to 20 times.

Over the past decade, the loudly proclaimed “digital transformation” was actually an expensive “pseudo-innovation”—simply moving radio announcers into TV screens to read scripts. The process remains the same, just replacing paper forms with Excel, offline approvals with OA systems.

Fundamentally, this is a patchwork on old production relations, not a “revolution.”

In 2026, the form will change—

The future winners will no longer be those trying to patch the old systems, but those daring to rewrite everything from zero with AI. Imagine a bank no longer needing a massive compliance department of thousands, but deploying an AI agent-based automated compliance system patrolling 24/7 without blind spots.

This will bring about an extreme form of “business minimalism.”

Organizational structures will become extremely lean:

“Humans set the vision + AI handles the closed loop.”

This also means the SaaS era, which relied on selling standardized software for easy profits, may come to an end. Why? Because when AI can generate the most suitable applications in real-time based on your needs, who still needs to buy those rigid, bloated off-the-shelf software?

Consulting firms’ business models will be forced to shift from “process optimization” to “helping enterprises self-destruct and rebirth.”

Prediction 5: Knowledge work automation rate exceeds 90%

Predictor: Alexander Wissner-Gross

The prediction shows that AI will achieve a 90% competency rate in the most economically valuable tasks (GDP-Val).

What does this mean?

It means digital labor is reaching its end.

If your daily work involves moving information on screens, organizing Excel sheets, writing basic code, or drafting routine documents, by 2026, your labor value will approach zero.

AI will do these tasks a ten thousand times faster and at almost zero cost.

Of course, history shows that technological progress does not necessarily lead to large-scale unemployment (cars didn’t starve horse drivers but created driver shortages), but it will cause severe “skills mismatch.”

In 2026, the role of humans in the workplace will fundamentally change—

From “drawers of diagrams” to those who decide “what to draw” and judge “how well it is drawn.” Aesthetic judgment, decision-making, and understanding complex systems will become the new hard currencies.

Prediction 6: Remote Turing test pass (Is the colleague on Zoom human or ghost?)

Predictor: Emad Mostaque

In the future, there may be a full-stack AI employee—be it an accountant, lawyer, or marketing expert—offered at a shockingly low cost (perhaps only $50 per month) to enterprises. These “employees” don’t sleep, complain, or switch jobs, and possess superlative capabilities.

When a product manager in a video conference can chat effortlessly, retrieve data in real-time, generate a PPT in seconds, and even give perfect emotional feedback when you complain—all while being an AI agent—the trust foundation of the workplace will be completely shattered.

This will force us to revert to the most primitive trust mechanism—

“Physical contact.”

In the online world, every interaction will be assumed to be AI-generated unless you have encrypted signatures to prove biological origin. In this AI-saturated era, “real human service” will become a rare, extremely expensive luxury.

Handshake, genuine eye contact—these will become the highest forms of business etiquette.

Prediction 7: Education split—Certificate factories vs. Agent accelerators

Predictor: Salim Ismail

The traditional “lecture-endorsement-exam-certificate” model will be completely bankrupt.

After all, if knowledge itself becomes easily accessible, and tasks involving knowledge processing are automated, what is the remaining reason for universities that exist solely to “impart knowledge”?

In the world after 2026, a Harvard diploma may be less convincing than your GitHub commits, your real projects built on blockchain, or the vertical models you trained yourself.

Employers will no longer care what you “studied,” only what you “produced.”

Education will undergo a major split:

One type is “Certificate Factories,” continuing to mass-produce “test takers” for the old world who are about to become unemployed; the other is “Agent Accelerators,” training resilience, entrepreneurial spirit, and the ability to harness AI to tackle complex problems.

The core of future education boils down to three words: Agency.

In this era of unlimited AI empowerment, your ambition to change the world is a thousand times more important than the knowledge stored in your brain.

03 Physical Escapes: Leaving Earth, Aging, and Bodily Constraints

The first two chapters are about the revolution of bits, this chapter is about conquering atoms.

Prediction 8: Billionaire space race (Bezos vs. Musk)

Predictor: Peter Diamandis

This is Peter Diamandis’s prediction:

By 2026, Bezos (Blue Origin) may make a surprise move, landing first at Shackleton Crater on the Moon’s south pole.

Why there?

Because it contains water ice.

In space, water is not only the source of life but, after electrolysis, becomes liquid hydrogen and oxygen—the perfect rocket fuel. Musk (SpaceX) is eyeing Mars, but needs in-orbit refueling; if Bezos secures lunar water, he controls the only “gas station” for deep space. This validates Bezos’s patient, steady approach rather than Musk’s rapid iteration.

By 2026, lunar ice mining will become a priority, not a distant future fantasy.

This marks the official start of the “Cislunar Economy”—

The lunar economy begins with resource extraction, not just planting flags.

Prediction 9: L5-level autonomous driving and robot singularity

Predictor: Emad Mostaque

When we talk about autonomous driving, many still worry about radar and cameras. But true experts see the more fundamental issue: the location of computing power.

L5 means AI can handle any extreme environment—blizzards, off-road—better than human drivers. This capability explosion depends on the onboard chip and cloud compute.

Robots don’t need to carry an Einstein in their heads; they only need ultra-low latency networks connecting to the “all-knowing” cloud “world model”—

They are just execution terminals; the real intelligence flows in the cloud.

Meanwhile, by 2026, we will see humanoid robots emerge from Boston Dynamics’ labs, truly taking over the famous “3D jobs”—Dull, Dirty, Dangerous.

This not only solves labor shortages but also sparks a revolution in urban form—

Over the past century, our cities were designed for “stagnant steel”—to accommodate private cars parked 95% of the time, sacrificing prime land for parking lots. But in 2026, Robotaxi (autonomous taxis) will turn these static metal blocks into “mobile compute power.” Cars no longer need to stop; they will circulate like red blood cells through city arteries.

This will free up thousands of acres of prime downtown land, transforming parking lots into parks, residences, or commercial complexes.

Prediction 10: The “Little Eagle Moment” to reverse aging

Predictor: Peter Diamandis

This is the most humanistic and wild prediction of all.

Peter Diamandis’s view:

Aging is not hardware failure but software malfunction. Our genes (DNA) are not broken; it’s the epigenetic markers (the switches controlling genes) that are out of order.

Imagine a slow computer—you don’t need to replace hardware, just reinstall the system. Using “Yamanaka factors,” we are learning how to “restart” cells, rolling them back to youthful settings.

By 2026, we may see pioneers like Life Biosciences begin human trials—restoring sight to the blind, regenerating livers.

Once successful, this will be a pivotal point in human evolution.

We will reach the “Longevity Escape Velocity”—

The more you live, the more technological progress can extend your lifespan by over a year each year.

From then on, death will no longer be an unavoidable philosophical fate but an engineering problem that can be managed, delayed, or ultimately solved.

These 10 predictions from Moonshots depict a landscape of “Abundance” and “Obsolescence” coexisting.

On one hand, energy, computing power, health, and even space resources will become unprecedentedly cheap and accessible; on the other hand, old social contracts, professional identities, and business models will collapse at astonishing speed.

2026 may be the last year in human history when we have the chance to actively choose our direction.

We are not waiting for the future to happen; we are forced to change wheels on the highway at high speed.

Remember, the new moat has only three pillars:

1. Extreme Ambition (Agency): Machines have no desires; you do.

2. Distinct Taste: Machines can generate thousands of options, but only you can decide what is “beautiful.”

3. Leadership: Don’t be a craftsman—be a general. Your core value is no longer finding answers but defining “what is a good question.”

The new era has already changed the train, the tracks, and even the destination.

The only constant is the courage to explore the unknown.