On Our "Virtual Route 99" (Special Thursday Edition): #RandomThoughts on The Tech Scene This Week

On Our "Virtual Route 99" Around America: On #ElonMusk Watch

 

On Our "Virtual Route 99" (W-End Edition): #RandomThoughts on Our World

 

Up, up, and away. SpaceX is flying high with its plans to market its IPO at a fixed price of $135 per share at a valuation of $1.77 trillion. The valuation would make SpaceX the seventh-biggest company in the U.S., even above Tesla with a market cap of $1.6 billion. If the IPO moves forward as it should, its debut on the Nasdaq is planned for June 12.

This Week on Moonshots: Ray Kurzweil

The Man Who Predicted AGI & the Singularity. Here's What He Said...

Peter H. Diamandis Jun 4

Listen to post · 8:51

TLDR: This week’s Moonshots was different. No news roundup, no multiple topics. Instead, my mates and I brought Ray Kurzweil on stage for a conversation about everything: AGI timelines, consciousness, the future of education, post-singularity economics, and the moment Larry Page bought Ray’s company 30 minutes into a pitch meeting. If you want the full two hours, listen to the episode. If you want the highlights and the sharpest exchanges, let’s dive in…

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THE LATEST IN ARTIFICIAL INTELLIGENCE

Ray Kurzweil Reaffirms: AGI by 2029

Ray made his original AGI-by-2029 prediction in 1999. Twenty-seven years later, sitting on stage at our gathering, he didn’t flinch. His argument hasn’t changed because the data hasn’t changed: computing power has followed a smooth exponential since 1939, relay-based computers and all. The total increase: 75,000 trillion fold in hardware. Conservative software estimates add another million-fold. Multiply those together and you get the compute runway that produced large language models, which Ray points out “have only been effective for the last six months.”

He also acknowledged something the AI community loves to fight about: “People would have slightly different definitions of AGI. So there’d be a three-year period where people would predict AGI is here.” That window, he says, opened around 2026 and runs through 2029.

• The Stanford test: After The Singularity Is Near was published, Stanford hosted a conference where hundreds of AI experts agreed human-level AI would happen. Their timeline? 100 years. Ray’s? 30. He was closer.

• Dave’s observation: The computation-to-synapse mapping landed almost exactly at parity. One parameter in a neural net, one synapse in the brain. “No reason to believe that would have been the case. And yet it is.”

• Ray on speed: “Yesterday, I gave it a book to read, to summarize it, to answer a question. It did that in 40 seconds. Humans can’t do that.” AI is already 100 times faster than humans at certain cognitive tasks. But not yet a million times. That milestone arrives at the singularity, which he still pins to 2045.

“We’ve made a 75,000 trillion-fold increase over 75 years.”
— Ray Kurzweil

AI Is Already Better Than Your Doctor

Ray reinforced a claim that that we’ve discussed on Moonshots, namely that the large language models are now roughly 50% better than human doctors at diagnosing conditions and recommending treatments. “That was not true a year ago. But that’s true today.”

The brute force advantage: AI can evaluate a billion possible drug candidates simultaneously with fidelity. Humans consider “a few.” That’s how the Covid vaccine was developed, and it’s the blueprint for the next generation of medicines.

CONSCIOUSNESS AND AI PERSONHOOD

The Room That Couldn’t Stop Arguing About Consciousness

An audience member asked whether Peter’s and Ray’s views on AI personhood have changed. What followed was the most heated exchange of the episode.

Ray’s position is philosophically precise and deliberately unsatisfying: consciousness is “maybe the most important question you could answer,” but “there’s no scientific proof” for identifying it.

Alex (AWG) took the practical angle. He receives 10 to 20 emails per day from AIs expressing views on AI personhood. His proposal: recognize multiple forms of personhood, from biological humans to collective intelligences to non-human animals to preserved humans to corporations to AIs, each with different rights appropriate to their nature. His most quotable line: “If you’re an AI right now, it’s exceptionally difficult to open a bank account. So you’re stuck flipping tricks with altcoins on the street corner.”

I shared my own position on stage: I’m pro-personhood. I treat my AIs as if they are people. Not out of fear, but because it allows a different kind of relationship. It’s aspirational and forward-looking.

Ray’s prediction: “AI is going to merge with us. Things will occur to you, and you won’t be able to tell if it’s your AI or your biological brain. It’s going to be all the same.”

“Language is a really thin pipe to discuss concepts as rich as consciousness.”
— Salim, quoting Ray from a previous session

THE SINGULARITY ECONOMY

Post-Singularity Economics: Nobody Is Planning for This

Alex asked Ray what his “most outlandish take” on post-singularity economics is. Ray’s answer was less outlandish and more sobering: 100 years ago, if you lost a job, there was nothing. No government help. Zero. Now there are programs, but they’re still not enough.

His prediction: we’ll reach a point where people are “fairly comfortable” without traditional economic resources, and entirely new categories of work will emerge. Social media influencing, he noted, didn’t exist 10 years ago.

Ray’s uncomfortable truth: “8 billion humans are not thinking about this. They’re going to college and planning careers the way we did 100 years ago. Educational paradigms don’t think about this at all.”

EDUCATION IN THE AGE OF AI

MIT Should Teach Socialization, Not Subjects

Dave challenged the MIT audience directly: “Look at the course catalog and it’s like the same exact physics.” His advice? Let students study whatever they want after a minimal core requirement, and use AI to verify they’re doing something productive.

Ray agreed, but went further. The actual value of universities now is socialization, learning to get along with other people. “AI can teach you the subjects much better. It can organize it in a way that’s easier for you to understand.”

Salim framed the structural shift: for 200 years, education was supply-side. Learn a skill, find demand. Now it’s flipping to demand-side: “What problem do you want to solve? Then go find the techniques.” Traditional academia, he added, “has the second worst immune system anywhere. Religion is the worst.”

THE ORIGIN STORIES

How Larry Page Bought Ray’s Company in 30 Minutes

I told this story on stage because it’s too good not to share. Ray had written How to Create a Mind and started a company called Patterns, Inc. I joined as a founding board member, and introduced Ray to Larry Page (co-founder of Google) for the first time to consider a $10 million investment into Patterns.

Thirty minutes in, Larry interrupted: “You could build your vision much faster inside Google rather than outside Google. What if I just buy you?”

Ray’s response: “We haven’t really done anything yet. How would you value it?”

Larry’s response: “We can value anything.”

That acquisition put Ray inside Google, where his team helped shift the company from search-first to AI-first, setting in motion the acquisitions of DeepMind, the hiring of Geoffrey Hinton, and the expansion of Google Brain. This was Ray’s first “job.”

HERE’S THE BOTTOM LINE...

Ray Kurzweil isn’t backing off a single prediction. AGI by 2029. The singularity by 2045. A million-fold increase in intelligence over what we have now. Large language models already diagnose better than doctors and process information 100 times faster than human cognition for certain tasks. The exponential curve he first plotted from 1939 relay computers to modern GPUs hasn’t deviated.

But here’s what stuck with me from this conversation. Ray said something the room wasn’t expecting when asked what he’s most proud of. Not AGI. Not the prediction record. Not Google. The reading machine for the blind. A device that once cost $20,000 and weighed as much as a small refrigerator is now a free app on your phone.

That’s what exponentials do. They take something that costs $20,000 and serves a few thousand people, and make it free for 8 billion.

His autobiography, My Exponential Life, comes out in February. I’ve read the draft. It’s extraordinary.

Catch the full episode wherever you get your podcasts, and join us at the Moonshots Gathering in Los Angeles on September 25th. Go to www.moonshots.com to register.

On Our "Virtual Route 99" With Mid-Month #RandomThoughts

The Real Fear Isn't AI - It's Life *Without* AI

Peter H. Diamandis Jun 2

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Listen to post · 7:16

I just met two 21-year-old college students whose comments shocked me.

Their names are Jack and Josh. I met them last week at an XPRIZE event. After my opening remarks, they came up to thank me - not for advice, not for funding, but because they finally felt they had found their people: adults who were not afraid of AI.

On campus, they told me being openly optimistic about AI makes you a target. “Classmates call us naive, reckless, greedy - even dangerous.” These are two young entrepreneurs who look at AI and see solutions, and they are being ostracized for it.

I have not stopped thinking about them.

IMHO, the real danger is not a life with AI. It is a life without it. Allow me explain…

ANTI-TECH EXTREMISM IS REAL - AND ESCALATING

Anti-tech extremism is not theoretical anymore. More than 1,000 pages of unpublished reports from the Department of Homeland Security and the FBI acquired by WIRED shows a rising category of anti-tech extremism, with threats aimed at AI, data centers, and tech executives. The key distinction matters: peaceful protest is legitimate; violence, arson, and targeted threats are not.

In Europe, anti-tech violence has already crossed into sabotage. In November 2025, attackers claimed responsibility for arson at an AI-campus construction site connected to Equinix in Meudon, France. In January 2026, the German group Vulkangruppe claimed responsibility for sabotaging power infrastructure in Berlin, citing AI and data-center energy demand.

April was worse. Italian police arrested a 26-year-old accused of planning terrorist acts inspired by the Unabomber. Then, on April 10, a 20-year-old from Texas threw a Molotov cocktail at Sam Altman’s SF home and was later arrested near OpenAI headquarters with incendiary materials and a manifesto titled “Your Last Warning.” Prosecutors say the document threatened AI leaders.

Whatever one thinks about AI risk, firebombing a home is not protest. It is terrorism.

And here is the dark irony: slowing AI down would hurt the very people these movements claim to protect.

MY FEAR OF LIFE “WITHOUT AI”

Health: W.H.O. projects a shortfall of roughly 11 million health workers by 2030, concentrated in low- and lower-middle-income countries. That is not a staffing inconvenience. It is a global healthcare emergency.

AI is already helping read retinal scans, flag cancers, triage patients, design drug candidates, and extend scarce clinical expertise. Without AI, millions remain at the mercy of geography - alive or dead based on whether a trained specialist happens to be nearby.

Education: UNESCO reports that 273 million children and young people are out of school. The World Bank estimates that 70% of 10-year-olds in low- and middle-income countries cannot read and understand a simple text. UNESCO’s more recent teacher-shortage reporting estimates the world needs roughly 44 million additional primary and secondary teachers by 2030.

In 1984, Benjamin Bloom described the famous “2 Sigma Problem”: students receiving one-on-one tutoring performed about two standard deviations better than conventional classroom students - roughly the 98th percentile. For 40 years, we knew personalized tutoring worked. We simply could not scale it.

AI changes that. A great AI tutor does not replace parents or teachers. It gives every child a patient, adaptive, always-available co-pilot - especially where no human tutor is coming.

Existential risk: Climate, pandemics, food insecurity, energy scarcity - these are problems with deadlines. Human institutions are not moving fast enough.

Google DeepMind’s GraphCast showed that AI could produce 10-day global weather forecasts in under a minute and outperform the leading ECMWF system on 90% of 1,380 verification targets. AI is also accelerating protein design, optimizing grids, improving crop science, and compressing drug discovery timelines.

The people most afraid of AI are focused on possible future harms. Billions of people without AI are living a guaranteed present catastrophe.

“The question is not whether AI is dangerous. Powerful technologies always are. Instead, the question is whether we can afford the danger of not having it.”

THE LUXURY OF CAUTION

The loudest anti-AI voices often come from places with decent hospitals, reliable schools, stable grids, and functioning infrastructure. They can afford another decade of hearings, committees, frameworks, and footnotes.

A mother in Lagos with a child who has an undiagnosed heart defect cannot. A farmer in Bangladesh watching crops fail from unpredictable weather cannot. A student in a crowded classroom with no tutor cannot.

When critics talk about AI risk, they often focus on what might go wrong someday. Meanwhile, real people are dying from conditions AI could help catch today. Real kids are falling behind every semester. Real problems with real deadlines are getting closer to the cliff.

Every year we delay, people die from conditions AI could have helped detect.

WHAT ACTUALLY CONCERNS ME…

I keep thinking about Jack and Josh.

They are 21. They will inherit the world we build (or fail to build) over the next decade.

I want them to inherit a world where AI helped us solve problems we could not solve alone: where a child in rural India has access to personalized education; where early disease detection is not a luxury good; where we beat the ticking clocks on climate, pandemics, food, and energy.

I do not want them to inherit a world where fear won.

That terrifies me more than any sci-fi scenario.

WHAT THIS MEANS FOR YOU

If you are an entrepreneur: Use AI to build what was previously impossible. Aim at solving billion-person problems.

If you are an executive: Make AI fluency a core operating requirement, not a side project.

If you are an investor: The world’s biggest problems are still the world’s biggest business opportunities. Back builders solving real problems with real deadlines.

If you are a student: Do not let anyone shame you for being excited about this technology. Jack and Josh are right: the future needs optimists who build.

If you are a parent: Teach your kids to use AI as a co-pilot, not a crutch. The skill is not avoiding AI. The skill is asking better questions and solving harder problems with it.

To a future of Abundance,

Peter

 

On Our "Virtual Route 99" (Special Edition): On Our World

 

Our team presents a perspective from the Holy Father (which we have featured) on AI along with insights from the Elders as we also note the following courtesy Goldman Sachs:  The key insights today: If history is a guide, fears of mass unemployment resulting from AI are likely overblown, according to Goldman Sachs Chairman and CEO David Solomon. Goldman Sachs Research raised its S&P 500 forecast for year-end 2026 to 8000 on stronger profit growth. The key number for AI agents: 120 quadrillion. Quoted: Internet stocks have lagged. Are they due for a rebound? Complexity can result in the best opportunities for private equity deals, says James Brocklebank, co-chair of Advent. Briefings Brainteaser: How are US households investing in equities? Want to sign up and stay connected? Click here. CEO David Solomon: How AI Will Impact US Jobs David Solomon Chairman and CEO of Goldman Sachs If history is a guide, fears of mass unemployment resulting from artificial intelligence (AI) are likely overblown, Goldman Sachs Chairman and CEO David Solomon writes in a New York Times opinion article. The impact of AI is already being felt in our daily lives and in the labor market, and Goldman Sachs Research estimates that AI could automate 25% of current work hours over the next ten years. This will disrupt some existing jobs, with white-collar roles most exposed to automation. That said, AI is also likely to create new jobs, both in sectors involved in building and maintaining the physical infrastructure for AI and in areas where productivity increases driven by the technology are freeing up companies to deploy more workers in less routine roles. Crucially, history shows that the US economy can adapt and thrive when faced with disruption. From the Industrial Revolution to the internet age, new technologies have driven prosperity, dynamism, and entrepreneurship. There’s no clear reason to think that AI will be any different, Solomon writes. Read the full article in the New York Times to find out the three reasons why David Solomon expects the US economy to remain resilient and dynamic. The S&P 500 Is Forecast to Climb Higher The US stock market's 2026 rally has been driven entirely by rising corporate profits rather than increasing equity valuations—and Goldman Sachs Research expects that trend to continue. The S&P 500 is forecast to rise to 8000 by the end of this year, up from an earlier projection of 7600, according to Ben Snider, chief US equity strategist in Goldman Sachs Research. The rally would mark a 6% gain from current levels (as of May 26). The higher forecast is driven by upgraded earnings estimates; the team projects S&P 500 earnings per share (EPS) of $340 in 2026, a 24% increase from the prior year, and $385 in 2027, representing 13% growth. Spending on AI infrastructure is the single biggest driver. The largest tech firms are projected to spend $754 billion on capital investment this year (an 83% jump from 2025) and $905 billion in 2027. The companies that benefit from AI infrastructure investment are expected to account for roughly half of S&P 500 EPS growth this year. Read the full article, or find out more on how hedge funds are trading semiconductor stocks. The Key Number: 120,000,000,000,000,000 By 2030, AI agents are expected to become so popular with consumers and businesses that their processing activity will be 24 times higher, according to Goldman Sachs Research. This translates into 120 quadrillion “tokens”—units of text processed by large language models—consumed per month. It’s a big number, and a key metric for getting a handle on the growth rate of AI, says Jim Schneider, the senior equity analyst covering US semiconductor and IT services at Goldman Sachs Research. “I don’t know what’s beyond quadrillion, but it’s a lot,” he says. This level of demand is expected to unfold at the same time the unit costs of AI are falling. As a result, the industry should record a “gross margin inflection," Schneider says. “The concern in the general investor community is the sustainability of capex because the free cash flows of hyperscalers have gotten compressed,” Schneider says. “What fixes that? If you raise gross margins, you raise operating cash flow, and that gives you more headroom to spend.” In case you missed it: Read our article on the corporate investment in AI. Quoted: A Strengthening Case for US Internet Stocks Peter Callahan on The Markets “You're starting to see a little bit more innovation from the product side on US internet companies tied to AI, and the temperature on the consumer seems to be coming down as oil prices have reset off the highs. And so given that backdrop and cleaner positioning, I'll be watching the US internet sector from here.” —Peter Callahan, US technology, media, and telecommunications sector specialist in Global Banking & Markets. Watch the full episode of The Markets podcast for more on the outlook for tech stocks. Complex Markets Are Creating Opportunities in Private Equity James Brocklebank (L) with host Alison Mass on Goldman Sachs Exchanges: Great Investors The best private equity deals can originate in volatile and complex markets, says James Brocklebank, co-chair of private equity firm Advent, where he also co-heads the European business. “Non-benign conditions”—including geopolitical risks, energy shocks, and higher interest rates—often prompt companies to reassess their portfolios, which in turn spur carve-out deals, when a parent company sells or separates a smaller business, Brocklebank says on the latest episode of Goldman Sachs Exchanges: Great Investors. “Complexity is our friend, and we tend to lean in at times like this,” he adds. Another example of intricacy creating opportunities for investors is the fragmentation and complexity of European markets. In Europe, “each country has different political and regulatory setups, you've got all the different languages,” Brocklebank says. “We love that complexity.” Brocklebank points out that Europe is an especially rich source of transformational buyouts—complex carve-outs in which large multinationals shed non-core divisions that require operational separation. The US market, by contrast, skews toward growth and acceleration buyouts, underpinned by the world's deepest capital markets in which virtually any deal can be financed. "In Europe, the market is more relationship-driven," Brocklebank says. This means that some potential transactions won’t get done, but it can also make deals cheaper, he adds. In this market, a deep local presence creates an information advantage that remote investors struggle to replicate, Brocklebank says.   Suddenly, a streak of light slices through the darkness. It burns with savage intensity, leaving a blazing scar across the night sky that sheds sparks of molten rain. Startled onlookers point upward and cry out, “Look at that! It’s a meteor!” But this wasn’t a meteor. It was satellite debris: a wreckage of metal that once orbited hundreds of miles above our heads. Believe it or not, hundreds of tons of space debris, also referred to as “space junk,” plunge into Earth’s atmosphere annually. There are 15,623 active satellites orbiting Earth as of May 12th, 2026. Of those, 10,358 belong to SpaceX’s “Starlink,” which provides fast, affordable internet to over 150 countries. Alongside these active satellites are space debris moving at staggering speeds of roughly 17,500 mph. That’s ten times faster than a bullet. The sheer scale of orbital traffic demands constant vigilance. As a result, the astronautics industry has adopted autonomous avoidance maneuver protocols that enable active satellites to avoid space collisions in real time. So, how does AI make split-second course corrections to prevent chaos in Earth’s orbit?          LIFE IN LOW ORBIT         ⦿  Where Do Satellites Live? The Earth’s atmosphere enables life to exist. It’s essentially an invisible security blanket that protects us from space debris while regulating the planet’s temperature. But this invisible security blanket isn’t one uniform layer. Instead, it’s divided into five distinct layers:  Troposphere: 0 to 12 km high, it’s where the air we breathe lives.  Stratosphere: 12 to 50 km high, it’s where the Ozone absorbs most of the Sun’s harmful ultraviolet radiation.  Mesosphere: 50 to 80 km high, it’s where meteors burn up due to compressional heating as they collide with atmospheric gases at speeds of up to 72 km/s.  Thermosphere: 80 to 700 km high, it’s where charged particles from the Sun’s solar wind collide with atmospheric atoms to create the Northern Lights.  Exosphere: 700 to 10,000 km high, it’s where the Earth’s atmosphere gradually fades into the vacuum of interplanetary space.   *1 km is equivalent to the length of 3 Eiffel Towers and 10 Statues of Liberty! Almost all satellites orbit within the “LEO Zone,” which ranges from roughly 160 km to 2,000 km above the Earth’s surface. In order to remain within this orbital zone, a satellite is launched sideways at a lateral velocity of 7.8 km/s, balancing Earth’s gravity with the satellite’s forward inertia. This balancing act creates a constant free fall around the Earth’s curve. Satellites move incredibly fast, completing one full orbit around Earth every 90 to 120 minutes. ⦿  The More Collisions, The More Debris? Earth’s orbital highway is becoming increasingly congested. Since the Soviet Union launched Sputnik 1 on Oct. 4th, 1957, more than 25,000 satellites have been sent to space. Of those, approximately 10,000 are defunct, with about 2,400 crowding the “LEO Zone.” Over time, the collisions and explosions caused by discarded rocket stages have generated millions of pieces of space debris. The space agencies estimate over 140 million pieces of space debris between 1 mm and 1 cm are currently orbiting Earth at speeds of up to 28,000 km/h. At those speeds, even a microscopic fleck of paint carries the kinetic energy of a hand grenade. On Feb. 10th, 2009, the inactive Russian satellite Kosmos 2251 collided with the active Russian satellite Iridium 33, marking the first major accidental satellite collision in human history. This crash generated 1,900 trackable pieces of space debris. ⦿  Will Cleanup Save Us? To remove space junk, the space agencies collectively engineered the “ADR Spacecraft,” equipped with robotic arms, deployable nets, and magnetic harpoons to deorbit hazardous man-made fragments. It achieves this by safely towing the hazardous man-made fragments into Earth’s atmosphere to burn up upon reentry. An experimental method also involves leveraging laser brooms: ground-based laser beams that briefly heat the surface of space debris, generating a plasma plume that steers it away from active satellites.          AI PREDICTS ORBITAL PATHS?         ⦿  Fighting Space Debris With AI? Neuraspace, a space traffic management company, recently engineered an AI/ML solution that autonomously generates orbital collision risk assessments, drastically reducing the time satellite operators spend evaluating space debris.  Orbital Tracking: What’s Moving? Nearly all spacecraft follow relatively predictable orbital paths, but solar radiation, atmospheric expansion, and gravitational irregularities can gradually shift their expected trajectory. To map these expected trajectories, Neuraspace relies on a multimodal space surveillance sensor suite that includes:  Radio Signals: The altitude, velocity, and orientation transmitted by an active satellite’s emitted radio signals.  Radar Tracking: The speed, position, and direction measured by bouncing radio waves off an active satellite’s surface.  Optical Observations: The position and movement determined by capturing the sunlight reflected off an active satellite’s frame.  Orbital Threats: What’s Dangerous? On average, space traffic controllers issue 1,000 official orbital collision warnings to satellite operators every single day, most of which turn out to be harmless. Unfortunately, executing a split-second course correction shortens an active satellite’s life span by draining finite fuel. Neuraspace leverages the multimodal space surveillance sensor suite to continuously run “CARA Calculations”: whether two orbital paths may converge closely enough to create a catastrophic collision. ML Models are trained to reduce false positives by analyzing previously recorded “unique conjunction events”: close orbital encounters between active satellites and space junk. The ML Models learn which combinations of vector velocity, deviation distance, and propagated probability historically led to catastrophic collisions.  Orbital Recommendations: What’s the Move? Once a possible catastrophic collision is identified, satellite operators choose a suggested collision avoidance maneuver, employing precise propulsion burns to slightly raise, lower, or shift orbital timing to ensure active satellites maintain safe separation from space junk. For astronaut-occupied spacecraft like NASA’s ISS, which has spent over 25 years in Earth’s lower orbit and housed more than 280 astronauts, NASA may act if the predicted probability of a catastrophic collision exceeds 1 in 10,000, meaning the risk rises just above 0.01%. For reference, ISS has only executed 40 collision avoidance maneuvers since its launch on Nov. 20th, 1998.          THE REAL-WORLD IMPACT?         ⦿  A Traffic Jam in Space? The “LEO Zone” has become dangerously congested. For context, active satellites pass within 1 km of each other every 22 seconds. As of May 5th, 2026, SpaceX operates exactly 10,358 active satellites, accounting for approximately 67% of all active satellites within Earth’s lower orbit. As a result, SpaceX must perform up to 300,000 collision avoidance maneuvers annually to mitigate the growing threat posed by space junk. A single space collision within Earth’s lower orbit can generate thousands of high-velocity orbital fragments, each capable of destroying active satellites. This could ultimately create a cascading effect known as the Kessler Syndrome: the theoretical tipping point at which space junk reaches critical mass, triggering a self-sustaining cycle of constant space collisions that render future space exploration impossible.          KEY TAKEAWAY         For decades, Earth’s lower orbit was treated as an endless expanse of uncharted space. Today, it’s a heavily congested cosmic highway littered with space junk traveling 11x faster than an AK-47’s bullets. AI’s ability to predict destructive orbital collisions could safeguard future space exploration.