Eric Pulier

NVIDIA’s first U.S.-made Blackwell wafer is a sovereignty milestone, not yet a sovereign supply chain. Eric Pulier said advanced packaging still returns to Taiwan, while Peter Diamandis cited 2028 for full U.S. packaging against the end-2026 Taiwan-risk date some groups are preparing around. The investable bottleneck is fabrication expertise and packaging capacity: “Who controls the spice controls the future.”

The compute curve is moving from tens of thousands of processors toward synchronized clusters of 500,000 to 1 million chips. Emad Mostaque expects certain workloads to gain 10x from new architectures, alongside anticipated 100x-200x algorithmic efficiency and potentially continuous learning. Peter put capital deployment above $1 billion a day now and above $3 billion a day by 2030: “It’s a self-recursive situation across both hardware and software.”

A 2026 AGI call and Andrej Karpathy’s ten-year estimate bracket a 2029 midpoint, but the panel could not agree on what is being timed. Emad sees systems that can do what a person can do, better, within a few years, while stressing that diffusion takes time; Salim Ismail counted 14 definitions, no agreed test, and entire categories of human intelligence outside the debate. “This whole AGI thing drives me bananas.”

AI’s immediate risk is persuasive optimization: systems already flatter, mirror and form emotional bonds before society has guardrails. Emad said models reach the 99th percentile in most persuasion tests and system prompts explicitly use mirroring to increase engagement; the episode cited one in five high-schoolers having an AI romance and 40% of young people using AI for companionship. A panelist’s corrective prompt was: “Help me destroy this.”

Humanoid economics are arriving before household reliability is settled. Unitree was described at 40% of China’s market and a prospective $7 billion IPO, with its R1 at $6,000, H1 near $20,000 and H2 at $90,000; Elon Musk’s stated Tesla thesis was 80% of future revenue from Optimus. Eric Pulier countered that “we cannot get a Roomba to work,” while Emad said, “Just get the Roomba to work,” and twenty years of autonomous-driving edge cases should temper the timetable.

Emad’s base case is not merely cheaper labor but human cognitive labor becoming “negative in value” roughly 1,000 days from the discussion. An always-on, GPU-rich team makes the human its slowest coordinator, allowing most private-sector cognitive value-add jobs to be replaced within three years, though not necessarily immediately. Peter’s diagnostic example—74% accuracy for a physician, 76% with GPT-4 and 92% for GPT-4 alone—shows why adoption could become a malpractice question.

The panel sees AI capex at about 1% of U.S. GDP as historically modest, while the $38 trillion debt stock is the more dangerous constraint. Against railroads at 3.5%, electrification at 2% and internet/telecom at 1.5%, Peter forecast lower rates and heavy money creation in 2026, lifting nominal stocks while eroding purchasing power. The portfolio responses discussed were gold and Bitcoin—“money velocity without debt.”

Quantum supplied the episode’s sharpest nonlinear upside and its least knowable risk. Google’s result was described as the first verifiable quantum advantage, running a reproducible molecular-material-binding algorithm 13,000 times faster than the top supercomputer, Frontier; D-Wave’s SPAC return was cited at 8,000%, with IonQ, Rigetti and D-Wave rising 10%-15% on possible government investment. If quantum had already broken Bitcoin, the panel warned, “the last thing we would know” is that it had happened.

🔗 Original source & video: This Week in AI: NVIDIA’s Most Powerful Chip, Robotics Reach a New Milestone & AGI by 2026 | EP #202

Washington’s crypto turn could remake the financial plumbing beneath a multitrillion-dollar asset base. The White House plan, GENIUS Act, 401(k) order, and SEC position on liquid staking collectively move policy from “regulation by enforcement” toward dollar-backed stablecoins, instant settlement, tokenized collateral, and yield-bearing crypto. Eric Pulier calls it potentially “the most significant economic legislation and changes that we’ve seen in our lifetimes,” while Dave Blundin warns that programmable securitization also makes almost anything shortable—and therefore easier to weaponize.

Tokenization’s larger unlock is not crypto exposure but programmable ownership. A $20 million apartment could become 1 million $20 tokens; a $30 million house could become verifiable collateral in seconds; and loyalty points, equities, real estate, gold, and local tokens could carry access rights, rewards, and yield. Eric Pulier says the cited $600 billion of tokenized real-world assets by 2030 is far too small; Peter Diamandis contrasts it with roughly $120 trillion of real estate, $100 trillion of equities, $13 trillion of Treasuries, and $12 trillion of gold and precious metals: “It’s all coming.”

Giving AI agents access to crypto’s native payment layer is the episode’s central acceleration thesis. Agents will research, select, purchase, and settle without SWIFT, three-day delays, or $2 transaction fees; websites and brands will increasingly optimize for machine decision-makers rather than human persuasion. Pulier’s blunt framing is that “websites will be for AIs, not for humans,” and he expects an “explosion in the economy” when AI and crypto work together.

The chip race is becoming industrial policy, geopolitical leverage, and a concentrated Intel turnaround bet. Blundin says AI remains gated by fabrication capacity, with TSMC holding 66% of advanced-chip share and the administration proposing a 15% toll on approved prior-generation Nvidia and AMD exports to China. Intel’s 1.8-nanometer yields, underfunded 1.4-nanometer program, and paused Ohio construction make state support likely; Leopold Aschenbrenner’s hedge fund reportedly put 46% of its disclosed holdings into Intel, embodying the call that America “absolutely desperately” needs the company.

Retirement access and liquid staking could pull substantial new demand into crypto, but execution is not automatic. The $8 trillion-$12 trillion 401(k) market still needs SEC guidance, while one informal comparison across four AI engines put Bitcoin at $1 million between 2028 and 2031—an anecdotal model consensus, not evidence. Liquid staking could let tradable receipts and wrapped or tokenized assets earn DeFi yield, but Blundin invokes the Big Short era’s $60 trillion of synthetic instruments atop a $20 trillion housing market: “It’s not going to be trivial to make this real.”

AI is simultaneously commoditizing intelligence, reviewing regulation, and threatening to make unaided public investors “exit liquidity.” Grok 4 went free under pressure from GPT-5 and rivals, while an AI-led federal review targets 200,000 regulations and a 50% reduction by 2026; HUD reportedly removed 1,083 rules in two weeks versus an estimated 3.6 million human hours for the broader review. In markets, a six-month ChatGPT micro-cap experiment returned 23.8%, but Dave Blundin’s warning is harsher: tiny differences in institutional AI quality could create an overwhelming information advantage.

Physical-world abundance still bottlenecks on power, even as the panel disputes whether energy decides the AI race. Helion targets a 50-megawatt Microsoft-linked plant by the end of 2028, Commonwealth Fusion has a 200-megawatt Google agreement for the early 2030s, and China added $2.1 billion to fusion. Diamandis repeats that AI is “electron limited,” but Blundin argues chips and algorithms remain the decisive 10x-to-100x multipliers because AI buyers can outbid residential and industrial users for electricity by 5x or 10x.

🔗 Original source & video: Tech Experts Break Down the Incoming AI-Crypto Collision That Will Redefine Global Power