May 2026
Chris Williamson, Andrew Huberman, Tom Segura and Matt McCusker use the Epstein case to examine why conspiratorial explanations now appeal to people they consider otherwise rational. Huberman argues that Epstein’s death is not plausibly explained by suicide, while the group’s wider discussion moves between skepticism of sprawling government cover-ups and concern that institutions have left too many public questions unanswered.
ElevenLabs is introducing an approved AI replica of Stan Lee’s voice through a partnership with Stan Lee Universe, positioning the late comic-book creator as a licensed feature inside its voice and creator tools. The company says users can request to license Lee’s voice for projects, hear it in Eleven Reader, generate Stan Lee cameos, and use Stan-inspired music, while repeatedly framing the launch around official authorization, rights ownership, and Lee’s mythology of stories being carried forward.
Marc Rowan, cofounder, CEO and chair of Apollo Global Management, argues that private markets are becoming central to capital allocation because public equity and fixed-income exposure is increasingly concentrated. In an a16z Show interview with David Haber, Rowan makes the case that Apollo’s future lies in originating investment-grade private credit for retirees, insurers and institutions while financing data centers, energy, defense, robotics and other capital-intensive technology infrastructure. He also says private-market products must adopt more public-market features, including daily pricing and standardized data, if they are to reach new pools of capital.
YC’s Pete Koomen argues that building “superintelligence” inside a company requires more than adding AI features to existing software: agents need access to the organization’s shared context, tools and accumulated work. In a Lightcone discussion with Garry Tan, Jared Friedman, Diana Hu and Harj Taggar, Koomen describes how YC’s internal agent system became useful once it could query a unified company database, reuse hundreds of internal tools and turn repeated judgment into improving skills. The broader claim is that AI-native organizations will depend as much on trust, transparency and broad access as on model capability.
Phil Hetzel of Braintrust argues that teams should stop treating evals for AI agents like unit tests meant to cover every possible failure. His maturity model starts with human judgments that record why an output failed, turns those justifications into scalable scorers, and then uses production traces to drive offline experimentation. The hard edge, he says, comes with tool-using agents, where useful evals must account not just for the final answer but for external system state and side effects at the moment the trace originally ran.
Bloomberg, ServiceNow, Nvidia, Cursor, Fireworks, EXO Labs, Unblocked, and Wall Street Prompt each point to the same shift: applied AI is becoming constrained by power, chips, inference systems, runtime controls, organizational context, and human fluency. The competitive question is moving from which model performs best to which companies can make the surrounding stack work reliably enough for deployment.
Billionaire software founder Joe Liemandt tells Shaan Puri and Sam Parr that his $1bn bet on Alpha School rests on a simple claim: AI and learning science can compress academics into two hours a day, freeing children to spend the rest of school on harder physical, social and entrepreneurial challenges. In the interview, Liemandt argues that parents, not children, are the main bottleneck, because they underestimate what students can do when high standards are paired with high support. His broader case is that education can be rebuilt as a scalable, capital-backed operating system rather than another low-return philanthropic project.
Nico Martin presents Transformers.js as the JavaScript application layer around local AI models, not the engine that performs the model math. In his explanation, ONNX defines the model graph and weights, ONNX Runtime executes the computation, and Transformers.js handles the surrounding work: loading assets, converting inputs to tensors, selecting devices and precision, and decoding outputs. Martin argues that this task-based abstraction is why one `pipeline()` API can support very different workloads, from text generation to depth estimation, while hiding much of the model-specific wiring from developers.
Bloomberg Primer argues that electricity grids have become a central constraint on economic growth as AI, electric vehicles and heat pumps push demand higher after decades of flat consumption in many Western countries. The piece contrasts China’s continuous grid buildout with stalled Western systems, and follows efforts including superconducting cables, grid-stabilizing machines for renewable-heavy systems and Nigerian mini-grids. Its central claim is that countries able to expand and stabilize power delivery will be better positioned to capture the next wave of industrial and digital growth.
Wen-Chin Wu, in a Hoover Institution talk drawing on multiple public-opinion surveys, argues that Taiwanese support for self-defense is high but conditional. He separates backing for national defense measures, including U.S. arms purchases, from personal willingness to fight or resist, and finds that both depend heavily on perceived threat from China, expectations of U.S. intervention, party identity, costs, and question wording. The result, in Wu’s account, is not a Taiwan that is either complacent or uniformly resolved, but a public that is “worried but cool” amid coercion and strategic ambiguity.
John Coogan and Jordi Hays argue on Diet TBPN that Ferrari’s first EV, the roughly $640,000 Luce, exposes a strategic problem rather than simply a design controversy: it is expensive, not clearly scarce, not obviously superior on range or performance, and positioned against EV makers with stronger software and scale. They make a similar case about the Enhanced Games, which Hays says had an appealing premise but failed to create the records, stakes or emotional context that make Olympic-style competition compelling. In both cases, the hosts contend that a strong concept is not enough to establish a market.
Eric Ries, author of The Lean Startup, argues in a TBPN conversation that strong companies are often undone not by lack of capital or ambition, but by governance, incentives and reporting systems that separate control from the mission that made them valuable. In discussing his new book, Incorruptible, Ries makes the case for mission-protective structures such as public benefit corporations, long-term trusts and employee ownership, saying durable profit depends on companies being built to resist extraction after founders and early cultures are gone.
Abstraction creates value only when responsibility for the hidden system remains clear, the TBPN discussion argued across AI ethics, company governance, logistics and inference markets. Christopher Hale framed the Vatican’s AI position as a claim that human dignity and accountability must govern algorithmic systems; Eric Ries argued that mission-driven companies need structures strong enough to resist capital and convenience; and Sean Henry and Alex Atallah described logistics and AI markets where software layers must still answer for the fragmented physical or computational systems beneath them.
Sands Capital portfolio manager Daniel Pilling argues Micron’s rally reflects a broader AI supply squeeze: demand is accelerating faster than semiconductor capacity can be added. Speaking on Bloomberg Technology, he said adoption remains early, suppliers have long lead times and pricing power, and the beneficiaries extend beyond Nvidia to memory, chip equipment, power providers and CPUs. He was more cautious on China’s chip advances, saying manufacturing constraints and the lack of ASML-like lithography remain a major barrier.
Alex Cheema of EXO Labs argues that running frontier AI locally is primarily an inference-stack problem, not a model-training problem. Using a four-Mac Studio GLM 5.1 setup that costs about $40,000 and reaches roughly 20 tokens per second as the current reference point, Cheema says local price-performance still has about 100x to improve through better kernels, interconnects, heterogeneous hardware, energy efficiency, orchestration, and benchmarks. His case is that today’s awkward home cluster is not the endpoint, but evidence of how much optimization remains outside the cloud.
Bloomberg’s Sally Bakewell argues that Wall Street’s AI challenge has shifted from buying software to teaching bankers how to use it in finance-specific work. She says firms have already spent heavily on AI tools, but demand is rising for trainers such as Wall Street Prompt, which can charge $25,000 a day to teach bankers how to apply generative AI to tasks such as founder diligence, earnings analysis and forecasting. In Bakewell’s account, banks are treating AI fluency as a competitive necessity as much as a productivity initiative.
Jay Ritter, the University of Florida IPO scholar known as “Mr. IPO,” told Bloomberg Technology that SpaceX’s prospective listing would test whether a genuine launch-cost advantage can support one of the largest valuations ever brought to public markets. Ritter argued that Starship’s engineering difficulty could help protect SpaceX from rivals and strengthen Starlink’s economics, but said a valuation around $1.5 trillion would require very large future profits to justify a roughly 80-times-sales multiple.
Bloomberg’s Craig Trudell argues that Ferrari’s first fully electric car, the $640,000 Luce, is facing a backlash less because of its technology than because critics do not think it looks like a Ferrari. But he says the commercial bar is much lower than broad approval: Ferrari may need only a few hundred wealthy buyers, especially if owning the EV helps them secure access to more coveted future models.
In a ServiceNow-sponsored interview, ServiceNow AI engineering executive Joe Davis and Nvidia agentic AI product chief Adel Hallak argue that enterprise AI agents should be built as governed systems, not as single models with broad autonomy. They describe agents as layered architectures of models, harnesses, tools, sandboxed runtimes, permissions and control towers, with default-deny access replacing trust in the model’s judgment. Davis points to ServiceNow’s internal automation of 90% of some IT support requests as the practical proof point; Hallak frames Nvidia’s OpenShell and model stack as infrastructure for making that kind of autonomy enforceable.
ElevenLabs is presenting Music v2 as a licensed-data AI music model built to generate vocal-led tracks from detailed natural-language prompts, not just loops or backing beds. The launch materials argue that the model can produce finished-sounding, one-shot outputs across styles and languages, while adding workflow features such as targeted inpainting, section-by-section composition, and deployment through ElevenMusic, ElevenCreative, and a forthcoming ElevenAPI.
Bloomberg’s Ian King reports that Qualcomm will supply AI data-center chips to ByteDance, identifying TikTok’s owner as the previously unnamed hyperscaler customer behind Qualcomm’s recent comments. King frames the order as a breakthrough for Qualcomm’s AI infrastructure ambitions, not only as a sale of its own processors but as evidence that the company is pursuing a Broadcom-like role helping large customers turn custom AI-chip designs into high-volume silicon.
Mardu Swanepoel of Flinn AI argues that the best agent products are not defined by maximum autonomy, but by how carefully they bound and expose it. Looking across Harvey, Cursor, Manus, and Claude, he identifies four shared patterns: focused modes that narrow the task, transparent execution that lets users inspect the work, personalization that reflects user or organizational methods, and reversibility that limits the cost of mistakes.
Chase Hughes, speaking with Chris Williamson, reads courtroom footage of Wade Wilson, known as the Deadpool Killer, as a display of defiance and attempted control rather than simple calm. Hughes argues that Wilson’s leaned-back posture, exposed neck, lip-licking and low blink rate point to challenge, appearance management and focused self-possession inside a setting where his autonomy was visibly constrained.
Bloomberg reports that SpaceX’s upgraded Starship completed several key ship-side milestones, including mock-satellite deployment and a return to Earth, but the test was not a clean success. The clip shows the upper-stage ship reaching the water after landing and shutdown callouts before toppling over and exploding, while Bloomberg’s description says the booster spun out of control and broke apart over the Gulf of Mexico.