7 September 2026
13 new episodes (12 hours listening) published by the 38 podcasts on the list. 7 highlight clips below (25 mins total).
Investment 7 September 2026 · 7 clips
Alpha Exchange
EPISODE 268 The Case for Tail Hedging
-
1 of 3 contrarian
Alpha Exchange argues the binding constraint on the AI buildout is capital rather than power or memory, with AI capex running about 0.8% of US GDP in the first quarter of 2026.
Hyperscalers borrow without caring what it costs, because in a Merton framing the spread they pay is option premium on a right tail they think is enormous, so a rate that stops a homebuyer at a 7% mortgage does not slow them at all. Computer equipment and software investment together contributed 1.09 percentage points of the 2% headline growth, against 1.0 from all personal consumption.
-
2 of 3 framework
Alpha Exchange adds a fourth risk-off to its taxonomy: a liquidation that starts in the Treasury market, where the 10-year note is the risk asset.
Equities falling while bonds rally is the classic case, the 2013 and 2022 taper has both falling together, and March 2020 had investors violently unwinding a rally to raise cash. Buyers step back from US government debt on a view that the level is too great and the governance too weak to fix, so everything priced off the risk-free rate reprices with it and monetary policy never has to move.
-
3 of 3 contrarian
Alpha Exchange puts one-month realised correlation in the S&P at 1%, with index volatility at 8.6 while the top ten names average 46.
Option prices follow what has just happened rather than what might, so a book sized off the recent number carries more risk than its manager thinks and the correction lands at the moment stocks start moving together. His cross-asset insurance index, averaging five-year percentiles of the VIX, TLT volatility, CVIX, high yield spreads and credit implied volatility, recently sat below the 10th percentile.
Masters in Business (Ritholtz)
Seth Bernstein, chief executive of AllianceBernstein.
The episode states he has been chief executive of AllianceBernstein since 2017 and is head of asset management for Equitable Holdings, with the firm managing over $905 billion. He arrived when it ran about $500 billion, after 32 years at JPMorgan Chase and its predecessors, where he ran high yield, debt capital markets and loan syndications, then was global head of fixed income and currency and global head of Managed Solutions.
-
prediction
AllianceBernstein's chief executive says the firm will launch no further mutual funds in the United States, with active ETFs and separately managed accounts taking the whole of new product.
Bernstein built the business from nothing to 31 strategies and $21 billion, and stresses that almost all of it sits in strategies which did not exist before rather than old products in a new wrapper. His case for the SMA is tax rather than fee, working around wash sales and clearing the unintended bets that stack up in a multi-manager portfolio, with 401k plans the one brake until the Department of Labor moves.
Audio streamed from the publisher.
The Meb Faber Show
Robin Wigglesworth
Editor of FT Alphaville at the Financial Times and author of Trillions, a history of index funds, now out with A Fabulous Debt on the thousand-year history of the bond market. He also presents an FT podcast on financial history and says he first started following private credit more than a decade ago.
-
explainer
Robin Wigglesworth points out that Argentina's century bond defaulted and still beat Austria's, which has never missed a payment.
Austria's carried the skinniest coupon imaginable, so when rates normalised the price fell as much as 80%. Argentina's paid enough coupon before it stopped that holders recovered more, and he runs the same arithmetic against anyone buying inflation-linked Treasuries expecting them to work as an inflation hedge.
AI 7 September 2026 · 7 clips
Dwarkesh Podcast
Beren Millidge, John Schulman and Charlie O'Neill.
The episode introduces Beren Millidge as CTO of Zyphra, which builds open source models; John Schulman as chief scientist at Thinking Machines, previously a co-founder of OpenAI, who led the RLHF work behind ChatGPT; and Charlie O'Neill as head of model training at Baseten. All three sit inside training stacks rather than commenting on them from outside.
-
contrarian
Researchers from Zyphra, Thinking Machines and Baseten locate the distillation bottleneck in the prompt distribution, and say Chinese labs now buy it from the router services that let Chinese users reach US frontier models.
Real coding sessions are the one input a lab cannot synthesise, which is why the panel argues the frontier houses no longer hold much edge in reinforcement learning environments despite owning the hardest ones and logit access. One speaker splits environments into difficulty and realism and argues a copied model only matches its teacher on benchmark-shaped work, losing the messy multi-turn behaviour.
Y Combinator
Seth Karten, Jon Saad-Falcon, Josh France and Regan Bell
Seth Karten is a Princeton PhD student and a researcher at Prime Intellect, and wrote Prime Agent. Jon Saad-Falcon is a Stanford PhD student and co-lead author of OpenJarvis. Josh France, newly promoted to head of YC Labs, and Regan Bell built QM, the agent harness every Y Combinator employee now uses.
-
explainer
Jon Saad-Falcon puts on-device models six to twelve months behind the frontier and running at 800 times lower cost than the cloud equivalent.
OpenJarvis cuts a personal stack down to five pieces, the model, the inference engine, the agent logic, the tools and memory, and the learning loop, then hands that whole spec to a cloud model to tune. Configurations optimised that way beat the same local models deployed out of the box, and the optimiser can be Gemini, Kimi or GLM as readily as Opus.
Worth listening to in full 7 September 2026
Most clips above stand alone. These are the episodes that justify the whole hour.
AI researchers debate how far the current paradigm goes
Ninety-seven minutes of three people who run training stacks disagreeing with each other in detail, with the disagreements resolved to cruxes rather than left as opinions. The sections on environment creation, catastrophic forgetting under repeated micro-updates, and why continual learning breaks at small scale are all substantive and did not fit a clip. If you want one episode this quarter on what the current paradigm can reach, this is it.
Why Bridgewater's CIO Says AI's Human Extinction Risk Is Real
Fifty minutes of a sitting chief investment officer on what his firm actually does with models, what it costs and what he thinks it does to the world, with a number on most of it. The interpretability exchange and his answer on the binding bottleneck are not clipped and both earn the time; the closing host debrief does not.