Interview, Fireside Chat, Podcast
E133: Market melt-up, IPO update, AI startups overheat, Reddit revolts & more with Brad Gerstner
- Travel plans include regular flights to Las Vegas via Southwest due to convenience and cost.
- Poker performance expectations involve losing approximately 2.5 pounds from mental exertion during 12-hour daily sessions, with a target of middle-of-pack finishes (42nd place) in 100k tournaments and top 10% placements in large field events.
- The speaker anticipates continuing poker practice in large tournaments for three to four years despite time constraints, though they do not currently have the availability to do so.
- Macroeconomic forecasts predict two additional 25 basis point rate hikes by the Federal Reserve before year-end, with inflation peaking soon and rates reaching their "final destination."
- Economic growth is projected at 1% for the year with a year-end inflation rate of 3.2%, differing from the 3.7% Goldman consensus, while sticky rates and inflation are expected for the remainder of the decade.
- The IPO market is described as "super hot," with Arm's filing expected later this year to assist SoftBank, targeting a valuation between $30 billion and $70 billion despite an intrinsic cash-flow value estimated in the mid-$20s billion range.
- Nvidia is expected to perform well through year-end following revised guides from $7 billion in Q2 to $11 billion, with the stock trading near end-of-year price targets within a 10% range.
- A hard landing in Q4 is deemed unlikely due to anticipated Chinese economic stimulus involving trillions of dollars, though internet and software multiples remain below the 10-year average suggesting a potential reversion to the mean.
- The speaker expects the S&P 500's equal-weighted index to underperform significantly without top tech stocks, while seven or eight leading tech stocks are priced to perfection with yields less than half that of 10-year government bonds.
- Market sentiment is driven by psychological exhaustion from 2022 losses and rate cut hopes, which may diminish following China's stimulus, leading to an expected AI-driven revenue and efficiency boost in the short-to-midterm.
- Structural changes due to AI are projected to alter investment banking business models in 7 to 10 years and automate factory machinery over 10 to 15 years.
- User interface trends are predicted to evolve into a "race to intimacy" where users have hyper-fragmented relationships with service providers rather than single aggregators, alongside a reverse client-server model where individuals control their own data IP addresses.
- Google is expected to outperform ChatGPT within the next six months due to superior indexing and ad distribution, though distribution upside is considered lower than pre-ChatGPT levels.
- Reddit's API monetization decisions are anticipated to cause content leakage to direct-monetization platforms, eroding value for centralized apps and accelerating value accrual to individual creators or "hubs and spokes."
- AI funding frenzies are characterized as a "power law" business similar to the 1997-2000 search bubble, with Mistral AI's $105 million seed round deemed a low-yield "teaser bet."
- VC investments in hardware like H100s are criticized as "financially illiterate" purchases of chips rather than intellectual property, with a prediction that model training costs will drop 100x in 18 to 24 months.
- Regulatory environments in Washington DC are expected to block hyperscaler acquisitions of AI startups over $400 million, fostering a "copy and compete" dynamic, while current exuberance is attributed to fund managers needing activity to justify fees.
- RFK Jr.'s claims regarding genetically modified mosquitoes are identified as misinformation, clarifying that the project uses natural Wolbachia bacteria to potentially reduce dengue fever rates by 75%.
- Market fear of "engineering the earth" is linked to recency effects from COVID-19, and the current hype around AI is expected to correct as many valuations lack numerical justification.
- CalPERS' increase of venture allocation from 1% to 6% is labeled an emotional decision lacking numerical justification, and the margin of safety for AI investments is currently viewed as too low.
- The AI training cost curve is predicted to exceed Moore's Law growth similar to DNA sequencing, shifting the compute scramble from equity investment to a normalized leasing model.