What caught my eye this week.
Bad news! Not only are the machines now coming from our cushy brain-based desk jobs, but our best response will be to hug it out.
At least that’s one takeaway from a report in the Financial Times this week on what kinds of jobs have done well as workplaces have become ever more touchy-feely – and thus which will best survive any Artificial Intelligence takeover.
The FT article (no paywall) cites research showing that over the past 20 years:
…machines and global trade replaced rote tasks that could be coded and scripted, like punching holes in sheets of metal, routing telephone calls or transcribing doctor’s notes.
Work that was left catered to a narrow group of people with expertise and advanced training, such as doctors, software engineers or college professors, and armies of people who could do hands-on service work with little training, like manicurists, coffee baristas or bartenders.
This trend will continue as AI begins to climb the food chain. But the final outcome – as explored by the FT – remains an open question.
Will AI make our more mediocre workers more competent?
Or will it simply make more competent workers jobless?
Enter The Matrix
I’ve been including AI links in Weekend Reading for a couple of years now. Rarely to any comment from readers!
Yet I continue to feature them because – like the environmental issues – I think AI is sure to be pivotal in how our future prosperity plays out. For good or ill, and potentially overwhelming our personal financial plans.
The rapid advance of AI since 2016 had been a little side-interest for me, which I discussed elsewhere on the Web and with nerdy friends in real-life.
I’d been an optimist, albeit I used to tease my chums that it’d soon do them out of a coding job (whilst also simultaneously being far too optimistic about the imminent arrival of self-driving cars.)
But the arrival of ChatGPT was a step-change. AI risks now looked existential. Both at the highest level – the Terminator scenario – and at the more prosaic end, where it might just do us all out of gainful employment.
True, as the AI researchers have basically told us (see The Atlantic link below) there’s not much we can do about it anyway.
The Large Language Models driving today’s advances in AI may cap out soon due to energy constraints, or they may be the seeds of a super-intelligence. But nobody can stop progress.
What we must all appreciate though is that something is happening.
It’s not hype. Or at least for sure the spending isn’t.
Ex Machina
Anyone who was around in the 1990s will remember how business suddenly got religion at the end of that decade about the Internet.
This is now happening with AI:
Source: TKer
And it’s not only talk, there’s massive spending behind it:
Source: TKer
I’ve been playing with a theory that one reason the so-called ‘hyper-scalers’ – basically the FAANGs that don’t make cars, so Amazon, Google, Facebook et al – and other US tech giants are so profitable despite their size, continued growth, and 2022-2023 layoffs, is because they have been first to deploy AI in force.
If that’s true it could be an ominous sign for workers – but positive for productivity and profit margins.
Recent results from Facebook (aka Meta) put hole in this thesis, however. The spending and investment is there. But management couldn’t point to much in the way of a return. Except perhaps the renewed lethality of its ad-targeting algorithms, despite Apple and Google having crimped the use of cookies.
Blade stunner
For now the one company we can be sure is making unbelievable profits from AI is the chipmaker Nvidia:
Source: Axios
Which further begs the question of whether far from being overvalued, the US tech giants are still must-owns as AI rolls out across the corporate world.
If so, the silver lining to their dominance in the indices is most passive investors have a chunky exposure to them anyway. Global tracker ETFs are now about two-thirds in US stocks. And the US indices are heavily tech-orientated.
But should active investors try to up that allocation still further?
In thinking about this, it’s hard not to return to where I started: the Dotcom boom. Which of course ended in a bust.
John Reckenthaler of Morningstar had a similar thought. And so he went back to see what happened to a Dotcom enthusiast who went-all in on that tech boom in 1999.
Not surprisingly given the tech market meltdown that began scarcely 12 months later, the long-term results are not pretty. Bad, in fact, if you didn’t happen to buy and hold Amazon, as it was one of the few Dotcoms that ultimately delivered the goods.
Without Amazon you lagged the market, though you did beat inflation.
And yet the Internet has ended up all around us. It really did change our world.
Thematic investing is hard!
I wouldn’t want to be without exposure to tech stocks, given how everything is up in the air. Better I own the robots than someone else if they’re really coming for my job.
But beware being too human in your over-enthusiasm when it comes to your portfolio.
The game has barely begun and we don’t yet know who will win or lose. The Dotcom crash taught us that, at least.
Have a great weekend!
From Monevator
Does gold improve portfolio returns? – Monevator [Members]
How a mortgage hedges against inflation – Monevator
From the archive-ator: How gold is taxed – Monevator
News
Note: Some links are Google search results – in PC/desktop view click through to read the article. Try privacy/incognito mode to avoid cookies. Consider subscribing to sites you visit a lot.
UK inflation rate falls to lowest level in almost three years – BBC
Energy price cap will drop by 7% from July [to £1,568] – Ofgem
House prices are modestly rising, driven by 17% annual spike in new build values – T.I.M.
Hargreaves Lansdown rejects £4.7bn takeover approach – This Is Money
Judge: Craig Wright forged documents on ‘grand scale’ to support Bitcoin lie – Ars Technica
FCA boss threatens private equity with regulator clampdown – CityAM
Sunak says it’s 4th July, in the rain, against a subversive soundtrack [Iconic]– YouTube
Sir Jim Ratcliffe scolds Tories over handling of economy and immigration after Brexit – Sky
No, it’s not all the Tories’ fault… but Sunak and Hunt were too little, too late – Bloomberg
Products and services
Pay attention to catches as well as carrots when switching bank accounts – Guardian
Which energy firm offers the cheapest way to get a heat pump? – T.I.M.
How to get the most from second-hand charity shops – Which
Get £200 cashback with an Interactive Investor SIPP. New customers only. Minimum £15,000 account size. Terms apply – Interactive Investor
Nine out of ten savings accounts now beat inflation – This Is Money
Problems when transferring a cash ISA – Be Clever With Your Cash
Nationwide launches a trio of member deals worth up to £300 – Which
Transfer your ISA to InvestEngine by 31 May and you could get up to £2,500 as a cashback bonus (T&Cs apply. Capital at risk) – InvestEngine
Seven sneaky clauses in estate agent contracts that can cost you dear – This Is Money
Halifax Reward multiple account hack: worth up to £360 a year – Be Clever With Your Cash
Hidden homes in England and Wales for sale, in pictures – Guardian
Comment and opinion
No, the stock market is not rigged against the little guy – A.W.O.C.S.
The life hedge… – We’re Gonna Get Those Bastards
…is easier said than implemented [US, nerdy] – Random Roger
Checking out a fake Ray Dalio Instagram investing scam – Sherwood
An open letter to Vanguard’s new CEO – Echo Beach
If you look past the headlines, London is charging ahead – CityAM
Most of us have too much in bonds [Search result] – FT
Why we still believe in gold – Unherd
Are ‘fallen angel’ high-yield bonds the last free lunch in investing? – Morningstar
For love or money – Humble Dollar
Naughty corner: Active antics
Fund manager warns putting £20k in the US now will [possibly!] lose you almost £8k – Trustnet
A deep dive into US inflation, interest rates, and the US economy – Calafia Beach Pundit
A tool for testing investor confidence – Behavioural Investment
When to use covered call options – Fortunes & Frictions
Valuing Close Brothers after the dividend suspension – UK Dividend Stocks
Meme stock mania has entered its postmodern phase [I’m editorialising!] – Sherwood
Kindle book bargains
Bust?: Saving the Economy, Democracy, and Our Sanity by Robert Peston – £0.99 on Kindle
Number Go Up by Zeke Faux – £0.99 on Kindle
How to Own the World by Andrew Craig – £0.99 on Kindle
The Great Post Office Scandal by Nick Wallis – £0.99 on Kindle
Environmental factors
Taking the temperature of your green portfolio [Search result] – FT
The Himalayan village forced to relocate – BBC
‘Never-ending’ UK rain made 10 times more likely by climate crisis, study says – Guardian
So long triploids, hello creamy oysters – Hakai
Robot overlord roundup
We’ll need a universal basic income: AI ‘godfather’ – BBC
Google’s AI search results are already getting ads – The Verge
AI engineer pay hits $300,000 in the US – Sherwood
With the ScarJo rift, OpenAI just gave the entire game away – The Atlantic [h/t Abnormal Returns]
Perspective mini-special
How much is a memory worth? – Mike Troxell
We are all surrounded by immense wealth – Raptitude
How to blow up your portfolio in six minutes – A Teachable Moment
My death odyssey – Humble Dollar
Off our beat
The ultimate life coach – Mr Money Mustache
How to cultivate taste in the age of algorithms – Behavioural Scientist
Trump scams the people who trust him – Slow Boring
Buying London is grotesque TV, but it reflects the capital’s property market – Guardian
The algorithmic radicalisation of Taylor Swift – The Atlantic via MSN
And finally…
“Three simple rules – pay less, diversify more and be contrarian – will serve almost everyone well.”
– John Kay, The Long and the Short of It
Like these links? Subscribe to get them every Friday. Note this article includes affiliate links, such as from Amazon and Interactive Investor.
Really good presentation from hedge fund Coatue here, considers both sides:
https://drive.google.com/file/d/1Y2CLckBIjfjGClkNikvfOnZ0WyLZhkrT/view
Bullish AI.
It is indeed an excellent presentation deck, but they seem to be using Next Twelve Months Earnings for the PE in both slide 10 (for SPY) and 32 (for NASDAQ/QQQ) and not FCF, which, as the Tweet you kindly linked to @#200 above rightly pointed out, could be potentially misleadingly reassuring: e.g. slide 32 shows the NTM PE at the peak of the TMT boom as being 89x versus just 28x now, but the FCF multiples for the hyperscalers now are actually almost comparable to the Dot.com peak in 2000.
I wonder if this timeless tale is aposite:
https://open.substack.com/pub/onveston/p/how-to-outsmart-wall-streets-goliaths
It’s basically the Mexican fisherman tale rewritten for value / mean reversion investors.
Or as ‘Dragon Invest’ substack put it back in February: “Would you rather fish in a pond with so many fisherman crowding up on the shore that there’s barely any fish left to catch and the ones that are left are now so prized for that there’s basically no chance of you a new fisherman with average skills catching one or would you rather fish in a remote pond in the middle of nowhere that people either don’t know about or don’t want to go to because they fear uncertainty? Most people would choose the first option, I mean how else do you explain the irrationality in public equity markets right now. The U.S. equity market alone accounts for 70% of the entire global stock market”.
EM is loathed. Small caps are shunned. Value languishes. Nvidia is worth 3x the US energy sector FFS!!
At the intersection of investor disinterest and dislike lies opportunity provided it’s debt free, has a real moat, high quality earnings and is cheap enough to be worth a punt. The anti AI trade.
Telegraph today back onto crash fears:
https://www.telegraph.co.uk/money/investing/stocks-shares/how-to-protect-your-money-from-a-market-crash/
Rereading the excellent Monevator 2010 Peter Lynch piece, I was struck that one of his 13 principles was to invest in firms that use tech, not make it.
I think there may be a lesson in there for the hyperscalers & semiconductor firms.
Brilliant meta-takes on the data centre buildout (with link to a spreadsheet of scenarios) from Dwarkesh last week:
https://open.substack.com/pub/dwarkesh/p/thoughts-on-the-ai-buildout
Just give me some Phil Fisher quality AI stocks at Benjamin Graham and David Dodd net net prices please!
Meanwhile, Gary Marcus today points out that China could ruin the single narrow track approach the US is currently taking to AI in pursuing only ever larger LLMs by making all their own lighter weight frontier models entirely open source, whose effectively zero cost would then completely undercut any business model which OpenAI or Anthropic might eventually alight upon.
Interesting angle today on improvement to memory (the straw) being more important than getting more ‘compute’ (the liquid in the glass).
http://uk.investing.com/analysis/ai-chip-war-just-shifted-why-memory-may-matter-more-than-compute-200619722
The scope for improvement in this area could be substantial and low hanging. Looks good for Qualcomm.
This one thinks that there’s not only not a bubble but that actually the problem is that we’re not building out nearly fast enough (the missing half of the equation being, in its view, an insatiable level of demand for tokens, tokens by the multi quadrillion now in fact):
https://open.substack.com/pub/asymmetricopportunities/p/the-ai-bubble-debate-is-missing-half
But, if the computational / token supply is indeed insufficient for the exponentially increasing levels of demand for it, is that not then perhaps simply because those tokens are, in effect, either being given away for free or sold at a substantial loss? Is paid up revenue not a better gauge than tokens?
I could no doubt do a roaring trade if I could somehow sustainably sell £20 notes for £10 each.
The comment by @Matt Newell in the comments (27 October) sums it up well IMO.
And a very deep dive into why it’s not a Ponzi:
https://open.substack.com/pub/artificialintelligencemadesimple/p/the-ai-is-a-bubble-narrative-is-stupid
Sure vendor circular financing may be no Ponzi but simply saying OpenAI has millions of paying customers doesn’t cut it.
Amazon survived the Dot.com disaster of 2000-02, and trades at north of $200 now; but, split adjusted, it still fell from a intraday peak of $5.60 in 2000 to 30 cents at one point in 2002, nearly 95% down, and it was right that it traded down so far then given how far valuation had gotten ahead of earnings.
The financing may well secure CUDA lock in for Nvidia, but so what?
Show me the money.
Where are the hundreds of billions of revenue to go with the product (and to frank the Opex and Capex)?
Of course it’s not a literal Ponzi, and, yes, Ponzi as a term does get bandied about too liberally.
But it does look distinctly like there’s going to be an epic revenue gap ahead, even if massive end user revenue does eventually arrive (as, in my example, it ultimately did for Amazon).
This one could be significant:
https://open.substack.com/pub/asymmetricopportunities/p/the-gpu-data-center-bubble-that-isnt
It’s a head on refutation of bearish narratives around rapid hardware obsolescence and accounting tricks with depreciation; using power cost math to try to show that even older A100 GPUs running at today’s electricity prices remain cash flow positive, typically generating gross margins several times higher than power expenses at industrial rates.
Another theme which it usefully explores is why real cash flow, rather than accounting depreciation, is the true health indicator for GPU investments, and that power costs would need to rise far above historical averages to make GPU rentals unprofitable, making claims of imminent mass write downs seem exaggerated.
Lots to process on this one.
If the GPU/TPU/NPU stack really can be legitimately depreciated over 5 or more years then that potentially is/would be a huge difference.
Although I don’t think that, as such, this impacts *directly* and *immediately* the paid end user LLM demand issue (i.e. insufficiency fast paid uptake); the amount of end user revenue needed to cover Capex is obviously much less if the depreciation cycle is really and truly economically significantly longer than I’ve recently given credit for.
From “What GPU pricing can tell us about how the AI bubble will pop” (Bryce Elder):
“One odd thing about AI equipment is that it’s very expensive to buy and very cheap to rent. Want an Nvidia B200 GPU accelerator? Buying one on its release in late 2024 would’ve probably cost around $50,000, which is before all the costs associated with plugging it in and switching it on. Yet by early 2025, the same hardware could be rented for around $3.20 an hour. By last month, the B200’s floor price had fallen to $2.80 per hour. Nvidia upgrades its chip architecture every other year, so there’s an opportunity for the best-funded data centre operators to lock in customers with knockdown prices on anything that’s not cutting edge. From the outside, the steady decline in GPU rental rates resembles the kind of predatory price war the tech industry relies upon: burn money until all your competitors are dead. The evidence, however, is more complicated. … among the hyperscalers (Amazon’s AWS, Microsoft’s Azure, Google and Oracle) prices have hardly budged. The result is an ever-widening gap between rates charged by the big-four and a growing number of smaller rivals.”
I ask myself, does the low rental cost but high(er relative) residual values for slightly older GPUs situation, support, or become disjunctive with, the analysis in the Asymmetric Opportunities substack post linked to immediately above?
Also, I’d understood/ read that Nvidia had moved to annual GPU release cadence, not every other year as before.
Bubble + something else?:
https://open.substack.com/pub/braddelong/p/yes-ai-is-a-bubble-but-it-is-a-bubble
Repeat the AI catechism in the three parts after me:
“Capabilities based on current methods will continue to improve smoothly”
“New methods will continue to arrive and accelerate progress”
“Compute development will accelerate and compute bottlenecks will be overcome”
Seeing around the curve with the true believers in the LLM road:
https://open.substack.com/pub/amistrongeryet/p/what-i-saw-around-the-curve
Meanwhile, out in the market, Meta plunges a couple hundred billion in market cap today (a massive 11% move) upon announcing that, in effect, it’s doubling down on AI Capex. Shades of 2022 with the Metaverse (or is that comparison just too obvious to be right?) At least their bond sale is well subscribed.
Feels like a turning point. No reward with a pump, unlike with Oracle recently (which has basically now lost its own gains in the stock price since saying it was going ‘all in’ on the AI buildout).
Nvidia margin= everyone elses’ opportunities, or is it instead Jevons’ paradox redux?:
https://open.substack.com/pub/davefriedman/p/when-gpu-demand-peaks
Zvi on the case of what OpenAI going to a for profit IPO would mean quantitatively, unsurprisingly concluding that all the value is in tail scenarios (with some really eye opening numbers for fully human labour substituting AGI being generated by Anton Korinek of UAV, who “used standard economic models to estimate that AGI could be worth anywhere from $1.25 to $71 quadrillion globally [using 4-12% p.a. discount rates when you look up his paper]. If you take Korinek’s assumptions about OpenAI’s share, that would put the company’s value at $30.9 trillion”.
This is a figure rightfully dismissed by Zvi as “silly” 😉 :
https://open.substack.com/pub/thezvi/p/openai-moves-to-complete-potentially
Real time AI boom or bubble monitor dashboard now live, and registering 1 out of 5 red flags:
https://boomorbubble.ai/
Anatomy of a bubble:
https://open.substack.com/pub/netinterest/p/bubble-trouble
MIT said 95% of businesses seeing no RoI on Gen AI but now Wharton says that in fact 74% are!:
https://open.substack.com/pub/bigtechnology/p/wait-are-74-of-businesses-actually
Meanwhile, MSFT’s Sep quarter had hidden ‘bombshell’: “a $4.1 billion loss from its equity-method investment in OpenAI”:
https://open.substack.com/pub/appeconomyinsights/p/microsoft-openais-wild-ride
And Boomer Bill Bonner takes the longer view:
https://open.substack.com/pub/bonnerprivateresearch/p/the-astonishing-ai-boom
With yearly release cadence for GPUs / TPUs / NPUs and a ~2.5x FLOP improvement/ watt per generation, with effective FLOPs (‘eFLOPs’) per FLOP up ~3x p.a. from algorithmic improvement and at least (maybe much more than) 1.35x p.a. from system architect optimisations (‘unhobbling’), and with inference/ eFLOP pegged at a ~2.5x increase p.a.; were currently looking at up to 25x inference/ watt/ p.a. increases.
With power usage doing 1.6x-2x p.a., overall that’s a 40x-50x inference p.a. increase.
The 40 fold figure is likely the source of Sam Altman’s claim of a 97.5% annual cost reduction for inference.
If demand for intelligence (or at least inference) is infinite and insatiable, then Jevon’s paradox reigns supreme, and picks and shovels plays will boom.
If it doesn’t though, then IMO the scenario looks similar to the Canadian cannabis industry post legalisation, where an irrational bubble in listed grower stocks met a massive oversupply in production, crashing wholesale prices, and resulting in escalating and ruinous losses:
https://open.substack.com/pub/stocksandstones/p/my-most-comprehensive-cannabis-update
If the second situation (i.e. no Jevons’ paradox) applies, then sitting out is the only winning move.
Otherwise, if it’s Jevons’ paradox all the way down on inference costs, then there’s no alternative but to stay invested in the AI game.
A brilliant comment from @David Friedman over in Substack notes about an hour ago now:
” ‘AI is a bubble.’
OK, but define what you mean.
There are at least six bubbles you might mean:
Valuation Bubble: Public equities and venture valuations priced for impossible growth. The criticism here is financial. Multiples and TAM assumptions detached from plausible cash-flow timelines.
Capital-Allocation Bubble: Over-investment in fixed assets (GPUs, data centers) or model training, relative to likely downstream demand. This is an asset-cycle claim: too much steel and silicon chasing too few monetizable workloads.
Narrative Bubble: Attention exceeds evidence. Journalists, founders, and investors inflate expectations to attract capital and talent. This is reflexivity at work: belief itself moves markets.
Talent/Opportunity Bubble: Too many people pivoting into AI with shallow expertise (boot camps, “agent startups,” grifters), creating a labor oversupply chasing ill-defined problems. Bubbles in career allocation are just as real as those in capital allocation.
Utility Bubble: The strongest skeptical claim: the technology’s practical impact will fall short of its theoretical promise. That inference automation, copilots, or synthetic media don’t translate to measurable productivity or profits.
Civilizational or Philosophical Bubble: The claim that AI optimism is a form of secular millenarianism, a faith-based movement promising transcendence through code. Here, “bubble” refers to metaphysical overreach, not balance sheets. Some of these strike me as more plausible than others.”
My thoughts on this are that it’s incredibly difficult, and really hard work, to try to figure out if this phenomenon of LLMs (for the moment, hybrid neuro symbolic approaches may follow) is a near term through intermediate term valuation and/or capital allocation bubble.
Honestly, I just don’t know! :(. I don’t think anyone can.
Given the promise of AGI and ASI, if ever realised (obviously disregarding the extinction risks here 🙁 ) I can’t say that it’s in a Utility bubble.
Indeed, the potential of AGI is radically underestimated in the popular consciousness: For which potential check out Forethought’s William MacAskill’s and Fin Moorhouse’s “Preparing for the intelligence explosion”, March 2025; the above referenced piece from Anton Korinek on “Valuing AGI”, April 2025; and “GATE: An Integrated Assessment Model for AI Automation”, April 2025, Erdil et al, from Epoch AI).
The economic impacts of full ASI would be more transformational than each of the agricultural, population, urban, scientific, industrial, energy and the information revolutions put together (i.e. Korinek using Erdil’s inputs in the GATE model, arrives at US GDP increasing, in a full on AGI/ASI economic singularity scenario, and in short order, by an astonishing *46 million times* (i.e. from $30 Tn p.a. ($3x10exp13), to $1.4 sextillion p.a. ($1.4x10exp21)).
Given the very high level of AI scepticism out there (it’s not exactly like Ed Zitron’s a lone voice, howling into the void, on AI hate), I doubt that there’s yet a Narrative bubble. Practically everyone else on Monevator seems to think AI is b*ll**ks, which may well be a contrarian indicator 😉
There is a Talent bubble in that there’s a pile into LLM related activity by people with low to no deep subject area experience/ expertise.
The same happened with the arm chair amateur virologists when Covid struck and, as with that, on the whole I’d expect that this inevitable but regrettable bandwagon jumping will weigh down on the pace of progress to AGI.
A bunch of intellectually johnny come lately hangers on and free riders never helps to constructively advance a suddenly popular project.
It’s very definitely a Civilisational or Philosophical Bubble. How could it be otherwise?
This goes way back beyond HAL 9000 in 1968 or Mary Shelly’s “Frankenstein; The Modern Prometheus” in 1818.
Basically this is religion dressed up as secular rationalism.
Have a read of the Robin Hanson’s “Age of Em, Work, Love and Life when Robots Rule the Earth” (2016) or Ray Kurzweil’s “the Singularity is Near, When Humans Transcend Biology” (2005) should you think otherwise.
Erratum: the Epoch AI GATE study by Erdil et al is 12 March 2025, not April 2025:
https://arxiv.org/abs/2503.04941
Korinek’s research is here:
https://www.korinek.com/research
And maybe the biggest bubble in AI isn’t financial but rather the thermodynamic/ entropy one, where data centre waste heat cooks us all 🙁 :
https://open.substack.com/pub/theclaritybriefing/p/the-thermal-wall-of-ai-when-compute
As Michael Burry issues yet another bubble klaxon (checks notes, predicted 7 of the last 2 recessions) How Money Works plays Devil’s Advocate today:
https://youtu.be/tAXKxKTGWFQ?si=SPSzAtXngufbh8yC
The ever brilliant David Friedman now has this to say:
https://open.substack.com/pub/davefriedman/p/why-the-gpu-boom-wont-burst-yet
https://substack.com/@davefriedman/note/c-172518526
Calling this one right is hard! 🙁 🙁
The $64 trillion question (or quadrillion, if the AGI / ASI accelerationists are right)…..
I still can’t work out where the 2 or 3 year GPU cycle is coming from. Nvidia is an annual releases and 2.5x FLOP/watt cycle improvements. I feel like the Captain of the Nostromo Arthur Dallas in Alien in the botched landing on LV-426 exclaiming “will someone give me a straight answer!’
Just because we use LLMs doesn’t mean we’re a technological civilisation any more than the Egyptian use of the abacus made them computer scientists (whatever that is):
https://substack.com/@aisupremacy/note/c-172633224?r=2kxl2k
NB: should have said “Nvidia is on annual releases…”, not “an annual releases” as accidentally typed.
Here’s the answer from Gemini 2.5 Flash on the current tempo of Nvidia GPU new releases:
“NVIDIA’s CEO, Jensen Huang, has recently indicated a significant acceleration, especially for their high-end Data Center and AI Accelerators.
Data Center/AI: The stated goal is to move to a one-year release cadence for their flagship AI accelerators (like the Hopper H100 successor, Blackwell B200, and future generations).
GeForce (Gaming): While the shift to an annual architecture release is confirmed for the AI chips, it’s expected to also impact the GeForce line, but historically, the new GeForce architecture has been closer to every two years (e.g., RTX 30-series launched in 2020, RTX 40-series launched in 2022).”
So, aiming for a 1 year release cycle for the cutting edge chips for AI, and at least every other year for gamers etc.
AI Capex now = Metaverse in 2022?
Is this “discretionary spending”?
And, if it ever stopped due to low / no RoI, then there’d be a big boost to the distributable FCF (and, therefore, to buybacks / divis) of the hyperscalers, which, in turn, *should* help to support their share prices.
A Capex “dilemma” but with (some) upside on the downside?:
https://open.substack.com/pub/bestanchorstocks/p/a-nuanced-view-on-the-aicapex-dilemma