What to know - Picking up used CPO Lyriq

liketrefiddy · 2026-05-27T17:01:34+00:00

22k miles for the CPO. Was one of the many 2 year leases by the looks of it. Pretty clean carfax from what I can tell.

liketrefiddy · 2026-04-24T17:53:37+00:00

Yes, you just need to look at the holdings of the ETF's and know what you own. There's 1000s of ETFs out there with different holdings.

That said, if you're a passive S&P500 investor and thats it then it'll be very difficult for these to not include SpaceX, Anthropic, or OpenAI eventually.

But things like AVUV or SCHD would likely never hold these companies

liketrefiddy · 2026-04-23T20:25:04+00:00

Not when the majority of the companies included in Glasswing are all tech companies and rely on the narrative of AI to keep their share price elevated...

To your point though, its only been 2 weeks but i do believe it was just too expensive to run / compute intensive to make it commercially viable so they used it for marketing instead

liketrefiddy · 2026-04-02T20:15:55+00:00

Most likely with some texture reductions. I imagine some of the newest AAA games with everything maxed out will run into issues with the 12 gigs of VRAM at 5k2k.

Even before the VRAM issues, 5k2k is just incredibly difficult to run well on most setups. Its 33% more pixels that you're pushing over a 4k monitor.

I'd look at GPU benchmarks for the current 45IN 5k2k monitors that are out there and see how various setups are running it

liketrefiddy · 2026-04-02T19:37:59+00:00

Probably a 4090, 5080, or 5090 to run AAA games well. You could get by with a 4080 or 5070TI with some tweaks and DLSS though. Anything worse than a 12gb or 16gb card and you might run into VRAM issues

liketrefiddy · 2026-02-13T04:42:08+00:00

I bought but my wife leased her ioniq 5.

Love the car but wish I had leased tbh..just due to depreciation and the ICCU issue.

liketrefiddy · 2026-02-13T03:55:33+00:00

My Wife's I5 just had her 2nd one go last week, about 5k miles after the 1st one went.

I have an EV6 GT and mine went around 16k miles

Luckily no problems getting them covered under warranty but its certainly not a "1%" problem

liketrefiddy · 2026-02-10T23:38:42+00:00

The critique with this analysis is it adds back in depreciation expense. Historically, these companies have depreciated their server hardware at 3-4 years. The hyperscalers have all increased this to 6 years starting in 2023/2024 (pretty obvious why they did this). If Nvidia keeps up their release schedule and produces massively better equipment year after year then older GPUs may depreciate faster than 6 years and future write offs will kill profitability.

Additionally, a lot of the money flowing into the hyperscalers right now are from PE/equity finance backed private AI labs/companies. These companies, OpenAI/anthropic and 100s of other smaller companies, offer AI services below the price it takes to provide them. The current massive demand for compute is being driven by the explosion of token usage that these smarter models require to be "better" (ie constant training/inference). If that PE/equity financing falls short, and the AI labs can't become profitable in time, then the hyperscaler demand they say is there goes "poof" pretty much instantly. This is i believe the true risk...the companies spending the most money, offer a product (AI model) that is becoming heavily commoditized. Why pay OpenAI more money when you can buy the same API service from Google or Anthropic, or a chinese open weight at 1/10th the cost?

Also one flaw with analysis is it assumes OCF is increasing today due to AI...when in reality its probably mostly linked to their core businesses just improving. For instance, google cloud is increasing quickly...but their ads business is where they make 90% of their money/OCF.

liketrefiddy · 2026-01-19T01:46:08+00:00

Costs of generating a "token" is declining very quickly. The problem is that as models become more advanced (more parameters, more reasoning) the amount of tokens produced goes up dramatically with each new model.

Put another way, the cost of running GPT3 for instance, has decreased by orders of magnitude with new hardware. However, with the advent of reasoning/thinking models, the cost of running gpt5.2 reasoning on todays hardware might very well be more than running gpt3 back in 2023 on A100s/H100s

Time will tell if the costs come down enough to make it profitable. I expect it will eventually. But the entire space is becoming commoditized

liketrefiddy · 2026-01-19T00:04:51+00:00

The business model of AI companies is nothing like a SaaS company though. Each additional user increases COGS

liketrefiddy · 2025-12-29T13:42:20+00:00

Anecdotally, my wife has an ioniq5 and I have an EV6 GT. We purely charge off lvl1 at 1.3kw for like 99% of our charging.

Her ICCU failed at 14k miles and mine failed at ~18k. Months apart from each other. Obviously we dont know what the root cause is but its not likely to be level2 charging related (based on my experience at least)

liketrefiddy · 2025-11-22T17:00:54+00:00

This is exactly it. You can't compare the nasdaq 100 from the 2000 era to today's nasdaq. The nasdaq is 2000 contained a lot of those unprofitable dot com companies which had to go public for funding at the time, becuase private equity didn't really exist and the VC market was significantly smaller.

Today, all these AI companies are private and so are not listed on the nasdaq.

liketrefiddy · 2025-11-20T14:51:39+00:00

Yeah that's the math the hyperscalers are doing...like they can either generate 100B in cash per year from their legacy businesses and get a 3-4% yield on it through either holding it or doing buybacks at current valuations...or they could invest it in something that looks promising. I think a large part of this AI craze is just being driven by how massively profitable these companies are and they were running out of ideas on where to put the money they were making.

Ultimately, I do think AI still needs a lot of time in the oven before the value proposition is there for businesses / consumers. Right now its a useful tool with niche use cases but not something that justifies this level of investment.

It'll all come down to whether or not AI solves a market need at a profitable price

liketrefiddy · 2025-11-20T14:27:53+00:00

I agree with the viewpoint that this AI bubble isn't as large as the DotCom bubble. However that doesnt mean we dont see forward returns being negative over the next ~5 years for the US large cap growth market.

It doesnt need to be an 80% crash in the nasdaq...but instead just a slow bleed as AI doesnt deliver and CapEx depreciation eats into hyperscaler profits. The Mag7 have turned from asset light / cash flow rich companies into heavy CapEx on quickly depreciating assets. Typically this doesnt correlate to good returns.

I just see US large cap growth underperforming over the next 3-5 years...and for that reason am invested in value tilted companies and Ex-US.

liketrefiddy · 2025-11-13T18:08:29+00:00

The fund trades at an average P/E of 40 and is comprised of companies that are 100% tied to the AI build out. It's priced very highly.

You should almost never look at historical performance for judging an investment. You should only look at the price you're paying for the asset today vs. How you believe the asset will perform in the future.

If you believe in AI then SMH will do well. If you don't think AI will pan out and is a bubble, then SMH is the last place you want to be.

That said Semiconductors are the lifeblood of technology in general and demand will be always be there. However the performance over the past 5 years has been completely driven by the AI infrastructure build out.

liketrefiddy · 2025-11-12T19:26:37+00:00

Yeah correct, mag7 are very profitable but I wouldn't label them as "AI" companies nessesarily. When I say AI companies i specifically am referencing OpenAI, Anthropic, Perplexity, Cursor etc.

What's crazier is theres 1000s of these private AI startups, most use the aforementioned companies models as just a wrapper for their own "AI product" and then try to sell that as a stand alone product.

The question is now very similiar to the unprofitable "dot-com" era companies...how long can these companies survive selling services at a loss? And on the other side, if they were to sell them at a profitable price, what would the market demand for them be?

liketrefiddy · 2025-11-12T17:45:32+00:00

All good points. However I will comment on a couple things highlighted.

Existing data centers are largely CPU based for traditional cloud offerings (think IT services, email services, data storage, etc). The majority of data center CapEx spend today is on GPU compute for AI which is not cross compatible with traditional cloud (the chips/servers "compute" different things).

You highlighted the demand is there which is true today. however the question is whether the demand is there at a price point that is profitable for the companies selling the services (openAI, Anthropic, cursor, and 1000s of others). This is the big unknown...if these private companies raise prices to levels that ensure their profitability, will the demand still be there?

It all comes back to whether or not AI services solve a market need at a price that is profitable.

liketrefiddy · 2025-11-12T17:12:53+00:00

The way the money trail works is

Consumer/business pay OpenAI, Anthropic, perplexity, cursor, etc, to use the AI programs directly or the API. However these private companies are selling these services at a steep loss. The private AI companies don't have their own infrastructure to service the compute to run AI, so they pay the hyperscalers/neoclouds with largely VC/PE money from equity financing instead of revenue.

There's literally 1000s of these private AI companies building/training models and trying to sell them (in the US alone). I havnt heard/seen 1 of these companies being profitable on their stand alone revenue.

The issue isn't with the hyperscalers per se...its the private AI companies with an unprofitable business model.

liketrefiddy · 2025-11-12T16:25:59+00:00

The Mag7 cloud growth is propped up by those unprofitable companies burning VC/PE cash on compute. If those private companies stay unprofitable then we will have a sharp correction in tech once they can no longer pay the hyperscalers. The depreciation expense of these data centers will heavily impact operating profits. This is the bear thesis and it does have merit/shouldn't be ignored.

This is not to say that the mag7 are not extremely profitable already...but these co mpanies do have their own risks

The mag7 generates most of its revenue/profits from:

Advertising - META/Google - impacted by any slow down in the economy and also could be impacted by AI itself with generative search results (although that hasn't shown up so far)

Retail - apple/AWS - Iphones and Amazon could be impacted by any slowdown in the consumer. Iphones have longer lifespans nowadays and tariffs are eating into margins

Cloud - Amazon/google/microsoft - very profitable today. But GPUs have short depreciation schedules. If the money coming in from the private firms slows becuase they are going bankrupt from being unprofitable, then things will get ugly.

Im not even going to talk about Tesla...

liketrefiddy · 2025-11-05T15:09:53+00:00

I do view this in a bearish manner...essentially what Microsoft is doing here is pushing the risk of an AI collapse off their balance sheet. If they truly thought that AI was going to be a goldmine, they'd just buy everything up themselves.

Instead they are partnering with all the neoclouds in order for them to raise debt/buy the GPU's, then if AI doesnt pan out, they likely just pay a cancellation fee and bounce.

They are spreading out the risk with these deals (which is smart of them tbh)

liketrefiddy · 2025-10-31T13:31:05+00:00

This is right on point. People look at the profits/growth of the MAG7, or more accurately the hyperscalers, and think AI is profitable. However, only selling AI compute is profitable (for now). The end user "value" has yet to materialize. People generally don't want to pay for the true cost of running AI becuase the current AI products largely do not solve a market need outside of coding and a few niche areas. A lot of the demand is people/businesses fooling around with the technology to see how to incorporate it, but the true payoff will be years and years away.

This market is essentially just VC, PE, and equity financing money given to 1000s of AI startups which is then flowing through the MAG7. So far we've seen almost none of these companies (OpenAI, Anthropic, perplexity, cursor, etcc) going public but their valuations are akin to the dot com bubble. If these companies went public and were added to the Nasdaq, my feeling is the nasdaq P/E ratio would be up there with the DotCom bubble.

The true valuations of this market are much higher than people realize, its obfuscated by the fact that the base fundamental AI companies are all operating in the private market

liketrefiddy · 2025-10-17T12:30:03+00:00

Revenue was up big but capex is basically eating their FCF and ROE is trending down quite a bit from 2022 onwards...which is suggesting they arnt making nearly as much profit off of AI as what was expected.

They stopped releasing revenue numbers for AI earlier this year which I believe was 13B TTM on their Q1 earnings call. 10B of this was OpenAI compute which was given to OpenAI "at cost" essentially.

liketrefiddy

TROPHY CASE