ASIC
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USA seems rigged against cfd trading?
Is Qualcomm actually capable of building a $15B+ data-center business, or are we underestimating Nvidia/Broadcom/hyperscaler competition?
WhiteRock Lithium Flags C$19.7m Error in Its IPO Prospectus
Diversifying out of NVDA position & putting ~10 to 20% into AVGO and MRVL?
Electro Optical Systems (EOS) potential short squeeze incoming.
$GCTS Full Breakdown as to Why I Believe Starlink or Amazon Got a Contract With GCT
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You won't need the best models... in-fact 95%+ of people don't need the best models now. Within the next few years we will see smaller models and open models get smarter and smarter. Eventually we will see ASIC's being made for specific models to run on which will make them blazing fast and extremely cheap.
Nope…Broadcom has every optical building block required for the post-copper era. What Marvell's acquisition of Lumentum changes is not that Broadcom is left without optics…it is that **Broadcom is no longer the** ***only*** **custom-ASIC vendor with captive laser fabs and end-to-end CPO.** And that’s after successful acquisition in 2028.Broadcom has every optical building block required for the post-copper era. What Marvell's acquisition of Lumentum changes is not that Broadcom is left without optics—it is that **Broadcom is no longer the** ***only*** **custom-ASIC vendor with captive laser fabs and end-to-end CPO.** And that’s after a successful acquisition and integration in 2028.
Agreed. ASIC is probably the final landing place, but we need long term stability first. What I'm talking about is more the QFN setup, with all the pieces of the hardware put to use, VRAM, RAM, NPU, SSD, etc. And then on the hardware side, unified memory (ala Strix/Mac), perhaps a faster bus path (PCI-Extra-Express?). There are just so many areas to make this better, jamming it all into wildly expensive HBM is a brute force approach to a problem that I'm nearly sure we're going to solve more elegantly in the future.
GPU is a horrible setup to run a LLM, things like cerebras chips are much much better. BUT you Cerebras is basically encoding the architecture in the chip. If you change it you need to tape out a new chip \~2 years start to finish. Shit changes way too quickly and a GPU allows you to be infinitely flexible - at the cost of speed/power. If/when things becoming more static we will see custom chips which will greatly increase the speed of outputs of llms. While you are correct ASIC is much better no one has any idea when the llm wall will be hit and things standardize. Crypto its much easier since the bitcoin protocol was static from day 1.
Burning them out isn't the major problem. The problem is that in 5 years we're likely to have an entirely different architecture that makes the Blackwell chips bought today cost prohibitive to power for the amount of revenue they can generate. We already saw this game once in crypto, once ASIC and specialized chips came out it was no longer worth mining on GPUs, it cost more in power than you could make in dollars to run them. Token prices are going to drop like a stone over the next 5 years and, IMHO, the entire architecture of these systems is wrong, shoving everything into GPU is very likely not the best way to run LLMs (it's more likely a mix of GPU, unified memory, and off device memory connected with very high speed links). Net/net, while I think the GPUs themselves will be physically fine, there's a real question if there will be anything you can do with them to drive economic value.
Depend on if the hardware company is willing to cooperate with you. Nvidia's software stack for ml model traning/inferencing/diffusion is well developed for tens of years, therefore if you do not have direct access to the chip's actual instruction set, CUDA is simply more robust against newly written models. However, for newly developed ml kernels, NVidia also need new dedicated trt-llm changes to optimize the #cycles of the kernel. Most of the ASIC companies' are customer-focused: customers provide the model they want to run, and the software stack team in the chip company will write kernels + improve compilers to support it.
The only robust VLIW system now are just Google TPU, Amazon Trainium and OAI's asic (which only needs to support OAI models). I also work at an ASIC company and I know how much pain in the ass it is to have a robust software stack that is "general" for llm inferencing, let alone training and diffusion.
You're not wrong about search revenue but the important caveat is that revenue went down but queries went up. This means that more and more people are using search, it's just that the use isn't converting to revenue. Simple explanation for this, AI overviews hasn't been monetized and people are starting to increasingly look at AI overviews and not bother with the links. So the question that should be asked is whether AI overviews monetization be as effective or more effective than classic search monetization. I'd argue that truthful, useful product placement in overviews will be better. Overviews understands what the user wants and can suggest products that are a good fit for the user..leading to better conversion. The only caveat is the cost to provide overviews and the margins of ads in overviews. I'd argue that advertisers will pay more for overview placement since the conversion rate will be superior. I'd argue that costs will go down once the models stabilize. Google will start etching models to silicon (see Frozen ASIC) and achieve insane compute density and cost efficiency. But short term? Like Q4 and 27Q1? Yeah, probably gonna be a painful ride for Google investors. Also capex won't settle down until 28Q1. On earnings call CFO said they expect capex to increase in Y28, so FCF will be even more negative.
Though let's look at events since. Asts have managed to get a dozen or so more satellites in to orbit, not even one of them with the legendary ASIC they they were selling so hard in the early days and more excuses than a cheating girlfriend. Spacex have put 600+ DTD birds in orbit, their service works, I made video calls, voice calls, used Google maps over it.. It's not great, but it's functional. So whilst ASTs has the better tech, they have no service and are about to admit to further delays. They have a nice cash runway, but a heavy burn rate, and with them being at 1/3 their ATH, further dilution is going to really hurt. ASTs could turn it around with a few lauches, but the feeling my side (I bought in at $7) is that they have huge manufacturing challenges, the fact that ASIC still hasn't made it to orbit is also very worrying. I can't help but feel that for the MNOs they are scared of musk, so ASTs is their only option at the moment, but the minute Amazon or another come along with an offering they'll drop ASTs like a hot potato (I sold 80% of my holding at $105 or so).
No one uses CRBS for training, it’s terrible at that. Amazon has their own ASIC but it sucks.
While binary options may be used in theoretical asset pricing, they are prone to [fraud](https://en.wikipedia.org/wiki/Fraud) in their applications and hence banned by regulators in many jurisdictions as a form of [gambling](https://en.wikipedia.org/wiki/Gambling).[\[4\]](https://en.wikipedia.org/wiki/Binary_option#cite_note-Globes_12-15-16-4)Many binary option outlets have been exposed as fraudulent.[\[5\]](https://en.wikipedia.org/wiki/Binary_option#cite_note-5) The U.S. [FBI](https://en.wikipedia.org/wiki/Federal_Bureau_of_Investigation) is investigating binary option scams throughout the world, and the Israeli police have tied the industry to criminal syndicates.[\[6\]](https://en.wikipedia.org/wiki/Binary_option#cite_note-FBI-6)[\[7\]](https://en.wikipedia.org/wiki/Binary_option#cite_note-ToIidesofM-7)[\[8\]](https://en.wikipedia.org/wiki/Binary_option#cite_note-:1-8) The [European Securities and Markets Authority](https://en.wikipedia.org/wiki/European_Securities_and_Markets_Authority) (ESMA) has banned retail binary options trading.[\[9\]](https://en.wikipedia.org/wiki/Binary_option#cite_note-esma.europa.eu-9)[Australian Securities & Investments Commission](https://en.wikipedia.org/wiki/Australian_Securities_&_Investments_Commission)(ASIC) considers binary options as a "high-risk" and "unpredictable" investment option,[\[10\]](https://en.wikipedia.org/wiki/Binary_option#cite_note-10) and finally also banned binary options sale to retail investors in 2021.[\[11\]](https://en.wikipedia.org/wiki/Binary_option#cite_note-asic.gov.au-11) The FBI estimates that the scammers steal US$10 billion annually worldwide.[\[12\]](https://en.wikipedia.org/wiki/Binary_option#cite_note-TimesofI3417-12)
How large are your trades? If you manage a significant amount of capital and conduct the trading in a professional manner, you’re best off creating a corporate bucket company. You’ll need to outlay the money to register with the ASIC, and get a good corporate accountant, but it’s much more tax efficient. If not, then find an accountant that has experience in foreign / US trading profits. Remember the capital gains / losses need to be converted to AUD at the average spot price for the trading day they occurred on.
Nothing. Bitcoin has been mined by specialized ASIC chips for over a decade.
> But NVDA did something very smart and more or less is a feature of every megacap, they created an ecosystem that is combined software (CUDA) and hardware (the entire rack not just chip). > > AI went through it's largest development phase over the past 10 years, all on NVDA CUDA platform. That is the reason why NVDA owns the AI market - every experienced AI engineer did it on CUDA. 100% agree with you and more. The moat of Nvidia is not the bits and bytes of the hardware. But the CUDA software, and all the open-source software they keep developing for it. Plus, compared to ASIC they are general purpose, so they are being "positioned" as fungible. As in, they can be used for anything.
Oh, great, another fork! Let's have a few more of those and see what happens. Imagine getting paid by your employed and then having to pick which grocery store to shop at based on whether they are on the same fork as your employer. What happens when there are so many forks around that the market becomes so fractured and you have exchange rates so you can move your money from one fork to another? Sounds like what we have now with extra steps and more harm to the environment. I am going to leave this aside, because I want to keep the conversation serious. The owner class are all in bed with each other. "The US" won't be doing it alone. It will be US tech oligarchs, Russian oligarchs, Saudis, you name it. You know, the usual power actually shaping the game rules in their favor. Sure, ASIC production is going to limit them, but they can control it to their favor like they are already trying to do for building data centers. How long do you think it would take for them to make their own "fork" in which you will have to be if you want your money to be worth anything? Half a decade? Maybe 1 decade tops?
Broadcom kind of screwed because there are very few customers where a custom ASIC program makes sense. I own AVGO (4% of portfolio), but it's not one of my highest conviction stocks.
Because it’s artificial. In that, RAM, GPUs, and other components are being set aside to get these data centers up and running. Also, see RAM producer collusion. I honestly wouldn’t be surprised if in 2 years we had an equivalent of ASIC chips for AI, making the GPUs NVDA is making currently obsolete before their contracts with these centers are up.
He's kinda pissed at the market because they doubled revenue and net profit this year with their ASIC ironwood and tomahawk chips, but the market hasn't really rewarded them at all - share price is literally flat on the year. So staff RSUs are in the toilet. So yeah, he's gonna take some jabs at the market, and if it takes down some other frothy AI plays, then so be it: the staff at a minimum don't want to see others being overly rewarded.
rotation back into ASIC
For some companies earlier. Look at Maia 300 announcement. Microsoft plans spending most of capex on their own chips for inference So now the loop is following: MSFT has products which are channel for monetization (windows, ai laptops, office365, LinkedIn, azure tools, nav etc.) they use their own chips, they use own/open models or licensed openai models - they don't need to buy GPUs. They don't need to do anything. This rally could end for amd and Nvidia sooner than hyperscalers cut costs, money will flow elsewhere if ASIC are better than vera rubin economics. I think investors are greedy and won't escape pick and shovel trade. Many ai skeptics don't believe ai will be a success. They just wanted to grab easy money seeing billions are spent. But in a decade winners will be hyperscalers (huge existing moat and fcf + ai as side business) + energy suppliers as it's crucial and China is so ahead. Any dip in companies like vst or ceg will print life changing returns in 20 years horizon
Hardware efficiency (GPUs, memory bandwidth, ASIC chips) only matters when an attacker is forced to brute-force the lock by guessing combinations. If an AI or mathematician proves that ECDSA can be broken in polynomial time (a mathematical shortcut), the attacker no longer has to guess
I own Nvidia. Risk I see is the continued rise of ASIC from the big tech hyperscalers. Their internal workloads will keep shifting to their own ASIC chip, but I keep an eye on how much the cloud customers and such will want to use the ASIC over Nvidia. I'm still a holder though.
I'm a pussy and don't actually gamble so take that for what it's worth But you know, you just sell and put it into VOO Stonks only go up but not all of them and not all of the time and not forever, you had a wild run, time to move to a safer allocation That way if AI boom continues you'll still profit on all fronts (Mag7, lab IPOs, memory, optics) and you're protected from NVDA risk factors (AMD/Intel somehow catch up, everyone diversifies into their own TPU/ASIC, Jensen specifically is found to have done some light fraud, new tech makes inference drastically cheaper, etc.)
No they are fabless and to quote todays results announcement… ‘EnSilica is now Europe's largest independent commercial fabless ASIC company and one of only four European members of the TSMC Design Centre Alliance, giving us a direct path from advanced-node design to volume supply and, with our growing re-usable IP portfolio, the credibility to win against far larger competitors.’ As well as TSMC who have foundries around the world, EnSilica also work with other firms such as X-FAB, GlobalFoundries and SK Foundry amongst others I believe.
Once frontier models hit a point of diminishing returns we'll see open weight models catch up a couple years later, alongside ASIC chips to run inference extremely cheaply.
NVDA makes largely standardized GPU's, AMD makes CPU's, Broadcom is mainly selling infrastructure software and ASIC's. While there is some overlap, I don't think all of the are necessarily competing in the way wall st makes it sound.
1. slop 2. the network / package trade is well known; see NVLink and others that I already know too little about 3. imo nvda's advantage is that it's not manufacturing inference ASIC's and that its compute is valuable for other things, with a competitive "enough" FLOPs / throughput per watt on inference workloads. Bear case is that inference will outgrow these "other things" by orders of magnitudes and sidelining NVidia's importance to the AI / ML ecosystem
We're still probably closer to FTL travel than AGI. The amount of power and processing AGI would need, mainstream quantum computing will be needed at least. Jenson knows that quantum is a prerequisite of AGI, hence why he shits on it all the time. It will ruin apu/gpu/ASIC companies. But we're still 10+ years from stable, scalable deployments of Quantum computing
Do you still like TSM? I think it's one of the safer AI plays out there. Whether it's ASIC's or GPU's TSM wins either way. I've been buying anytime it goes near $400. In 2-3 years I think it can be $800+.
I’m rooting for them, and I hold a position too, but idk. I pay a lot of attention to what people wear, and Nike is being worn by few. All I see is OC, Hoka, ASIC and New Balance on people’s feet these days.
Broadcom and Marvell come with their own set of risks compared to Nvidia. Their costumer concentration is even more extreme and it's not like they can sell the ASIC's to other companies if say Google for example decides to switch vendors or even one day do the chip design in house. They are heavily reliant on retaining a small number of hypsercaler commitments. Nvidia is also heavily reliant on the hyperscalers but they have the ability to diversify their customer base (which they slowly are) in a way that Broadcom or Marvell can't.
ASIC demand is super high for the inference buildout. That’s why AVGO trades at a higher PE ratio than NVDA.
It’s baffling to say the least AVGO is a key player in AI. They have their hands in the networking side and AI ASIC design side. I don’t own them myself because I’m all in on NVDA and MSFT.
AVGO has to hit 92% yoy in ASIC and networking otherwise everything you hold dearly will be red. Aside from Netflix, the anti stock.
Nike Vomero are more comfy than any asic, hokac, new balance, or on cloud shoe I’ve tried. I own over 20 pairs of sneakers for running, walking, and daily life. I just don’t think the statement that Nike doesn’t have shoes that compete on comfort is accurate. Of course Nike Dunks or AF1 don’t compete on comfort with ASIC Nimbus tho, and that’s what I think people are comparing and is just a dumb comparison.
Robots don't all use LLM based AI. A lot of the processing is done by good old algorithms. I'm an electronics engineer. I've been in satellite development, drone development, FPGA and semiconductors. For anything that requires latency, you need something like an ASIC, FPGA or Microcontroller. You don't need a datacenter kilometers away. "AI Robots need more data centers for latency" is a dumb argument by OP. Robots will always need their hardware on their person (metaphorically). For example, IMUs used for Attitude Control by robots need kilohertz or even megahertz of polling data to correct position in a 3D space. No self respecting roboticist will build a robot that needs a datacenter to operate.
Well, rather than have general purpose hardware (memory, etc), they baked the model weights into the chip structure itself, which is a bit different than eg making an ASIC that specializes in one algorithm. That lets it run at wire speed, almost like one of the old analog computers, rather than iterating over it at the clock speed to come out with the final result. Downside is that models are changing fast, and the whole line of model specific chips would be stuck with the model they were built with for all time.
It's a totally different kind of chip, OpenAI are ASICs which are custom hardware explicitly designed for a particular workload while NVDA chips are general purpose chips. The ASIC is probably tailored for very specific LLM architectures.
That facility is a bitcoin mining center. You can’t use bitcoin miners for AI, they’re specific ASIC chipsets that can only run specific calculations that only work for bitcoin, they literally can process nothing else. They’re also lower in power, 30MW for AI would be like a 10K sqft building. This thing is MASSIVE for its power consumption, which means it’s crap tons of low energy devices, the only thing that fits that footprint is ASIC miners.
This is why I'm glad I'm diversified and hold both: Marvell (2% of portfolio) & Broadcom (4%) It's so easy for hyperscalers to choose who they want for a custom ASIC program.
too many hobbyist miners running an ASIC in their basement, spread all over the world. good luck to mr. state actor. gonna cost him billions just to try. perhaps he overrides a single block. not a good investment.
ASIC ( application specific integrated circuit) miner
New models are released frequently, but flagship ones like Fable don't come along as often. If they put Fable on an ASIC, I'd wager that would be "good enough" for most development purposes for many years to come for most people. When it comes to cybersecurity on the other hand, organizations that want the latest and greatest can always subscribe to SOTA models. I have a feeling the future will be a hybrid of local hardware users and SOTA users, kind of like how we have companies that have moved all of their servers to the cloud while others remain on-prem.
Sure bro, that is why they buy up all the overflow and expose themselves to constant criticism. Its not a conspiracy when you can look up the list of fines incurred by Citadel Securities and Citadel Advisors. US regulatory fines: 1. In 2007, Citadel Securities was fined $22,500 by FINRA for failing to properly report short interest positions. 2. In 2009, Citadel Securities was fined $3 million by the SEC for allegedly engaging in improper trading practices that artificially impacted the price of securities. 3. In 2014, the US Securities and Exchange Commission (SEC) fined Citadel Securities $800,000 for allegedly violating the market access rule, which requires firms to have adequate risk controls and supervisory procedures in place when providing direct market access to customers. 4. In 2015, Citadel Securities was fined $800,000 by the SEC for violating the Market Access Rule. 5. In 2015, Citadel Securities was fined $1.5 million by FINRA for violating various rules related to trading activities. 6. In 2016, Citadel Securities was fined $3.5 million by the SEC for violating the National Market System Plan governing the consolidated data feeds that disseminate stock prices and trades to the public. 7. In 2017, Citadel Securities was fined $22.6 million by the SEC for misleading customers about the quality of its pricing and execution. 8. In 2017, the US Financial Industry Regulatory Authority (FINRA) fined Citadel Securities $1.5 million for allegedly providing inaccurate information to customers and for failing to report trades to the appropriate regulatory entities. 9. In 2018, Citadel Securities was fined $3.5 million by the SEC for failing to provide customers with accurate trade data. 10. In 2019, Citadel Securities was fined $100,000 by the Commodities Futures Trading Commission (CFTC) for exceeding speculative position limits in wheat futures. 11. In 2020, Citadel Securities was fined $97,000 by FINRA for failing to properly report certain equity trades. 12. In 2020, the US Commodities Futures Trading Commission (CFTC) fined Citadel Securities $700,000 for allegedly violating swap data reporting requirements. 13. In 2021, Citadel Securities was fined $700,000 by FINRA for failing to report a significant number of trades to FINRA's Trade Reporting and Compliance Engine (TRACE). International regulatory fines: 14. In 2017, the European Securities and Markets Authority (ESMA) fined Citadel Securities €1.1 million for breaching market-making obligations and engaging in algo-trading activity that may have contributed to market disorder. 15. In 2017, the Autorité des marchés financiers (AMF) in France fined Citadel Securities €5 million for allegedly manipulating French government bond futures. 16. In 2018, Citadel Securities was fined €1.6 million by the Italian securities regulator (CONSOB) for market manipulation and insider trading in the Italian government bond market. 18. In 2018, the Australian Securities and Investments Commission (ASIC) fined Citadel Securities AUD 360,000 for alleged trading violations related to market integrity. 19. In 2018, the Monetary Authority of Singapore (MAS) fined Citadel Securities $230,000 for market manipulation related to its trading activities on the Singapore Exchange (SGX). 20. In 2020, the French financial regulator, Autorité des marchés financiers (AMF), fined Citadel Securities €2 million for allegedly manipulating the bond market and breaching its best execution obligations. 21. In 2020, the UK's Prudential Regulation Authority (PRA) fined Citadel Securities £1.2 million for failing to provide accurate and timely transaction reports to the regulator. 22. In 2020, the Swiss financial regulator, Swiss Financial Market Supervisory Authority (FINMA), fined Citadel Securities CHF 1.12 million for violating trading rules and engaging in market manipulation on the SIX Swiss Exchange. 23. In 2020, Citadel Securities was fined £1,445,000 by the UK Financial Conduct Authority (FCA) for inaccurate transaction reporting and failing to take reasonable care to organize and control its affairs responsibly and effectively. 24. In 2021, the UK's Financial Conduct Authority (FCA) fined Citadel Securities £1.4 million for failing to adequately report certain trades to the regulator. 25. In 2021, Citadel Securities was fined $97,000,000 in China for alleged "malicious" short-selling practices. 26. In 2021, the Korea Financial Investment Association (KFIA) reportedly fined Citadel Securities 175 million won ($155,000) for allegedly engaging in high-frequency trading activities that violated local laws. 27. In 2022, Citadel Advisors LLC was fined $20,000 by the New York Mercantile Exchange (NYMEX) for violating position-limit rules involving November 2021 Henry Hub natural-gas contracts. NYMEX found that Citadel held 2,365 short contracts—365 above the standard 2,000-contract limit—and lost the benefit of a conditional limit when it established a position in the underlying Henry Hub Natural Gas futures contract. The settlement became effective September 12, 2022; Citadel neither admitted nor denied the rule violation. 28. In 2023, South Korean regulators imposed approximately ₩12.98 billion in penalties—about $10.55 million at the time—on Citadel Securities (Hong Kong) Limited. This consisted of ₩11.88 billion, roughly $9.66 million, relating to findings that its high-frequency algorithmic trading disrupted the Korean stock market, plus approximately ₩1.1 billion, roughly $890,000, relating to short-sale violations. Reuters reported the principal ₩11.88 billion sanction in January 2023. Citadel disputed the market-disruption findings and appealed them; its current FINRA BrokerCheck affiliate disclosure reports that portion as “On Appeal,” while stating that the firm did not contest the short-sale findings. 29. In 2023, the SEC fined Citadel Securities $7 million for violations of Regulation SHO's order-marking requirements. The SEC estimated that over a five-year period Citadel incorrectly marked millions of orders, including short sales marked as long and long sales marked as short, because of a coding error in its automated trading system. The inaccurate information was also transmitted to regulators. Citadel accepted a censure, cease-and-desist order, $7 million penalty and remedial undertakings without admitting or denying the findings. 30. In 2024, FINRA fined Citadel Securities $1 million for widespread Consolidated Audit Trail (CAT) reporting violations. FINRA found that from June 2020 through August 2024 the firm failed to timely or accurately report tens of billions of equity and options order events to the CAT Central Repository, involving numerous different types of reporting errors. Citadel was censured and fined $1 million in an October 9, 2024 AWC. Nothing to see here folks, were just not good enough to cheat enough for it not to even matter when you get caught.
I'm not one for hyperbole, but Lisa Su will literally have a fucking picnic on the graves of her competitors. Current monolithic chip designs will max out, pushing design towards low friction networks of heterogeneous compute architecture (CPU + GPU + FPGA + custom ASIC). The world economy is leaning on dreams about the taste of theoretical AI fruit, and the fabled tree grows out of hardware. Hardware scaling is a prime motivator, our power grids are maxed out, we are cranking out and stockpiling hardware that we can't even use, we have to because it could theoretically be super valuable and we as humans can't fucking help ourselves. The further expansion, I think, will be in the form of more efficient chip/server architecture as a proxy for more energy (trading complexity of manufacturing/organization for both grid buildout time and literal electricity generation/delivery), likely a shift to photonics will shift the numbers dramatically. With photonic interconnects at least we could put the copper stuff to work without losing a huge chunk of it to thermal/interference issues and signal processing, its essentially necessary past 1.6T speeds anyways (and for quantum). Google the lead time on ordering an industrial transformer, think about how many we need, now remember that lead time is using existing orders/demand estimates. I could, of course, be completely wrong, but look at Lisa and ask yourself what she would do.
Everybody knows this, they can't stop talking about Blackwell, rubin, cerebras, tenstorrent, jalapeno, TPU, GPU, ASIC, Maia, whatever Meta has, Trainium. "Hardware is the real benefactor of AI" has been the main narrative for the entirety of 2026 so far
I'm an analyst, I've been looking into this; its an accounting debate that's legitimate to question, especially for the datacentre/neocloud dynamic. Many industries in the past have gamed the system in ways that allowed them to transmute capital investment into operating expenses, effectively creating a financial engineering mechanism to keep the balance sheet clean. Airlines, telecom companies, Energy during the Enron SPV era. There's a long history of companies exploiting gaps in accounting standards, they eventually get closed, but in the interim, yes they create legitimate risk. Under modern GAAP and IFRS, the loopholes exploited in the past have been aggressively closed. Most companies cannot move finance/capital leases off their balance sheets, because if they use the majority of the economic life of an asset, there's ownership transfer, purchase or buyback options, or the asset is custom to the user (eg an ASIC), if any of these are true, it becomes a finance lease liability directly on the balance sheet of the user (eg META, MSFT), which is treated like debt. As of 2019, even operating leases have to be recorded as a ROU asset and liability on day one, making it even harder for companies to play this game. Everything I spoke about though, only applies when the assets in question are fixed. eg, If your company leases you a car for work, that's treated as though they bought it for you. It shows up as an asset that depreciates, and debt if they took any on. If, however, your company pays for car rentals, that's an expense, because you get a different car each time. As you can see, this creates a legitimate path for neoclouds/ hyperscalers to play this game once again: they commit to buying compute, but it doesn't have to come from the same silicon. That means, by current accounting regulations, they are not leasing (i.e. buying) a server, they're renting it.
OpenAI: "be careful he's got an ai chip" NVDA (brandishes Blackwell): "give me all ya Capex" CBRS: (chickling) "that's not an inference chip" (pulls out dinner-plate sized WSE-3 mega-ASIC) "*that's* a chip."