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Nvidia is killing itself, same as Intel, but a big difference in the current case is that the AI story is very new, and, unlike Intel was, Nvidia is not all that entrenched yet.
How is Nvidia killing itself?
1) Customer lock-in techniques can only go so far before there's a rebellion. The proprietary nature of Nvidia, results in a stifling of innovation. There's only one innovator vs potentially thousands, and Nvidia is in a conflict of interest position, it will not introduce, and will repress innovations, that go against Nvidia's best interests vs the interests of their customers.
2) Nvidia's reliance on very large monolithic dies, will increasingly become a major handicap. There's longer time to market, because reuse of previous gen concepts, have to be designed back into a new larger die, rather than packaged in as a reusable chiplet on a previous gen node (or a node that is appropriate for a specific chiplet). If a die has too many defects, it may have to be thrown out, which increases manufacturing costs, vs using smaller sized chiplets. Packaging together larger numbers of very large dies, becomes increasingly difficult, and clustering, plus scaling out, is really the only practical way to increase performance. I think Nvidia plans to package up to 4 dies for Rubin, and that may result in lots of issues causing delays, and failures after ddeployment. It works for Nvidia only inside a locked down monopoly, because customers have to replace Nvidia with Nvidia, they cannot scale out using another vendors solution.
3) Not enough supply or diversity will work against Nvidia, because it simply cannot supply enough of the growing demand, and growing demand for variable needs, such as inference, which will require a diversity of low cost solutions, including embedded solutuons.
4) Nvidia lacks great CPU technology. They tried to lock down ARM, but failed. There's no way they can buy out AMD, which leaves ARM and Intel. Intel is no longer king of CPUs, and is set to be lose its majority share inside server deployments by next year, leaving AMD with the majority. Nvidia will refuse to use AMDs solutions, due to its conflict of interest position (see item 1), and that leaves only ARM, which I belive is still only single digits in terms of market share vs x86 based servers. In addition, AMD can use x86 along with ARM for its solutions, both at the highest level inside servers, or at the lowest level inside embedded solutions. Xilinx, which is now a part of AMD, brought with it, expertise with ARM based solutions.
In summary, Nvidia has a lot of deficits, but they are rarely mentioned, likely due to conflicts various authors have. Nvidia uses clever marketing, along with shady anti-competitive tactics to retain its monopoly. The same methods Nvidia used within the gaming sector, is being used within the AI sector. They are buying out competitors, not to innovate, but to kill competitors and retain dominance, and are strong arming influencers, to give Nvidia glowing reviews, while dumping buckets of crap on top of AMD. Nvidia's methods worked well within the gaming sector, but will at some point stop working within the AI sector. AMD knows what a monopolistic looks like, and is carefully taking down Nvidia's methods, in a step by step fashion.
Next year, is when Nvidia will start to feel the pain from serious competitive actors, with AMD leading the way. Everyone, except for Nvidia and Intel, has a reason to join AMD as a partner, using open solutions that resolve each of the negative items that Nvidia has brought to the AI industry.

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