| ▲ | xnx 2 hours ago |
| > Nobody has a moat. Custom hardware, data centers, huge cash reserves, deep/broad talent pool, and non-AI customer base are all huge advantages if not moats. Google, Microsoft, or Amazon are more likely to be the AI leaders than OpenAI or Anthropic. |
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| ▲ | dmix 8 minutes ago | parent | next [-] |
| The technical crowd will always overvalue the recent technical advantage of software over the available customer base and business model math. |
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| ▲ | woah an hour ago | parent | prev | next [-] |
| > Google, Microsoft, or Amazon are more likely to be the AI leaders than OpenAI or Anthropic. If not now, then when will these companies be AI leaders? Even Google, with its staggering advantages in cash, compute, real estate, training data, and having basically invented the field only manages to briefly claim a 1-2 week lead once or twice a year. |
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| ▲ | koe123 an hour ago | parent [-] | | The financials for Anthropic and OpenAI are likely borderline suicidal, google and co are publicly traded. Moreover, all innovations downstream to them dont they? Why not just stay slightly behind, especially given many have stake in those other companies? | | |
| ▲ | lossyalgo 22 minutes ago | parent [-] | | Microsoft owns 51% of OpenAI, so they just have to wait for them go bankrupt then they come in and clean house. |
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| ▲ | bluGill an hour ago | parent | prev | next [-] |
| There are many companies that have data centers. They are conceptually easy to build. An ASIC is difficult enough that if you make one someone will leapfrog you while you are still making it (at least so far), though once you have one your costs will be enough lower than the competition that you can perhaps undercut them. |
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| ▲ | xnx an hour ago | parent [-] | | True, but have other hyperscalers caught up to Google's AI data centers?: fully liquid cooled, torus networking(?), 100,000+ TPUs interconnected, etc. Google is already on gen 8 of its TPUs and is certainly already working on the next version or two. |
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| ▲ | IX-103 2 hours ago | parent | prev | next [-] |
| If Moore's law continues, then in less than 10 years today's state of the art model will be able to run on a cell phone. How much smarter do we actually need AI to be? Would it still require datacenters and custom hardware? |
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| ▲ | xnx an hour ago | parent | next [-] | | Moore's law stalled ~2015. Unfortunately, no way current models will run on the <100W thermal budget of a cell phone. Printing the weights directly into a chip would help efficiency a lot, but not enough. | | |
| ▲ | CuriouslyC 44 minutes ago | parent | next [-] | | In all likelihood in a few years we'll get ~200-400bA~4-6 MoE models that are on chip, and they'll be better than the current frontier. | |
| ▲ | spacebanana7 23 minutes ago | parent | prev [-] | | Is it conceivable that in 10 years time we’ll have 7B models that have the same level performance as modern frontier ones? |
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| ▲ | LightBug1 an hour ago | parent | prev [-] | | They probably said the same thing about social media back in the day. I'm sure the thinking out there, and hence investment, is all about how to tether the user to the most addictive, network-effected, incredibly deep, server-side, moat-able version of AI possible. |
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| ▲ | junehwi 2 hours ago | parent | prev [-] |
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