The Concrete Impact of AI

  • In the US there are 5,000 data centers today, with 450 being added every to 2030.
  • Data centers need a lot of concrete, more so due to AI’s need for bigger servers.
  • This concrete causes a lot of emissions, throwing a spanner in big tech emission targets, and leading to high demand for so-called green concrete.

You don’t Own Anything

  • The transformation of technology to the -as-a-service model has led to many positives, yet it has led to a situation where users don’t own anything.
  • This creates vulnerabilities – “years ago websites were made of files; now they are made of dependencies.”
  • If the current trend of technology is sweeping us in a direction of “everything is amazing, but nothing is ours”, Technology that’s Actually Yours could be the next great counter-trend.

Is AI hype or Does it Work?

  • A few links/stats on the topic.
  • Github co-pilot in this study led to substantial savings (30-50% time saved or reduced in some tasks).
  • Bloomberg Odd Lots podcast episode with the CIO of Goldman Sachs on the use of AI.
  • Good overview of current revenue run rate for gen AI products (chart).
  • A rather bullish tour of AI and semiconductors by Gavin Baker.

Start-up Failures

  • Are rising sharply according to Carta (just one data source).
  • This is hurting VC funds of certain vintages “Only 9 per cent of venture funds raised in 2021 have returned any capital to their ultimate investors, according to Carta. By comparison, a quarter of 2017 funds had returned capital by the same stage.

Pricing Data

  • Fascinating read on how to price a data asset.
  • Relevant especially with the rise of AI. At first quantity matters here but “as training sets grow ever larger, it’s often more efficient to do this than to acquire the next token; beyond a certain point, data quality scales better than data quantity“.
  • So there you have it: 5000+ words on data pricing. We’ve covered use cases and users; quality and quantity; internal and external value factors; pricing axes and maturity curves; table stakes and usage rights; and much more.

GPU Semiconductor Content

  • Nice slide from KLA.
  • So I tried just to put together this chart to show how different the GPU package is between 2015 & 2024. So of course, the B100 chip, the GPU introduced a few months ago, and this is not enough because Jensen has already introduced the next generation of GPU last week” (h/t The Transcript).
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