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Threat to competition, “explosive” AI, OpenAI’s income from subscriptions, and the $600 billion question — the top 4 AI news stories of the week

Our latest AI Digest covers the biggest breaking AI news for the week. Anywhere Club community leader, Aliaksei Kartynnik, comments on key stories.

Anywhere Club community leader, Aliaksei Kartynnik

Published in AI18 July 20242 min read

#1 — AI competition is safe for now

Microsoft invested $13 billion and joined the OpenAI board as an observer — following developments and communicating with top OpenAI management without voting rights. EU and US antitrust authorities expressed concerns that the Microsoft–OpenAI partnership was inhibiting AI market competition because of the control that these two companies exert in the AI industry. Microsoft withdrew from the OpenAI board of directors, and Apple, which was planning to join, declined to do so. For now, challenges remain, but so does competition.

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#2 — AI will “explode” the world of science

OpenAI and the Los Alamos National Laboratory will work together to study how to safely use genAI for biological research in a physical laboratory setting — for things such as cell cultivation, data analysis, and sample preparation. The Los Alamos lab is involved in providing scientific and engineering support for the US nuclear weapons stockpile. Internet users have already joked that such collaboration will be a “bomb.”

#3 — Has anyone heard of ChatGPT Team?

According to Futuresearch.ai, OpenAI’s annual recuring revenue — income from customer subscriptions — is estimated at $3.4 billion. The sources are as follows:

  • 55% ($1.9 billion) – from 7.7 million ChatGPT Plus subscribers;
  • 21% ($714 million) - from 1.2 million ChatGPT Enterprise subscribers;
  • 15% ($510 million) – from OpenAI API users; and
  • 8% ($290 million) – from 980,000 ChatGPT Team users.

The last one is surprising: who uses this ChatGPT Team? Is it useful at all?

#4 — The AI bubble is growing

Sequoia Capital released an article titled “AI’s $600B Question” about the "AI bubble" — focusing on the gap between the AI revenue expectations based on AI infrastructure and actual revenue growth. Half a year ago, to cover the costs of Nvidia GPUs, $200 billion in revenue was needed. Now, it’s $600 billion. How to turn AI into mass market products is still unclear. For now, there are no signs of a reduction in the gap between costs and profits. However, it gives food for thought.

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