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Analysis: Google DeepMind has lost frontier-model momentum amid leadership and RL talent departures, with Google Cloud emerging as a winner with more compute

GCP YoY rev growth >100%, DeepMind's long term failure is Google Cloud's short term gain  —  On Wednesday, August 5th …

SemiAnalysis

Context & Ripple Effects

Google Cloud had already been winning AI customers from AWS, including several AI-focused companies, while Google’s overall compute footprint was reported at roughly a quarter of global AI compute. The new allocation makes Cloud’s capacity position more consequential as it pursues those workloads.

DeepMind’s position has shifted markedly from its post-merger profitability, with 2023 operating profit rising after the Google Brain merger. Leadership and reinforcement-learning departures now put the research organization’s frontier-model standing in tension with Cloud’s commercial growth.

First-order effects

  • Google DeepMind loses leadership and reinforcement-learning expertise at the same time its frontier-model momentum is reported to be weakening.
  • Google Cloud receives more compute capacity and pairs that supply gain with reported year-over-year revenue growth above 100%.

Second-order effects

  • Google Cloud can use the added capacity to support the AI customers it has been taking from AWS, making available compute a more central part of its competitive position.
  • AWS and Azure face a Google Cloud competitor with both an established AI-customer pipeline and additional internal compute resources, increasing pressure on their AI infrastructure offerings.

Third-order effects

  • If Alphabet continues redirecting scarce frontier-research resources toward Cloud, its AI advantage becomes more monetized through infrastructure access than concentrated within DeepMind’s model-development program.
  • The pattern points to a more integrated frontier-AI market in which cloud providers’ access to compute and talent allocation increasingly shape which labs can sustain model competition.

The trend: AI competition is increasingly being decided by how large platforms allocate compute between internal frontier labs and external cloud customers.

Discussion

  • @tzedonn Donn on x
    another semianalysis banger line after Jeff Dean's departure from Google's deepmind [image]
  • @petergostev Peter Gostev on x
    First time I'm hearing of Douglas [image]
  • @firstadopter Tae Kim on x
    YUP! SemiAnalysis: “For all intents and purposes, we believe DeepMind is no longer a frontier lab.” “due to large numbers of departures from their reinforcement learning teams and poor compute allocation. Google will continue meandering on and releasing models, but their odds
  • @zephyr_z9 @zephyr_z9 on x
    GDM getting only 15% of GCP's total compute will be extremely sad [image]
  • @jukan05 Jukan on x
    This is insane. GCP is basically a money-printing machine. No wonder Google executives are choosing GCP over Gemini. [image]
  • @s8mb Sam Bowman on x
    SemiAnalysis: Google has given up on building frontier AI and DeepMind is no longer a frontier lab. They did not believe in recursive self-improvement enough to devote scarce compute to Deepmind instead of selling it to competitors. [image]
  • @semianalysis_ @semianalysis_ on x
    Gemini is Cooked but GCP is Cooking GCP YoY rev growth >100%, DeepMind's long term failure is Google Cloud's short term gain https://newsletter.semianalysis.com/ ...
  • @firstadopter Tae Kim on x
    Good night DeepMind. Wow. FT: “Google is shifting control of its AI effort from London back to Silicon Valley” “executives and board members remained concerned by its weaker position in coding models and enterprise AI, where Anthropic and OpenAI have established an early lead.”
  • r/singularity r on reddit
    “OpenAI has overcome their pre-training issues, and a much larger model code named “Doug” is actively in the works”
  • @shakeelhashim Shakeel on x
    I mean look, maybe Gemini team is working on something great. But all I can say is that I notice lots of GDM staff constantly posting screenshots of Claude, which they're clearly using all the time, and I never see them post about using Gemini. Which says something!
  • @officiallogank Logan Kilpatrick on x
    @SemiAnalysis_ Nothing but love for SemiAnalysis, but this is such a superficial take. Gemini team is cooking, so many incredibly smart and wonderful people doing their life's work to make incredible AI models and products for the world. I could not be more bullish!
  • @haider1 Haider on x
    apparently, openai has fixed its pre-training issues and is now developing a much larger model codenamed “Doug” this would be a big deal because OAI spent years getting huge improvements from RL and post-training, and now they can combine that with pre-training scaling again [ima…
  • @carnage4life Dare Obasanjo on bluesky
    I've read a lot of criticism of Sundar with Jeff Dean leaving Google which I think is hard to agree with.  —  Any big name AI researcher is essentially guaranteed billions of dollars if they go solo.  The AGI prize of replacing workers is now clear.  —  Zuck opening the checkbook…
  • @carnage4life Dare Obasanjo on bluesky
    Google as a company both competes with Anthropic and benefits from it.  The Gemini team tries to compete with Claude while the Google Cloud team hosts Claude's API.  —  So Google has to decide if to use their datacenters to compete with Anthropic or make money from them.  —  Maki…
  • Demis Hassabis Demis Hassabis on linkedin
    I've been working towards AGI my whole life and I believe it is now close at hand.  It's critical that as a society we get the next steps right …
  • @luke_metro @luke_metro on x
    at what point does GDM start trying the MSL-style giant pay packages
  • @caseynewton Casey Newton on bluesky
    Btw regarding the claim in here that Gemini 3.5 Pro has been “silently canceled,” Google tells me that is not the case.  [embedded post]