Small nitpick: the models probably make some money on actual inference. Might not be a massive amount, but hard to see them not having a positive contribution margin purely on inference.
What's losing OpenAI money is paying for the whole of R&D, including training and staff. Microsoft doesn't pay that, so they get the money making part of AI without the associated costs.
It's unclear. That was never disclosed. It's similarly unclear what it means that they will no longer pay revenue share to OpenAI. Do they get the models for free now? How does OpenAI make money from the models hosted on Azure if not via revenue share?
It's kind of shocking, given financial transparency, that Microsoft gets away with not disclosing any details of this agreement (or the one it is replacing) to its shareholders. We know there's a cap on the revenue share from OpenAI to Microsoft, but we have no idea what that cap is (not whether it's higher, lower, or unchanged from the prior agreement).
We have no idea what it means to be the "primary cloud provider" and have the products made available "first on Azure". Does MSFT have new models exclusively for days, weeks, months, or years?
Both facts and more details from the agreement are quite frankly highly relevant to judge whether this is a net positive, negative or neutral for MSFT. It's unbelievable that the SEC doesn't force MSFT to publish at least an economic summary of the deal.
We updated our analysis of Meta's AI infrastructure spending after yesterday's Q4 call. Some specifics from the earnings call on where the money is going:
Ad models: They doubled the GPU cluster training their main ads ranking model. The architecture now reportedly "scales with similar efficiency as LLMs." They also consolidated multiple models into fewer, more capable ones (12% increase in ads quality) and moved their ads retrieval engine across NVIDIA, AMD, and custom MTIA chips, nearly tripling compute efficiency.
Internal tools: Management cited a 30% increase in output per engineer since early 2025, mostly from agentic coding tools. Power users saw 80% gains.
Ad products: Video generation tools hit a $10B combined revenue run rate. Incremental attribution drove a 24% lift in conversions.
On the financial side: Q4 ad revenue was $58.1B (+24% YoY). FY25 FCF was $43.5B, a 22% margin, down from 32% in FY24. They paused buybacks and signaled they may take on net debt. Management committed to FY26 operating income above FY25 in absolute terms against $162-169B in guided expenses.
For context, Meta's 2025 capex alone roughly equals the total lifetime investment in Reality Labs over 10+ years.
The article covers the full AI model stack (GEM, Lattice, Andromeda), capital intensity breakdown, and peer comparison.
This is primarily a story of a failure to supervise the creation of the report, rather than anything related to AI.
The role of the outsourced consultancy in such a project is to make sure the findings withstand public scrutiny. They clearly failed on this. It's quite shocking that the only consequence is a partial refund rather than a review of any current and future engagements with the consultancy due to poor performance.
There shouldn't be a meaningful difference if the error in the report is minor or consequential for the finding, or if it is introduced by poorly used AI or a caffeinated up consultant in a late-night session.
To expand on the overlooked point: it gives you a DB and a programming environment (however challenged) that you can use without needing sign-off from IT. In any moderately sizeable organization, getting approval to use anything but standard software is slow and painful.
Nobody wants to explain to IT that they need to install Python on their machine, or drivers for sqlite, or - god forbid - get a proper database. Because that requires sign-off from several people, a proper justification, and so on.
What's losing OpenAI money is paying for the whole of R&D, including training and staff. Microsoft doesn't pay that, so they get the money making part of AI without the associated costs.