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OpenAI’s biggest math result yet
Plus: Kiro expands to 132 universities
Rimsha Bhardwaj, Hasan Toor & Ihtesham Haider
September 09, 2026
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Today, we will talk about these stories:
OpenAI says AI solved Navier–Stokes
Amazon gives students a year of Kiro
Qualcomm lands a deeper AWS AI deal
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10,000 agents took on a 90-year-old math problem
Image Credits: OpenAI.
OpenAI says its internal AI system produced a proof resolving the Navier–Stokes Millennium Prize problem, open for roughly 90 years.
The scale stands out.
About 10,000 concurrent agents worked on the final effort, exchanging 2.7 million messages and generating roughly 130 billion output tokens before reaching the result after 88 hours.
The proof still needs scrutiny. What matters to me is the research process: thousands of agents explored separate approaches, shared useful intermediate work, and were redirected when one path started looking more promising.
That is a much more serious scientific workflow than asking one model a difficult question and hoping it gets the answer right.
You can picture the activity over those four days: code running, proofs being checked, groups passing results between each other.
If the mathematics holds up, how many other problems become tractable once researchers can throw this level of coordinated machine effort at them?
Amazon wants AI agents in the classroom
Image Credits: Amazon
Millions of students can now get a full year of Kiro, AWS’s AI coding agent, across 132 universities in 18 countries.
That is a big distribution move.
The offer includes 1,000 credits a month, access to current models, and Kiro Web, giving students enough room to finish real projects instead of burning through a short trial.
Amazon started with 11 universities in March.
What stands out is the timing: AWS wants students to learn agent-based software development before they arrive at their first engineering job.
A laptop open in a dorm room is now competing with the internship as a place where professional workflows get learned.
If students graduate already comfortable writing specs, reviewing generated code, and steering agents, employers may start treating those skills as basic rather than specialized.
That could change what “entry level” means.
Qualcomm wants a bigger role inside AWS
Qualcomm and Amazon are planning multiple generations of custom silicon for AWS AI inference.
The scope is broader. They are also developing optical connectivity reaching 1.6T, with Qualcomm supplying technologies that move data between machines inside large AI systems.
That part matters. Training and inference increasingly depend on how quickly thousands of chips can exchange data, so faster links can directly affect performance, power use, and cost.
You can picture rows of servers connected by fiber, moving huge amounts of data every second. For Qualcomm, this is a clear expansion beyond the phones and edge devices where most people know its chips.
AWS also gets another experienced silicon partner as it keeps designing more of its AI infrastructure around custom hardware.
How large can Qualcomm’s data center business become?
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