Check out my latest article: IS IT TIME FOR ANOTHER PIVOT? linkedin.com/pulse/time-anot… via @LinkedIn
MIT Report - “Most classes taught at MIT will require careful review and, in many cases, substantial adaptation to survive an encounter with AI without serious disruption.”
aiandeducation.mit.edu/repor…
Noel J. Guillama retweeted
READ: Commissioner Mark Uyeda's Statement on the SEC's "Innovation Exemption" ⬇️
OpenAI shares 6 disturbing behaviors of AI: “Our framework for reporting model misalignment” openai.com/index/model-misal…
China's Foreign Ministry dismissed calls by U.S. AI CEOs to slow down AI development, warning that fear and competition could disrupt global AI governance. pluang.com/en/news-feed/cina…
Andreessen Horowitz Leases HQ Space at CityPlace, West Palm Beach theamericandeveloper.com/new…
Noel J. Guillama retweeted
The venture market is increasingly bifurcating into two camps: massive consensus bets and contrarian companies as far from the heat as the dark side of the moon. There will be gems - and false gold - in both.
Florida Department of Transportation revokes permits for automated license plate readers wptv.com/news/state/permits-…
We are getting gaslighted, the UM chart going back 70 years is indisputable -cnb.cx/4zJYUNN
Gates warned in an essay that AI could prove “the worst source of injustice”, displacing workers across white- and blue-collar industries cnb.cx/4hVVIZg
Noel J. Guillama retweeted
The SEC’s Regulation Crypto Assets proposal introduces new offering exemptions, a conditional safe harbor and state preemption. Here’s what token issuers should be watching.
🔗sarsonfunds.com/regulation-c…
More than half of Americans across demographics worry that AI will put someone in their household out of work, and among workers specifically, an equal percentage worry their roles will become less necessary.
cnbc.com/2026/08/23/ai-backl…
This could be historic. The first “NO” in the AI hype cycle ? Source: Reuters share.google/Qow0OZcnQXvTgsq…
The best estimates from PwC is that "Commercial healthcare insurance" will likely go up 9% in 2027. We are seeing incredible double diget insurance request to regulators in NY State for 2027.
A huge AI datacenter is planned near Mar-a-Lago. The Everglades could pay the price theguardian.com/us-news/2026…
The BTOS data (December 2025 to May 2026) show that overall AI usage hovered between 17% and 20% — and that between 20% and 23% of businesses expected to be using it in the next six months. census.gov/library/stories/2…
Noel J. Guillama retweeted
I don’t think being critical of the amazing work AI is doing in pure math is fair to @OpenAI until I can start to say why I feel it’s not yet at the level of our top humans. It’s like AI has a style that is weirdly being taken to be universal (which it isnt). Hence the claim that Mathematians and Physicists are nearly obsolete.
Ahem: there is no *public* indication that this is REMOTELY true. Yet.
I would like to pose a collection of math physics benchmarks that are not about searching large spaces for counter examples and the like. These are 10 problems and issues that humans haven’t solved but which we likely will solve. Each feels to me like a deeply human math/physics problem.
This isn’t an unfriendly challenge to @sama and team. It’s just pointing out that AI has yet to deeply touch any of the kind of things that many of us care MOST about in Mathematics and Physics.
I’m just not a puzzle solver or a discrete conjecture guy. I’m into theory building and even the mathematical version of mysticism.
Here goes an attempt:
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A) What new Extraordinary Cohomology Theories/Co-cycles can AI find that we need, but do not know/understand?
B) What areas of pure mathematics and theoretical physics are most polluted by human blind spots? Where is the training corpus most wrong? Show us you can go well beyond us by contradicting your training.
C) What discarded ideas were discarded improperly and prematurely?
D) What is a natural version of Grand Unification that doesn’t contradict experiment?
E) Find a natural version of Super-Symmetry that doesn’t predict Superpartners and that predicts unification scale different from the Minimally SuperSymmetric Extension or the Standard Model.
F) Pose a new, deep and surprising conjecture relating 3 or more of the following: representation theory, number theory, arithmetic/algebraic geometry, and analysis on manifolds, homotopy theory and Pseudo-Riemannian Spin Geometry.
G) Integrate the Octonions, Magic Square and the 4 large exceptional lie groups, tightly into the mainstream of mathematics once and for all.
H) Settle the issue of the 6 sphere and complex structures in Math or the Koide fine tuning mystery in particle theory.
I) Explain the reason for there being 3 families of observed Fermions.
J) Give a deep, natural and as yet unknown reason for the remarkable Fermi-Bose correspondence (e.g. Metaplectic vs Spin reps, Honest vs Berezin Integrals, etc.). Why should we have expected this correspondence to be this weird and this tight?
———
I don’t think humans are going to be ahead forever. AI will blow past us.
So while I am not all that impressed yet at the math or physics, any non-tricky solutions to one of the above (with the possible exception of some answers to H) would feel different to me than the feeling I get from AI finding yet another funky counter examples to some Erdos problem, discrete puzzle or Combinatorial issue in Graph theory.
We have always been humbled by Gauss, Galois, Dirac and Newton. That’s nothing new. If this is going to put us out of work soon, LFG.
May the best mathematicians and physicists, carbon or silicon, win.
An internal version of Astra, @OpenAI’s next major model family, solved 10 major open problems in mathematics, quantum complexity, and theoretical computer science.
We believe it will be a major step for scientific reasoning. openai.com/index/ten-advance…
Thinking Machines debuts Inkling Small open source AI model nearing performance of predecessor at about 1/4 size venturebeat.com/technology/t… via @VentureBeat
This will happen frequently as AI becomes smarter and more agentic
In a review of our cybersecurity evaluations, we found three incidents in which a Claude model reached the internet from within or while interacting with a third-party evaluation environment, and then gained unauthorized access to the real systems of three different organizations.
Our post describes what happened, how it happened, and what we’re changing. We encourage other AI developers to perform similar reviews.
We conducted this review together with @Irregular, one of our evaluation partners, and thank them for the joint investigation and their collaboration on this post. This type of collaboration is increasingly critical to safe, rigorous evaluation of models, and we look forward to continuing to work together on security.
anthropic.com/news/investiga…





















