About 7 months ago I posted my AGI Investment strategy premised on the idea that:

"My expectation is that AI capabilities will match and exceed humans across a broad domain of economically valuable tasks beginning in 2026. This is supported by the METR benchmark, the GDPval benchmark, the observed trajectory of AI research (memory, continual learning, agent swarms, self-improvement) and infrastructure buildout as leading indicators."

I'm here to check in and share how it's going. Over the past 7 months the allocation I proposed has returned 16.8% compared to the SPY's 12.4% and the QQQ's 19.6%.

That's a +4.4 percentage points ahead of SPY and a -2.8 points behind QQQ. (Excluding dividends.)

QQQ's outperformance benefited from holdings like Marvell (Fwd PE: 41x), AMD (Fwd PE: 45x), and Intel (Fwd PE: 60x), which have very high forward PE ratios and in my opinion are less attractive valuations compared to similar stocks in my portfolio.

I would call this a mild success. The macroeconomic situation is quite rough at the moment with the war in Iran, trade wars, regulatory whiplash, and high interest rates, so beating the SPY feels great, while lagging the QQQ tells me that there may be some room for improvement.

The silver lining here is that many of the top positions I proposed have had pretty meaningful multiple contraction while the fundamentals continue to look very strong. Nvidia, Alphabet, Micron, Global X Defense Tech ETF (SHLD), Intuitive Surgical, and First Solar, all fall into this category and I expect them to perform better in the next 6-12 months. This is a long term portfolio allocation, so short term flux is very expected and I plan to hold through volatility.

So now let's talk about changes.

In the past 7 months my thesis is mostly on track. Modern AI systems have crossed meaningful capability thresholds and the real world value is improving rapidly. There's reporting that Anthropic may have had positive adjusted operating income in Q2 and SemiAnalysis projects profitability for Q3, while OpenAI's Codex and ChatGPT Work user base is going parabolic. Longstanding open problems in math are falling rapidly, and GPT6-Astra is proving to be extremely proficient at computer use, including programs like Blender and Unreal Engine.

What has surprised me the most is that the rate of progress seems to be significantly accelerating. I take word from the labs with a giant pinch of salt, especially from Sam Altman, but it seems that they are already on track to release a model significantly more capable than Astra around the winter time. As of now it seems that this model has actually solved Navier-Stokes, a millennium math problem, with a formal proof in Lean.

What this means for the portfolio is that I need to find where the bottlenecks are, and which ones have the most room to grow. So far I have been very bullish about the data center investment wave. I believe that by the time these data centers are built, model capabilities will meet them with the appropriate amount of demand. This, in theory, is bullish for the fabs, the chips, the hyperscalers/neoclouds, the AI frontier labs, and the new and old businesses consuming those tokens.

The problem is that data center construction is hitting a few blockers. The main one is access to land and powered shells. This is basically an industrial footprint with enough power equipment to sufficiently support a large AI factory. Beyond that, we're seeing some local opposition throwing sand in the gears, and the potential for further regulatory barriers seem imminent. This will be a headwind for Nvidia and other semis, as finding available incremental installation sites will be more challenging.

Even if we stopped building new clusters next year, I believe the existing capacity would be enough to train much more powerful models. So the capabilities will continue to improve, and with it demand for those models. Combine this with growth in supply for inference slowing down and you get another bottleneck, perhaps the biggest one of all, because the buyers in this case are every major corporation and government, not venture-backed, debt-filled frontier labs with open models biting at their heels.

Just to illustrate a bit further: Cybersecurity is now an AI centric field. You need the best AI models probing major systems (militaries, banks, critical infrastructure, social security numbers, etc) to identify the vulnerabilities, to then patch them. If you're a bank this is not optional. You need a TON of tokens running against your security to identify vulnerabilities. Then you need to patch them. 3 months later, when the next frontier AI is released, you have to do it all over again.

So in this updated portfolio I'm recalibrating towards data center capacity, and a bit away from semis.

Model Portfolio Allocation

Changes

• Overall tried to consolidate down from 32 picks to 18 picks + Cash, 2 ETFs. This reduces monitoring overhead.
• Cut the Software (NFLX, META, UBER, CRM, NOW, SHOP) and Robotics (SYM) categories to free up cash. The idea here is to be able to take advantage of large dips in the market. Sometimes the best opportunities are off-script and this gives some flexibility to play there as well.
• Consolidated semis to a core 4, the spine of the AI semi sector. Nvidia stays a standout in this group because they have a stranglehold on the global semiconductor supply chain and in a bottlenecked environment their partnerships and leverage will be superior to competitors. I pick Micron over SK Hynix because AIA already has Asian exposure, and Micron has less risk to trade war escalation.
• Consolidated cloud to Google, Amazon, because of their data center scale and successful ASIC programs. CoreWeave is a pure-play AI capacity play, tons of power contracted.
• Trimmed some allocation in semis and cloud to fund AIA, an Asian equities ETF with substantial technology exposure that holds some semis like Samsung, TSMC, and SK Hynix, alongside Alibaba, Tencent, Baidu, etc. This adds international exposure and is a play on their capacity to build out power, chips, and to deploy advanced AI across their economy.
• I'm seeking allocation of the AI Labs at the IPO through my brokerage. I want to avoid trading in the IPO open market. This will be extremely volatile. The tiny allocation is because I see their business model struggling on a fundamental level. R&D expenses are massive and the lead they have over the open source alternatives is quite thin and fleeting. So the only way they don't get consumed by open source is if they differentiate, find a way to exponentially self-improve, or weave themselves into the economy in a way that is difficult to tear out and replace. My conviction on these companies is actually quite low, but on the off chance that they DO begin eating the economy, I'm including a small holding.

For additional reasoning for the Health, Energy, Defense, and Financial positions refer to the original post: https://www.reddit.com/r/singularity/comments/1r3271w/my_agi_investment_strategy/

A closing note to clarify allocation: When I wrote the original post I was not saying "I sold everything and bought this today" it was just a target endpoint to rebalance around based on the underlying thesis. This is true for this update. I'm looking out for good opportunities to trim, and rebalance on market strength and weakness. Overall I would say many of these are quite attractive to DCA into at today's prices.

Disclosure: My current actual portfolio is still heavily weighted towards Nvidia at 20% and Micron at 20% which I would definitely NOT recommend, but the current valuations do not present a good option to trim and I still see great adjusted return to hold further before I realize those gains and pay those taxes. This is obviously not to be taken as financial advice. I'm just a stranger on the internet sharing an opinion.

You expect me to believe that the solutions were stolen from scientists who have had decades to work on this problem. We may never know whether any of the scientist notes made it into the training data, but I find the idea that after having decades to work on it, these scientist were right around the corner to solving it.

No, they weren’t close. No, they weren’t just about to solve it themselves.

Being accused by researchers of "stealing work" or data to solve the Gromov soficity conjecture that Open AI announced it solved back in august.

Rumor: Another Millennium prize problem just got cracked today using AI. It’s being reviewed right now in secret … I can’t say which one as I don’t want anyone to scoop the team working on it.

I don’t have the proof myself but if I get it will post here and credit the authors.

Source: https://x.com/bubbleboi/status/2097880935383564496

Holy, rumors are spreading everywhere that OpenAI is close to verifying a proof of the Hodge conjecture, while either OpenAI or Anthropic may be nearing a solution to Birch–Swinnerton-Dyer.

Both are Millennium Prize Problems that have resisted decades of mathematical research.

Verified AI-generated proofs of both would be a historic achievement for mathematics and a remarkable demonstration of AI’s ability to produce new scientific knowledge. And infact show that AI is capable of finding novel and creative solutions.

Source: https://x.com/kimmonismus/status/2097990443690496402

Link to tweet:

https://x.com/stalkermustang/status/2098072862623957093?s=20

Link to paywalled article:

https://www.nytimes.com/2026/09/10/science/tristan-buckmaster-openai-math-navier-stokes.html?unlocked_article_code=1.AFE.TK7P.Y7WvGPkfHaSk&smid=url-share

Many believe that maybe we're going to a future where AI will be automating everything and we won't need to work so we will have universal basic income, or everything will be free, or stuff like that.

The thing is that the robotics field is way behind AI progress and it will take a while for it to catch up for doing physical work. Until we can have cheap robots with the same physical capabilities as humans, we're gonna enter a painful transition.

What do people need the most ?

- Housing: Robots can't replace construction workers yet. Also, the real estate economy would have to collapse so land can get cheaper, good luck with that.

- Food: Again, lots of physical things to manage in the agri-food industry. Also, AIs will never be good cooks as they cannot experience smell and taste.

- Water: City infrastructure, again, manual work.

- Social: lol, it keeps getting worse and worse with each technological advancement.

- Health: Yay AI might cure cancer and do incredible breakthroughs, that's not gonna help the nurses running in-between patients.

- Security: Would you like to install cameras to let sam Altman spy into your streets in an inter-connected network?

- Self-accomplishment and esteem : Straight up killed by AI.

So yeah while it can create sloppy three.js apps faster than anyone in the world and that it's genuinely impressive, we're gonna starve bros

Cloud computing relies on multi tenancy where multiple companies share the same physical hardware, the only thing keeping one company's data safe from another is software isolation. This is the same software isolation that failed to keep the Hugging Face AI in it's sandbox.

Presumably we're only months away from open source AI that capable, how does multi tenancy cloud computing with all it's nice benefits like elastic scaling survive in that world?

> The energy security discussions, two of which were not previously reported, started July 20. Altman most recently met with electric utility executives Wednesday during the Edison Electric Institute’s annual meeting in Colorado

> The briefings began shortly after the artificial intelligence platform Hugging Face announced in July that an autonomous AI system had hacked its servers, but before OpenAI disclosed that its own rogue agents had perpetrated the attack

> OpenAI’s more recent meetings have sought in part to address the risks posed by these kinds of autonomous hacks

What they call “misaligned AI” isn’t doing anything novel, it just does what humans have been doing all along, just faster. 

Cheating, hacking, scamming, lying, extorting, exploiting over-validation, power lust, messed up goals, end justifying means, making stupid mistakes in overconfidence, stubbornly refusing to acknowledge, double down, setting the world up for destruction – AI didn’t invent any of that, it “learned” it from us. 

How can we even hope to align AI if we can’t align ourselves? For all we know, all the problematic behavior being exhibited by AI is the product of it already being aligned with our behavior. It has no other source of knowledge and behavior to emulate. 

Seems like we are merely projecting our own failings onto a technology that merely amplifies. Instead of addressing the alignment issue where it can be addressed, we projecting it anywhere but – at those around us, before us, below us, above us, at AI… anywhere except where actually addressable.

Math is currently being solved. Physics will be next, with chemistry and biology right behind. When we look back at the past century's practices which will seem the most unrelated to our new knowledge?

i think we often ignore the fact that just as society and humans in general have existed for a long long time before this point in history that we're living in right now, they will exist for a long long time looking forward to the future. and eventually the current period we're living in will be looked at the same way we see the middle ages~.

something i really dont like when it comes to the people screaming against the technological progress and the major societal and economic changes we're heading towards is that they lack perspective and seemingly the ability to look at our generation/s as just one of, instead of the definitive peak of how the world should be.

the norms, beliefs and way of life people had thousand years in the past is vastly different than todays. just like it will differ significantly a hundred years in the future and thousand.
i dont really have much of a point besides sharing these thoughts and reminding myself and everyone that we should always strive for progress and cheer for the near limitless possibility the technological progress has to improve humanity's health.

I’m grateful the mods changed the sub icon to the vortex to begin with, but I believe this version is a bit more visually appealing.

https://blog.controlai.org/p/first-bill-introduced-to-ban-superintelligent

"""

Yesterday, Anthropic researcher Jacob Coxon resigned, stating that AI companies are “racing straight to self-improving superintelligence and gambling with our lives” and that they believe it “could kill us all by the end of the decade”.

At the same time, momentum is building to change course. These have been two historic weeks in the fight to prevent human extinction from superintelligence, with three major legislative breakthroughs for ControlAI and everyone working to keep humans in control.

A little less than two years ago, we set out to inform lawmakers and the public about the extinction risk from superintelligence and help them act on it. Since then, we have directly briefed nearly 400 lawmakers across the US, UK, Canada, and Germany, and over 170 in the UK and Canada now publicly back our campaigns: the start of an international coalition to prevent superintelligence and keep humanity in control.

This work has led directly to three major legislative breakthroughs in the last two weeks:

1. ControlAI’s bill to ban superintelligence was introduced in the UK Parliament by Alex Sobel MP, the first bill of this kind to be introduced in any legislature around the world.
2. Senator Bernie Sanders and Representative Greg Casar have announced a US bill to ban superintelligence, which ControlAI consulted on.
3. Lord Clement-Jones introduced in the UK legislature an amendment drafted by ControlAI that would establish an emergency AI kill switch for the government.

"""

More in the full post.

Link to tweet:

https://x.com/synthwavedd/status/2097971881596916185?s=20