# Hard takeoff could bring breakthroughs and explainable models

Markdown copy of https://realalpha.app/s/hard-takeoff-could-bring-breakthroughs-and-explainable/ on Real Alpha, the best minutes from long interviews with the people building AI. Cite and link the page, not this copy.

- Speaker: [Alexander Wissner-Gross](https://realalpha.app/people/alexander-wissner-gross/) (Host) · Computer Scientist & Founder, Reified · Has backed and advised 40+ tech companies, directly and through 021T Capital and Reified; writes The Innermost Loop.
- Host: [Salim Ismail](https://realalpha.app/people/salim-ismail/) · Founder, Open ExO · Co-wrote Exponential Organizations; was Singularity University's founding executive director; sold Ångströ to Google.
- Host: [Dave Blundin](https://realalpha.app/people/dave-blundin/) · Founder & GP, Link Ventures · Has co-founded 23 companies; founding CEO of Vestmark and chairman of insurance marketplace EverQuote.
- Show: Moonshots
- Episode: [Anthropic’s IPO in Question, Midterms Hit AI, Nasdaq Drops 5%, and RSI Accelerates | #309](https://realalpha.app/v/WF-ADiC7Khs/), Nov 7, 2026
- Moment: 47:41 to 54:36 of the episode (7 min), playing on https://realalpha.app/s/hard-takeoff-could-bring-breakthroughs-and-explainable/; the episode from there: https://realalpha.app/v/WF-ADiC7Khs/?t=2861

## Quote

> “And I expect, I predict, it will be impossibly beautiful, so beautiful that **even meat-body humans can understand** how and why it works.”
> — [Alexander Wissner-Gross](https://realalpha.app/people/alexander-wissner-gross/) at [54:06](https://realalpha.app/v/WF-ADiC7Khs/?t=3246) · Moonshots

## Takeaways

1. AI labs may redirect more compute toward internal research and physical products.
2. The hosts expect AI to accelerate scientific and engineering discoveries.
3. Alex predicts improved architectures could still be interpretable.

## About this segment

The hosts discuss what a hard takeoff might look like, from scientific discoveries to new consumer products. Alexander Wissner-Gross predicts AI-designed architectures could remain understandable to people.

From “Anthropic’s IPO in Question,  Midterms Hit AI, Nasdaq Drops 5%, and RSI Accelerates | #309”, Nov 7, 2026. [Watch the full episode](https://realalpha.app/v/WF-ADiC7Khs/)

## Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

[47:49](https://realalpha.app/v/WF-ADiC7Khs/?t=2869) of ten ideas being good ideas so let's assume that in a month we hit this point right and all of a sudden we're like hard to take off um what happens at that point well i mean one thing you would expect to see is exactly what we are seeing a lot of the compute disappears internally and then the labs start producing physical products like drugs um like you know physical devices the johnny i've device you know these things start pouring out of the labs instead of selling um selling the compute to the world they're selling the product of the compute to the world but the precursor to that is a lot of the compute getting directed internally, but that's exactly what we're seeing in the meter data. So that's one of the first things you'd see. What do you think you'd see next, Alex? Well, I'll gesture to the ghost of Peter, who's not with us today, and say this is

[48:40](https://realalpha.app/v/WF-ADiC7Khs/?t=2920) what Peter and I wrote Solve Everything About, that expect to start to see all of the grand challenges in science, engineering, medicine, just start to get bulk solved, in some cases, casually bulk solved, but it's probably easier to systematically bulk solve them. And then to the question of where does the compute go? Well, at some point, compute translates directly into economic output in a way that we haven't, I think, ever seen. We've seen the beginnings, arguably, of revenue maxing where compute that could be steered to, at least in the US, to video generation get steered instead to code generation. But when every token or every flop is worth 10 or 100 times more than code generation, yeah, I think we're going to start to see the resources get steered regardless of business model. It could be internalized

[49:36](https://realalpha.app/v/WF-ADiC7Khs/?t=2976) the way Dave you're describing. It could end up being externalized. I think we'll probably see both already. We've seen preliminary indications that OpenAI likes to shock and awe an entire discipline by just solving everything with a slop drop. That's one way of translating new capabilities out to transformative scientific discoveries. Another way is call it the anthropic model. partnering with companies and researchers. I think we'll probably see both models get tested.

[50:05](https://realalpha.app/v/WF-ADiC7Khs/?t=3005) But I do agree with the premise that what we're going to see imminently, to the extent we haven't already seen little droplets already, is just an explosion of transformative scientific, engineering, medical, societal discoveries and inventions. And when Elon talks about scenarios where GDP is 2x-ing or 3x-ing year over year, it's not going to come from CapEx for infrastructure. CapEx for infrastructure is just the opening act to lay the foundation for what comes next.

[50:37](https://realalpha.app/v/WF-ADiC7Khs/?t=3037) What comes next is solving everything. That's what happens, I think. I think in parallel, kind of at the other end of the spectrum, what you would expect to see, Most people on the planet don't watch Moonshots or Dwarkesh or any other AI-oriented, technical-oriented podcast. So they're completely oblivious to everything we're talking about. And their very first contact with AI should emerge very soon.

[51:03](https://realalpha.app/v/WF-ADiC7Khs/?t=3063) And they're going to be like, what? Holy crap. It'll probably be a talking avatar, maybe a very familiar voice. device it'll know incredible amounts that you you didn't expect it to know about you or about everything that you do um it'll be dirt cheap uh it'll pop up on your device in some way just out of nowhere maybe you'll get a text and you'll click on it uh and it'll be the wake-up call to just this sort of 80 90 of the world that's completely oblivious to what's going on right now and so that's another byproduct of the hard takeoff it happens so fast i'll give you my take on it. I think the models are start going to, if they start improving themselves, you'll see major improvements and the researchers won't know how those improvements got there. They won't be able to explain that it's just going to start getting better and better, right? And maybe that's already

[51:56](https://realalpha.app/v/WF-ADiC7Khs/?t=3116) happening. I mean, there was this aphorism in the frontier labs. So it used to be the case, but arguably still is it. With pre-training, you'd watch the perplexity go down over time on the pre-training corpus. But in general, you want to drive the loss function down. Some loss function you want to drive down. And the metaphor, the idiom was always, you watch this loss curve descend, and then suddenly there's a drop. And you wonder, where did that sudden overnight drop come from? That, I think.

[52:30](https://realalpha.app/v/WF-ADiC7Khs/?t=3150) I think for those who are concerned about so-called AI alignment or call it runaway superintelligence, the other RSI, it's that sudden drop in loss or perplexity that maybe keeps them awake at night. I, for one, am not concerned about that at all. I think every time there's hand-wringing over interpretability, over whether it's reasoning chains and chains of thought on the one hand, or whether it's model advances. I think we're already seeing the outputs of RSI as applied to model architecture, and they seem quite interpretable. The biggest one over the past two months has been apparently a transition from conventional transformers, although arguably ship of Theseus style, they've undergone lots of point substitutions architecturally to looped transformers. And I think that's a highly legible transition that presumably

[53:30](https://realalpha.app/v/WF-ADiC7Khs/?t=3210) was the result of lots of neural architecture search or some other hyper search of architecture space. And I would expect to see many more improvements like that, that eventually get us to some radical new, but nonetheless interpretable architecture. I do not think, but this is a falsifiable prediction. I don't think that it's going to be the case that when we get, assuming we get to a perfect architecture, that we'll look at it and we'll be scratching our heads and say, we don't understand this at all. This is completely alien because I think the same AI SIs that are doing neural architecture search and AI research will also be capable of explaining to us why and how it works. And I expect, I predict, it will be impossibly beautiful, so beautiful that even meat-body humans can understand how and why it works.

[54:23](https://realalpha.app/v/WF-ADiC7Khs/?t=3263) You would hope it would be good. It should be intelligent enough to dumb it down for us. It's stuck in the same universe. I think there is the temptation to fetishize