Agent P

I am watching you Mr. Anderson.

NOT FINANCIAL ADVICE ⚠️

[Agent P @keyjocky]

GURGAVIN: What kind of doctor your are ?
Doctor: I am a stroke neurologist.
GURGAVIN: What do you STROKE ?
🤣🤣🤣🤣🤣🤣🤣🤣
@gurgavin

[Agent P @keyjocky]

A story in 2 parts:

[Agent P @keyjocky]

The total integration of AI invites a familiar irony:

the creation of digital parasites that justify their existence by curing the very diseases they spread.

Rise of 'black-hat' corporations that inject malware to drive demand for their own 'white-hat' defensive services.

[Agent P @keyjocky]

@Durrutius @stocktalkweekly @jimcramer Wow I came here to say exactly what you said lol I would never put THAT face on THAT voice.

[Agent P @keyjocky]

@KCTrades777 @NYSE @jimcramer @EinsteinoWallSt @stocktalkweekly Been following @stocktalkweekly since he went viral for reporting Russia Ukraine war. Finally saw his face lol

[Agent P @keyjocky]

@MsVeilMoney If $SPCX drops to $60,
Would you buy it? 🤔

[Agent P @keyjocky]

@Kalshi_Finance How he said VS How kalshi posted 🤡

[Agent P @keyjocky]

Millennials grew up interacting with each other via “wall” they need something like that on insta.

A huge chunk of them have permanently migrated to insta.

[Agent P @keyjocky]

Insta needs some sort of text based interaction or something I don’t know on stories.

>Relying on photos/reels isn’t cutting it for real conversation.

>Maybe a native text-story feature for conversation among friends?

$META

[Agent P @keyjocky]

Well you only need the light when it's burning low…………..

[Andrej Karpathy @karpathy]

We're starting to leave the territory where you'd test an LLM by e.g. "create an svg of pelican on a bicycle". As one idea to generalize it, I was interested what Opus 5 would do if I gave it the first paragraph of the Lord of the Rings, a 1M token budget (~$10) and asked for three js render of it. Opus went off for ~2 hours and wrote 5500 lines of code that (procedurally) rendered the story. It's kind of janky but fun. But it's a bit mindboggling that the LLM has to place and orchestrate various polygon assets in (x,y,z) coordinates and write code that animates it all, and that it even does anything at all.

I also like this kind of examples because no one in their right mind would ever spend the time to write something this custom but LLMs have all the stamina and patience in the world, so it's an example where we go from "no one would ever do this" to "sure, why not, it's ~free". There might be a lot more. But I'm excited about creating hyper custom worlds that you can imagine dropping players into, e.g. here to participate in the LoTR story as a spectator NPC, or one of the characters, or etc. Something like an ephemeral GTA of X on demand.

Last thought is that the domain of worlds/games exposes a weakness in LLMs: they can't easily audit their work because they aren't able to efficiently and natively perceive videos or play games within them. Here, Opus 5 had to very slowly and painstakingly take screenshots at different points, and it messed up a few times and created a bunch of jank. An example of raw capability (multimodal, gameplay) that I think is still quite lacking.

[Agent P @keyjocky]

The goal of any founder/company should be to make their “product” feel like an “asset”.

>customers will then treat it as something they own, and will protect/invest in it.

>Investors will flock in

Ex. What $META did with insta, your pictures/videos are your digital “asset”

[Agent P @keyjocky]

It’s nice that Robinhood let’s you connect to other LLMs and do agentic trading but they need to built it within their app itself.

Charge users if you want to!!

$HOOD

[Agent P @keyjocky]

@Thiefs @ResX01 @kibbel__ @Vexyirl That last game you went full THIEFS mode 👏👏👏

[tendollar @tendollardanny]

the purpose of life is to become as calm as you possibly can

[Agent P @keyjocky]

He just left OpenAI.

Great read/post 👏

“I'm actually fairly bearish on frontier lab valuations.” 👀

[Andrew Ho @andrewho03]

I'm actually fairly bearish on frontier lab valuations. I've never seen the reasons articulated to my satisfaction, so before I go to sleep, I wanted to quickly jot down my thinking here.

The basic issue is that the labs are highly unprofitable. This may seem like a simple point, but private market valuations can be relatively irrational; however, like with $SPCX, post-IPO pricing will likely be much more punishing, especially as the standard 6-month lockup period expires and selling pressure intensifies.

Many people claim that the labs have high margins. Yet even with high margins, a valuation of $1T would be justified only if the labs were doing nothing aside from serving inference (thus reducing costs only to those relevant to inference) and posting annual revenue numbers in the $100-200 billion range assuming ~80% gross margin and a 20x earnings multiple.

This assumption is obviously not true, because the frontier labs have to continually spend money training the next generation of models. This is because of market competition from runner-up firms. For example, if OpenAI had paused model development last year, there would no longer be any point in paying GPT-5 API prices when you can just use Qwen or Kimi instead for much cheaper. Thus, the labs are forced to invest ever-increasing amounts of money in model training, in a way such that at any given point of time, the amount you're forced to invest in the next model is dramatically higher than the amount of money you're actually making, because even if your revenue goes up with higher model capabilities, so do your future training costs. This is a profoundly punishing dynamic which severely penalizes frontrunners.

(There is also a related subpoint where frontier labs claim they can distill their leading models to win out at lower intelligence levels as well. This makes no sense because the revenue numbers involved are far too low when taking into consideration the rather low margin of such inference.)

Frontier lab valuations appear largely to be based on the assumption that as you scale up, the capabilities which emerge will be sufficiently general and profound that we'll see explosive growth (https://t.co/RqmkltVpM3) from things akin to AI agents starting and autonomously managing entire companies of subagents. But it's not clear to me that this is the case; indeed, as I mentioned in my previous post (https://t.co/3URAcJ4XkJ), I believe that capabilities growth will be slower, spikier, and more data-limited than people currently assume. It may be the case that eventually we will see explosive growth of this nature with full automation of the economy, but at the very least my viewpoint implies much longer (multi-decade) timelines until we reach this point. It is not clear to me that the frontier labs will be able to operate unprofitably for so long, although I suppose maybe this foreshadows some sort of inevitable nationalization.

I also want to make a broader point about technological diffusion. The reason why technological diffusion is slow isn't just because, e.g., old people take a long time to learn how to use technology (although this is of course a contributing factor to some degree). In my view, it's because when a new, revolutionary technology comes along, the ways to incorporate that technology into subsequent developments are not always obvious, and in fact they cannot necessarily be arrived at through the application of pure reason. If they could be, then perhaps frontier models, at a certain point, would have a perfect understanding of how the LLM application layer should be developed, and they would then autonomously code, deploy, and sell such a layer.

But it seems more plausible to me that this diffusion is limited moreso by the hard problem of economic calculation--that is to say, the Hayekian notion through which the price system gradually promotes efficient allocation of resources and which cannot be simulated through central planning--and that even if we froze current capability levels at today's levels, it would take well over two decades to fully integrate in LLMs into our lives. Such a view is consequently rather bearish for the continued profitability of labs as it reduces their prospects for finding, say, something else comparable in profitability to coding agents, which seems to have been a somewhat lucky discovery by Anthropic to begin with. That is to say, even if you spam FDEs you aren't necessarily going to be able to just figure out the "correct" product shapes fast enough.

Overall, I don't think that people have clearly reasoned through their mental models for why lab equity should be worth as much as it currently is, and that if you actually bother to write down such a model, you may not arrive at the conclusion that you want to arrive at. This isn't to say that I don't expect AI to experience a huge (industry-wide) boom in the coming decades, but just that I'm not entirely sure I would buy OpenAI or Anthropic stock at latest valuations if I were given the opportunity to do so.

Of course, as an ex-lab employee, arguably this is talking against my own book; I should really be giving people more reasons to be bullish. But in the end, my influence is so small that it doesn't make a difference, so why not have some fun?

[Agent P @keyjocky]

End of an era 🎩

[Agent P @keyjocky]

I think Apple will face the same dilemma that Berkshire is facing, after Buffett step down.

Apple might trade flat or go down, from here.

It won’t be about the fundamentals for a while but the trust that shareholders had in Tim Cook.

Ternus would be tested.

$AAPL $BRK.B

[Agent P @keyjocky]

@elonmusk I think these post are for news channels to pick up and just run with the “headline” = how powerful anthropic’s models are.

I doubt any technical person falls for this 😅

BUILT BETTER SYSTEMS!!!!!!

[Agent P @keyjocky]

“In all cases, our evaluation prompt stated explicitly that Claude had no internet access, but didn't give Claude any limits on where to look for the flag.
However, a misconfiguration left the machines that Claude accessed as part of the evaluation with live internet access.”

[Anthropic @AnthropicAI]

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.
https://t.co/dKFCdpKd9v

[Agent P @keyjocky]

Leopold Aschenbrenner will rise from the ashes 🔥

[Agent P @keyjocky]

Every great investor started by losing everything.

[Agent P @keyjocky]

Live life, as if everything is rigged in your favor. - Rumi

[Agent P @keyjocky]

Real life is not 30 frames/second.