Evolution discovered a bunch of structural patterns at different layers (fragments, folds..) that are energetically favorable, versatile, easily foldable, robust to mutations and then kept reusing them. As a result it sampled more and more in these parts of the space. That's why the fold space is uneven.
Are there any folds and patterns that evolution evolution has not discovered that are also useful? I think Baker Group created a bunch of new folds. I'm not sure if they are as useful as the one discovered by Evolution. After all, Evolution had more compute power than us.
Evolution takes surprisingly little time to home in on solutions which are durable enough to handle local conditions. It's not demonstrably good at preparing its offspring for anything that would be useful outside the local environment. It also has a way of forgetting anything before the most recent data set (or global reset).
Our compute capacity isn't deployed to brute force Monte Carlo sims (mostly). So it's apples and oranges.
And it seems very few proteins appear to be significant problems.
The most famous is the prion protein which can misfold in ways to cause a variety of contagious diseases. Like mad cow disease, chronic wasting disease, scrapie and in humans CJD and vCJD, fatal familial insomnia, Kuru, GSS.
Perhaps because misfoldings of the prion protein can convert others but why is it all affecting that same protein? Always baffled me why aren't other/many proteins suspitible to becoming a prion?
There are others we call "prionoid" because they can have shades of the catetrosphic misfolding prion can.
I think you are underestimating both the value of both projects (autoresearch and personal wiki) just because they are simple. I see both POCs for continuous learning / optmization on the harness layer, which in my opinion is a very interesting direction.
I think Andrej has the experience (and now ressources) to productionize this research into something very interesting.
p.s. called it
> Karpathy will help launch a new team focused on using Claude itself to accelerate pretraining research — an increasingly important frontier as AI companies race to automate parts of AI development.
(https://www.axios.com/2026/05/19/anthropic-openai-karpathy-a...)
No, these are developed off of the assumed uses of the models (predictive autofiller) rather than their actual, cognitive and potential industrial use (developing large scale frameworks for industrial production, automating systems that normally require human monitoring), and uses that we have not yet discovered, because we have not figured out all the constraints and limitations of these models. If Karpathy was in the game like he used to be, he would be on real product. Right now he’s probably so lost by the very thing he helped create that he is stuck doing these mini projects for his own personal interest, without anyone really critically engaging with his work.
Those projects are a complete joke. Neither of them were even original, people have been playing around with those ideas for well over a year.
They just became "famous" because Karpathy is effectively an AI celebrity, so he could throw shit at a wall and post it on X and it would get 10k Github stars.
But seriously, people have been using the models to tweak hyperparemeters, or using LLMs to help create a second brain using markdown or json files or 100X other combinations of files, for a long time already.
Going to Kabuki was one of the most amazing experiences we had when visiting Japan. Although I am not a theater person, and the whole thing was in Japanese ,and we did not have the auto-translate tablets, we enjoyed it a lot. It was very beautiful, and funny.
I recommend to anyone visiting that part of the world.
This seems like a hit job by a competitor. Really ruthless.
> Two months ago, an email went out to a few hundred Delve clients informing them that Delve had leaked their audit reports, alongside other confidential information, through a Google spreadsheet that was publicly accessible.
Who leaked the audit reports? Who sent this email? Who is taking the time to write this analysis and kill the company?
In my opinion, the majority of the points in the article are no news. A compliance saas that offers templates for policies, all of them do. The AI is a chatbot, well who thought.
I think the main point is the collusion between delve and the auditors. Is the evidence for that clear?
The key problem is the audits and the auditors. I have independently verified for our vendors that they have the same templated SOC2 as all of the leaked reports, which is concerning because that shows the auditors did not actually validate the controls.
SOC2 is supposed to give you an INDEPENDENT evaluation of the compliance of a company "are they doing what they say they are"
If the SOC2 report is just a pre-populated template, it is meaningless.
It doesn't really matter the motivation of the "DeepDelver" - this has implications across all companies that rely on these vendors that have been "assessed" by Delve.
Really curious what you're going to do, going forward. Will you be rejecting compliance certified with Delve? Will you be forcing your vendors to redo compliance?
Hit piece or not, the blatantly fraudulent behavior displayed by Delve is reprehensible.
And they didn't even try. Read this management assertion for one of the (known) affected companies:
> We have prepared the accompanying description of Cluely, Inc., system titled "Cluely is a desktop AI assistant to give you answers in real-time, when you need it." throughout the period June 27, 2025 - September 27, 2025(description), based on the criteria set forth in the Description Criteria DC Section 200 2018 Description Criteria for a Description of a Service Organization’s System in a SOC 2 Report (description criteria).
> The description is intended to provide users with information about the "Cluely is a desktop AI assistant to give you answers in real-time, when you need it." that may be useful when assessing the risks arising from interactions with Cluely, Inc. system, particularly information about the suitability of design and operating effectiveness of Cluely, Inc. controls to meet the criteria related to Security, Availability, Processing Integrity, Confidentiality and Privacy set forth in TSP Section 100, 2017 Trust Services Principles and Criteria for Security, Availability, Processing Integrity, Confidentiality and Privacy (applicable trust services criteria).
It's a juicy story to talk about that hits a lot of checkboxes that make it viral --
1. the hustle culture they promoted online was gross
2. they followed the 30u30 Forbes pattern like Liz Holmes, FTX, etc.
3. they're a YC co, so their's plenty of popular voices supporting them
The 3rd isn't to slight the program but folks definitely slam any companies that seem to be in the moral gray area as a proof the program is nihilistic and a net negative. People like to shove mistakes in the face of "successful" folks like investors/VCs.
Finally, the security and compliance community is litigious by their nature and this startup, in general, was a net negative for a lot of people who do fractional / consulting work in security.
What's more surprising to me, as a layperson, is that I found this out and investigated their shady auditor network in late December. It didn't take much work.
Insight Partners invested in a 32 MILLION DOLLAR ROUND without any apparent shred of due diligence. What does that say about the VC market writ large?
Not sure I agree with the AI edited comments. Using AI to improve the readability and clarity is fine. Sometimes a well structured comment is much better than a braindump that reads like ramblings. And AI is quite good at it (and probably will get better). To make the point, here is how this comment would have looked if edited:
"I don't fully agree with banning AI-edited comments. Using AI to improve readability and clarity is a reasonable thing to do. A well-structured comment is often much better than a braindump that reads like rambling. AI is quite good at this, and it will probably get better. To illustrate the point, here is how this comment would have looked if edited"
I prefer your non-edited version. My brain automatically starts to zone out with the AI edited version, side effect of having read way too much AI text
It's a matter of taste, but your original writing is way better. Your writing has your voice. Like dropping the "I am" from your first sentence, using parentheticals, couching your point in understatement (e.g "sometimes" meaning often instead of just saying "often").
The AI comment might be clear, but it sounds like a press release, not a person, and there's nothing to engage with.
For all the people saying they prefer the non-edited version: would y'all be saying that if you didn't already know which one was the non-edited version? Be honest.
There's nothing inherently better about the edited version. It's just saying the same thing with synonyms substituted, at a slightly more formal but less personal register. HN comments are not academic text, colloquial turns of phrase are perfectly fine and expected.
I don't know why this is confusing. If I forget to put the "not" qualifier in a sentence, do we agree that it can confuse (or worse, mislead) the reader?
You're saying removing ambiguity does not make it easier to read? You're saying using a word that means nothing like what you meant to say is easier to read than using the correct word?
OK. My brain farted, and I misunderstood the top post to be saying something else, and your and others' criticisms were misinterpreted by me.
Now here's the thing. I wrote all my prior comments on a machine with no LLM access. On my personal machine, I had a while ago installed a TamperMonkey script that sends my draft, along with all the parents (to the root) to an LLM for feedback (with a specific prompt). All it does is give feedback (logical errors, etc). So I tried again with one of my comments, and its feedback found several flaws with my comment, and ended it with this suggestion:
"Considering all this, it might be BETTER to either not reply ..."
Had I had this advice when I was writing those comments, it would have saved me and others a fair amount of time.
This is (mildly) useful. It'd be sad to ban such use.
I don't follow the need to write CLIs for the agent. Why not use simply the API and document it well? The token difference between using an API and CLI is not that much, and models are trained to use REST APIs and understand their patterns, compared to your random CLI.
That's a basic fact in bio. Check the rossman fold page for example: https://en.wikipedia.org/wiki/Rossmann_fold it's a template used for many functions.
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