AI's top startups are barely publishing their research • Hacker News Board

Re: AI's top startups are barely publishing their research

#331

Post by KaiserPro » Thu, Jul 30, 2026, 9:45 PM UTC

jmalicki wrote: post #279

KaiserPro wrote: post #245

Earlier quoted context omitted.

The problem with research is that you are supposed to be creating novel works, not derivatives. This means you are creating IP, not modifying.

All research builds upon previous ideas. E.g. you can patent a novel idea that would require licensing another patent to use.

but you patent something requires proving that you have done something novel. You're effectively asserting that the thing you invented is new and different enough to be not a derivative of a previous patent.

sure to build a new system, you might need other patents. but a pateent it's self should be unique enough to defend. Which means its copyrightable as its own thing

Re: AI's top startups are barely publishing their research

#332

Post by jmalicki » Thu, Jul 30, 2026, 9:56 PM UTC

KaiserPro wrote: post #331

jmalicki wrote: post #279

Earlier quoted context omitted.

All research builds upon previous ideas. E.g. you can patent a novel idea that would require licensing another patent to use.

but you patent something requires proving that you have done something novel. You're effectively asserting that the thing you invented is new and different enough to be not a derivative of a previous patent. sure to build a new system, you might need other patents. but a pateent it's self should be unique enough to defend. Which means its copyrightable as its own thing

An idea can be both novel and derivative at the same time.

You create idea B.

It absolutely builds upon idea A, and is in some sense derivative.

But your idea B introduces a lot of new novel concepts on top of idea A that makes it novel.

An idea can absolutely be both novel and derivative at the same time. Most of the best ideas are.

For a hypothetical example, an innovative Linux filesystem requires having the Linux OS, or similar, as a base to operate. In some sense, it is derivative of that prior work. But the new ideas extend the old ideas enough to be novel.

Re: AI's top startups are barely publishing their research

#333

Post by don_esteban » Thu, Jul 30, 2026, 10:04 PM UTC

bonoboTP wrote: post #330

don_esteban wrote: post #283

Earlier quoted context omitted.

You are assuming incompetence on the scientist saying that the branch from the left of A is a dead end. While nobody is perfect, there are numerous perfectly valid scientific negative results. You know, there exist things like impossibility proofs in mathematics and computer science. There are equivalents in other sciences (e.g. if X was true, that would lead to Y that is easily observable and clearly not observed).…

There are different types of research. Negative AI results are not like Michelson-Morley experiment in physics that can positively establish the lack of something. It's more of a craft, the "make it work" style of thing. Give the same task or goal to two different teams, you will see massively different outcomes. Simply failing to make it work is not conclusive. To make such a negative result acceptable in AI, you'd…

I did read OP's post much more generally than only about AI research. There are many research areas where (properly done!) negative results would be very valuable, but are not properly encouraged.

I do agree that in a new area with too many degrees of freedom (and yes, AI research is one of those), negative results (especially poorly done) are of limited usefulness.

Re: AI's top startups are barely publishing their research

#334

Post by threethirtytwo » Thu, Jul 30, 2026, 10:32 PM UTC

himata4113 wrote: post #210

dgellow wrote: post #195

Earlier quoted context omitted.

Did you publish on that topic? Just curious, would love reading more

There's a pretty large paper on the topic: https://arxiv.org/pdf/2606.15497 , but results are somewhat mixed.

[flagged]

Re: AI's top startups are barely publishing their research

#335

Post by threethirtytwo » Thu, Jul 30, 2026, 10:37 PM UTC

himata4113 wrote: post #210

dgellow wrote: post #195

Earlier quoted context omitted.

Did you publish on that topic? Just curious, would love reading more

There's a pretty large paper on the topic: https://arxiv.org/pdf/2606.15497 , but results are somewhat mixed.

My response, which was flagged by automation (I used AI to verify the paper and it says the paper is NOT what you claim it is), was spot on. This paper is not recursive self improvement, it is AI in a feedback loop, but it is not improving itself. It turns your entire premise into something questionable. You said this one done everywhere by many people including you.

Then you present a paper which WAS NOT recursive self improvement so it clearly is not "everywhere".

To be real with you, I don't think you're being entirely honest. You're not presenting a fair argument. You have bias. Recursive self improvement can only be done by frontier labs who created these models in the first place. Academia simply Does not have the funds.

If this is being done, we're not privvy to it. The amount of compute to build these things is astronomical.

Re: AI's top startups are barely publishing their research

#336

Post by 5555watch » Fri, Jul 31, 2026, 4:12 AM UTC

ninjahawk1 wrote: post #134

colingauvin wrote: post #125

Earlier quoted context omitted.

Curious what you mean by proactive? Could you share a bit more?

Happily, current AI is interacted with in a reactive loop. I open the Claude app, CLI, whatever, say my prompt, get an output. I personally wanted an AI that was able to reach out to me about my life before I had to reach out to it. An example, a friend just emailed me asking to meet for at 1pm but I have class at 1:30, so a proactive AI would see that conflict and send me a notification about it, asking if the propo…

But it's not proactive then? There's just a hidden loop or some cron-like signal that feeds data to a reactive loop..

I'd imagine proactive as something like, hmm, no signal from X, I wonder how they're doing...

Re: AI's top startups are barely publishing their research

#337

Post by perpetuallunch » Fri, Jul 31, 2026, 8:00 AM UTC

lenerdenator wrote: post #318

perpetuallunch wrote: post #175

Earlier quoted context omitted.

What do you mean by this? What are investors who don’t have money? Perhaps I should have said investors and speculators , but this doesn’t help you here.

I'm saying that there's no difference between doing it for money and doing it for the attention of investors, because investors are also money. OP's startup is publishing because they think there's an economic advantage to doing so. That's not good or bad; it just is. Very, very few things in the tech world are done "just because". Even fewer things when we're talking about AI being developed in the US. For better or…

Sure.

Quite reductionist.

But I don't disagree.

Re: AI's top startups are barely publishing their research

#338

Post by sam_lowry_ » Fri, Jul 31, 2026, 5:21 PM UTC

Davidzheng wrote: post #168

fc417fc802 wrote: post #162

Earlier quoted context omitted.

The GNU RPL (research public license), a viral knowledge license. By reading this paper you are legally obligated to openly publish all vaguely related future research that you perform.

Sounds dystopian.

Pretty much like the patent system sounded at first to commoners.

Re: AI's top startups are barely publishing their research

#339

Post by BetterThanSober » Sat, Aug 01, 2026, 4:05 AM UTC

epolanski wrote: post #298

BetterThanSober wrote: post #203

Earlier quoted context omitted.

LinkedIn can and should be a platform like this, for professionals and catered to professionals. It is a shame that it's now a cesspool of engagement bait and larp entrepreneurs

LinkedIn is not and should not be a medium for scientific discussions.

Agreed, not discussions but networking

Re: AI's top startups are barely publishing their research

#340

Post by YeGoblynQueenne » Sat, Aug 01, 2026, 9:21 AM UTC

okaleniuk wrote: post #223

YeGoblynQueenne wrote: post #208

Earlier quoted context omitted.

Tier 1 journals have high standards (that's why they're tier 1) and they also have hundreds of submissions every cycle. It's common to have a paper rejected. On the upside you get your work seen by some of the most experienced researchers in AI, who are also specialists in your paper's subject. For example, here's the editorial board of the Journal of Machine Learning Research: https://jmlr.org/editorial-board.html S…

The alternative is to use your network directly. The very notion of "I'll publish my work and someone will notice me" is wrong. Most people in academia are too concentrated on their own work to care about yours. The only minority that cares is already in your contact list.

Not always. AFAICT my papers have often been reviewed by people I have never met and who have expertise that overlaps with, but does not fully match, mine, and I couldn't possibly contact those people out of the blue to ask for feedback, particularly because I'd never get the chance to meet them outside of peer review (they wouldn't be in the same conferences as me etc). And that's a good thing because that way I get a sort of "outsider looking in" view.

I've sure given and taken informal feedback in the past from people I know and that's great but peer review also makes the whole process more formal and less sloppy; at least sometimes and depending on the venue and to my experience.