Most published research is controlled by 5 for-profit corporations.

  Academic publishing is predominantly controlled by a small
  oligopoly of five for-profit corporations that collectively
  publish roughly 50% of all scientific articles: Elsevier
  (owned by RELX Group), Springer Nature, Wiley (John
  Wiley & Sons), Taylor & Francis (owned by Informa PLC),
  and SAGE Publications.

Going forward, colleges can pay for ChatGPT and things like it, and presumably will. The AI companies will be happy to sell to them. There's really no problems here except for self-created ones (for example, if some researchers don't want to use AI). Of course, they're free to do that, just like they're free to not use computers. But then don't complain that doing stuff takes too long.

I'm more worried that >90% of the computers on the planet are controlled by a company that obeys the whims of an arguably-demented narcissist and oppose the rule of law.

You're right, my bad. It not only talks about IP as being an enclosure idea, it also does talk about FOSS (GPL).

I still disagree but it looks like the author makes a cursory attempt to address the issues that I think are more relevant.

It's not terrifying because it's unknown. It's terrifying because a tiny number of obscenely rich psychopaths are trying to take sole control of it so they can enshrine themselves as living gods and make 99% of humans so obsolete that they die sick and cold in the streets. That's their overt goal, and almost all evidence we have from history and current politics suggests that they will be wildly successful at this. None of this is for you, it's all for them. All of it. That's why it's terrifying.

> AI labs have not worked well with affected communities at all and often downright exploited them

The first reviews of OAI's dump on math are coming out. Quasi-Riemann Hypothesis Proof looks to be valid. The irony is that is uses and approach that the people who work in that area have disregarded for the most part. As well as mining some other parts of maths corpus. There really isnt "innovation" there.

For as much as OAI is guilty of leveraging work in progress, the complaints about some of the other work(s) are looking spurious (and I'm being very kind using that word).

Games are starting to be remixed; closed-source software can be cracked open at will.

It's happening all around but you're somehow not seeing it.

Agreed it's not settled - my comment isn't about whether they're right or wrong.

I'm advocating mindfully managing your own influences.

Not necessarily, not in some of the most useful ways of simply having a significantly more capable way of automating research & experimentation of many sorts. Anyone with a dataset and a laptop with a decent gpu, or pretty reasonably priced API or subscription to access models that don't even need to be frontier level, they can setup a loop for intelligent iteration through countless analytical methods, subset analysis, enriching the data with other sources, search and retrieval of research literature to cross reference results of analysis with other findings and write a basic summary for the person to review, look for alternative methods for analysis.

Yes, not everyone will be able to launch a swarm of agents and a few billion tokens, but scientific research has always had areas where the most advanced tools were beyond the reach of every scientist who might like to have access.

Maybe but are those limitations more or less onerous than the current requirements to contribute to scientific research? It remains to be seen I think.

Only for about five more years. In 7-10 years the price of memory and compute should drop by 80-90%. In ten years the bleeding edge 14,000 token/s machines and 4TB memory is going to look quaint, "that stuff can't even bootstrap a kernel and entire (usable) posix-compliant OS in less than a week" vs the future of "the computer updates it's firmware in real time to meet the needs of the current task"

Not only resources being controlled by a few organizations, but the noise of all of the people who have used AI to “discover” something novel, when they don’t understand the domain in the first place. When everyone is discovering something, but what they are publishing is either incorrect or already known, how do you wade through the slop to find the gems (maybe academic publishing was already filled with human slop, though).

Echoing what the other reply to your question said, I don't disagree that much of this post-hoc, but I think the thinking has evolved such that this post-hoc reasoning is now truly believed. I'm primarily speaking of it as an observer of how and where funds are being directed and to what ends: often big, non-university-centered programs to build labs or generate datasets for AI discovery. While some of the ideas may have merit, there is no free lunch unfortunately, as that was money that would have supported individual PIs and their trainees.

Going by the public announcements, the original plan was to cut science funding but once Congress said "no," the backup plan became directing it towards non - human - scientist items like facilities operations and the Genesis program.

Unfortunately it is entirely related. The initial wave of cancelations were about those topics, but the more structural thing they are attempting now is to focus funds on tool development for AI models as opposed to human capital development as NSF does.

No it is about AI too. Trump et al want there to be no dispensing of federal grants to academics in the future. They want the government to instead cut checks directly to xAI et al who will do all our research for us in the future and will for certain represent our best interests and not those of shareholders exclusively.

You mean in relation to AI? Well I think we also need to do something in relation to GPL code for example.