Sure, but isn't the response worse than the problem? When intellectual standards are abandoned (as opposed to correcting a specific bias), discourse degrades into mindless anger, conspiracies and leaders who defraud their own supporters.
Given the money available to conservatives, why haven't they been able to setup vibrant universities, films, art etc. The point here is not to blame conservatives, but push the analysis of the cause to something deeper than just saying that the opponents have all the power.
If it just a mundane chatbot, the discussion is moot. But, we already have AI making breakthroughs in research and approaching the abilities do science just like a scientist does. (The last two paragraphs of your comment also assume such a high capability scenario).
Imagine giving the access, to whoever wants it, to a scientist who may not have many fresh insights, but has the advantage of a huge memory containing all the scientific literature in their mind, the standard patterns of deductions, and the ability to work at a very fast pace 24/7. They could identify vulnerabilities in biological mechanisms, just like AI identifies security flaws in code today.
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Regarding hurting themselves, I was not referring to someone who is too dumb to follow lab safety precautions, but someone who has a nihilistic mindset. State actors and militia use weapons to take over and enjoy the power they acquire - they dont want to get killed by a deadly virus(unless they engineer and selectively apply the vaccine before they release the weapon - but this is very hard to keep secret). Someone who is nihilistic wont have such reservations on using the weapon even if it destroys them eventually.
Regarding restrictions on API LLMs leading to use of local LLMs, it is the local LLMs which will be used anyway (once they have the capability). That we live in a mass surveillance envirnoment is common knowledge. The bottleneck, where restrictions can be applied, is not inference but training which requires hundreds of millions of dollars. Chinese scientists have themselves spoken about AI safety concerns and it is indeed a threat to China just like anyone else.
Also, restricting high end weapons ability does not interfere with 99.9% of LLM usage (open-weights or proprietary) - so it need not interfere with business strategy.
Wikipedia is a presentation of partial selection of biology textbooks and research papers, not using them as a collective brain to generate new artifacts.
There is a big difference between having a large bookshelf of programming language/networking/OS manuals and the ability to generate a functional software product which previously required a hundred or more developers. Even a hundred developers may not be able to find a subtle exploit in code which requires a tedious scan of millions of lines. Computer security hacks can be much less of a problem in comparison to exploits in biology.
Also, even Wikipedia (and public resources in general) have restrictions - there is information dangerous enough to be not published. In the 1930's itself, Szilard (who discovered the chain reaction) and Bohr advocated for restrictions on openly publishing research on uranium fission.
Restricting things like creation of a highly infectious virus is very different from restricting books or even guns. There is no 'monopoly' over such a technology, as a use of the technology will inevitably harm the creators themselves.
Restrictions on high end biology, chemistry would leave overwhelming number of use cases of LLMs unaffected - no need to ban open weight LLMs. Such restrictions can be even more effective, if it is coupled to researchers getting early access to see the possible problems and have an opportunity to prevent the outbreak or create new vaccines well in advance.
Restrictions are not enabling monopolies. The opposite is true, if a LLM engineered virus or other harmful technology is let loose, public opinion can very quickly swing towards draconian regulation. (see nuclear power after Chernobyl).
There are plenty of weapons (see custom made virus) which no state actor (or even an informal militia) would want to release, as these weapons attack everyone. But, open access to details of its construction leaves everyone vulnerable to motivations of small groups of crazy individuals.
This doesn't seem to be investment focussed activity, but rather extending Claude credits for education and research. Which is a good thing, independent of other bad things that might be happening.
This is not about employer vs employee and job security. In fact, the post mentions that there could be good reasons for layoffs. What the post highlights is -
1. Trust - When an employer tells the employee something and then ignores it - then a truth based culture gives in to cynicism. Communications in the company become suspect. Even when there are win-win situations, where cooperation could lead to positive outcomes for both management and workers, a lack of trust means the company cant execute.
Also, this will affect communications with customers and shareholders.
2. Regardless of being right, the author is helping others in similar situations, who can adjust their expectations.
3. The post isn't so much about company vs employee, but competing factions within the company, who are invested in alternative tools/proposals. Promotion is used as a means of making one's faction stronger. This need not be for the benefit of the company or customers. Lobbying will also, of course, affect truth.
Factions might be inevitable (and there can even be good reasons - people genuinely have differences of opinion). But, if the company has good leaders, they will prevent this from erupting into a strong zero-sum conflicts which drown other goals - company's profits, promoting competent people, a culture of trust.
There is a purely geometric reason for why elliptic curves have group structure. A geometric shape which is also a group, such that the group operations are smooth maps, has to be homogeneous - it has to look the same from every point[1]. Not just that, if you have a vector at some point, there is a natural way to transport it to every other point on the shape. The only surface (curves over complex numbers are really 2d surfaces) which obeys this property is the torus[2].
[1] Why should the homogeneous property be true? Because in a group, multiplication by g, pushes the identity e to g. M_g(e)=g where. This is a continuous isomorphism of the shape. So the shape looks the same at g as it looks at a (a neigbhourhood of g looks the same as neighbourhood of e). So an 'X' or 'Y' shapes cant be groups, as there are points which are locally unique, but 'O' shape can be a group. Moreover, M_g can also push a fixed non-zero vector v at e to a vector v_g at g.
Don't want to get into low quality generalizations in your post except to note tahta casual Google search will show you that Tata group is one of the most philantropically oriented groups. Which of course, doesn't excuse this issue.
This is a great way to present the concepts. Something like this would have been useful some years back when I was trying to use the Haskell library for lens.
For someone new, this was a really interesting read. Thanks for the effort. The picture of how the sky looks from underwater was so surprising to learn.
Regarding the 'first-principles' discussion, it is a relative term in usage despite the name. Explaining from a layer of abstraction below normal explanations.
Someone explaining how a computer works starting with machine instructions is doing first-priniciples, even if they wont explain details of atoms. The literal meaning would be almost impossible to implement, for instance none of Newton's work would be first principles given today's knowledge. Similarly, current physics can be subsumed in future principles.
A formal program with funding, faculty and grad students would greatly help to make something which is not superficial. (Although I don't know of how much making art is a university subject, art criticism seems to be more in vogue).
Currently, undergrads take double majors (Witten was a history grad!). But, this doesn't tend to happen at the graduate level. The obstacles can be getting funding(siloed into departments), and courses being demanding enough already for one subject.
Faculty sometimes do hold a side appointment in other departments. But, the main incentive emerging from the academic job system is to get specialized expertise and publish in high reputation journals.
There is a tendency here to pattern match the advice in this article with frustrating experiences about office politics. But I dont see this as a post about politics.
Rather, what I got was that the spec is an incomplete description and there needs to be more inquiry into how the software is going to be used. This can require a little bit of 'going up the stack' to see how business need relates to the software requirement(single enterprise customer with a precise requirement, acquisition of new customer, software for some internal vision of CEO etc). Compare with a startup where one doesn't even have a spec and one is trying to find a product-market fit or when developers take sales calls and find new insights on how the software is actually being used.
A completely broken spec is indeed a failure in management process. But, in general, it helps a library developer to think beyond a library spec and see how it is being used.
Given the money available to conservatives, why haven't they been able to setup vibrant universities, films, art etc. The point here is not to blame conservatives, but push the analysis of the cause to something deeper than just saying that the opponents have all the power.