First, impact factor (not impact score) is used to compare journals, not individuals. Second, it is the average citations of every paper in a journal so one paper that gets a high citation rate through fraud will have minimal effect on the impact factor...and if you have so many fraudulent papers that it does then you are going to have a widepsread reputation in the field as as the journal if science-fiction at which point it will not matter what your imapct factor is, you'll be judged on that reputation.

Which is exactly how it should be because if all you have done is exactly reproduce someone else's work nobody has learnt anything new so the impact is close to zero. This is the sort of project you give to an undergrad, not something you would want to publish. Simply reproducing a previous work is a wasted opportunity to improve on it. Instead of aiming for replication, aim for improvement: increase the precision of the measurement or use an entirely different method that tests different assumptions. Replication usually happens naturally when people start to build on your result and improve it. This is why, despite as you point out there being no funding specifically for replication, we still catch scientific fraud.

You are NOT the one person who has trained AI in this discussion, I have been using it for the last 20+ years. I'm not afraid of AI at all but, unlike you, I am very much aware of its limitations because, also I suspect unlike you, I have actually trained and used AI systems. However, given that you failed to read that in my post I suspect you may be the one person in the discussion who can't read and understand English which is another reason to doubt your claims.

Peer review is not the same as a fraud investigation. When we review papers we start from the assumption that the data in the paper was collected "honestly" i.e. that the researcher accurately reported to the best of their ability what they did and the data they collected. We then look at that data to ensure it looks consistent with what they did and that the method did not contain anything that might cause misleading data. Then we check that the conclusions in the paper are consistent with the data and analysis.

Peer review is there to prevent a researcher from fooling themselves (and others) by making claims that are not warranted by data or missing some subtle effect that could explain what is going on without the need for new science etc. It cannot check that the data are real although sometimes it can catch fraudulent data if that data are not consistent with well-known and established science. However, fakers are usually smart enough to be able to mske the data look consistent enough so it can be very hard to spot that in peer review. Ultimately it will get spotted as others try to reproduce results, faill and then start to look in much, much more detail at previous claimed results but peer review can't spot things at that level of detail.

Impact factor generally is a credibility factor or at least I do not know of any journal in my field where there is a low-credibility journal with a high impact factor, although there are some specialist journals - e.g. instrumentation - which are highly credible but with a low impact factor. Generally speaking though anyone in the field worth their salt will know which the good journals are and where a paper is published generally does have a large impact on how we regard its quality.

I do not see a good way for a "credibility factor" to be calculated in an objective manner that would not have significant negative repurcussions e.g. counting the number of retractions would be bad since it would encourage journals never to retract papers. Similarly even the best intitutes can hire rogue researchers - or more commonly have bad grad students or postdocs - and enouraging journals to accept anything from any researcher in a "respected" instistute to boost their credibility would be bad too. Also papers in many fields cannot and do not have a single "primary" author.

That is utterly wrong. As a scientist who has sat on several grant review boards there are no politicians involved at all in deciding who gets funding. The politicians set the size of the pot we have to give out but grant applications undergo rigorous, multi-stage peer evaluation. Even in the US where a single expert program officer has a lot of control over a grant program (or at least they used to) peer evaluation was still critical to the process. The only exception to this are "mega-projects" where the cost is so significant that it merits a line-item in the national budget and then yes, politicians obviously have to be involved but this is not where the vast majority of research funding comes from and at that point they are listening to the views of multiple experts and weighing in the national and political interests, not counting papers.

When grants are peer reviewed nobody just looks at the number of papers if the appilcants and goes "oh wow that guy published X papers lets give him everything he asked for!". Instead we look at the quality and impact of that work as well as what they are actually proposing. Different people weight these things differently - I tend to weigh the proposal more, others weigh past pulication record higher and both are very valid. However, in evaluating publications we use things like venue of publication (how many are in top journals for the field?) and citations (h-index) - although even then you have be to careful since that depends a lot on the field. Rate is a consideration but large numbers of papers in dodgy journals will count for nothing, indeed they would be detrimental since those reviewing it would be asking what he person is up to and how can they not know that the journals they are publishing in are trash.

They did learn but like any good follow-on they added a twist. Instead of the computer driven insane by its programmer, in the MS version it will be the user driven insane by the computer.

It will not be the chatter that kills this but the input bandwidth. Even if you assume it would allow you to set up some "verbal macros" to execute when a single word is spoken I can still click mouse buttons faster than I can speak words. The same goes for output bandwidth but even more so - it is much, much faster to see diagrams, buttons and read text then it is to listen to the computer speak information.

I can see this being useful in limited applications - such as in-car systems where a verbal inface and lowing bandiwicth would be a huge benefit. However, I cannot see it replacing a regular desktop/laptop OS.

I've trained many machine learning models as well, from BDTs through to GNNs but never an LLM - although arguably not entirely from scratch (except for an early BDT) since we used existing libraries to implement a lot of ML functionality and once setup we just provided the training data. If you really have trained an LLM "from scratch" as you claim then surely you must be aware of how inaccurate they can be? I mean even the "professional grade" ones like Gemini and ChatGPT get things wrong, omit details and make utterly illogical inferences from time to time.

I'd agree with the OP that you do not know AI - even if you are capable of building an ML model from scratch (I presume using a suitable toolkit so not realy from scratch) you clearly do not understand the reliabilty of its output or are incapable of seeing how that might be a serious problem when advising someone with mental health issues which raises questions about exactly how much you understand of what you might be doing.

The new law seems to be well written. All it does is ensure that a medical professional has approved the use of the system. It's the same type of protections we have for drugs, we do not just let companies release any drug they like before it has undergone testing and a panel of medical experts agrees that it is both safe and effective and even then they do not always get it right! How is it stupid to have similar protections for computer software used to treat mental health problems? It does not prevent you from using software in this way all it requires is that an expert has said that it is safe and effective.

That's probably why it is so useful for advertizing: the goal there is not to reproduce reality but an idealized approximation of it and some of the photoshopping ad companies have done in the past has produced results far worse than current AI is capable of.

Actually we "nerfed" the monarchy in 1649 while you were still part of the UK and still saying "god save the king!" from across the pond. It happened as a result of the English civil war that established parliament's pre-eminence over the monarchy - and the "nerfing" was pretty severe since Charles I was beheaded! While the monarchy was restored in 1660 it was as a figurehead position with little to no political power, or as you would put it, a severely "nerfed" version of what went before!

Even if you had not rebelled though you would almost certainly not be ruled over by the UK government by now, in the same way that the UK government has absolutely no control over Canada. Canada is a completely separate nation from the UK that just happens to have the same monarch as the UK. The two titles: King of the United Kingdom of Great Britain and Northern Ireland and King of Canada are entirely seperate and equal. However, I doubt Trump would be interested in a position as king though, while they do get a degree of deference, UK monarchs have not been able to rule by royal decree since we "nerfed" them and they are subject to the law.

Mathematician is a valid job just like any science specialization. What I fail to see is how these jobs are really vulnerable to AI. I can definitely see that the job will be transformed by AI - much like physics has been transformed by using machine learning for data analysis - but I do not see much chance that it will be eliminated by AI.

What I see happening is mathematicians using the powerful capabilities of AI to do more just like almost every other branch of science has so I see it more as tool that enhances the capabilities of people in such jobs, not as something that will replace them.

There was an interesting video related to this on the Smarter Everyday Youtube channel about trying to make something in the US. One of the problems a US innovator found manufacturing his idea in China was that once the manufacturer had run of the parts he needed, they then ran off more parts from themselves, added it together with cheap, shoddy components and then undercut the original innovator on price selling crap versions of the original patented idea online.

If the effect of removing this exception is that it motivates the development of more small-scale manufacturing in the US then the result may actually protect US inventors because it will let them build their devices in the US where it will be much harder to make illegal knock-offs and while the cost may be higher, and so volume lower, the result might be higher quality items in consumers hands and more money in the pockets of the actual innovators.

I'm not American so this does not affect me either way but I can't help but wonder whether this might help the US far more than it hinders....even an idiot can stumble into a good idea by accident sometimes.

True, but I expect that most if not all of them will come into existence more or less as negotiated, even the awful (for the EU) US-EU trade deal. This is because all our economies are currently strongly connected to the US and it is better to sign even a bad trade deal temporarily to give us the time to disconnect them than it is to unplug overnight.

I expect in a few years time they will go away as those of us outside the US have integrated with each other more and and no longer so reliant on the US. So enjoy your deals while you have them, I hope the cost to the US in terms of lost soft-power economic leverage was worth it even if it will take several years to become apparent but personally I do not think the world will be a better place when China takes over the trade pole position.

No it is not. Not knowing that you are wrong does not mean that you are not wrong. Ignorance is bliss, not being right all the time.

Besides, while Newton was definitely an incredible genius he was also an utter bastard - look up sometime how it dealt with Leibntiz and Hooke - so it is not only fair to say he was wrong, he very much deserves to be called wrong, even if you do have to admire his genius.

The problem is that quantum effect already has a clear definition which, as you say, renders the statement both true and it is trivial. What I suspect you mean is an observable effect due to quantum mechanics that is different to what is predicted by classical physics. Even then though we can easily see effects that can only be explained by quantum mechanics.

Actually we do because most of the light we see is reflected light that shows a particular colour because of the quantized absorption of certain wavelengths by the material it reflected off. Classical physics cannot explain the colours of reflected light. Magnets are another example and our eyes can even see single photons in ideal circumstances.

What I think you are trying to get at is a more general point: the behaviour of everyday objects is different to the behaviour of particles at the quantum scale and therefore we have not developed a language that can readily describe the nature of quantum mechanics. Hence, the limit we face with QM is not understanding it but in explaining our understanding to others because our languages (other than maths) lack the required concepts to properly communicate it. It is our human languages, not our senses, that are limiting us.