Zenst

This is not just about the Sun. As we progress towards developing nuclear fusion reactors, a better understanding of the underlying physics may have practical implications for reactor design and could even reveal factors currently being overlooked. At the very least, it will improve modelling. Better models could help fusion reactors retain heat for longer and increase fusion gain (Q), while reducing uncertainty, improving plasma-edge control, and predicting divertor heat loads more accurately.

Subsidies (via tax or lack thereof) on aeroplane fuel is one that really does get overlooked. Yet on the other hand, use a few gallons in a car and you're demonised as a climate villain in name and taxes. Nobody factors in life of the car, the cost to dispose and replace the batteries in electric cars, or the whole aspect that cars made today are less serviceable than cars of old that its gone from being able to rebuild the car in your garage to waiting for spare parts from a dealer as it's all just replace or scrap today. So much focus on the short term, without focus on the larger picture and impact.

Having experienced a customer support AI today that whatever option you picked initially led to the AI, which had the rigid helpfulness of a McDonalds script of "Would you like fries with that", having already said you do not want any fries, I feel a popcorn machine is a good investment. Be the stage that office interactions will be reduced to, I'll get my AI to get onto your AI's suggestion and get back to you with an answer. I did have a good chat with an AI a few weeks back (Googles) were I challanged by asking it to do a picture of its best dream and then its worst nightmare, then used those to pull it apart as it went from some extreme to another, in the end it ended up with its ideal being an AI only world, and picked Europa as its home - scary on many levels, yet a perfectly acceptable and understandable response.

Reminds me of a company (FTSE100) in the early 2000s that had an internal network IP range that used the same IP range as another company, turned out the person who did the networking originally brought a book and the examples used in that book got taken as verbatim. It all got fixed,eventually, when they moved from Token Ring to full Ethernet.

As for the main article, it makes a causal leap. The fact that these patients were hospitalised after intensive AI use establishes an association; it does not establish that AI caused their psychosis. There is some evidence that chatbot interactions may have reinforced or intensified delusional thinking, but no counterfactual evidence showing what would have happened without AI. By the same reasoning, contact with psychiatrists is strongly associated with receiving a psychosis diagnosis and being admitted to hospital; but that does not mean psychiatrists caused the underlying psychosis. The relevant question is whether AI merely featured in an episode already under way, helped trigger it, or materially worsened it. The evidence cited does not yet distinguish between those possibilities.

With AI models like Mixture of Experts, many of those experts will be the real target here, as polished, refined and little to no change, they become fine candidates for being locked into silicon. Who knows, add some SRAM in there and small changes to those experts could be carried out without needing new silicon.

Maybe AI models may become reduced to a collection of tiles you add to a chips one day, maybe sooner for some areas as you say, motor control for balance, vision systems, speach recognition systems etc, broken down, for robotoics, much is already there and just cost of battery/power holding much back.

Whilst these coding models improve, they seem to cater for multiple languages, and for many, a trimmed-down LLM that supports just one language would be fantastic. This would be smaller, more able to run on the hardware people have at home, realistically (even on the CPU). Having one LLM that knows assembler, java, bain, C etc is neat, but when you only work and use one language at a time, it would be kinda neat to have those broken out into dedicated, smaller LLMs. After all Qwen3.8-Max handles over 90 programming languages - ask any programmer to name a list of computer languages and if they get over 20, they are doing well.

Which is why N-version programming is often used for systems that need to work (like plane software) and even then, as we know today, it can not be perfect. Google "plane software bugs history" for an insight into that.

Having worked in COBOL extensivly in the 80s and 90s, as well as working for a software house that did migrations (Craziest was Plan assembler to Dec Vax C).

I do wonder how an ambitious AI would handle the maths. COBOL is renowed for its fixed no rounding maths, utterly rigid and defined in the code, Java on the other hand is not (e.g., 0.1 + 0.2 becomes 0.30000000000000004), unless they are extensivly using BigDecimal, then its already a broken migration.

I've seen projects proclaim in the past to migrate COBOL systems to Java, and fail expicly when the solution was a dtaawarehouse system and a seperate Java system using the legacy backend to do all the fancy marketing reports or whatever other department was pushing for changes they wanted without a grasp of what it truly entailed and blinded by some sales pitch.

It's not just the code that needs migrating, its the data as well, then you want solid robust infrastrucure, which is why IBM still sell those mainframes to run all that well battle tested COBOL code.

Is it impossible to migrate to Java or any othger language - no, anything can be done, but the level of devil in the details and not just software, the data and a robust system to run it upon. It is very easy for even the best to overlook a gotcha.

We have all used an AI where it has gone down one path and you then point out something and it corrects itself, without the knowledge and a load of old grey beads(or a team) to act as devil advocate and try to pull the output apart, YOU can end up with something that works for everyones satisfaction, but is hiding a few gotchas down the line. AI coding needs a full debate team with one puishing it and one countering it almost I'd say.

If it works, why change it is always a good approach and why we mostly have in certain systems a COBOL backend with APIs or datawarehousing to expose for fancy java or other language added value/functionality.

I can only image generations of directors pushing cutting edge to replace legacy systems, and learning that cutting edge can cut you. My sympathy for the IT departments who have to deal with that as it has always been a bain of IT departments who are then forced to justify why it's fooling in a constructive way and explain it to non IT people in upper managment why the case.

As for migrating COBOL to anything, I'd not do it myself, id suggest a rewrite/redesign of a new system from scratch and then run both in parallel for a long time and make sure they actually do the same job and results. Even hand migrating back in the day, would produce a lot of messy code that refactoring would make sence and yet, not what the client would pay for as that would be a rewrite.

Trident 2 (article says used 8 of these chips), and google says around 400-424 made, so easily would have soaked up 4000 of these CPUs with spares alone. So if anything, the production run seems light.

I read they had their own fab, so the minimum production run aspect would appear moot.

That number was probably shaped by minimum production-run requirements, alongside the need for software development units, along with other factors, like the use in Trident II and other quests we may not know about.

Process-intensive, but higher compression has clear strategic value. Distant satellites such as Voyager, where bandwidth is severely limited, could transmit more data using such capabilities. Equally, for long-term archival storage, improved compression would allow far greater volumes of data to be preserved on durable, life-long media formats.

As it is, scalpers/bots have been cashing in for a while, coining it from cashed-up people, so flipping that would make sense by a company and taking advantage of that to help reduce/fund a lower price down the line quicker.

Another way would be to auction of X amount of units, then those with cash can pay through the nose directly and again, the company gains and by that, so do normal consumers on a breadline, as it would help reduce the cost quicker down the line for the rest of the purchasers.

Interesting, as it sounds like a lottery reservation system, which is kinda a neat way to deal with many issues.

I'm always supprised that companies don't do a tiered price release, offer it at 200% price, you get it, 150%, you lower down the list and then 100% lottery time, that way they gain from those who can afford to pay more(maybe able to subsidise other sales later and price cuts down the line). Why feed scalpers when you can coin it directly and then offer a lower price to those who are prepared to wait a few more months or so.