The prompts provided to the LLM should be copyrightable as code and the code generated should be protected the same way compiled or intermediate code is protected.

The issue at hand is how the model was trained. And the users of the LLM should be made clearly aware by the model trainer whether the user or the model trainer is responsible for the liability related to using other peoples code for training the model.

That said, we should soon be seeing models that are trained using training courses rather than massive amounts of code. Once that happens, the models will make use of agents to search the web and learn from stackexchange or other sources how to solve problems the same way a human would. Of course, when a human learns how to do something from searching the web, simply copy/pasting other peoples code can be an issue and we have to read license restrictions. But learning how someone did something and doing it ourselves is generally safe. If a model reads an articles while searching and then learns how to do something, it should also be protected if it's not copies verbatim.

We have a lot of legalities to deal with.

1) Massive models are going to die. I don't know whether it's with wasting time with nonsense like OpenAI and Anthropic. They won't even be in business by the time the lawsuits come through.

2) Agentic models will be the focus of the future because they work more like humans. We give them the base information needed to learn and find the answers themselves. Using cloud based solutions where companies hosting the solutions keep massive amounts of data locally cached so the model can research faster could be an issue. But these will cost money and really just won't do more than local-AI will. They'll just be faster. For legality sake you'd want to avoid the cloud models since caching can be seen as theft. But, local-AI is much different. With agentic solutions, I think most legal issues are back to the same issues with copyright we always have. We just have to make sure our models which we use are following the copyright rules. If it's allowed, copy/paste. If it's not, then learn how it's done and make your own solution. In a perfect world, we'd then have a stackexchange or alternate github for AI generated code and post that different LLMs could use to learn from each other. The problem then becomes whether that would be seen as training a large model and whether they are in violation of copyright again.

So, the rest of the world can continue as usual and the US will be isolated.

Now, will the US owned TikTok or the Chinese owned TikTok win the competition.

I hope US tiktok gets banned here since I think the US just has too much influence on youth outside of the US

I expected it to take 6 more months. But, if they're playing the victim already, either it's time for them to cash in on patents or to sell off their shares while they can.

That's kind of hitting on the point but not quite.

IBM mainframes are online transaction processing systems. The language hasn't been and issue for a long time and it really doesn't take more than a few days for a programmer to learn to use COBOL. The problem is that JCL, RPG, CICS. DB2 and all the surrounding infrastructure is very confusing.

The uptime you're talking about is that a mainframe is basically a special purpose computer built specifically to make it so you can suffer loss upon loss upon loss and it will still keep processing transactions. This is because they have a specific workflow which is designed specifically to support this. I have implemented the exact same topologies and workflows using more modern tools on small computers ... because frankly you don't need big computers for this. And it works. I can scale almost infinitely and lose all but 2 nodes and it will keep chugging. But I'm not going to provide support on it and I'm not going to back my project with insurance company support.

IBM is offering a lot more than computing in the price they charge. That's the real issue. And no other company has built that up.

Great experiment but of course glass has some pretty obvious downsides. We tried something similar some years ago using a DVD laser and coated glass. It is extremely reliable and thankfully cheap. The problem is... how do you read it? There's no instructions.

The worst movie ever so see a screen... Contact... should have taught everyone in this business the rules of this.

"The medium is irrelevant if no one can read it"

and

"You have to leave Jodi Foster a key to be able to build a machine"

So, the beauty of metal is that you can etch it clearly at many levels. In fact, it makes an amazing analog media. What you do with the metal is that you calculate the analog image to etch on it. Then using a laser and the scanning head from a laser printer, you can pass the scanner across the metal and print. A4 paper size or a nice 210x210 square is great for this.

What will you print. This is interesting, you'll layer many images on top of one another at different resolutions.

The first image show clearly in mostly pictures that are readable with the human eye which will explain how the second layer can be read. It should be simple enough that the reader can build said machine by hand using simple tools. Or, they should be able to read it by hand by measuring. See, you're explaining binary and a simple table such as ASCII or a 5 bit subset of it. It should also contain a Rosetta stone to allow linguists to decipher the language.

The second layer explains that we're storing information that should last forever and is a history of our world. And it should describe how to read the third layer which is much denser and contains a more advanced machine. But because the materials required to read the machine may not be available, it also describes the method of storage as well as detailing the more advanced character set. It should describe that the card which has all jagged edges is a dictionary containing 10,000 commonly used words and their definitions. But that each layer and card will contain partial dictionaries around their edges at the 3rd layer.

Density wise, We've managed to simulate 6 layers on increasing density and complexity allowing for about 1tb per A4 sheet of 1mm platinum (I'm sure other metals will work, it was just a good starting point) and the layers of course last more or less time based on the frequency and detail of the layer. Of course, I included extensive error detection and correction on more detailed layers. The simulation suggested that we could store for about a million years (no real way to test) and that most data would remain readable.

Oh, and you could build the devices fairly inexpensively.

We've been testing this in 3 different nation's archival departments. It was really funny because when I met the people from the archives at a symposium, I asked why they weren't doing this. They were like "what" and I just blurted out the design while chewing my lunch. I mean, I thought the idea obvious and they had been wasting time on all kinds of silliness like what Microsoft was doing.

People need to watch more bad movies.

Dude, I like going to the shooting range. I think it's fun. I don't imagine I'll ever own a gun and I'm not particularly interested in making guns.
That said, I think the second amendment is definitely taken greatly out of context. We are honestly using the thoughts and ideas of people who lived 200 years ago to have the slightest idea what makes since in terms of things like state run militia. And we're also using their perspective on what makes sense when the entire population of the US was 2.5 in 1776. 2.5 million people barely counts as a single city in 2026.
3 out of 10 people I know who own guns are precisely the people I would not like owning guns. These are the people who own guns because they're really into guns and they're really into gun ownership rights. I'm pretty ok with the other 7 out of 10. So, I think gun ownership should simply be highly regulated.

So, solving a network issue, 4 senior network engineers with a combined 70 years of experience and close to 100 Cisco certifications between us (at least until I decided not to bother anymore) were trying to get a complex VPN routing issues between 3 sites working while not sacrificing security. Everything worked except this one little thing. We use hours troubleshooting... and the pizza arrived.

I configured SSH (with temporary keys) to login to all three routers and three endpoints with administrator privileges. Then I opened SSH and explained
"This is the details of how to connect to these devices. These devices are located on these sites with these addresses. These devices should be able to communicate like this, not like this. We are sitting down to eat pizza. I can't be bothered with this shit anymore. Please fix it."

So, we 4 sat around watching the 85" TV like it was a sporting event and the AI chugged as we ate pizza.

And we watched...

Right as the AI started down a rabbit hole like "If we went here, we know that it's time to start reinstalling and go from the beginning".

And then it said "The systems can now talk together as you described".

WTF!!!!!

I wiped the grease of my fingers and we checked and I wrote

"You listened to the letter of the request, not the spirit. You got two computers talking, not the networks. Please fix the whole problem"

And 5 minutes later... it was done.

The AI was better than we were and we were like "Thank god we can make it to retirement.... the kids are fucked"

If only someone though it would be a good idea to make a much cheaper design that could be tried over and over again until the kinks were worked out rather than spending obscene amounts of money on trying to get something so unimaginably complex right on the first try and it costing so much that you can't even financially budget for another try.

I have been cutting bloat like Tailwind by using LLMs. After all, Tailwind is a tool which makes life easier for me as a programmer at the cost of efficiency. I basically stopped using web toolkits now. I just tell the LLM to build from scratch what I need most of the time.

I think the best one was when I wrote a parametric CAD program recently (not a web project, C# on the web this time), and I needed a specialized PDF export engine because the existing ones cost money or sucked. So, I told the LLM what I wanted and it did an amazing job. It coded everything I needed for high quality PDF output with font embedding that actually works with Affinity (no font embedding works with Affinity), and it did it in 30 minutes or less.

Tailwind is definitely a goner. We don't need CSS tools when the AI's can do the job more efficiently without them... and no, we really don't need to be able to read the code. We have unit tests for verification.

Give credit where it's due.

I basically stopped using Google most of the time because I could use Copilot for most things. So, I suppose if I were to measure, I google about 70% less than i used to. I mean, most of my googling was figuring out how to do things and these days, I spend my of my time telling copilot to figure out how to do things instead.

That said, I tend to Google when ChatGPT is failing. And well, it fails a lot. It's really just not a very good product.

So, then I use Gemini through Google and more often than not, it gets it right when OpenAI bombs it.

Gemini has become a better set of models than ChatGPT. I probably wouldn't even use ChatGPT if Windows wasn't so utterly intertwined with it.

That said, I pay $10 a month for AI. I have my own LLM server and it's based on a $120 graphic card and it's getting REALLY good now. I don't think I'll be using cloud llms much longer. Thinking models don't need to be big. So, a 10-16GB GPU should be enough. 24 would be nicer for a longer context length though. It's pretty funny that Qwen 2.5 7b actually outperforms the biggest and baddest models if you use it agenticly and tell it to just figure it out. It doesn't need to know absolutely everything. it only needs to know how to research and take notes as it goes along.

Is this the new version of saying something like 'Thanks boomer"?

I was able to use this fancy new invention you may have missed called a hyperlink to look at your commenting history. Apparently, like myself you spend too much time on Slashdot and make allusions to things like tape recording off the radio which even suggests we're in the same approximate age group.

The big difference is, I write shit comments the length of small novels, you like one liners. We both seem to follow the pattern of offering nothing of any value and coming off as arrogant prigs.

I see you like to say things like "I use slackware with systemd" with pride rather than shame. Do you also listen to vinyl for that true sound and use a tin percolator to get that coffee how it was meant to be flavor? I assume you also take pride in walking past the Starbucks and every time you pass one you point out that their coffee is .. actually what do you people use as an insult for mainstream coffee?

Anyway, I assure you, there was no ChatGPT involved. I'm just a sad and pathetic late-middle-aged man like yourself. I tend to prefer to embrace intelligence rather than embracing masochism so I might to hold on tight to that lovely old tech because it's my woobie. I use Slashdot as my outlet to try and see if I can get someone else to agree with my opinion anonymously... again like yourself.

  The one liners... god.. they're probably even more annoying that my books. It's like a MAGA hat, designed to be endearing to people who can't handle more than 4 letters in a thought.

What surprises me isn't that China has been doing it. I think that the UK was in fact the country which glorified spying and government espionage for decades. Even now, I still remember Gorbachev crediting James Bond as the biggest single cause for the rise of Putin. The UK LOVES spying. They think it's sexy. They love the suits and the cars and let's never forget Q, the true hero in the movies.

So... why would the brits ever be surprised that someone would be spying on them using tech?

I think what's really amazing is that they didn't realize this sooner.

Doesn't this kind of prove that the UK government is criminally stupid that they never stopped it... and yes, it is absolutely preventable. Even the US manages to secure presidential communications and we see what their leadership looks like.

So, here's the real question.

If the brits have done nothing to secure their prime minister's communications, then who else is listening?

Next, how did it happen? Did they do it using government mandated back doors in encryption? After all, only criminals have anything to hide.

Even better... shouldn't we be impressed that the technology allowed probably every government with a spy network to all spy on British leadership without each other knowing it.

Or did they all know it?

I can almost imagine spies from the US, Russia, Israel, North Korea, China etc... all sitting at a Starbucks listening to a speaker together. Hell, I can even imagine at the next table, a british spy, an american spy, etc... all listening to Xi. Do they date each other? I mean, think modern nerd 007. Does the British spy get the girl? Maybe a sexy hungarian who is in the process of spying on Putin?

What about when people need sick days? Does the Chinese spy call the Taiwanese spy and ask "Can you share your notes with me today? I need to stay in bed"

This new generation of chips from Microsoft, Google, and Amazon are insanely impressive. I mean really really impressive.

What happens to them when they are no longer economically viable for Microsoft, Amazon, and Google?

I have made my side hustle for years teaching data center training courses using outdated data center technologies. For example, I'm still running a pretty considerable cluster of E5-2600v1 servers with 2TB of RAM. They cost me a small fortune to buy, but I paid far less than the cost of a single node retailed for for the whole cluster including massive network bandwidth (the thing I actually teach).

Almost everything I do depends on buying other people's junk and milking the remaining life out of it.

I suspect that Google, Microsoft, and Amazon will make about a million chips each of this technology before the next generation rolls out. They will also produce large motherboards with custom chipsets, though I expect them to be mostly broadcom switching silicon or similar. But whatever happens, there will be about a million chips worth of Maia 200 AI silicon that will be worthless in a year or two and will head to dump. It will have precisely 0% reusability because the ecosystem will be 100% closed.

Should these companies be legally required to make these boards more open? In other words, should it be required that they should make it possible for the recyclers to reclaim more than just rare metals from the boards? Should someone like myself be able to buy this trash and use it for 5-10 more years as compute? Should their stack be open sourced or licensable or even just downloadable as binary?

First of all, I'm guessing he probably writes most of his stuff in Ruby. It's a shame. He could probably write much better systems in a proper language.

Next, he apparently doesn't know how to use LLMs for coding and he insists on making nonsensical observations about tools he doesn't understand.

LLM is the name of the programming language. As with any programming language, you can learn to code it in a few minutes. But if you want to claim proficiency, it takes 12-18 months of daily usage.

LLM is not a replacement for the programmers. LLM is the tool the programmers use to make systems. And someone who uses Ruby should understand this better than most. Anyone could write hello world in Ruby. But it takes 10 years of daily use of Ruby to make code that isn't just disgusting. Sadly the Ruby code itself is worse than the code that most people write in Ruby.

So, if you sit down and choose to develop a project. You open up your word processor and you design a project plan and break it into steps of development and then you feed it to the llm which implements each step. You then verify or implement the mcps to automate verification and you move on to the next step.

He's a fool who is trying to replace programmers with LLMs rather than replacing inefficient programming languages like Ruby with LLMs.

I think that there's also the issue that he's hoping it will generate good Ruby code... here's a little secret.... not even the best LLM will ever be able to do that.

P.S. - there's a reason Ruby never really caught on. It was the worst language and toolchain to curse the earth. Oddly Rails was great. But what's the point of a tool written for a language that never had a decent implementation? You might was well have used Ada.

He's been using electronic instruments for ages to produce music. I know for a fact that his bass effects are produced by computerized synthesizers.