Meanwhile back in 2002 from What's the Business Case for Microsoft and Open Source?

With apologies to Dr "Suse", to the tune of "Green Eggs and Ham".

Linux can. Linux can .Use Linux

That Linux can! That Linux can! I do not like that Linux can!

Do you like open sourcing plan?

I do not like that Linux can. I do not like the open sourcing plan.

Would you like to free source share?

I would not like to free source share. I would not like it anywhere. I do not like open sourcing plan. I do not like that Linux can.

Would you like it very stable? Would you like it to enable?

I do not like it very stable. I do not like it to enable. I do not like to free source share. I do not like it anywhere. I do not like the open sourcing plan. I do not like that Linux can.

Would you use it in a X-Box? Would you use it if it ROCKS?

Not on X-box. Not if it rocks. Not if very stable. Not to enable. I would not let them free source share. I would not let them anywhere. I would not allow open sourcing plan. I do not like that Linux can.

Would you? Could you? In your biz? Use it! Use it! Here it is.

I would not, could not, in our biz.

You may like it. You will see. You may like it if it's free!

I would not, could not if it's free. Not in our biz! It should never be!

I do not like it on the X-box. I do not like it that it rocks. I do not like it amongst our biz. I do not like it that it is. I do not like they free source share. I do not like that anywhere. I do not like that Linux can. I do not like you Linux man!

service! service! service! service! Could you, would you, as a service?

Not as a service! Not if it's free! Not in my biz! Man! Let not it be! I would not, could not, on a X-box. I could not, would not, if it rocks. I will not use it if its stable. I will not use it even to enable. I will not let them free source share. I will not let them anywhere. I do not like open sourcing plan. I do not like that Linux can.

Say! if in copyleft? always free copyleft! Would you, could you, copyleft?

I would not, could not, in copyleft.

Would you, could you, why so nervous?

I would not, could not, I'm NOT nervous. Not as copyleft. Not as a service. Not in my biz. Not if it's free. I do not like that it can, you see. Not if it's stable. Not on X-box. Not to enable. Not if it rocks. I will not let them free source share. I do not like it anywhere!

You do not like open sourcing plan?

I do not like that Linux can.

Could you, would you use what we wrote?

I would not, could not, use what you wrote!

Would you, could you, to avoid your bloat?

I could not, would not, avoid bloat. I will not, will not, use what you wrote. I will not compete with them as a service. I will not because it makes us nervous. Not in our biz! Not if it's free! Not if it is! You let me be! I do not like it on the X-Box. I do not like it that it Rocks. I will not use it if it's stable. I do not like that it does enable. I do not like they free source share. I do not like it ANYWHERE I do not like open sourcing plan!I do not like that, Linux can.

You do not like it. So you say. Try it! Try it! And you may. Try it and you may, I say.

Man! If you will let me be, I will try it. You will see.

Say! I like open sourcing plan! I do! I like that, Linux can! And I would use it because it's stable. And I could use it to enable... And I could charge for providing a service. And I could copyleft without being nervous. And in my biz. And still source free. For you can still charge for a service fee!

So I will use it on the networked X-box. And I will promote it because it ROCKS. And I will use it because it's stable. And I will use it to enable.

And I will use it here and there. Say! I can use it ANYWHERE!

I do so like open sourcing plan! Thank you! Thank you, Linux man!

By The Cat with the Red Hat

,,, we accept selective amnesia in our politicians every single day. Every time they show a public face. In all political parties. We know it and ignore it. Bit of a double standard to call it out here.

Jensen Huang to college grads: "Run. Don't walk" toward AI

https://www.axios.com/2026/05/...

Nvidia founder and CEO Jensen Huang told graduates at Carnegie Mellon University in Pittsburgh yesterday that demand for AI infrastructure is creating a "once-in-a-generation opportunity to reindustrialize America and restore the nation's capacity to build."

Why it matters: With many college grads fearing AI could obliterate their career dreams, Huang pointed to boundless opportunity as a "new industry is being born. A new era of science and discovery is beginning ... I cannot imagine a more exciting time to begin your life's work."

Nvidia, which makes AI chips, is the world's most valuable company. Huang told 5,800 recipients of undergraduate and graduate degrees that the AI buildout will require plumbers, electricians, ironworkers, and builders for chip factories, data centers and advanced manufacturing facilities.

"No generation has entered the world with more powerful tools â" or greater opportunities â" than you," he said. "We are all standing at the same starting line. This is your moment to help shape what comes next. So run. Don't walk."

"Every major technological revolution in history created fear alongside opportunity," Huang added. "When society engages technology openly, responsibly, and optimistically, we expand human potential far more than we diminish it."

Full speech: https://www.youtube.com/watch?...

...like "Tell me about Tiananmen Square" or "Tell me about Xinjiang".

Is this what you want for the future?

My thoughts back when R1 came out:

https://www.afcea.org/signal-m...

Don't you mean "from the well duh! dept"?

I never said Folding@home was exactly like modern AI algorithms that accomplish the same thing. I used it as an example of datasets being farmed out to many nodes for processing using specific algorithms.

Modern AIs like Alphafold3 are trained using these large datasets, possibly even including results from Folding@home, and applying modern LLM AI algorithms to find results.

The point I was making is that these AIs are trained on a specific set of datasets and targeted towards a specific purpose. Unlike general purpose AIs which are trained on the garbage heap of the Internet and only occasionally find a nugget of gold

Again tldr; AI trained on specific datasets: Useful. AI trained on the Internet: Crap

I am impressed that algorithms trained on specific datasets have improved to the point whereby they can find solutions to protein folding, or discover new drugs. The principle is not new however, it has just vastly improved in speed and efficiency
You may or may not recall Foldit@home or Seti@home which used a similar principle, but spread it out amongst many nodes.
These are instances of using large datasets from within a specific field where the algorithms of AI are useful and certainly impressive

What is not impressive however, are the LLMs trained on datasets taken from every corner of the Internet and then pretend to have all the answers. There is a large amount of slop/crap/bs on the Internet and these general purpose AIs are not trained to tell the difference between that and useful/factual data.
Sure if you want it to write a piece of fiction (though the output may not actually be worth reading), or to create a piece of artwork it will likely perform well. But if you're using it for serious work/research then much of the time you will get slop. Garbage In/Garbage Out

tldr; AI trained on specific datasets: Useful. AI trained on the Internet: Crap

97.94% of the energy required to power a Flux Capacitor fitted to a Delorean going at 88 miles per hour in order for it to leave 1955 and instantly arrive in 1985.

The Alexa division has never been profitable.

https://www.wsj.com/tech/amazo...
https://www.mobileworldlive.co...

You can bet that a part of the Alexa+ strategy is to turn that around. You are going to see tons of ads, those AI CPU cycles are super expensive.

Thinkpad 701C with a Framework brain transplant ( work in progress )

War is Hell

War isn't hell
War is war and Hell is hell, and of the two, war is a lot worse.
How do you figure that, Hawkeye?
Easy, Father. Tell me, who goes to Hell?
Sinners, I believe.
Exactly. There are no innocent bystanders in Hell.
But war is chock full of them. Little kids, criples, old ladies.
In fact, except for a few of the brass, almost everybody involved is an innocent bystander.

That's a spicy meatball!

So lets all get AI to create a bunch of BS videos and get Gemini to watch them. And then get Gemini to create a bunch of videos based on those same videos, and then watch those. Wash, Rinse, Repeat...

They already have an OS - what they need is an editor :)

...an article worth considering from Princeton University's Zeynep Tufekci:

We Were Badly Misled About the Event That Changed Our Lives

Since scientists began playing around with dangerous pathogens in laboratories, the world has experienced four or five pandemics, depending on how you count. One of them, the 1977 Russian flu, was almost certainly sparked by a research mishap. Some Western scientists quickly suspected the odd virus had resided in a lab freezer for a couple of decades, but they kept mostly quiet for fear of ruffling feathers.

Yet in 2020, when people started speculating that a laboratory accident might have been the spark that started the Covid-19 pandemic, they were treated like kooks and cranks. Many public health officials and prominent scientists dismissed the idea as a conspiracy theory, insisting that the virus had emerged from animals in a seafood market in Wuhan, China. And when a nonprofit called EcoHealth Alliance lost a grant because it was planning to conduct risky research into bat viruses with the Wuhan Institute of Virology â" research that, if conducted with lax safety standards, could have resulted in a dangerous pathogen leaking out into the world â" no fewer than 77 Nobel laureates and 31 scientific societies lined up to defend the organization.

So the Wuhan research was totally safe, and the pandemic was definitely caused by natural transmission â" it certainly seemed like consensus.

We have since learned, however, that to promote the appearance of consensus, some officials and scientists hid or understated crucial facts, misled at least one reporter, orchestrated campaigns of supposedly independent voices and even compared notes about how to hide their communications in order to keep the public from hearing the whole story. And as for that Wuhan laboratoryâ(TM)s research, the details that have since emerged show that safety precautions might have been terrifyingly lax.

Full article