"macOS 27 Beta Boots Asahi Linux Off Apple Silicon "
I initially thought the above headline meant "MacOS capable of running Asahi Linux on Apple Silicon"... where as it appears the article is instead about almost the opposite, an incompatibility with a recent Apple change hampering its ability to run Asahi linux.
Most people simply don't care because they feel no need to hide anything.
I'd rephrase that as: Most people don't understand how much they have to hide, and -- because it's daunting for them to create an alternate tech ecosystem for themselves -- they psychologically push aside whatever nagging worries they have about what they might indeed want to hide.
Put another way: people are addicted to the current status quo, and trapped by their lack of tech expertise. Which is not the same as objectively self-assessing that they have nothing to hide.
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
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?...
an amusing example of how training can go wrong
My understanding is that this isn't a consequence of a flawed training algorithm or process; it's instead a consequence of the limitations of LLMs, emergent from their training materials. It closely parallels another example I've seen around the net, that of asking an LLM about getting a car to the mechanic, noting it's a sunny day and the mechanic is just a block away, and having the LLM suggest walking... which is a consequence of the bias in training materials toward walking because lots of people make visible posts about their having done so (because it's looked on favorably), whereas people who drive short distances (of which there are many, probably outnumbering walkers) don't trumpet having done so online, leading LLMs to emit advice about walking when possible (and in the case of the mechanic example, having a lack of comprehension of the pivotal aspect of having the car make it with you to the mechanic's shop).
...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:
"Fire Phone" is a terrible name
I suggest "Layoff Phone".
Windows is now slower than Linux.
To be clear, this was true over 20 years ago. (In light of which, the word "now" probably doesn't belong in the above phrase, since it implies recentness.)
It is sad to see an innovator lose out,
They were first to market, but I don't think of them as having invented the product.. The emergence of chatbots seems inevitable once the paper in 2017 was authored by several google engineers (titled "Attention is all you need")... it was just a question of exactly who and when. If OpenAI hadn't gone first, someone would have shortly after.
And, in a lot of ways even that google paper's "breakthrough" wasn't so much the tech (neural nets) but the precise adaptation of it that made it highly parallelizable.
And a necessary ingredient was tons of data, and processing power. So this couldn't have happened in a garage operation like the innovators of yore. And the biz models they're all coming up with are all cloud based -- not that I don't see the profit motivation, but so utterly to the exclusion of any offering that could guarantee privacy; all we "know" about chatbot conversation privacy is what each vendor claims at the moment,, which isn't much, wouldn't be verifiable if it was, and could change on a whim tomorrow.
For these reasons, I don't attach much "early innovator" romanticism to the players here.
"Just the facts, Ma'am" -- Joe Friday
