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).
"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.
because careering neutrons leave no trace of their activity behind
It's always this. Neutrons are "the little MBAs" of the subatomic world, and they chew through role after role so quickly that it can be dizzing to trace. Compounding the issue is that most subatomic particles don't take the time to fill out their LinkedIn profiles.
We still remember how to do things without AI, I mean, it's been maybe 3-4 years now?
I asked chatgpt how long it has been part of culture, and it confidently said it's been 26 wonderful years.
"The Computer made me do it."