6,954 karma · joined December 27, 2018
I remember many years ago telling a senior executive that I had concerns that some of the steps we were taking to boost current quarter financials would negatively impact business performance in the long term. He just chuckled and said, "there's no such thing as the long term, only a never ending series of current quarters".
It points to an article on "The Information" as the source, but that link is paywalled.
> “We hate the model picker as much as you do and want to return to magic unified intelligence,”
> “a top goal for us is to unify o-series models and GPT-series models by creating systems that can use all our tools, know when to think for a long time or not, and generally be useful for a very wide range of tasks,”
> the company plans to “release GPT-5 as a system that integrates a lot of our technology, including o3,”
He even slips up and says "integrates" in the last quote.
When he talks about "unifying", he's talking about the user experience not the underlying model itself.
I'm not disputing that these later became the building blocks for computers, just as the quantum gate experiments being conducted in laboratories today may become the building blocks for quantum computers in the future. But that's not where we are now.
This is the real problem. Companies have ALREADY starting laying off significant percentages of their workforce because they're buying into the AI "digital worker" hype without any idea of how exactly AI is going to do the jobs of 80% of THEIR employees across all departments in the next year or so.
This needs to be a disclaimer on every discussion of "quantum computing."
A few years ago there was a recall of OnePlus cables that were melting and catching fire, I had 2 of them and both melted.
But yes 240W/48V/5A is insane for a spec that was originally designed for 0.5W/5V/100mA. I suspect this is the limit for USB charging as anything over 48V is considered a shock hazard by UL and 5A is already at the very top of the 3-5A limit of 20AWG for fire safety.
Try it with a 12L jug and a 4L jug and ask for 4L. See if it tells you to just fill the 4L or to fill the 12L and pour into the 4L twice discarding both times and there will be 4L remaining in the 12L jug.
Even though it's still technically correct, it demonstrates that there's no real "reasoning" happening just regurgitation of training data.