I don’t think anyone in the org wanted to face the fact that the underlying assumptions in their model was flawed. The older an upvote the less reliable it becomes.
61,710 karma · joined September 21, 2007
I don’t think anyone in the org wanted to face the fact that the underlying assumptions in their model was flawed. The older an upvote the less reliable it becomes.
For most professionals it’s just safer to avoid having output in your workflow. Keep using AI, but stop copying and pasting AI output.
Sure you can combine this with a regular search but there’s opportunity cost whenever you say LLM + something else rather than just the other thing.
Calling out bias however is a standard practice for groups whose beliefs don’t match reality. You see that on political extremes, but also revisionist history, many religious groups, conspiracy theories, etc.
Stuff you can do for a week doesn’t automatically extend to maintaining that over the next 50 years.
You didn’t give any numbers, just stated things very confidently without actually reviewing any of the relevant literature.
> the false assumption that moving from each tier is a low probability event
Doesn’t need to be a low probability events, multiply probabilities and the result becomes less likely every single time. And that’s of course ignoring the underlying reasons why the probability at each stage isn’t low in the first place. A smart kid at 6 is unlikely to turn into a dumb kid at 16 etc.
The data doesn’t support that assertion. Elite collages do favor elite high schools, and elite high schools do favor elite middle schools etc but each link in the chain dilutes the impact of the steps further up the chain. Kids have many opportunities to jump up the chain before college and many to fail to keep up with the elite track. Which is why statistically elite preschools have such a minimal impact.
Of course that’s adjusting for the role of the parents which impacts attendance at elite schools but is obviously not impacted by their kids attendance.
Health and wellbeing pay the best dividends as you can maximize the nurture aspect of intelligence early and build resilience against unexpected hardships.
Note: * = Anchor player (fixed rating, used for calibration)
Programming state gets way more complicated, but code is generally written to help people understand it greatly simplifying the process. Feed in “cursed” code leveraging obscure language features in creative ways and LLM’s and most people fail.
Net effect you lose money living in a worse location.
You may discount England but it’s got enough DC links to move a large fraction of demand.
Japan has two networks for historic reasons, but they can move well over 2% of each grid’s average demand to the other. It’s just significantly less efficient but that’s relatively minor vs the other disadvantages of a split 50hz vs 60hz national grid.
This is a map of where the grid is frequency matched across internal borders allowing easy exchange. DC connections don’t need this synchronization, but it reduces losses with AC. https://en.wikipedia.org/wiki/Continental_Europe_Synchronous...
In war this might be a minor issue, but in war electrical infrastructure ends up a target so it doesn’t matter that much.
Chile still wants transmission north south because in the winter solar closer to the equator has longer days and in the winter solar near the poles does.
The old model of cheap peaking power plants and cheaper base-load power is equivalent to cheap peaking power + cheap but inconsistent green energy. It’s a very complicated optimization problem to work out the optimal mix of locations and quantities to of each, but price signals can help assuming you haven’t completely distorted the market.
Personally it wouldn’t be worth the money to me because the only thing that matters is the time to plug it in and the time to unplug it.
Plug in at home takes way less of your personal time than a gas station and costs significantly less than public charging.
LLM’s will happily regurgitate multiple paragraphs practically verbatim if you don’t specifically design them not to behave in this way.
Because ultimately when you design a system to best predict the next output based on a given input perfect replication of prior training is the correct response mathematically.
> not because of plagiarism concerns
I’ve second hand accounts of meetings focused on exactly the problem of how much verbatim text was being spat out and what to do about it. Some versions of specific models are far worse at this but it’s a huge legal liability not to address it.
You’ll get something to show up on schedule but it’s frequently needs to be returned because of a problem on their end. No I don’t accept paying full price for a used product in subpar repair. No I don’t want a convincing fake.
The hassle of even 1 return in 20 isn’t worth faster delivery. Worse even if I just throw away their junk I still need to make a new order.
Needs isn’t quite the right term as AI energy use is way higher than the market actually supports.
A large fraction of AI’s energy use is pure bubble me too redundancy. A long list of companies are doing essentially the same training with essentially the same data. When grok dies all that training goes away independent of any use of AI by consumers.
Similarly, by subsidizing usage with VC funds you get a lot of demand that goes away at market rates.
LLM intentionally randomize output to cover up all the plagiarism, but this largely destroys the consistency that cause writers to feel unique. Larger patterns still emerge but it just feels stale.
So you’re just clueless here, wow what a rude question.
Oxfordshire etc but most of the cost is stuff you’d see at any nuclear power plant.
> Only $11 billion of the $183.3 is true expending
That’s not how money works, there’s zero difference between a tax break and handing out money because money is fungible. The IRS will write you a check on a “tax” break.