maltelau
Joined 8 years ago
Joined 8 years ago
From the article:
> The self-driving bus, with passengers onboard in Gothenburg, braked suddenly and was hit from behind by a tram.
They are also by far the biggest (measurable) eeg signal change you can manipulate intentionally (other than motion artifacts). Closing your eyes or focusing your attention inwards reduce the power of those oscillations so much it's visible right away just looking with your eyes at the signal trace.
It would be very straightforward to program in decision points to the light show where someone can select an option by tuning their attention inwards or outwards.
TLDR: It's the "press X to doubt" of human-computer interfaces.
> There are fewer and fewer organizations protecting civil rights without being dragged into left/right tribalism.
I would rather challenge this image that civilization is declining, independently of the political forces in power. This is a common motif in facism; I'm reading from your comment something along the lines of: "once we had noble organizations that were pure and didn't bother with ideology -- now things are worse, and in fact those guys are dirty for engaging in politics". What's really happening is that power in the US has been seized by fanatics and you fucks (respectfully) are letting them get away with it.
Who's organizing a fork, or is python back to having only shitty packaging available? :(
Accuracy and reliability are necessary to know real productivity. If you have produced code that doesn't work right, you haven't "produced" anything (except in the economic sense of managing to get someone to pay for it).
For example, if you produce 5x more code at 5% reliability, the net result is a -75% change in productivity (ignoring the overhead costs of detecting said reliability).
https://en.wikipedia.org/wiki/Electromagnetic_absorption_by_...
(The above is my human sarcastic attempt at hitting a sycophantic tone common to chatbots today)
git commit --fixup <sha>
and git rebase -i --autosquash <previous-sha>
do what you need? Random blog link explaining it: [1][1] https://fle.github.io/git-tip-keep-your-branch-clean-with-fi...
Ads are 509 pixels wide coming in 3 ... 2 ... 1 ...
The canonical approach is to build a generative model with a parameter (or multiple for ~anova) that codes for the difference between groups and do inference on that parameter of interest. Most of the recipes taught in statistics classes can be modelled as a regression of some kind (this counts for frequentist stats too, see https://lindeloev.github.io/tests-as-linear/ ). Some advocate to do that inference with bayes factors. Others, like discussed elsewhere in this thread, advocate combining the resulting posterior with a cost/value function, but either way the lesson is that there is less focus on "t-test-vs-anova" because they're the same thing anyways.
The point is that while LLMs can solve the puzzle when the constraints are unchanged -- as you said, there are loads of examples of people asking and answering variations of this puzzle on the internet -- but when you change the constraints slightly ("you can open the door to look at the bulbs and use the switches all you want") it is unable to break out of the mold and keeps giving complicated answers, while a human would understand that under the new constraints, you could simply flip each switch and observe the changes in turn.
A similar example that language models used to get stuck on is this: "Which is heavier, a pound of feathers or two pounds of bricks?"