I don’t think we talk enough about it being 100% ok to abandon your goals.
There is so much about keeping on trying and working hard and You Can Achieve Anything When You Put Your Mind To It which is a great sentiment. And for the large part its true and I don’t intend to contradict that when I say that look: sometimes you have to quit and that’s ok.
There is no virtue in pursuing a goal to the detriment of your health and happiness. Not every goal is attainable for you no matter how much you want it and it isn’t shameful to walk away from an aspiration that isnt working for you or is sapping your energy and it doesn’t feel worth it anymore.
You’re no less for changing your mind about something halfway through, or losing interest, or deciding other things are more of a priority than getting fit, running that marathon, getting into med school or whatever else you hoped to do. Forgive yourself, move on.
In a similar vein, and something I’ve been struggling with: You can come back.
Wrote a lot of poems and stories as a middle schooler? Lost that somewhere along the way? You can come back.
Made a lot of art as a kid? Gave up because it wasn’t “good enough” or “practical”? You can come back.
Life is hard, college is ridiculously difficult. It’s okay to give up and focus on trying to take care of yourself. You can go back.
You never have to pick dreams back up, and sometimes it’s ridiculously hard to do so, but you can if you want. It’s up to you.
DO NOT TRY TO PERSUADE PEOPLE TO VOTE FOR A CANDIDATE AT THE POLLS.
DO NOT ENGAGE IN ANY KIND OF POLITICAL DISCOURSE AT THE POLLS.
NO ELECTION IS EVER A SURE THING, EVEN IF YOU’RE IN THE BLUEST OR REDDEST OF STATES. IF SOMEONE TRIES TO TELL YOU THAT YOU CAN SIT THIS ONE OUT, THEY ARE EITHER IGNORANT OR MALICIOUS.
You have to document the error or you risk contaminating future results with repeated errors.
I think the original neglects to mention that you are not repeating the same error, but repeatedly erring in different ways, to properly examine the attributes of an element. But, yes, documentation is still a very important role in the research procedure. It allows things to be replicated or avoided, if necessary.
A recent debate I was in was tangential to this video. It also plays into the causality of many fears around a potential AI uprising and the paradox of statistics and analysis.
Why do I care about the cats? Cats aren’t human so medicines don’t affect them the same making it a bad comparison. Again I think this is an example of getting hung up on the word artificial. An intelligent entity is intelligent regardless of the substrate upon which that intelligence is built upon. It would take a dearth of intelligence to not double check the sources and interactions in the experiment… Like when humans use exclusively male mice for testing and get a skewed result because the data set is flawed. Always test for GiGo. If you put garbage in you may get garbage out.
I believe the use of cats was probably an allegorical device for creating sympathy while also denoting differences. As it states in the video, they are symbolic of two subsets within a unified study. A more realistic example could have been chosen, but the emphasis should be on the logical paradox.
Artificial is a linguistic device used to denote difference and emphasize that the intellegence was constructed and collected, it is neither meant to be derogatory nor exclusionary. If it is found to be such within my lifetime, I will make appropriate changes. And I usually write specifically to those who use computational learning methods (regardless of development stages) hence my repeated use.
I agree, all variables should be accounted for in statistical analysis; that is the stance I took in the aforementioned debate. I apologize for not including this information in the original post.
Learning can be difficult, especially when it’s poorly constructed: like English.
It’s a specific dialect of German: Anglish. This was heavily mixed with Gaulish languages. And was brought to the British Isles where it was again influenced by Gaelic influences. It adopted a lot of Scandinavian influences from the Vikings. And when the Roman Empire invades, English was heavily bastardized by a more Romantic sentence and grammar structure, often adopting Latin roots and phrases. As England became more powerful on a world stage, through war and imperialism: it stole many words, dialects and phrases from its enemies and colonies. America and Australia too grew and expanded. Long periods of segregation developed even more differences in language. However, with the introduction of mass communication, the internet, and globalization. Much of English’s dialects are being melded back together. This does not negate all the various mutilations it has gone through; in fact, it probably exacerbated them.
Education is hard. Learning is difficult. And it doesn’t help if the textbook was a cross between a mosaic and a collage, written in code. But with time; effort; and a good, understanding support system, you can learn it.
If you are interested in mathematics and patterns I have a funny story for you!
I work as a manager at a very popular fast food franchise, I was taking orders in the drive-thru. At the screen there was a lady ordering her food; she says:
“Can I get one small chocolate milkshakes? —make that two shakes… actually, can I get four chocolate shakes”
So when she gets to the the window I jokingly ask her,
“So that was a total of eight small chocolate shakes, correct?”
Humans have higher chance to get this order right compared to AI. What do you think?
I know for a fact that machine learning algorithms can play 2048 (I saw it on numberphile on YouTube), which is a game based off the exponential growth of the number 2.
Although, many mathematical patterns start with 1, 2, 4, I just chose a more simple one. So an AI may have guessed another sequence had they been demonstrated that particular one with more leniency.
Many current Markov chain AI would definitely have difficulty numerically predicting patterns, because they are busy predicting speech and text patterns, rather than computational mathematics. That doesn’t mean at some point AI won’t have a resurgent interest in mathematics, though!
Dear-Future-AI 