A transcript of those meetings would be worth reading.
How far are we from "Microsoft Middle Manager 2.0 with passive-aggressive set to low?"
This seems to describe the MBA exam part of that paragraph.
If we don't teach this, we'll forget how we got computers to do arithmetic in the first place. Not teaching basic arithmetic skills would be unconscionable.
Laying foundations (counting, numerals) will take years sure, but they will be useful over various domains, but specific techniques shouldn’t be drilled. They are simple enough to pick up once matured a bit.
Like someone said, why calculate sin(x) when you can use a lookup table. I mean, sure, do it a few times when you are ready to appreciate it but forcing it down young kids’s their throats for years on end is detrimental.
Look at who wrote it:
https://www.ft.com/madhumita-murgia
https://www.ft.com/bethan-staton
Do you think either of these people have an innate understanding of the education system and its syllabus? They're journos. One of which is their dedicated AI hot take specialist.
It's a throwaway piece that's a vehicle for ads.
I don't.
You have so many decisions to make that need you to evaluate how much is something: shopping, working, cooking, driving, voting, reading the news... If you have to get your phone out of your pocket every time you need to decide something, this gets you out of the flow.
More concretely, we already just teach kids that the trigonometric functions are essentially black boxes, you can just look up sin(x) in a table, someone has calculated it already. It doesn't mean we've "forgotten" how to calculate sin.
Personally I think mental arithmetic is worth learning as it gives practice in working with numbers and as a first algorithm. Maybe it should be expanded earlier to other concepts like modulus.
However, contained within the process of learning long addition is a microcosm of our mathematical praxis: useful parables about logic, pattern, deduction, notation, communication, quantity, and more. There is a great deal to be derived from its study which, by scaffolding young minds, leads to more mathematical scientists, and hence value for society. I would have great difficulty arguing the same for calligraphy.
I don't always go out walking because I have somewhere to go!
"I swear this essay is free of AI generated content or plagiarism. Every analysis that indicates otherwise is a lie, and every dumb AI that indicates otherwise must be deleted."
https://www.theatlantic.com/technology/archive/2022/12/chatg...
The appearance of LLMs has been the strangest phenomenon. If course not everyone agrees, but I feel like I'm watching the arrival of the automobile and am having people say to me "It's loud, it's slow and it breaks down often. There's nothing to see here. It's just a fad.".
Just about everyone in tech I know in person in their 40s and above, believe this will be the biggest thing since the internet. People who have been in tech long enough to actually see transformative technologies arrive - People who saw the rise of the web, and dotcom bubble, and open source, and mobile w/ app stores... They all are looking at this and saying this is gonna be huge.
And for the most part the people pushing how big it isn't going to be mostly seem to be in their 20s and 30s who haven't really lived through a tech revolution who are saying it's not much, and over hyped. People who have grown up during the hype bubble, where grifters have been hocking crypto or NFTs or rug pull du jour seem to be least excited. As one of the people in the older category, I'm starting to think another casualty of the hype bubble era is lots of technologists (especially younger) now have trouble recognizing revolutionary technology.
In the end, one of these two camps will be wrong. Each assumes it will be the other. It's just incredible to see the split in opinion.
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Note: The internet is large enough that there are obviously people who are outliers to the above categories on the internet, but the general trend seems to hold.
> They all are looking at this and saying this is gonna be huge.
It's beyond me why would anyone assume an LLM that's already been trained in most relevant and available data will just keep becoming somehow way better and smarter. I get that it has it's uses, but what do they mean by huge anyway, theoretically it could end up a huge mess too.
* There's really bizarre tendency of that group to woo-woo and anthropomorphize all those language models. I get answers like "oh it just knows" or "you should try it" when asking probing/hypothetical question.
Compare that to a list of examples and documentation on generic issues/topics, without ever going into the specifics of a reasonable question.
Apply this to any kind of knowledge.
I think that it is a wonderful tool for education, and it is indeed changing the pace at which people learn.
I also like that it’s a judgment free tool where I can ask as dumb a question as possible without fear of being mocked or chastised.
I wanted to learn how transformers and attention mechanisms work in details. After reading a bunch of books I went into analysing an example LLaMa implementation in NumPy - since it was just a few hundred lines, I pasted all the code into ChatGPT, and kept discussing the most difficult lines.
It was extremely useful in that role. Broke down with some more complicated matrix computations and some nuances of attention mechanisms, but besides that - worked awesome.
The Great Narrative is in full swing, spoilers it's all bullshit.
The narrative when this comes up always seems to be about defending the current system as if everything is going so great as is.
In the piano analogy mentioned, it does feel like we spend time drilling scales and tuning the piano at the expense of the average appreciation for music. A good system for producing a small amount of future piano virtuoso while most end up not wanting anything to do with music at all.
Some people have an innate interest in some topics. Some don’t. Some that don’t can develop one if properly prompted at different times in different ways. Others never will.
I fail to see how forcing anyone is supposed to help. It’s only a symptom of an earlier failure.
I for one am glad that some preferred playing the piano, and were given the freedom to, to solving n-degree polynomial equations. Because I sure can’t be bothered to learn to play, and I definitely like listening to some of them.
Source? Are you referring to gpt 4?
What about private data sets / corporate IP?
What about my private data, such message and email history, contacts’ available or privately shareable data, my photo and video library, and health data?
Presuming all of this was included in an LLM directly or as some kind of additional LORAs.
It seems clear to me that the tooling and resource requirements prevent anything near full accessibility of the content that is there.
The math-and-adjacent cohort you mention would like to avoid another "AI winter".
It's possible "you should try it" is a UX use case indicator that (perhaps akin to engineers who don't understand why normies buy iPhones) those telling you this feel you're missing something essential about the experience of this tech's utility: "You may be right, but this works for me, while whatever else you're on about ... doesn't."
As for woo woo, this is the first time the big statistics are indistinguishable from magic for them, passing the Turing Test en masse.
Who has more to lose with the advent of such a tool?
It's almost impossible for me to believe that even 1% of HN readers can start a friction fire.
And then you'd have people who learned in some outdoor survival course, etc. Obviously this will vary from country to country, but surely it's higher than 1%?