h a l f b a k e r yA few slices short of a loaf.
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This AI program has a chat-bot interface. I give it material to
read and websites to look up. It reads them and analyzes the
until it has an "understanding" of how to program. This
means
1. It aquires a lexicon of words and phrases, and rules how to
use the programming language, and what
for. And then uses
this to broaden its knowledge by searching the internet and
reading relevant material.
2. The learning process is interactive with a human mentor.
You help it learn by
answering questions it has and pointing it in the right
"direction". But since the program itself is online it also
learns
how to search for answers to its own questions online.
3. Once its competent enough you can register it to do
online
courses and get tested.
4. In an advanced stage you can allow it to even post
questions
on Stack-Exchange, monitored at first of course.
5. At the final stage it learns to create programs upon
request
in natural langauge. You ask it to create a program that does
so
and so, it discusses it with you, does the web research and
comes up with the computer program that you want.
It will probably work for a narrow type of programming, but
lets get started.
Within a few years you'll have ASLPs who are experts in their
field, and who could make possible many new types of
applications. For example: Today, if I wish to make a
speech
recognition program for some isoteric language such as
Hebrew, or a program that analyzes and categorizes
handwritten letters from manuscript images, you need to
spend a few years and raise the money for programmers.
Here
you just put the computer to work and get your user
interface
and algorithms all by just managing your digital programmer
in
natural language.
It will learn how to do effective code review, and even how
to
clearly explain the concepts and algorithms that it came up
with.
It will learn how to keep version control, with good
documentary, readable also to humans.
The management will stay ours but the know-how will be
their's. (This will change at some point, and then we'll ask
them to write science fiction).
https://www.youtube.com/watch?v=G6Z_S6hs29s
YouTube: 14 Cool Apps Built on GPT-3
Some of these are cooler than others, but there's bash, react, html, css and other design/simple coding applications where GPT-3 accepts user input in natural language, and outputs functioning code. [zen_tom, Nov 09 2020]
https://www.youtube.com/watch?v=_8yVOC4ciXc
YouTube: GPT3: An E...del - Computerphile
Primer on GPT-3 an humungous pre-trained generalised language model with surprisingly good adaptation to what we humans normally consider quite specific tasks. [zen_tom, Nov 09 2020]
[link]
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Teach it to say "Well, it works on my machine". |
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Didn't they try something like this, with the result of it
"learning" about Pizzagate or some other nuttiness?
I thought I had read something like that. |
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Will you end up having to teach it Phenomenology ? |
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I think I've seen some GPT-3 work in this area - will try and
dig it out as a link. |
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This is already science fiction. Or fantasy. One small step above posting "lets make a computer that can fix any problem because it's on the internet" |
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People have been trying to accomplish exactly this for decades, and often enough using exactly this approach. |
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"Bot learning from the internet" has been tried, and it
failed. Because it learned from humans, and some humans
are idiots (especially when they're on the internet...).
Found it: TayTweets. Had to be shut down because of idiots
teaching it stupid stuff.
(Similarly, there was a Google sketch learning thing that was
useless, because people were giving it really crap (and often
completely wrong) sketches of the objects it requested...) |
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In answer to [neutrinos] and [Voice]: During the main stages
of learning, which may take very long and is an essential part
of the ASLP setup, It is a tool for the mentors, who are
teaching it how to learn, and putting it back on track when
things go awry. |
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And then there are [zen tom]'s links. |
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On the youtube from Zen tom's link to GPT3: |
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[00:10:20] but what about things like scientific papers? If you fed it enough science, enough scientific papers, do you think, could it come up with something that we've not really realized before? Or something new? |
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[00:10:29] Yeah, so my instinct, is to say NO. It's just predicting the next word. Right? It's just a language model... It doesn't have the ability to build the kind of abstract mental structures that you need in order to actually synthesize new um knowledge. |
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[00:10:56] BUT there's a kind of an outside view that says that we thought that about a bunch of things that it now seems to be doing so... I'm not gonna say that it definitely couldn't do that. So one example of a task which it got better at, tremendously better at, is arithmetic. Which is kind of an interesting task, because again, it's a language model, not trying to do arithmetic, it's not designed to do arithmetic. But in GPT2 if you put in two plus two equals, and get it to give you the next token, it would give you a four. But that's not very surprising. Like, that's not very impressive. Because You would expect to see in its dataset the words two plus two equals four very many times. That's pure memorization... |
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...[00:15:14] for 3-digit addition and subtraction, again it's getting like 80%, 90%, and that's a big jump from the smaller models. |
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...[00:15:24] what they're suggesting in the paper is that it has actually learned how to learn... like that's the interpretation that they're pushing. |
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But no. I think a dedicated model with terms from programming and graphics, and ways of solving certain known tasks could be achieved. ALONG with a GPT3 like model for all language which would assist (but only assist) the ASLT and be one of (but only one of) its many tools at hand. |
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