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There's a lot of fiction around JARVIS but I believe there are things that "could" be possible. But, you've got experience and have done research so that doesn't really apply here. IMO it is better to give people an idea of the scope of the difficulty of their tasks so they can decide what they want to do more realistically. People who are just getting started tend to be really optimistic in general, so they pop in with really high expectations. We should probably be more generous with our assumptions, sorry. Honestly, we get all sorts questions here, so some of the responses you are getting might be not be assuming that. Of course I am not that idiot to want to build a military-grade AI robot at home. This is fun programming which I really really enjoy.
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This is a side/fun project, something just like "I want to be a pilot" for some people. I would also want to program this system to write its own small programs/scripts so it can expand on itself. I don't care about fancy stuff, just make something VERY basic work. Then I want this service to find patterns in information (possibly NLP here) and the most difficult/impossible part could be to reply to questions.
#BUILD JARVIS AI DEGREE PDF#
from various text files, websites, pdf ebooks or images. I want to find a way to feed this machine information e.g. a Raspberry Pi with a core service (brain/heart) that controls subsystems/services (openCV for vision etc.). What I want to accomplish is to setup a dedicated device e.g. I can see the pattern and the algorithm that improves behind that. For example, (I guess that's supervised learning) finding interesting personalized news to show to me, movies or music. Voice recognition, text to voice, some neural network pattern matching for each field but very specifically. I've researched solutions like Siri and open source ones like M圜roft AI. and ML (finished some books and uDemy courses about Tensorflow). I've been an engineer for the past 12 years and I've programmed in a few languages and big, demanding web apps. Thanks for your serious and detailed reply.
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On the bright side, the failure-paths of each of these steps will probably still be pretty good. Maybe Apple would like a general machine intelligence, they don't have as much data as Google, so they might want a machine that is better at abstracting on their limited data. This will be hard, because many of the major machine learning players are major players because their workloads are well suited to the current paradigm.
#BUILD JARVIS AI DEGREE SOFTWARE#
So, the steps would be:Ģ) Come up with a revolutionary theory that upends the field.ģ) Become employed by a major company that has the software development resources to implement that theory. It isn't at all clear that the currently popular strategy of convolutional neural networks will ever be able to form a general intelligence - they just compact old knowledge, they don't generate new thoughts (but maybe that's all there is to intelligence. Sometimes very clever pattern matching, but it isn't anywhere near the type of general intelligence that J.A.R.V.I.S. Current "AI" is mostly just pattern matching.