18

Siri and co. are AI to some extent. The usual label is "Weak AI" (also called "narrow" or "soft" AI). It turns out the Wikipedia article on Weak AI explicitly refers to Siri: Siri is a good example of narrow intelligence. Siri operates within a limited pre-defined range, there is no genuine intelligence, no self-awareness, no life despite being a ...


11

Informally, AI-complete problems are the most difficult problems for an AI. The concept is not mathematically defined yet, as e.g. NP-complete problems. However, intuitively, these are the problems that require a human-level or general intelligence to be solved. Real natural language understanding is believed to be an AI-complete problem (this is also ...


10

Short answer: No. Longer answer: It depends on what IQ exactly is, and when the question is asked compared to ongoing development. The topic you're referring to is actually more commonly described as AGI, or Artificial General Intelligence, as opposed to AI, which could be any narrow problem solving capability represented in software/hardware. Intelligence ...


9

The "Turing Test" is generally taken to mean an updated version of the Imitation Game Alan Turing proposed in his 1951 paper of the same name. An early version had a human (male or female) and a computer, and a judge had to decide which is which, and what gender they were if human. If they were correct less than 50% then the computer was considered "...


8

I would classify both as having / using elements of AI, yes. But I wouldn't say either represents a truly "intelligent" (in the AGI sense) program. But here's the rub... as you'll see in other questions asking about definitions of AI, there's a sort of memetic thing where anything that AI begins to do successfully, immediately stops being considered "AI". ...


8

Yes, although how useful this AI can be is another question entirely. mpgac is a "minimally intelligent AGI" trained on the GAC-80K corpus of MIST questions. As a result, it should be able to "minimally" pass this test. However, being trained on the GAC-80K corpus obviously make it lacking for any practical purposes. From the README: Obviously this ...


7

I think it is mostly right. But not that intelligence is hard to define. In my opinion, it is simple: A is more intelligent than B if A achieves some purpose in less steps than B. It is functional/algorithmic efficiency. What is difficult to define is human intelligence. But when someone says, "No, X is not real intelligence," what they mean is that it ...


6

An umbrella term for the application of heuristic techniques to software development is 'Search Based Software Engineering' (SBSE). SBSE emerged as a distinct activity around the turn of the century, with a strong initial focus on automating the generation/prioritization of test cases. With respect to some of your specific queries: 1.2 Paper on Automated ...


6

The answer to your question is "In principle, yes" - in it's most general form, EQ testing is just a specific case of the Turing test ("How would you feel about ... ?"). To see why meaningful EQ tests might be difficult to achieve, consider the following two possible tests: At one extreme of complexity, the film 'Blade Runner' famously shows a test to ...


5

No. TL;DR: The Lovelace Test 2.0 is very vague, making it ill-suited for evaluation of intelligence. It is also generally ignored by researchers of Computational Creativity, who already have their own tests to evaluate creativity. Longer Answer: According to Google Scholar, there are 10 references to the "Lovelace Test 2.0" paper. All of those references ...


4

Typically, I think of intelligence in terms of the control of perception. [1] A related, but different, definition of intelligence is the (at least partial) restriction of possible future states. For example, an intelligent Chess player is one whose future rarely includes 'lost at chess to a weaker opponent' states; they're able to make changes that move ...


4

Interesting question. I don't think anybody knows a definite answer, but some rough-sketch ideas seem apparent. Think about what it means to you to be "self aware". You'll probably cite the way you "hear" your own thoughts in your head when you think about something. One can speculate that inside the brain, the various centers that are responsible for ...


4

The other answers are correct that machine IQ test results are currently not indicative of machine intelligence. One of the surprising facts of human intelligence is that performance on almost all cognitive tasks are correlated with each other; that is, there is such a thing as 'general smartness' and IQ tests attempt to measure that thing. People have ...


4

In machine learning you normaly split your data into 3 parts(80-10-10%). First part is for the training of your ML-model. The second part (10%) is the development set (or validation set). This is used as measuring your performance with various hyper parameters (e.g. in neural networks: layer size). After you found your best hyper parameters, you learn the ...


3

I am a future neurologist with a very complete understanding of linguistic processing in the brain. I am also an overprotective parent, so I monitor every phrase uttered to my child, and also completely determine all the books she reads in the course of her education. When my child writes a poem, then, I know the dataset on which her brain was trained, as ...


3

There are two main subjects you need to look at to understand the problem: The Turing Test The Turing test, developed by Alan Turing in 1950, is a test of a machine's ability to exhibit intelligent behavior equivalent to, or indistinguishable from, that of a human. wiki See also: Turing Test (Stanford Philosophical Dictionary) There is a linguistic ...


3

Shane Legg and Marcus Hutter proposed one in 2006. The main descriptive quotes (see the paper for the actual formula): Intelligence measures an agent’s general ability to achieve goals in a wide range of environments ... It is clear by construction that universal intelligence measures the general ability of an agent to perform well in a very ...


3

One of the challenges of AI is defining Intelligence. If we could precisely define general intelligence then we could program it into a computer. After all an algorithm is a process so well defined that it can be run on a computer. Narrow AI can be evaluated on its success at achieving goals in an environment. In domains such as computer vision and speech ...


2

I believe this is exactly the kind of test where Doug Lenat's cyc would do very well at ? But I can't answer the question : how much of that corpus could it answer correctly ? Probably quite a lot ! (and how many humans could pass that test ? probably not all of them, but many can...) [but is cyc considered an AI? probably not... so I may be out of topic. ...


2

There are really two questions here, that I can see. One is "what were the specific requirements of the original Turing test, as stated by Turing himself?" The other is "What should the specific requirements of a modern Turing test be?" Things have advanced a lot since Turing's day, and I think it's reasonable for us to consider extending/modifying his test ...


2

It all depends of what your A.I. can do. Even humans cannot do everything. If your AI program is so smart, ask it to take the general IQ tests for humans. Because the real IQ tests are made of several questions from different areas, so in that way you can measure IQ of your AI. This is because the IQ means the tests which are designed to assess human ...


2

According to the Wikipedia definition, a problem is said to be AI-complete if it requires generalized, human-level intelligence, that is, requires strong AI. The Turing test and its variants are the best ways we have of measuring this. See, for example, Turing Test as a Defining Feature of AI-Completeness. As suggested in this paper, in order for the Turing ...


2

To ask what makes a system intelligent almost begs the question 'in this context what do we mean by artificially intelligent?' which I think this what this question is really gearing towards. From my studies, I've come to see that 'Artificial Intelligence' is a catchy term to use but perhaps misleading, and it conjures up images of these self-driving cars ...


2

Short Answer, No. Explained, Siri and Cortana are just inference engines. Though how applaudable their ability to synthesize text from speech and parse lexical maps from the text using Machine Learning Techniques is, the artifact is still just a program, trained with substantial myriad of Q/A tuples, that generates an output given an input. Statistically ...


2

They are virtual artificial agents which exhibit intelligent behavior (AI). Tim Urban on Wait But Why website wrote the following: The software and data behind Siri is AI, the woman’s voice we hear is a personification of that AI, and there’s no robot involved at all. Source: The AI Revolution: The Road to Superintelligence Related: What is the ...


2

We don't know. However, an important line will have been crossed - it will be impossible to tell the difference between an intelligent agent and the machine by use of a text interface. Which is the main point of the test - "if it quacks like a duck". It is also an important philosophical point. Whether intelligence is defined purely by behaviour in an ...


2

"Consciousness" does not have a universal definition. However, if you are really into "consciousness", you should probably read about Searle's Chinese Room experiment or Marvin Minsky's society of mind. In my opinion, there are many more fundamental obstacles in current AI research that we have to tackle first. Furthermore, a more formal question would be ...


2

I think general artificial intelligence will only be possible with some form of self awareness included. Many aspects of human communication do not work if one of the communicating partners does not have self awareness. A good example are many of today's chat bots. They seem to not even hear what they say and only rarely seem to have episodic memory. ...


1

This evening I got inspired by this paper: http://www.dphrygian.com/bin/David-Pittman-GOAP-Masters-Thesis.doc (GOAP paired with the Command and Control Pattern) What do you think about this solution? Each goal has a relevance (that depends on the agent needs) When agent1 working on the "AskAgent2ToTalk" Action, it only sends a goal recommendation to ...


1

Not going into details of Stanford–Binet test, but just looking at wikipedia page it shows many subtests like knowledge, reasoning, verbal tests etc. Most of the efforts in the artificial intelligence today is directed into research of specific areas like computer vision, natural language processing, machine learning, but also combination of fields like ...


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