This is just redefining what counts as "real intelligence" to raise the bar.

Once we have computers that can think like humans, there'll be people saying 'oh, it's not real "understanding", it's just generating speech that matches things it's heard in the past with some added style', not realizing that the same also applies to human writers.

As long as the bar keeps rising and we've found business applications, there will be no AI winter.

It isn't redefining anything. There's a classification in AI research called "strong AI" that includes Artificial General Intelligence and machine consciousness. Current uses of ML are instances of so-called "weak AI" which is focused on problem-solving and utility.

No redefinition, and using proper distinctions takes nothing away from the accomplishments made in the field. We don't even have anything close to a scientific understanding of awareness or consciousness. Being able to create machines actually possessing awareness seems fairly far off.

Being able to create machines that can simulate the qualities of a conscious being, doesn't seem so far off. I suspect when we get there the data will point to there being a qualitative difference between real consciousness and simulated. Commercial interests, and likely government bureaucracy will have a vested interest drowning out such ideas, though.

The bar hasn't moved. We've just begun aiming at different targets. That we succeed in hitting the more modest ones only makes sense.

This is a nitpick but regarding "strong AI" and "weak AI", I take issue with the use of those expressions to refer to actual software systems, or to sub-domains of AI research. Those expressions in fact refer to two hypotheses pertaining to the philosophy of AI and not to any concrete AI research field. Even within the weak AI hypothesis, a system that perfectly replicates the appearance of human consciousness is not conscious. See [0]. Therefore the strong vs. weak dichotomy is unrelated to progress towards emulating human intelligence and behavior. It is concerned with the question of whether a certain fundamental barrier can be broken, not unlike the speed of light.

The meanings people ascribe to those terms nowadays are very diverse and distant from the original hypotheses. Sometimes language evolves usefully so that expression is easier and ideas can be conveyed more accurately, but I'm afraid when it comes to "strong" and "weak" AI, another, more damaging kind of semantic drift has taken place that has muddied and debased the original ideas.

Those terms are victims of the hype surrounding AI. I suspect this is part of why the field has trouble being taken seriously.

[0] https://ai.stackexchange.com/questions/74/what-is-the-differ...

AGI is not currently in scope for any solutions on the market. The current crop of AI systems are simply analytical engines.

AGI isn't something that is scoped. It must be painted.

Isn’t artificial intelligence a very broad term anyway, of which expert systems, statistics, fuzzy logic and all the new wave neural network / deep learning are examples?

You seem to be thinking about artificial general intelligence, which is much more difficult to achieve.

Time was that the term AI meant what has now come to be referred to as AGI or machine consciousness. Marvin Minksy wasn't looking to make better facial recognition, or better factory robots. His research was about making a mind.

Twenty years ago, that kind of work ran into a brick wall. But neural networks were still useful. Enter Machine Learning, and it borrowing the term "AI." But Artificial Intelligence, for many, always meant the dream of building R. Daneel Olivaw, or R2D2.

AGI is even difficult to define, it's still up for debate if/what is part of what we call intelligence and if it's present on animals and if it can exist without a "subconscious" or "feelings".

I don't know if Something that have a survival instinct is AGI but to me this is enough to call Strong AI. Does the Caenorhabditis elegans worm have AGI ?

The hard problem of consciousness, which everyone has a hard time defining?

I wonder if we could detect harassment today in a chat for example. With like GPT3 or something.

Highly unlikely. It's pretty much impossible to detect the difference between a friendly banter, a heated debate, trolling, and genuine harassment for most people given just a chat log.

There's often much more information required (prior communication history of the involved parties, previous activities in other chats, etc.).

Using automated systems like GPT-3 would simply lead to people switching to different languages (not in the literal sense, but using creative metaphors and inventing new slang).

Pre-canned "AI" is unable to adapt and learn and I doubt that any form of AGI (if even possible without embodiment) that isn't capable of real-time online learning and adapting would be up to the task.

Mmh I'm not convinced. There is pattern in aggressiveness. One of them being the harasser is talking about the victim or something that's strongly linked to the victim (like it's work, member of familly, etc).

We can, though the teams I know who are doing it are not using GPT-3. If you look at any platform that has live chat features (think Instagram Live or Twitch) and an ML team, then there is almost certainly someone working on toxicity filtering along with propaganda detection etc. It's a really really hard problem, particularly when you think about how chat platforms tend to develop their own short hand and slang.

A double bind detector!