Recent comments in /f/MachineLearning

he_who_floats_amogus t1_j44k1rd wrote

Reply to [D] Would you consider the computer program Theo Jansen used to design the Strandbeest (beach walking mechanisms) to be Machine Learning? by lavaboosted

I’m going to say no. Machine learning is a field largely dedicated to methodology that improves performance of an agent at fulfilling some task, whereas a genetic algorithm is a heuristic approach that can be used to find optimal (enough) solutions to some specific problem, which is how it used in this case.

It’s not a good or bad thing, these are just categorical descriptions of types of things, which are meant to help us delineate. All algorithms that produce an output have now “learned” something (the output!), but to say that any machine that could be interpreted as having learned something is tantamount to machine learning is too broad to be linguistically useful, and isn’t what is being denoted by the categorical description.

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Ucalino t1_j44hgn1 wrote

Reply to [D] Has ML become synonymous with AI? by Valachio

No. Good old expert systems, which are other kinds of AI, are still very common in a lot of industries. While there is very little research on this kind of AI, there is a lot of work and engineering applied on it.

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Sirisian t1_j44fz5x wrote

Reply to comment by wind_dude in [D] Has ML become synonymous with AI? by Valachio

> now AI is AGI

It's not. Keep correcting people. AI is task or multi-task specific. It's perfectly fine for someone to say ChatGPT is a dialog AI, for example. It completes tasks (multiple in this case) using an artificial intelligence that happens to be created using machine learning techniques.

What you're describing in your second part is AGI. Non task-specific problem solving at the level of a human. The boundary between advanced AI, especially multi-task learning models, and AGI will get smaller and fuzzy in the coming decades, but there is a difference. There will be very advanced AIs that check a lot of boxes researchers create. When an AGI is created there are effectively no boxes left to check. The system can collect data, reason, and create a logical solution for any test way outside of its training data.

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sabertoothedhedgehog t1_j44ff9b wrote

Reply to comment by sabertoothedhedgehog in [D] Has ML become synonymous with AI? by Valachio

I should explain to be useful:AI is the vision and effort to replicate human intelligence. Human intelligence includes learning from data (--> ML). But one could argue there is more to it, e.g. knowledge bases etc. This is not something typical ML algorithms consider (LLMs do that indirectly). Also, our current ML models are still super narrow. The idea of AI is general intelligence.

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codemaker1 t1_j448ig5 wrote

Reply to [D] Has ML become synonymous with AI? by Valachio

They are not synonymous. It's hard for a layman to grasp the difference so it's called AI in the media. That's also probably why big companies call their teams AI teams publicly. Laymans make the public names at big companies and have to make it easy to understand hard things.

ML is a subset of AI: https://www.researchgate.net/figure/Domains-of-AI-ML-DL-and-widely-used-algorithms_fig1_361501987

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