Machine Learning vs. Deep Learning vs. Foundation Models

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The recent interest in AI as meant a lot of people have been encountering new vocabulary. Martin Keen is to help you sort it out. This video runs through key terms like machine learning, deep learning, foundation models, and large language models and how they're related to each other.

[@fxcheux1681]

I love this guy's energy, very informative

[@toenytv7946]

Learnt a new term claro. Like that and this. Great explanation!

[@prasadraavi390]

Beautifully explained. Thank you.

[@bobanmilisavljevic7857]

Great way to start the day 💪🤖

[@Ugk871]

Thank you for bringing this video

[@pankaj16octdogra]

Superb explanation

[@rodrigoherrera7392]

Your videos are amazing, thanks

[@JoeGariano]

Excellent!

[@hermenegildowilliam7938]

Very informative

[@FabrizioBianchi]

What is there under AI, other than Machine Learning?

[@michaeloguidan3038]

Hello, what about data science

[@rrbbb-qv9kv]

How do you write so well backwards on the glass?

[@IBMTechnology]

See ibm.biz/write-backwards

[@arrowhead261]

Where is NLP located?

[@andrewjohnson6792]

How valuable is data, authentication for the training of these tools, refined thoughts, at rapid speed. Would a new supply chain movement towards generating a new standardize benchmark system, be useful? Potential sufficient to correct the potential errors, of miscommunication via scholarly debate. Perhaps chaos, but perhaps the cure. 😅 all in the amount of effort

[@xaviermagnus8310]

Chaos. Pretty much every field breaks down to assumptions somewhere. A lot of words but no explicit gain in this. Any piece of data almost worthless. The mass has the value. You're assuming not only that there is a definite right/wrong... but that we know it well enough to be sure.

[@Cmpct3]

There's a huge circle that encapsulates all the boxes and it's called tooling. Not sarcastic.

[@KumR]

where does hugging face and cohere fall?

[@sk3ffingtonai]

eXcellent. Thank you.

[@revathik9225]

Where does NLP fit in?

[@user-il9vr9oe7b]

Multiple regenerated training data how is this used to reinforce data trends of the final output. I call the issue training Emphasis.

[@user-bh1pc1ck2w]

Awesome

[@AChang007]

Not sure I agree that RL belongs under ML

[@MilesBellas]

Enormity isn't size, it's more like being horrorified.