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The AI Revolution Hasn’t Happened Yet

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Re: The AI Revolution Hasn’t Happened Yet

#11
Michael Jordan is just mad he missed the boat on deep learning. Must be tough being that brilliant and at the same time get left in the dust by algorithms from the 90's and just sheer brute force. The AI revolution is here, from Google search to Uber pool to auto correct to recommendation engines, it is just a slow process.

Re: The AI Revolution Hasn’t Happened Yet

#12
The AI Revolution is happening right now. There's enormous proven potential which is materializing in ever increasing rates. The first generations of hardware accelerators are slowly coming out and they're going to leave everyone astounded.

It's a bit like the early days of the internet, it's not always the most practical solution, but it definitely works.

Re: The AI Revolution Hasn’t Happened Yet

#13
post #12

The AI Revolution is happening right now. There's enormous proven potential which is materializing in ever increasing rates. The first generations of hardware accelerators are slowly coming out and they're going to leave everyone astounded. It's a bit like the early days of the internet, it's not always the most practical solution, but it definitely works.

Do you have any examples?

Re: The AI Revolution Hasn’t Happened Yet

#15
What are we defining as AI now? It seems like AI has had a lot of hype in the past few years, but I really don't think we're even close unless it's created by mistake. We don't understand the brain fully, we don't understand consciousness, we just know so little in the grand scheme of things.

Do we have the computing power to come anywhere close to what we need, will we have that computing power any time soon without a major breakthrough?

Re: The AI Revolution Hasn’t Happened Yet

#16
> The problem had to do not just with data analysis per se, but with what database researchers call “provenance” — broadly, where did data arise, what inferences were drawn from the data, and how relevant are those inferences to the present situation?

Plug: I work at a company (https://www.pachyderm.com) whose product is designed precisely to track data provenance across pipelines and through a company's larger data-processing operation for this reason

Re: The AI Revolution Hasn’t Happened Yet

#17
post #5

I'm not an AI researcher (although from my internet reading that's not a hard title to claim ;)) but I feel that ML/DL can't go much farther than they already have. The concept of "we just need more power" is an obvious fallacy to me.

Humans are proof that machine intelligence can be improved quite a bit. We are just complicated machines, no?

I'm specifically talking about the strategies used in Deep / Machine learning to approximate intelligence through probability.

Re: The AI Revolution Hasn’t Happened Yet

#18
post #12

The AI Revolution is happening right now. There's enormous proven potential which is materializing in ever increasing rates. The first generations of hardware accelerators are slowly coming out and they're going to leave everyone astounded. It's a bit like the early days of the internet, it's not always the most practical solution, but it definitely works.

This exact tired old argument is being applied to: blockchain / DLT AI VR CRISPR in some senses

Unless you have a reason to compare it to the "early days of the internet", don't. A technology being new and unknown doesn't make it like the internet.

Re: The AI Revolution Hasn’t Happened Yet

#19
post #5

I'm not an AI researcher (although from my internet reading that's not a hard title to claim ;)) but I feel that ML/DL can't go much farther than they already have. The concept of "we just need more power" is an obvious fallacy to me.

'if I asked my customers what they wanted, they would have said a faster horse'.

Maybe throwing more power at the current solutions won't ever make the progress we want, we need to find our car, so to speak. And a lot of people are working on that.

Re: The AI Revolution Hasn’t Happened Yet

#20

> The problem had to do not just with data analysis per se, but with what database researchers call “provenance” — broadly, where did data arise, what inferences were drawn from the data, and how relevant are those inferences to the present situation? Plug: I work at a company ( https://www.pachyderm.com ) whose product is designed precisely to track data provenance across pipelines and through a company's larger dat…

You all should really play that up more in your messaging - "provenance" is one of the hardest and least-addressed components of building AI/ML/data science systems that actually have measurable impact (rather than analysts making plots and speculating). In general having a structured, centralized representation of business processes is super valuable I'm sure.

If you write a blog post describing how critical that is to practical data science efficacy with some examples I bet you'll end up in a bunch of VP inboxes.

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