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Comment by ianbutler | Hacker News Reader

Has it been over hyped? Some ML created in the last 8 years is in most major products now. It has been transformative even if you don’t see it, is informing most things you use. We’re not close to AGI but I’ve never heard an actual researcher make that claim or the orgs they work for. They just consistently show for the tasks they pick they beat most baselines and in a lot of cases humans. The models just don’t generalize but with transformers we’re able to get them to perform above baselines for multiple problems and that’s the excitement. I’m not sure who has overhyped it for you but it’s delivering in line with my expectations ever since the first breakthrough in 2013/2014 that let neural nets actually work.

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It's just that the day to day instances of "AI" that you might run into are nowhere near the level of hype they initially got. For instance all kinds of voice assistants are just DUMB. Like, so so bad they actively put people off using them, with countless examples of them failing at even the most basic queries. And the instances where they feel smart it looks like it's only because you actually hit a magic passphrase that someone hardcoded in.

My point is - if you don't actually work with state of the art AI research, then yeah, it's easy to see it as nothing more than overhyped garbage, because that's exactly what's being sold to regular consumers.

I agree about the assistants that they are not as much as I would expect but also there are self driving cars heavily using a.i. even at the current state I am personally impressed or indirectly we get the help during pandemic for protein folding/ mRNA vaccine development [1] , I also remember a completed competition for the speeding up the delivery of cold storage mRNA vaccines to quickly figure out which ones could fail

[1] https://ai.plainenglish.io/how-ai-actually-helped-in-the-dev...

It is overhyped because in the end it has failed to deliver the breakthrough promised years ago. Car drinking cars are a great example.

The AI that has taken over google search has made a great product kinda of awful now.

What breakthroughs are you referring to?

A. Most people still think Google search is good. B. Unless you work for Google specifically on that search team I'm going to say you don't know what you're talking about. So we can safely throw that point away.

I've implemented a natural language search using bleeding edge work, the results I can assure you are impressive.

Everything from route planning to spam filtering has seen major upgrades thanks to ML in the last 8 years. Someone mentioned the zoom backgrounds, besides that image generation and the field of image processing in general. Document classification, translation. Recommendations. Malware detection, code completion. I could go on.

No one promised me AGI so idk what you're on about and that certainly wasn't the promise billed to me when things thawed out this time but the results have pretty undeniably changed a lot of tech we use.

Why would you discount someone who has been measuring relevancy of search results and only accept information from a group of people who don't use the system? You are making the mistake of identifying the wrong group as experts.

You may have implemented something that impressed you but when you move that solution into real use were other's as impressed?

That's what is probably happening with the google search team. A lot of impressive demos, pats on the back, metrics being met but it falls apart in production.

Most people don't think Google's search is good. Most people on Google's team probably think it's better than ever. Those are two different groups.

Spam filtering may have had upgrades but it is not really better for it and in many cases worse.

Maybe because a single anecdote isn't really useful to represent billions of users? They have access to much more information.

I used it in real use, the answer was still a hard yes.

One of Deepmind's goals is AGI, so it is tempting to evaluate their publications for progress towards AGI. Problem is, how do you evaluate progress towards AGI?

https://deepmind.com/about

"Our long term aim is to solve intelligence, developing more general and capable problem-solving systems, known as artificial general intelligence (AGI)."

AGI is a real problem but the proposed pace is marketing fluff -- on the ground they're just doing good work and moving our baselines incrementally. If a new technique for let's say document translation is 20% cheaper/easier to build and 15% more effective that is a breakthrough. It is not a glamorous world redefining breakthrough but progress is more often than not incremental. I'd say more so than the big eureka moments.

Dipping into my own speculation, to your point about how to measure, between our (humanity's) superiority complex and with how we move the baselines right now I don't know if people will acknowledge AGI if and until it's far superior to us. If even an average adult level intelligence is produced I see a bunch of people just treating it poorly and telling the researchers that it's not good enough.

Edit: And maybe I should amend my original statement to say I've never heard a researcher promise me about AGI. That said that statement from DeepMind doesn't really promise anything other than they're working towards it.

Shane Legg is a cofounder of DeepMind and an AI researcher. He was pretty casual about predicting human level AGI in 2028.

https://www.vetta.org/2011/12/goodbye-2011-hello-2012/

He doesn't say so publicly any more, but I think it is due to people's negative reaction. I don't think he changed his opinion about AGI.

If we are going to start saying "but it hasn't achieved X yet when Y said it would" as a way to classify a field as overhyped then I don't know what even remains.

I mean, Zoom can change your background of video in real time, and people all over the world do so every day. This was an unimaginable breakthrough 10 years ago.

>This was an unimaginable breakthrough 10 years ago.

We had real time green screens 10 years ago. I don't think it's that unimaginable.

What does that have to do with AI though??

How do you think that's done?

Definitely not with AI?

I mean Photoshop could do that 10+ years ago without "machine learning" even being a thing people talked about.

This is sort of the interesting thing with AI. It's a moving target. Every time when an AI problem gets cracked, it's "yea but that's not really AI, just a stupid hack".

Take autonomous cars. Sure, Musk is over-hyping, but we are making progress.

I imagine it will go something like:

Step 1) support for drivers (anti sleep or colision).. done?

Step 2) autonomous driving in one area, perfect conditions, using expensive sensors

Step n) gradual iteration removes those qualifications one by one

.. yes, it will take 10/20 years before cars can drive autonomously in chaotic conditions such as "centre of Paris in the rain". But at each of those steps value is created, and at each step people will say "yea but..".

Arguably most autonomous driving solutions can already perfectly emulate typical driving in Paris in the rain.

And you'd be wrong. The key part here is "live in real time video"

Photoshop definitely cannot do that, I know that for a fact.

https://towardsdatascience.com/virtual-background-for-video-...

There's an example article on the subject.

I just don't see how that's AI , sorry. Machine learning to recognize a background isn't AI.

ML is most certainly AI. I had a visceral feeling you'd respond with this. Sorry but what ever magic you have in your head isn't AI -- this is real AI and you're moving goal posts like alot of people tend to do.

You have single cell organisms which are able to sense their nearby surroundings and make a choice based on the input - they can differentiate food from other materials and know how to move towards it. They are a system which can process complex input and make a decision based on that input. Yet you wouldn't call a basic single cell organism intelligent in any way. The term usually used is that it's simply a biochemical reaction that makes them process the input and make a choice, but you wouldn't call it intelligence and in fact no biologist ever would.

I feel the same principle should apply to software - yes, you've built a mathematical model which can take input and make a decision based on the internal algorithms, if you trained it to detect background in video then that's what it will do.

But it's not intelligence. It's no different than the bacteria deciding what to eat because certain biological receptors were triggered. I think calling it intelligent is one of the biggest lies IT professionals tell themselves and others.

That's not to say the technology isn't impressive - it certainly is. But it's not AI in my opinion.

> We’re not close to AGI but I’ve never heard an actual researcher make that claim or the orgs they work for.

The fact that the researchers were clear about that doesn't absolve the marketing department, CEOs, journalists and pundits from their BS claims that we're doing something like AGI.

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