Hacker News Reader

Comment by AndrewKemendo | Hacker News Reader

You're missing the point.

We expect that DNNs will a fundamental thread to computing going forward. AFGAM has effectively locked up all of the talent and data in the broadest markets already. Not only that they are building and deploying the frameworks that new products will be built on in those other markets. So they don't need to create the product, they just need YOU to use Tensorflow or CUDA or whatever they come up with that runs on GoogleCloudGPU or Azure Compute etc...

What you're missing is that it's not about making a few million as a startup. It's that they are so far ahead in what is the most fundamental game changing, final human technology that I don't see a future where they are unseated.

View on HN

While deep learning and related technologies are exciting and extremely powerful, they have not yet proven that they will achieve the "final human technology" status that you are proposing. We may be centuries away from that, and at this point trying to speculate is foolish. However, even if they don't live up to those lofty outlandish prospects, they will still prove very valuable and useful.

What is "proven" to you? I mean, the tech displayed today is basically unmatched by most humans. Curating the best shots in Google Photos, all the integration with Google Home, Lens that can identify almost any object in meat space... the list goes on and on. It is not going to regress somehow... I mean, it is probably exponentially increasing in power by the day.

There is no AI competition against a company that has Tensor Processing Units among the absolutely incomprehensible data store that Google has amassed.... Especially if you are not some world class mathematician or computer scientist. The best you can hope for is to be acquired if you are in the ML/AI space as a stand-alone entity. In most cases they can probably safely ignore the bulk of AI startups.

That's still only computer vision and speech recognition. Google still does piss-poor at answering your questions using snippets.

It seems like picking the best photos, at least, is a pretty forgiving task. It's subjective, and I expect people will accept any set of pretty good shots.

Also, those TPU's are available for rent.

Definitely forgiving, but I think you are missing the point. The fact is, Google owns the whole process from top to bottom.

Nice that TPU's are available for rent, but to what end? If I run something truly innovative on their hardware (TPU), with their software platform(Tensor)...is that actually innovation, will they have the means to just copy it? How do I compete with that?

Would you say the same thing of Go or Chrome? These are tools anyone can use. Building something higher in the stack isn't cheating, it's just reuse. (Snapchat is built on Google Cloud, for example.)

As always you want to be careful about dependencies, but that doesn't mean rewriting everything.

Yes, I would, as there is no way for me to truly compete with Google if I am using their tools. The premise is so flawed that I have trouble even formulating possible counter arguments you may suggest.

I use chrome and little snitch is always telling on it. It calls home so much that I have just given up in order to have a decent experience and gave it full connection rights. I don't know how much of the browser Chrome owns, but I guess it is not insignificant. That is a lot of data that I will never have access to... let alone for my family nor on at Google scale.

Netflix uses AWS and competes with Amazon Prime... I get it. I do think that no one knows the whole story.

Getting back to OP... it has to be damn tiring/frustrating to even contemplate competing in AI/ML space with these big mega corps. I simply would not, that ship has sailed.

That's the age old question - what if Facebook copies what you did, in a week? Like they did with Twitter or Snapchat?

By the time they copy you, you're already big. I don't really see the problem as long as the tech companies don't hoard the information and spread the knowledge - which they are doing with initiatives like OpenAI and many more.

The big question is, what happens when they invent AI that builds its own programs and exponentially accelerates? Who needs startups at all then?

Bull. Instagram is eating Snapchat for lunch right now, for starters. Twitter is going down in flames soon enough as well. There is a massive consolidation taking place in social, and I think with tech in general. We are at a point where automation, AI/ML and resources are the next battle grounds. Sure there will be wins here and there, but like the app stores in 2014... the gold rush looks like it's over.

So in your opinion having accurate visual recognition/identification is the final human technology? We can stop now?

No, you didn't read what I wrote: It [Google AI efforts] are not going to regress somehow... I mean, it is probably exponentially increasing in power by the day.

They not only have custom silicon (TPU), they have the software too. Do you have extraordinary insight|foresight|genius or have you discovered/developed a major breakthrough in AI/ML? If not, good luck competing with these companies. It is a resource problem at this stage, as consolidation happened and there is no going back.

I don't know - maybe I'm just irrationally optimistic but I don't believe anyone has "locked up all of the data".

You can download the whole Wikipedia data dump at under 100GB uncompressed (text only - with media is around a TB). The entire common crawl with 3bn pages is only around 250 TB. While the Wikipedia dataset is too large to fit in ram for most people and the common crawl is too big to fit on a single disk, you can process these in your own local cluster quite easily and relatively cheaply.

Honestly I think the real breakthroughs to be made will be algorithmic and I don't believe those are out of reach for "civilians" outside of the tech giants.

While I think OP is a bit too pessimistic, in a way s/he is right. Facebook can design a simple experiment, implement the changes in their whole platform, roll out, gather data, and iterate on it.

You are stuck with 25TBs of wikipedia for the rest of forever. And "academic datasets".

Because the important data is probably not inferable from web links or otherwise semi-passive Internet structures.

That said, I think the missing component is still a good mind theory.

Humans don't run split tests on alternate realities but they can learn from wikipedia alone - I think we just don't know quite how yet.

We need a lot of data currently because algorithms don't generalize like people do.

I'm not convinced you need to be a tech giant to be able to make that breakthrough - I think it's a problem of approach, not a lack of data.

People ingest a lot of data. Especially when they are young. They touch everything, look at everything in funny ways, chew on things, and so on. Try to interact with everything to gain data.

It's just not textual.

Great, so who are the people going to make those breakthroughs?

Last I checked they all work for...AFGAM (or are teaching)

> final human technology

Can you share your reasoning behind this opinion? Humans have invented a lot of tools and technological platforms over the years, what makes you think ML is the final frontier?

A lot of people have written about this over the years. I'll just let Yoshua Bengio go into it:

[1]https://www.youtube.com/watch?v=ZHYXp3gJCaI

> that I don't see a future where they are unseated.

The way I see it, consumers (at least right now) are free not to buy into the hype and consume whatever it is that these companies produce. So if prices are too high or quality too low, a new company can enter in.

The real danger I see is the possibility that essentially all consumers will be forced to pay for this stuff through some regulatory capture, in a similar fashion to the state of the healthcare industry in the US.

Reply on news.ycombinator.com