9 ms·

To me, the particular use case and whether it is fair use or not, is of minor interest. A far more pressing matter is at hand: AI centralization and monopolizat

by fleddr 5y ago

To me, the particular use case and whether it is fair use or not, is of minor interest. A far more pressing matter is at hand: AI centralization and monopolization. Take Google as an example, running Google Photos for free for several years. And now that this has sucked in a trillion photos, the AI job is done, and they likely have the best image recognition AI in existence. Which is of course still peanuts compared to training a super AI on the entire web. My point here is that only companies the size of Google and Microsoft have the resources to do this type of planetary scale AI. They can afford the super expensive AI engineers, have the computing power and own the data or will forcefully get access to it. We will even freely give it to them. Any "lesser" AI produced from smaller companies trying to compete are obsolete, and the better one accelerates away. There is no second-best in AI, only winners. If we predict that ultimately AI will change virtually every aspect of society, these companies will become omnipresent, "everything companies". God companies. As per usual, it will be packaged as an extra convenience for you. And you will embrace it and actively help realize this scenario.

tvirosi 5y ago
I largely agree. But there are still some fun opportunities around. One are things google would never touch because of PR reasons (e.g. state of the art scalable face identification). Another is just silly out-of-the-box creative uses of AI which wouldn't fit well with Google's brand.
jspaetzel 5y ago
If Google makes an amazing model that no-one can beat it will only be dominate as long as others get access to it freely. But if there are restrictions on access or if it's too expensive, other options will appear and even if they're not as perfect, they'll still be very usable. Imagine a coalition of companies all feeding data, that could compete just as well.
- est31 5y ago
  Google has all the data of all the users though. I'd wager that they won't just let AI companies scrape it.
  - londons_explore 5y ago
    I don't think Google uses user photos to train their photo search algorithm. They use photos from the web for training, and then user photos are only used for the actual indexing.
ncr100 5y ago
I think it's an innate quality of technology. Yes sophisticated AI tech concentrates power for those who already have power. And the technology we all (presumably readers of HN) create can enhance the impact of the user. And this can result in unfair circumstances, in reality. Law and force can prevent disproportionate use of power. Of course one must define the law, which may be done AFTER the offense has been committed. Further, if those who make the laws are corrupted by those with e.g. this AI tech power, then no effective law may be enacted and the hypothetical abuse will continue.
mtrn 5y ago
The final step is to break down these monopolies. The government can do that and has done it before.
mikewarot 5y ago
I have about 300,000 photos that haven't been scanned by AI (unless someone at Backblaze did it without permission). I'm sure there are lots of other photographers out there who miss Picassa, which Google killed off to push everyone's data to their service. (It did really well in matching faces, even across age, but the last version has a bug when there are multiple faces in a picture, sometimes it swaps the labels) If there were offline image recognition we could train on our own data privately, could the results of those trainings be merged to come up with better recognition on average than any one person could do themselves with their own photos? In other words, would it be possible for us to share the results of training, and build better models, without sharing the photos themselves?
- mostdataisnice 5y ago
  While interesting, we don't know enough about how models are learning to where we would be able to consider doing this.
- cgio 5y ago
  I am not an expert on the field. But my hope was that this could be facilitated by Transfer Learning. Still don’t know how the scale economies could be achieved. Maybe just out of the sweat and network of passionate people like in the case of open source.
  - Mehdi2277 5y ago
    I work in the field. Transfer learning helps get you decent/good models, but the best models remain ones trained on large amounts of data. You may be able to get away with good performance and not great on your task. For some areas you really care a lot about long tail performance (like self driving) that you will need massive dataset. For other areas if your goal is to be the best relative to other large companies you will need a massive dataset. Transfer learning best use cases are for fast prototypes or for ml tasks that do not need state of the art performance.
    - mikewarot 5y ago
hexa22 5y ago
There is a second best though. Apple offers image AI which is worse than googles but wins because it works offline.
aeyes 5y ago
For years we thought Google Translate was the best machine translation we would ever get. Then DeepL just popped up out of nowhere and today other services still didn't manage to catch up. Every now and then you get someone to think about an old problem on a clean sheet of paper and you might get a better result with less training data / investment.
sgrove 5y ago
I believe this is actually powered by OpenAI, which while large (now), is nowhere near the behemoth that Microsoft or Google is. This suggests that seeing the future a bit ahead of the rest of the world, and then assembling a motivated all-star team is (perhaps in the short term at least) one way of out-competing the "super AI" of the giants.
- BlueTemplar 5y ago
  Last I've checked, Microsoft pretty much owns OpenAI ?
- shoo_pl 5y ago
  Not only Microsoft basically bough OpenAI a couple of years ago, they also made the GPT-3 closed thing that you can only access via API. Don't let the name fool you, OpenAI is anything but Open.
someperson 5y ago
On the other hand, DeepL (made by a small German company) is better than Google Translate.
- minxomat 5y ago
  Makes it sound like DeepL exists in isolation. It's good because the company behind it has the largest hyperlocal (small phrases with confirmed usages) translation data set.
lathiat 5y ago
I've got 70,000 photos in my library, with AI search and recognition, all done on my device. Thanks Apple. In fairness it's not quite as good, but, it's good enough for the searches I've wanted to do so far and gets better all the time. And they're adding searching text in photos this release. I'm happy to wait a little for this better implementation.
spyckie2 5y ago
The thought that data monopolization will be a moat against competitors is actually argued against by VC firms specializing in AI companies, who claim that after a certain amount of data (which is accessible to most people) the additional data isn't going to improve the model much. https://a16z.com/2019/05/09/data-network-effects-moats/ https://a16z.com/2019/05/09/data-network-effects-moats/ https://a16z.com/2020/02/16/the-new-business-of-ai-and-how-its-different-from-traditional-software/ https://a16z.com/2020/02/16/the-new-business-of-ai-and-how-i...
- hankman86 5y ago
  And in case of Copilot, the training data isn’t a moat anyhow. Last I looked, everyone could freely access GitHub public repositories.
pyuser583 5y ago
Google doesn’t have the best (publicly) available reverse image search AI. That would be Yandex. Google is actually pretty crappy at reverse image searches. https://www.bellingcat.com/resources/how-tos/2019/12/26/guide-to-using-reverse-image-search-for-investigations/ https://www.bellingcat.com/resources/how-tos/2019/12/26/guid...
- colordrops 5y ago
  It's pretty clearly intentionally hobbled for various reasons (e.g. privacy, obscenity, etc). It used to work a lot better.
  - IfOnlyYouKnew 5y ago
    Which would explain why Yandex, specifically, is the best-in-category: being based in a country where your government enjoys trolling developed world's idea of decency and responsibility can have its advantages. (Until, of course, they force you out and give company to some crony oligarch. But that idea is also not unknown to Yandex, I believe?)
- _fizz_buzz_ 5y ago
  The point still stands though, Yandex is also a behemoth with access to a massive amount of data.
sdevonoes 5y ago
We can decide to stop using some (or most of) Google services. It's hard, but it's not that they are pointing us with a gun in order to use their services, right? Sure, for the cases when one cannot escape Google, use it; but for the rest of scenarios? It's all about tradeoffs: Can I live without YouTube? Can I live with DuckDuckGo (Google Search is "better" but I don't mind)? etc.
- redeux 5y ago
  You, a person knowledgeable in this field, may choose to stop using Google services, but that won’t have any societal impact if you can’t also convince the “average” user to do the same.
- hankman86 5y ago
  Google search would be hard to replace. In fact, if Google search was turned off over night, the world would probably see a major economic downturn, caused by a sudden drop in productivity.
kulikalov 5y ago
This seem to be inevitable. An individual doesn't have horizontal scalability, you know... So, unless we'll have some kind of brain extension capabilities, there is no other choice but to build such technologies collectively. Also, I think you are overdramatizing this. Governments used to be omnipresent (maybe still are), in a different way, more threatening to individuals and probably as threatening to societies as "everything companies" could be.
abiro 5y ago
> If we predict that ultimately AI will change virtually every aspect of society, these companies will become omnipresent, "everything companies". God companies. What we currently call AI is very from AGI, and it's not clear that sitting on piles of proprietary data gives an edge towards AGI. If the goal is human-level intelligence, that has been demonstrably achieved with the far lesser resources of the public school system. :) Current DL systems need huge amount of data, because they are very primitive: they work with immediate associations, so they require seeing data very similar to all possible inputs to generalize well. As we develop more sophisticated systems, I expect that the leverage from data will tip over to engineering finesse, and nothing is better at fostering great engineering than the permissionless tinkering environment of open source.
- visarga 5y ago
  > If the goal is human level intelligence, that has been demonstrably achieved with the far lesser resources of the public school system. Seems unlikely human education costs less than AI education in total.
- SirensOfTitan 5y ago
  > If the goal is human-level intelligence, that has been demonstrably achieved with the far lesser resources of the public school system. Pretending that the scientifically managed public school system, that attempts to manufacture uniform educated humans on a conveyer belt, is responsible for human education is fairly ridiculous. Children have a remarkable capacity to learn, and do so automatically through free play and exploration until public education wrings that curiosity out of them and turns education into a job. Humans get educated despite the public education system, not because of it.
  - guythedudebro 5y ago
    Yeah everyone knows children will innately learn calculus from flinging mud at eachother.
  - dragonwriter 5y ago
    > Pretending that the scientifically managed public school system, Say what now? There may be places on Earth that practice scientific management, there are definitely some that pretend to, but IME public school systems are neither.
visarga 5y ago
They are not hoarding the latest results, except for a few cases where the general public is a year behind their secret sauce. Take a look at the huge zoo of planetary-scale models that are published by the big companies and universities (HuggingFace, https://modelzoo.co/ https://modelzoo.co/, ...) The problem with the huge models like GPT-3 is that they are too expensive even to run by regular people, not train.
- hankman86 5y ago
  Regular people yes, but no problem for decently funded startups.
hamilyon2 5y ago
Interesting, given that HN thinks that it is yandex who has SOA image search, not google https://news.ycombinator.com/item?id=23976172 https://news.ycombinator.com/item?id=23976172 which kinda counters your logic. It is yandex who now collects massive amounts of data to improve their image search now, while google apparently doesn't. Yandex is a giant, for sure, but google is, like, 10 times bigger and still doesn't provide the best service.
cbolton 5y ago
Well of course only the huge companies can develop products that require enormous resources. But I'm not too worried here because everyone gets access to larger datasets every year, and it gets cheaper to process every year, so whatever Microsoft or Google is capable of doing now, smaller companies will be capable of doing in a few years.
- hankman86 5y ago
  It’s also a huge call for innovation. When a student learns to code, (s)he doesn’t need to analyse millions of Git repositories to get good at it. Throughout their entire career most developers will probably only see comparatively little code. Perhaps the equivalent of the Linux kernel, if that. And yet, we’re able to learn from the little we see and get reasonably good at coding. It even stands to reason how much better one gets by reading more code (most of which is pretty crappy anyway).
hankman86 5y ago
I don’t think that your premise concerning “planetary-scale AI” (and the ability to pull it off) holds up. If Google and Microsoft are so dominant and had such an insurmountable head start, why are we seeing such an enormous number of AI startups? In fact, there are countless startups busy figuring out how to make AI work for software development. I’d even argue that copilot was not that expensive to build. I very much doubt that GitHub (or Microsoft for that matter) had a huge team working on this or has spent such a vast amount on hardware resources that they’d outcompete the rest of the market by virtue of their cash reserves. Any decently funded startup should be able to finance such as effort. Especially since in this case, the training data is cheap (and legal) to access for anyone. Where Microsoft does have an “unfair advantage” is in their marketing and sales firepower. Replicating their B2B and B2C sales channels is indeed very expensive. GitHub will be able to monetise Copilot by some upselling campaign. Then again, startups regularly manage to break into markets that are supposedly locked down by the likes of Microsoft.
Siira 5y ago
And I have yet to see a single life-changing AI application. I haven't tested Copilot yet, but I'll bet it is so precariously useful that a lot of people will feel more productive without it. (BTW, the last time I opened VSCode, it could not even autocomplete Numpy, so I am not holding my breath for AI autocomplete.)

by fleddr 5y ago

tvirosi 5y ago

I largely agree. But there are still some fun opportunities around. One are things google would never touch because of PR reasons (e.g. state of the art scalable face identification). Another is just silly out-of-the-box creative uses of AI which wouldn't fit well with Google's brand.

jspaetzel 5y ago

If Google makes an amazing model that no-one can beat it will only be dominate as long as others get access to it freely. But if there are restrictions on access or if it's too expensive, other options will appear and even if they're not as perfect, they'll still be very usable. Imagine a coalition of companies all feeding data, that could compete just as well.

est31 5y ago
Google has all the data of all the users though. I'd wager that they won't just let AI companies scrape it.
- londons_explore 5y ago
  I don't think Google uses user photos to train their photo search algorithm. They use photos from the web for training, and then user photos are only used for the actual indexing.

ncr100 5y ago

I think it's an innate quality of technology. Yes sophisticated AI tech concentrates power for those who already have power. And the technology we all (presumably readers of HN) create can enhance the impact of the user. And this can result in unfair circumstances, in reality. Law and force can prevent disproportionate use of power. Of course one must define the law, which may be done AFTER the offense has been committed. Further, if those who make the laws are corrupted by those with e.g. this AI tech power, then no effective law may be enacted and the hypothetical abuse will continue.

mtrn 5y ago

The final step is to break down these monopolies. The government can do that and has done it before.

mikewarot 5y ago

I have about 300,000 photos that haven't been scanned by AI (unless someone at Backblaze did it without permission). I'm sure there are lots of other photographers out there who miss Picassa, which Google killed off to push everyone's data to their service. (It did really well in matching faces, even across age, but the last version has a bug when there are multiple faces in a picture, sometimes it swaps the labels) If there were offline image recognition we could train on our own data privately, could the results of those trainings be merged to come up with better recognition on average than any one person could do themselves with their own photos? In other words, would it be possible for us to share the results of training, and build better models, without sharing the photos themselves?

mostdataisnice 5y ago
While interesting, we don't know enough about how models are learning to where we would be able to consider doing this.
cgio 5y ago
I am not an expert on the field. But my hope was that this could be facilitated by Transfer Learning. Still don’t know how the scale economies could be achieved. Maybe just out of the sweat and network of passionate people like in the case of open source.
- Mehdi2277 5y ago
  I work in the field. Transfer learning helps get you decent/good models, but the best models remain ones trained on large amounts of data. You may be able to get away with good performance and not great on your task. For some areas you really care a lot about long tail performance (like self driving) that you will need massive dataset. For other areas if your goal is to be the best relative to other large companies you will need a massive dataset. Transfer learning best use cases are for fast prototypes or for ml tasks that do not need state of the art performance.
  - mikewarot 5y ago

hexa22 5y ago

There is a second best though. Apple offers image AI which is worse than googles but wins because it works offline.

aeyes 5y ago

For years we thought Google Translate was the best machine translation we would ever get. Then DeepL just popped up out of nowhere and today other services still didn't manage to catch up. Every now and then you get someone to think about an old problem on a clean sheet of paper and you might get a better result with less training data / investment.

sgrove 5y ago

I believe this is actually powered by OpenAI, which while large (now), is nowhere near the behemoth that Microsoft or Google is. This suggests that seeing the future a bit ahead of the rest of the world, and then assembling a motivated all-star team is (perhaps in the short term at least) one way of out-competing the "super AI" of the giants.

BlueTemplar 5y ago
Last I've checked, Microsoft pretty much owns OpenAI ?
shoo_pl 5y ago
Not only Microsoft basically bough OpenAI a couple of years ago, they also made the GPT-3 closed thing that you can only access via API. Don't let the name fool you, OpenAI is anything but Open.

someperson 5y ago

On the other hand, DeepL (made by a small German company) is better than Google Translate.

minxomat 5y ago
Makes it sound like DeepL exists in isolation. It's good because the company behind it has the largest hyperlocal (small phrases with confirmed usages) translation data set.

lathiat 5y ago

I've got 70,000 photos in my library, with AI search and recognition, all done on my device. Thanks Apple. In fairness it's not quite as good, but, it's good enough for the searches I've wanted to do so far and gets better all the time. And they're adding searching text in photos this release. I'm happy to wait a little for this better implementation.

spyckie2 5y ago

The thought that data monopolization will be a moat against competitors is actually argued against by VC firms specializing in AI companies, who claim that after a certain amount of data (which is accessible to most people) the additional data isn't going to improve the model much. https://a16z.com/2019/05/09/data-network-effects-moats/ https://a16z.com/2019/05/09/data-network-effects-moats/ https://a16z.com/2020/02/16/the-new-business-of-ai-and-how-its-different-from-traditional-software/ https://a16z.com/2020/02/16/the-new-business-of-ai-and-how-i...

hankman86 5y ago
And in case of Copilot, the training data isn’t a moat anyhow. Last I looked, everyone could freely access GitHub public repositories.

pyuser583 5y ago

Google doesn’t have the best (publicly) available reverse image search AI. That would be Yandex. Google is actually pretty crappy at reverse image searches. https://www.bellingcat.com/resources/how-tos/2019/12/26/guide-to-using-reverse-image-search-for-investigations/ https://www.bellingcat.com/resources/how-tos/2019/12/26/guid...

colordrops 5y ago
It's pretty clearly intentionally hobbled for various reasons (e.g. privacy, obscenity, etc). It used to work a lot better.
- IfOnlyYouKnew 5y ago
  Which would explain why Yandex, specifically, is the best-in-category: being based in a country where your government enjoys trolling developed world's idea of decency and responsibility can have its advantages. (Until, of course, they force you out and give company to some crony oligarch. But that idea is also not unknown to Yandex, I believe?)
_fizz_buzz_ 5y ago
The point still stands though, Yandex is also a behemoth with access to a massive amount of data.

sdevonoes 5y ago

We can decide to stop using some (or most of) Google services. It's hard, but it's not that they are pointing us with a gun in order to use their services, right? Sure, for the cases when one cannot escape Google, use it; but for the rest of scenarios? It's all about tradeoffs: Can I live without YouTube? Can I live with DuckDuckGo (Google Search is "better" but I don't mind)? etc.

redeux 5y ago
You, a person knowledgeable in this field, may choose to stop using Google services, but that won’t have any societal impact if you can’t also convince the “average” user to do the same.
hankman86 5y ago
Google search would be hard to replace. In fact, if Google search was turned off over night, the world would probably see a major economic downturn, caused by a sudden drop in productivity.

kulikalov 5y ago

This seem to be inevitable. An individual doesn't have horizontal scalability, you know... So, unless we'll have some kind of brain extension capabilities, there is no other choice but to build such technologies collectively. Also, I think you are overdramatizing this. Governments used to be omnipresent (maybe still are), in a different way, more threatening to individuals and probably as threatening to societies as "everything companies" could be.

abiro 5y ago

> If we predict that ultimately AI will change virtually every aspect of society, these companies will become omnipresent, "everything companies". God companies. What we currently call AI is very from AGI, and it's not clear that sitting on piles of proprietary data gives an edge towards AGI. If the goal is human-level intelligence, that has been demonstrably achieved with the far lesser resources of the public school system. :) Current DL systems need huge amount of data, because they are very primitive: they work with immediate associations, so they require seeing data very similar to all possible inputs to generalize well. As we develop more sophisticated systems, I expect that the leverage from data will tip over to engineering finesse, and nothing is better at fostering great engineering than the permissionless tinkering environment of open source.

visarga 5y ago
> If the goal is human level intelligence, that has been demonstrably achieved with the far lesser resources of the public school system. Seems unlikely human education costs less than AI education in total.
SirensOfTitan 5y ago
> If the goal is human-level intelligence, that has been demonstrably achieved with the far lesser resources of the public school system. Pretending that the scientifically managed public school system, that attempts to manufacture uniform educated humans on a conveyer belt, is responsible for human education is fairly ridiculous. Children have a remarkable capacity to learn, and do so automatically through free play and exploration until public education wrings that curiosity out of them and turns education into a job. Humans get educated despite the public education system, not because of it.
- guythedudebro 5y ago
  Yeah everyone knows children will innately learn calculus from flinging mud at eachother.
- dragonwriter 5y ago
  > Pretending that the scientifically managed public school system, Say what now? There may be places on Earth that practice scientific management, there are definitely some that pretend to, but IME public school systems are neither.

visarga 5y ago

They are not hoarding the latest results, except for a few cases where the general public is a year behind their secret sauce. Take a look at the huge zoo of planetary-scale models that are published by the big companies and universities (HuggingFace, https://modelzoo.co/ https://modelzoo.co/, ...) The problem with the huge models like GPT-3 is that they are too expensive even to run by regular people, not train.

hankman86 5y ago
Regular people yes, but no problem for decently funded startups.

hamilyon2 5y ago

Interesting, given that HN thinks that it is yandex who has SOA image search, not google https://news.ycombinator.com/item?id=23976172 https://news.ycombinator.com/item?id=23976172 which kinda counters your logic. It is yandex who now collects massive amounts of data to improve their image search now, while google apparently doesn't. Yandex is a giant, for sure, but google is, like, 10 times bigger and still doesn't provide the best service.

cbolton 5y ago

Well of course only the huge companies can develop products that require enormous resources. But I'm not too worried here because everyone gets access to larger datasets every year, and it gets cheaper to process every year, so whatever Microsoft or Google is capable of doing now, smaller companies will be capable of doing in a few years.

hankman86 5y ago
It’s also a huge call for innovation. When a student learns to code, (s)he doesn’t need to analyse millions of Git repositories to get good at it. Throughout their entire career most developers will probably only see comparatively little code. Perhaps the equivalent of the Linux kernel, if that. And yet, we’re able to learn from the little we see and get reasonably good at coding. It even stands to reason how much better one gets by reading more code (most of which is pretty crappy anyway).

hankman86 5y ago

I don’t think that your premise concerning “planetary-scale AI” (and the ability to pull it off) holds up. If Google and Microsoft are so dominant and had such an insurmountable head start, why are we seeing such an enormous number of AI startups? In fact, there are countless startups busy figuring out how to make AI work for software development. I’d even argue that copilot was not that expensive to build. I very much doubt that GitHub (or Microsoft for that matter) had a huge team working on this or has spent such a vast amount on hardware resources that they’d outcompete the rest of the market by virtue of their cash reserves. Any decently funded startup should be able to finance such as effort. Especially since in this case, the training data is cheap (and legal) to access for anyone. Where Microsoft does have an “unfair advantage” is in their marketing and sales firepower. Replicating their B2B and B2C sales channels is indeed very expensive. GitHub will be able to monetise Copilot by some upselling campaign. Then again, startups regularly manage to break into markets that are supposedly locked down by the likes of Microsoft.

Siira 5y ago

And I have yet to see a single life-changing AI application. I haven't tested Copilot yet, but I'll bet it is so precariously useful that a lot of people will feel more productive without it. (BTW, the last time I opened VSCode, it could not even autocomplete Numpy, so I am not holding my breath for AI autocomplete.)