> AI burst into the public consciousness with the launch in late 2022
Because 70 years of named work based on centuries of interest and efforts can remain unseen if one really tries. /R
> But easier access to AI also means bad actors will be able to fine-tune systems for nefarious purposes, such as generating disinformation. It means Western attempts to prevent hostile regimes from gaining access to powerful AI technology will fail. And it makes AI harder to regulate, because the genie is out of the bottle
And the fact that after centuries of steep increase of technical possibilities in spite of low spiritual growth, with clear consequences every time met with bewilderment - you know, e.g., WWI and the surprise (historically noted) post-facto after the heightened possible devastation -, should not suggest that what are to be tackled are the root issues? The «genie is out of the bottle» at least after the industrial revolution.
> Because 70 years of named work based on centuries of interest and efforts can remain unseen if one really tries.
You’re really trying to be uncharitable eh?
We’ve been talking about time travel for millennia. But I can guarantee you that if tomorrow we figure out a way for most people to actually reliably perform it and play with it, it will be defined as “bursting into the public consciousness”.
I must have overlooked all those conferences on time travel that are on the same level as, e.g., AAAI.
But yes, public perception is a different thing. Most people are totally baffled when I tell them that the first spam email was sent in 1978, because for a lot of people the internet (and with it email) popped into existence somewhere around 2004.
Oh, it's a different time for any group of people you ask. For some it was AOL, for others the media coverage that picked up around 1995/1996. And some were late to the game and only noticed when every one around them got DSL in the early 2000's. I kind of picked 2004 at random. It represents a (sadly rather sizeable) group of people in rural areas who neither got DSL nor internet over cable before that time and therefore just didn't pay attention.
Really not the same. Time travel is hardly achievable and has a crisp goal. Artificial Intelligence, on the contrary, has been producing results since the start, and there are (there have been) entire businesses based on it.
> uncharitable
I was being «uncharitable» in front of the depiction of "masses discovering with surprise things that would have been noted by exploitation of the information available (and never had been as available as it is today)", also because on practical terms I find this unawareness of the world socially dangerous.
Or we could opt for a bet that this public is selected enough to possibly avoid the «flame war» and allow some "normal" liberty and maybe instead risk some constructive exchange, even productive.
"Leaked Google memo" is true in a sense, but the doc was written by one person who isn't the primary leading force within relevant orgs at Google. The headline is more accurately described as "what does the opinion of one Googler reveal..."
"Leaks" can be press releases. "Oops, you weren't supposed to see that" can make the message seem more credible. Is this Google preemptively fending off accusations of monopoly in an important space?
On the other hand, if Google is perceived as weak, then its share price will be negatively affected. So maybe not.
Maybe it's just what some guy wrote.
But then how did the leak happen? Somebody chose to publicize this particular bit of text. Why?
It'd be weird not to integrate the comments first if this was being done by PR.
> But then how did the leak happen?
Somebody thought the doc was interesting and shared it with a news outlet.
I've read 100+ docs that read like this. Some sort of position paper designed to spark discussion, much of which happens in the comments alongside the doc. All of them are just the opinion of a person, not the company.
Well, how do you tell the difference between a truly leaked internal document that reflects the opinion of one person, and a "leaked" document that just so happens to put forth a position that's beneficial to Google given its current standing in the LLM space? I think some skepticism is healthy here, as long as we understand that no one knows for sure.
Does it matter what is the origin of that opinion? As long as it is a good insight into the situation and accurately reflects the state of affairs, it shouldn’t matter, right?
And as to not being the leader at Google, this hardly matters. Being politically adept and leadership skills don’t necessarily correlate with having better feel and insights into the future technology.
And not being the leader reduces filters, doesn’t have a pull of a contract to protect specific people you lead and your own project, etc.
It’d be better to hear that from a founder, for certain, but a honest opinion of a well seasoned engineer often enough is a better reflection of the reality, than an official statement by a “leading force”.
Well, there a honest opinion of an unbiased engineer, ideally a researcher who was trained to filter his own biases, from the inside of the organization , speaking honesty is likely the best approximation that you can get for “an opinion of Google”.
It is important that the engineer is an insider, as from outside of Google access to its internal knowledge is limited.
Googlers are no more unbiased than someone who gets a job somewhere else. Getting a job at Google might affect your opinions somewhat when you see what people are doing, but there is no special training in being unbiased.
Also, the document we're discussing was not written as a serious research paper. It's a more like one of Steve Yegge's rants, written to be provocative.
When something Yegge wrote while at Google leaked, people knew who he was, so it was interpreted as "here's what Yegge thinks." It's the same in this case, but it's someone else who isn't famous.
Was any previously unknown info about Google leaked in the memo, that only an insider could know? If not, then why does it even matter that a googler wrote it? If "Anonymous" wrote the doc and uploaded it to pastebin, would you lend it the same credence you are to this doc?
It does matter, because Google is an important actor in this “industry”.
Even if it doesn’t represent a monolithic “googles thoughts on AI” it is interesting and newsworthy to consider how at least some folks who work at Google think about the recent developments.
If Google goes on a AI-everything spree and forces it awkwardly into all their products a la Google+ — this may indicate how and where AI will be useful to people (or not).
Google has nearly 200,000 employees. Almost every possible opinion is held by somebody within the company.
Imagine this was written by Blake Lemoine, who believed that one of the earlier models was sentient. Would it be reasonable to present this as a company-wide belief?
No, but a company-wide belief doesn’t matter. Some 200,000 lemmings can be mistaken, along with the chief lemming. Or all of them can be right.
The discussion here is regarding a particular opinion of a particular employee.
And what matters is how informed and honest that particular employee is. And if ultimately that employee is right or wrong. If there is some objective truth in his or her statement.
(And for a reference, I don’t think that these 200,000 Googlers or Lemoine were right or wrong, it feels like Lemoine was asking/answering a wrong question, which needs to be asked differently to have a well defined answer).
>Does it matter what is the origin of that opinion? As long as it is a good insight into the situation and accurately reflects the state of affairs, it shouldn’t matter, right?
It does matter a great deal whether a particular opinion is held by someone with the power to act on it or by someone who can only try to influence those who can act on it.
At the same time, I'm not sure I'd give any more weight to something written by "leading forces within relevant orgs" when these are the same people who missed ChatGPT and are playing catch-up.
I don’t know. If you define “AI” as having a great chatbot then probably no company has a moat anymore. But there are a lot more types of tasks which have nothing to do with that. Robotics, for one. Self-driving cars is another example. “AI” in the abstract is a meaninglessly vague concept but for all intents and purposes Google still has advantages over others in important areas.
Their perpetual disadvantage of course is comically poor product vision, which puts any of their actual advantages in jeopardy.
First is to neutralize the threat: support the open source efforts covertly and/or overtly, as those efforts undercut the revenue of OpenAI and other potential competitors for the base technology. This is what they did with Android: at a minimum all they had to do was ensure that Apple did not become a monopoly, which they accomplished (the secondary effect was to cut the underbrush of any other competitors). A name for this is to “commoditize your competition”.
The second half is to use their internal experience with LLMs and their other ecosystem to use supercharge their strengths. Side inventions can either be expanded in the hope of a (desperately needed, unrelated to LLMs) new revenue stream or given away to starve potential new entrants.
The big guys have good experience in weaponizing open source. But google has become flabby and seemingly lost any culture of execution so I don’t know if they can pull it off. But the path is there.
The doc is too short and not puffy to be a normal google doc. There is a high likelihood this was placed to proactively shake off any regulation or scruitiny while they get the deck chairs in order.
They might not appear to have a moat, but they definitely have an advantage that they can keep for 5+ years. They also have a "copy of the internet" that no one else does.
What are the chances that their copy is more useful than CommonCrawl? It’s been the target of SEO for decades - are they even capable of separating the good content from the crap anymore?
Their data may not be that much better; however Deepmind is still one of the best institutions that study AI fundamentals. OpenAI works hard and focused towards products, but the academic research is far better from Deepmind. So since Google hasn't been trying to put any AI into products really at all for the past 10 years, they're going to have to push a little bit to make the public facing interfaces and put polish on things, but the underlying models they have made are far better than OpenAI (just not the ones made publicly accessible to anyone).
I would heavily disagree with that - the only reason that you think that is that GPT-4 is available to the public for cheap, whereas Deepminds models have not been released publicly.
1) algorithmic improvements beat processing capacity. One of the examples in the paper was that $100 in training compute budget was enough to get within 2% of Google Bard performance
2) data quality (even for "tiny" data sizes) beats dataset size in improvements
Hence both aspects of the moat of large companies (dataset size and available compute) matter less than you'd expect.
In contrast the advantage of "open source"/academics/"the market", the many warm bodies trying out new strategies, yields improvements at a rapid pace that Google, even with a huge team, cannot match.
On the low end, google can sprinkle in well integrated cost-optimized 'pretty good' LLMs into all their products which already have billions of DAU. It's hard for OpenAI to compete here, their models have to be significantly better to encourage people to copy and paste into ChatGPT and yet still cost effective. The high end is more interesting in that I'm not sure Google has a response to Gpt4. Specialized Palm2 models are allegedly SOTA in certain verticals but they're not generally available so it's hard to say. It's possible Google could offer a beefy model to Google One subscribers or something but they seem to be focused on the low end for now at least in the B2C arena with specialized models for B2B. I honestly don't think OSS is a big factor business-wise but it's nice to see and certainly enables more participation in the ecosystem.
This idea that ChatGPT is better than the models that Google has is false; but I understand the perception.
Deepmind has far better models than OpenAI, and the models OpenAI have made are based on the research done at Deepmind.
For example, ChatGPT was not the first model trained by RLHF - that was Sparrow by Deepmind.
The difference is that Google has been very disinterested in making products out of these systems, and didn't spend any effort to make them publicly accessible.
Deepmind is still the leader in AI, and they have much better models - it's just going to take a while for people who don't study ML to realize this because Google hasn't released any of their good models for public use yet (and yeah, I'm not counting Bard, etc because the real model was probably put together by one guy in an afternoon at Google, and the rest of the time working was marketing).
> I honestly don't think OSS is a big factor business-wise
Lots of companies are evaluating fine-tuning strategies for <60B LLMs. Such models can be efficient, private, cheaper and adapted to the use case. They may not be generalists like GPT-4, but you need them for scaling up usage on high volume calls on the same task if you don't want to have to pay a fortune to OpenAI, or for processing confidential information such as in medical, B2B and other cases. Not to mention the fear that OpenAI might snoop on their private data and use it in their corpus.
Wasn't this note from someone at Google discussed on HN last week, before The Economist picked it up?
It is a huge issue for Google. Not because they're behind, but because chat engines don't seem to map well to an ad-supported model. Unless they talk like the Youtubers who start with "But first, let me tell you about our sponsor, FBX Crypto".
They do map well to a surveillance model. That's already getting regulator attention. Look what happened to TikTok, which is really good at focusing on a user's interests. Chat engines focus like that. They have to, to work well.
54 comments
[ 3.1 ms ] story [ 119 ms ] threadBecause 70 years of named work based on centuries of interest and efforts can remain unseen if one really tries. /R
> But easier access to AI also means bad actors will be able to fine-tune systems for nefarious purposes, such as generating disinformation. It means Western attempts to prevent hostile regimes from gaining access to powerful AI technology will fail. And it makes AI harder to regulate, because the genie is out of the bottle
And the fact that after centuries of steep increase of technical possibilities in spite of low spiritual growth, with clear consequences every time met with bewilderment - you know, e.g., WWI and the surprise (historically noted) post-facto after the heightened possible devastation -, should not suggest that what are to be tackled are the root issues? The «genie is out of the bottle» at least after the industrial revolution.
You’re really trying to be uncharitable eh?
We’ve been talking about time travel for millennia. But I can guarantee you that if tomorrow we figure out a way for most people to actually reliably perform it and play with it, it will be defined as “bursting into the public consciousness”.
But yes, public perception is a different thing. Most people are totally baffled when I tell them that the first spam email was sent in 1978, because for a lot of people the internet (and with it email) popped into existence somewhere around 2004.
Really not the same. Time travel is hardly achievable and has a crisp goal. Artificial Intelligence, on the contrary, has been producing results since the start, and there are (there have been) entire businesses based on it.
> uncharitable
I was being «uncharitable» in front of the depiction of "masses discovering with surprise things that would have been noted by exploitation of the information available (and never had been as available as it is today)", also because on practical terms I find this unawareness of the world socially dangerous.
"Leaked Google memo" is true in a sense, but the doc was written by one person who isn't the primary leading force within relevant orgs at Google. The headline is more accurately described as "what does the opinion of one Googler reveal..."
On the other hand, if Google is perceived as weak, then its share price will be negatively affected. So maybe not.
Maybe it's just what some guy wrote.
But then how did the leak happen? Somebody chose to publicize this particular bit of text. Why?
It'd be weird not to integrate the comments first if this was being done by PR.
> But then how did the leak happen?
Somebody thought the doc was interesting and shared it with a news outlet.
I've read 100+ docs that read like this. Some sort of position paper designed to spark discussion, much of which happens in the comments alongside the doc. All of them are just the opinion of a person, not the company.
And as to not being the leader at Google, this hardly matters. Being politically adept and leadership skills don’t necessarily correlate with having better feel and insights into the future technology.
And not being the leader reduces filters, doesn’t have a pull of a contract to protect specific people you lead and your own project, etc.
It’d be better to hear that from a founder, for certain, but a honest opinion of a well seasoned engineer often enough is a better reflection of the reality, than an official statement by a “leading force”.
The opinion is as relevant or not as any opinion expressed on Hacker News, the fact that the person who expressed it works for Google is irrelevant.
It is important that the engineer is an insider, as from outside of Google access to its internal knowledge is limited.
Also, the document we're discussing was not written as a serious research paper. It's a more like one of Steve Yegge's rants, written to be provocative.
When something Yegge wrote while at Google leaked, people knew who he was, so it was interpreted as "here's what Yegge thinks." It's the same in this case, but it's someone else who isn't famous.
Citation needed! ;-)
I suppose you might be referring to diversity training, but it's not the same thing.
Even if it doesn’t represent a monolithic “googles thoughts on AI” it is interesting and newsworthy to consider how at least some folks who work at Google think about the recent developments.
If Google goes on a AI-everything spree and forces it awkwardly into all their products a la Google+ — this may indicate how and where AI will be useful to people (or not).
Imagine this was written by Blake Lemoine, who believed that one of the earlier models was sentient. Would it be reasonable to present this as a company-wide belief?
And what matters is how informed and honest that particular employee is. And if ultimately that employee is right or wrong. If there is some objective truth in his or her statement.
(And for a reference, I don’t think that these 200,000 Googlers or Lemoine were right or wrong, it feels like Lemoine was asking/answering a wrong question, which needs to be asked differently to have a well defined answer).
It does matter a great deal whether a particular opinion is held by someone with the power to act on it or by someone who can only try to influence those who can act on it.
Their perpetual disadvantage of course is comically poor product vision, which puts any of their actual advantages in jeopardy.
I've found the Gartner AI Hype Cycle to be a useful tool for making this point with people who are under the impression that "AI" is mostly generative AI, and LLMs specifically: https://www.gartner.com/en/articles/what-s-new-in-artificial...
In particular, the chart conveys this really quickly.
Google has a good, two part strategy available.
First is to neutralize the threat: support the open source efforts covertly and/or overtly, as those efforts undercut the revenue of OpenAI and other potential competitors for the base technology. This is what they did with Android: at a minimum all they had to do was ensure that Apple did not become a monopoly, which they accomplished (the secondary effect was to cut the underbrush of any other competitors). A name for this is to “commoditize your competition”.
The second half is to use their internal experience with LLMs and their other ecosystem to use supercharge their strengths. Side inventions can either be expanded in the hope of a (desperately needed, unrelated to LLMs) new revenue stream or given away to starve potential new entrants.
The big guys have good experience in weaponizing open source. But google has become flabby and seemingly lost any culture of execution so I don’t know if they can pull it off. But the path is there.
They might not appear to have a moat, but they definitely have an advantage that they can keep for 5+ years. They also have a "copy of the internet" that no one else does.
Google may already be terminal
Google of all companies is sitting on exaflops of TPU capacity, they can retrain models larger than anyone else, faster than anyone else.
Loads of internal position papers read exactly like this. I've written docs that write like this.
1) algorithmic improvements beat processing capacity. One of the examples in the paper was that $100 in training compute budget was enough to get within 2% of Google Bard performance
2) data quality (even for "tiny" data sizes) beats dataset size in improvements
Hence both aspects of the moat of large companies (dataset size and available compute) matter less than you'd expect.
In contrast the advantage of "open source"/academics/"the market", the many warm bodies trying out new strategies, yields improvements at a rapid pace that Google, even with a huge team, cannot match.
Deepmind is still the leader in AI, and they have much better models - it's just going to take a while for people who don't study ML to realize this because Google hasn't released any of their good models for public use yet (and yeah, I'm not counting Bard, etc because the real model was probably put together by one guy in an afternoon at Google, and the rest of the time working was marketing).
Lots of companies are evaluating fine-tuning strategies for <60B LLMs. Such models can be efficient, private, cheaper and adapted to the use case. They may not be generalists like GPT-4, but you need them for scaling up usage on high volume calls on the same task if you don't want to have to pay a fortune to OpenAI, or for processing confidential information such as in medical, B2B and other cases. Not to mention the fear that OpenAI might snoop on their private data and use it in their corpus.
It is a huge issue for Google. Not because they're behind, but because chat engines don't seem to map well to an ad-supported model. Unless they talk like the Youtubers who start with "But first, let me tell you about our sponsor, FBX Crypto".
They do map well to a surveillance model. That's already getting regulator attention. Look what happened to TikTok, which is really good at focusing on a user's interests. Chat engines focus like that. They have to, to work well.
Related:
Google “We have no moat, and neither does OpenAI” - https://news.ycombinator.com/item?id=35813322 (May 2023)