[brokencode]

There was a point in time when basically every well known AI researcher worked at Google. They have been at the forefront of AI research and investing heavily for longer than anybody.

It’s kind of crazy that they have been slow to create real products and competitive large scale models from their research.

But they are in full gear now that there is real competition, and it’ll be cool to see what they release over the next few years.

[Arainach]

>It’s kind of crazy that they have been slow to create real products and competitive large scale models from their research.

Not really. If Google released all of this first instead of companies that have never made a profit and perhaps never will, the case law would simply be the copyright holders suing them for infringement and winning.

[zipy124]

It's not even that. It's way easier to do R&D when you don't have a customer base to support.

[drewstiff]

Also think of how LLMs are replacing web searches for most people - Google would have been cannibalising their Search profits for no good reason

[wslh]

> It’s kind of crazy that they have been slow to create real products and competitive large scale models from their research.

It’s not that crazy. Sometimes the rational move is to wait for a market to fully materialize before going after it. This isn’t a Xerox PARC situation, nor really the innovator’s dilemma, it’s about timing: turning research into profits when market conditions finally make it viable. Even mammoths like Google are limited in their ability to create entirely new markets.

[DSingularity]

This take makes even more sense when you consider the costs of making a move to create the market. The organizational energy and its necessary loss in focus and resources limits their ability to experiment. Arguably the best strategy for Google: (1) build foundational depth in research and infrastructure that would be impossible for competition to quickly replicate (2) wait for the market to present a clear new opportunity for you (3) capture it decisively by focusing and exploiting every foundational advantage Google was able to build.

[hosh]

I also think the presence of Sergey Brin has been making a difference in this.

[refulgentis]

Ex-googler: I doubt it, but am curious for rationale (i know there was a round of PR re: him “coming back to help with AI.” but just between you and me, the word on him internally, over years and multiple projects, was having him around caused chaos b/c he was a tourist flitting between teams, just spitting out ideas, but now you have unclear direction and multiple teams hearing the same “you should” and doing it)

[hungryhobbit]

Please, Google was terrible about using the tech the had long before Sundar, back when Brin was in charge.

Google Reader is a simple example: Googl had by far the most popular RSS reader, and they just threw it away. A single intern could have kept the whole thing running, and Google has literal billions, but they couldn't see the value in it.

I mean, it's not like being able to see what a good portion of America is reading every day could have any value for an AI company, right?

Google has always been terrible about turning tech into (viable, maintained) products.

[belter]

Because after the death of Epstein he suddenly had a lot of free time?

https://www.wsj.com/finance/jeffrey-epstein-advised-sergey-b...

https://x.com/MarioNawfal/status/2017428928814588323

[smallnix]

> It’s kind of crazy that they have been slow to create real products and competitive large scale models from their research.

I always thought they deliberately tried to contain the genie in the bottle as long as they could

[mullingitover]

Their unreleased LaMDA[1] famously caused one of their own engineers to have a public crashout in 2022, before ChatGPT dropped. Pre-ChatGPT they also showed it off in their research blog[2] and showed it doing very ChatGPT-like things and they alluded to 'risks,' but those were primarily around it using naughty language or spreading misinformation.

I think they were worried that releasing a product like ChatGPT only had downside risks for them, because it might mess up their money printing operation over in advertising by doing slurs and swears. Those sweet summer children: little did they know they could run an operation with a seig-heiling CEO who uses LLMs to manufacture and distribute CSAM worldwide, and it wouldn't make above-the-fold news.

[1] https://en.wikipedia.org/wiki/LaMDA#Sentience_claims

[2] https://research.google/blog/lamda-towards-safe-grounded-and...