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Google DeepMind shifts from research lab to AI product factory

216 points by kjhughes 2y ago

l1n 2y ago
https://archive.is/5XdU8 https://archive.is/5XdU8
deleted 2y ago
[deleted]
jsemrau 2y ago
"The Overviews launch didn’t go well." understatement of the year.
kevindamm 2y ago
One thing that classic Google did right was embed researchers into product groups. It's true there were always some teams that were pure research but for the most part researchers were working within a product group. Then some acquisitions and internal musical chairs and it became less like that. Now I'm not all doom and gloom like this article (although with DeepMind why not leave well enough alone? They do excellent research). But, it does seem suboptimal to pivot all the way to AI Product Factory... were there no other existing product factories they could have turned instead?
- curious_cat_163 2y ago
  I agree: hybrid teams with a diversity of product/research skills at the team level is the way to go. It is thinkers and doers that need to come together. It is way easier said than done, though. You need true buy in from a ton of stakeholders — employees being the primary ones. And people get set in their ways. I do like a product bias though. Not because it is more valuable somehow but because it provides the applied scientists deeper exposure to the problem space, early and often.
- flakiness 2y ago
  The heads of the research once wrote about that. They called it a "Hybrid Approach to Research" (as other comments pointed out). https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/38149.pdf https://static.googleusercontent.com/media/research.google.c...
  - moandcompany 2y ago
    The "Hybrid Approach to Research" paper describes how "Google Research" first started when Google was mostly, if not entirely, about Search and "Research" was part of the Search organization. In these days, there were no "pure research" roles, nor were there formal designations for "research scientists" as a career ladder at Google. There were "SWEs" and in some cases "Members of Technical Staff." Since then, "Research" became its own organization or "Product Area" at Google (i.e. the equivalent of a company division). "Google Brain" was also created. Deepmind was acquired. All of these existed simultaneously, however Deepmind remained as an organizationally separate entity. In this era, the "Research Scientist" role was created, which generally existed exclusively within "Google Research." A large span of this era had John Giannandrea ("JG") at the helm of the Google Research org; (note: Giannandrea left to head and build Apple's "AI/ML" organization, which includes Siri, a few years ago. After JG's departure, Google Brain and Google Research were brought together under the common leadership of Jeff Dean, as an organization called still called "Google Research" with a branch still called "Google Brain." For perspective, it may be useful to consider too that the size of "Google Research" in staff headcount here measured in the several-thousands. This configuration existed for the last few years, with the latest changes being the merging of "Google Research" and Deepmind into "Google Deepmind." - I am a Xoogler, formerly from this product area. One of the things I and at least a few others observed was that "Research" was becoming defacto synonymous with "Machine Learning / AI," yet not all of Google's storied research accomplishments, or problem areas, are limited to Machine Learning and AI. In the last few years, Google made its public statements of being an "AI-first," previously "mobile-first," company in recognition that it would be incorporating and leveraging ML and AI technology across all of its products and services. This raised a significant question: What should "Google Research" or Research at Google be if product areas across Google began full incorporation of AI/ML technology and methods in their products? What if they incorporated their own AI/ML teams? If Google was truly successful at becoming AI-first, how should "Google Research" define and focus its organizational purpose, research portfolio, and show its value when Moonshots/X also exists within Alphabet? Over time, there were many parts of "Google Research" and research at large across Alphabet that felt that their purpose, or at least their individual reason for joining, was to do "pure research," yet this is not how the organizations started at all in the beginning. Many researchers and teams also knew that for practical reasons (e.g. promotion) that they generally needed to present and align their work with things like product launches with partner organizations. I suppose we are seeing some of the answer to this with Google DeepMind stating that they will be aligning more strongly with creating AI products, but in addition to the question of what happens to foundational research (for AI), what happens to foundational research in non-AI areas for Google and Alphabet?
radicaldreamer 2y ago
Why? Attach seasoned product teams from Google to the research org and have experienced PMs paired with experienced EMs launch products. Trying to transition a research org into a product org is going to be needlessly painful, especially since the research org needs to be firing on all cylinders in this hyper-competitive space.
- advael 2y ago
  God, yea. I've flipped between R&D and product development a few times in my career, sometimes at the same company, and it's a really rough transition even for an individual experienced in both. I can't imagine trying to flip a whole research team to make products is going to go well, especially when the products are getting a ton of well-deserved bad press and a lot of those researchers were coming from academia rather than elsewhere in industry in the first place
- gaogao 2y ago
  Agreed. As an example of that, Meta's kept its research org, FAIR, still doing fundamental research. Research orgs are great at demos, but actual productionalization takes a different mindset.
  - nomad_horse 2y ago
    FAIR is considerably downscaled from what it was before, in eg 2022.
  - fooker 2y ago
    Fun anecdote: some folks from FAIR reached out to a friend, asked her to apply, and then rejected her without an interview!
    - htrp 2y ago
      Facebook's recruiting funnel is super broken after they fired a ton of their HR teams
    - bsilvereagle 2y ago
curious_cat_163 2y ago
> While no one is getting as much computing power as they want, the supply is tighter for teams engaged in pure research, say the former employee and others familiar with the lab. Good! Maybe they will focus on researching how to make these things more compute efficient.
- caycep 2y ago
  true. I wonder how much energy in food/farming to develop a 6 yr old human is required vs. the amount required to run a hojillion GPUs running the latest generative algorithms
  - dontlikeyoueith 2y ago
    Assuming dollar cost is a relevant metric, the 6yr old human is far cheaper.
  - whamlastxmas 2y ago
    The training costs of the 6 year old are millions of years of evolution and suffering of billions of people.
    - lupire 2y ago
      Irrelevant, as that's already been paid.
      - FactKnower69 2y ago
        sunk cost fallacy
  - Izikiel43 2y ago
    But can a 6 year old answer millions upon millions of queries? You need a lot of 6 year olds.
    - DrScientist 2y ago
dinobones 2y ago
Overall probably a good move for Google. They were were spending 100s of millions of dollars a year to train RL agents to get good at playing Qwop for close to a decade.
- 29athrowaway 2y ago
  Or chess, go, shogi, arimaa, StarCraft II, etc.
  - summerlight 2y ago
    In a PR perspective, at least AlphaGo did a prominent job for Google. It failed to keep its prestigious status but at least it's a leadership/product side issue, not DeepMind's.
    - hot_gril 2y ago
      That stuff gave Google the appearance of "nerds playing with their toys." Sure it's worthwhile research, but it's not great how many things Google announced that close to 0 people could use. They're trying to be more user-oriented now, and because of Cloud, their users are businesses.
      - FactKnower69 2y ago
        No. AlphaGo et al gave the appearance of "world class researchers achieving state of the art on problem classes that humans have been devoting lifetimes of study for thousands of years". the current desperate LLM scramble, including stuffing shitty, hallucinating, half-baked paraphrase spam to the top of every Google search result page, gives the appearance of "panicked flailing and tacit admission that high level decisionmaking has been captured by terrified MBA types"
        hot_gril 2y ago
        There's a good long middle ground. Search results do seem desperate now, but they got into this position in the first place by failing to execute when they had the advantage. None of Google's customers have ever cared how well an AI can play Go. If there's one place the bragging could've translated to profits, it'd be Tensorflow dominance, which didn't happen.
light_triad 2y ago
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- HWR_14 2y ago
  What's the issue with large companies plowing their profits into pure research?
  - light_triad 2y ago
    ___
  - viscanti 2y ago
    It seems to be difficult to turn the pure research back into new products. Apple famously got lots of ideas for free from Xerox PARC. Google researchers wrote the Attention Is All You Need paper and they're now desperately playing catchup because they couldn't convert it to any kind of product. There's nothing wrong with companies investing in pure research, but these large companies sometimes are unable to take advantage of the research. The people running the business want to keep doing what got them successful, not some new experimental thing that might not work.
    - chasd00 2y ago
      Yeah being first doesn’t mean you win automatically. There’s a story about the Ramones playing a show at a famous club in NYC and everyone in the crowd went home and started bands that became way more successful and famous than who they were trying to be like. …I think blondie was one of the bands that came out of that crowd.
      - n4r9 2y ago
        You might be thinking of the Sex Pistols gig whose audience of 30-40 included Morrissey, Mark E Smith, the Buzzcocks and Lower Broughton: https://www.bbc.co.uk/manchester/content/articles/2006/05/11/110506_sex_pistols_gig_feature.shtml https://www.bbc.co.uk/manchester/content/articles/2006/05/11... The docudrama 24 hour party people is good to watch about this era.
deleted 2y ago
[deleted]
karmasimida 2y ago
AI product factory seems like an odd choice of phrasing ...
- kevinventullo 2y ago
  It’s MBA-speak. “So we put in researchers, and products and money come out. This slide deck is gonna get me promoted.”
ruraljuror 2y ago
> In May, the lab released a new version of AlphaFold, a landmark tool for predicting protein structures. Hassabis says it could develop into a $100 billion business, but some people at Google have questioned whether he should be dedicating so much time to it. Wonder what the timeframe on that speculative return is?
prithvi24 2y ago
> Researchers inside the AI unit have told colleagues they’re proud of their advances on Gemini, such as its “context window,” the amount of information the system can analyze at once. This is particularly useful to a company whose enormous amount of data is one of its key competitive advantages. what does a large context window have anything to do with google's data moat?
- gradus_ad 2y ago
  It's the sort of careless, superficially meaningful statement that an LLM would make...
- mitthrowaway2 2y ago
  My reading is that the large context window makes Gemini useful as a tool to Google.
- seanhunter 2y ago
  I suppose superficially, for retrieval augmented generation use cases, the more data you have (and the better you are at retrieval), the more useful extra space in the context window is because you put things from retrieval into the context of the model to do the generation. That said, literally everyone has more than enough data to completely dwarf the context window of any of the existing models so it seems true but irrelevant. One thing about gemini that may be a benefit here is not just the size of the window, but the fact that the context window seems to be better utilised by the model. GPT-4 seems to have a characteristic where the start and end of the context window are much more important to the model than anything in the middle, meaning that if you stuff the window with retrieved data, things in the middle of the context get ignored by the model. Istr that is not the case with gemini, which takes more notice of things in the middle of the window. Maybe attention is all you need.[1] [1] Sorry for the pun but I couldn't resist. Any case if you search "Perplexity over long sequences" in the gemini 1.5 tech report it explains this effect and shows their results https://storage.googleapis.com/deepmind-media/gemini/gemini_v1_5_report.pdf https://storage.googleapis.com/deepmind-media/gemini/gemini_...
ethbr1 2y ago
> Hassabis says that he’s learning more about introducing products and that Google’s product teams, in turn, are dealing with the novel challenges of generative AI, which has the potential to behave unusually when placed in the hands of the general public. This part isn't rocket science. Step 1) Post on 4chan and SomethingAwful "What is the worst thing you could do with genAI? Go." Step 2) Test your beta product against all the answers you get.
- Barrin92 2y ago
  the tricky part with systems like these isn't to find and fix the worst things that people can come up with on 4chan because they're by definition obvious. The much trickier part is finding the little problems that way more people run into and that most people might not even immediately recognize or report. And that is a very complicated science in particular with something that can be as fuzzy and intransparent as generative AI.
  - eitland 2y ago
    This has been going on since long before[1] the recent AI craze. IMNSHO it seems Google just cannot miss an opportunity to mess up the basics in the quest for amazing and then fail at amazing or cancel it just as they are about to achieve it. And, ironically this has transformed their search engine from unbeatable leader in its field to something much closer to what it replaced. [1]:This is from 5 years ago: https://erik.itland.no/more-fun-with-google-mixing-images-from-different-sources https://erik.itland.no/more-fun-with-google-mixing-images-fr...
  - robertlagrant 2y ago
    > the worst things that people can come up with on 4chan because they're by definition obvious If they're finding your flag through star patterns and flying drones at it to set it on fire, I think they go a bit deeper than "obvious".
- cloudking 2y ago
  I think the challenge is you can't QA every edge case, because there's unlimited edge cases.
therobots927 2y ago
Hadn’t these two AI orgs within Google been fighting over resources for a long time? At the end of the day that’s just counterproductive. A merger was all but guaranteed and it’s clear given current stock market sentiment why the product team was chosen. Doesn’t mean I don’t feel bad for the Deepmind researchers impacted. The genAI hype is sparing no one, not even the foremost AI labs in the country.
banish-m4 2y ago
Meta needs to emulate this because they're sinking tens of billions without being focused enough on delivering profits with all that hardware they're spending treasure on.
- fhub 2y ago
  Meta did $12.4B profit in Q1 2024 which was 116.7% increase year-over-year. They have a lot of treasure to spend and the treasure chest keeps getting bigger.
- aprilthird2021 2y ago
  Pretty untethered take. Meta has seen one of the largest growths in profit in the past few years. Their improvements in AI have made far more profitable their AI ads targeting business
nelsonic 2y ago
Let's not forget that Demis Hassabis (DeepMind CEO) created Theme Park so he knows how to create products. I have full confidence in his leadership. Buy more Alphabet (GOOG) shares! Ref: https://en.wikipedia.org/wiki/Demis_Hassabis#Bullfrog https://en.wikipedia.org/wiki/Demis_Hassabis#Bullfrog
- stephen_cagle 2y ago
  ...and (burying the lead) wrote it while he was under 18! But, that is one of the odder takes for why he would be good at building a product?
  - nelsonic 2y ago
    Demis understands the “customer” and can use everything he has learned in the last 20 years to build something incredible. If he can build a great/successful game with low resources, he will smash a consumer product with unlimited resources and excellent people.
    - seanhunter 2y ago
      I definitely don't think that follows at all.
- pixelpoet 2y ago
  Saw him briefly at my first job at Lionhead Studios, and also worked with Alex Evans (Media Molecule cofounder, coauthor of InstantNGP, legendary demoscener, ...) there. Pretty amazing how much talent was buzzing around there.
nabla9 2y ago
Hassabis moves from fundamental AI research into app development. (alternative title)
chucke1992 2y ago
Essentially Google has no idea how to leverage their AI as Gemini for search just does not work. Apple went with deep AI integration into OS in hope to sell more devices and Microsoft went full blown corporate + windows devices. Google can try to integrate it maybe with Chrome OS to sell more devices? They are also trying with various providers (like Samsung) but nature of Android is that people might just go with basic apps and stuff.
- nolist_policy 2y ago
  Don't forget Google Docs, Drive, Photos, GMail and Chrome.
  - chucke1992 2y ago
    The problem is that none of Google's products are unified into a fully used ecosystem. For example with Apple they integrated everything together seamless into the OS - granted I am not sure if people are using their email app or calendar that often. But with AI they integrated it all together at least. With Microsoft they benefit from their tight integration between Office suite, Outlook, teams (and calendar integration between outlook and teams is quite convenient) etc. They only have issues with consumer products as they are unable to achieve the same level of integrations as they achieve within the corporate - corporate Windows instances with laptops and stuff are corporate to Apple products for consumers. Microsoft does not have user facing products, but their enterprise solutions are nicely connected to each. And new services like Loop or Copilot are just naturally expanded on that. But Google? I literally use Gmail but only for emails. Chrome for browsing but I have no integrations between Chrome and Gmail aside the account overall in my flow. They have their streaming service with Youtube Premium but it is not really that connected to overall other infra or services - unlike for example Apple, that is offering their Apple One subscription. App Stores? Google Play exists in its own universe that has no relation to other google services either. And that's without AI stuff. There is something missing between google services.
    - blueboo 2y ago
      I dunno. Android, Chrome, ChromeOS, Workspace. There’s a lot there that’s knit together. Compared to what, Safari, Pages and Messages? Teams, Word, and Outlook? They all have their issues. Maybe the crux of it is chat. If your work is integrated into your chat — the day to day online social space — it’ll feel “integrated”
amunozo 2y ago
IMO, older DeepMind research was much more exciting and original than nowadays. We do not need more LLMs, we need creativity.
a_bonobo 2y ago
Looking back, I feel like the AlphaFold 3 launch a month ago was a precursor to this move. The public-facing side of AlphaFold 3 ('AlphaFold Server') is severely constrained; if you want the novel parts around drug binding prediction you need to pay Isomorphic Labs instead. https://blog.google/technology/ai/google-deepmind-isomorphic-alphafold-3-ai-model/#drug-discovery https://blog.google/technology/ai/google-deepmind-isomorphic... I expect other developments to follow suite: a bit of R&D with a lot of hype and commercialisation.
- deleted 2y ago
  [deleted]
vladsanchez 2y ago
http://archive.today/zsnps http://archive.today/zsnps
iamleppert 2y ago
Good on them for cracking the whip on those intellectuals and extracting value out of them. Even smart people don't get a pass when it comes to driving shareholder value and fast ROI.
theGnuMe 2y ago
This is most likely a tax thing.
rldjbpin 2y ago
people aka shareholders got what current trends want. but i personally don't think they needed to restructure research division for this.

216 points by kjhughes 2y ago

l1n 2y ago

https://archive.is/5XdU8 https://archive.is/5XdU8

deleted 2y ago

[deleted]

jsemrau 2y ago

"The Overviews launch didn’t go well." understatement of the year.

kevindamm 2y ago

One thing that classic Google did right was embed researchers into product groups. It's true there were always some teams that were pure research but for the most part researchers were working within a product group. Then some acquisitions and internal musical chairs and it became less like that. Now I'm not all doom and gloom like this article (although with DeepMind why not leave well enough alone? They do excellent research). But, it does seem suboptimal to pivot all the way to AI Product Factory... were there no other existing product factories they could have turned instead?

curious_cat_163 2y ago
I agree: hybrid teams with a diversity of product/research skills at the team level is the way to go. It is thinkers and doers that need to come together. It is way easier said than done, though. You need true buy in from a ton of stakeholders — employees being the primary ones. And people get set in their ways. I do like a product bias though. Not because it is more valuable somehow but because it provides the applied scientists deeper exposure to the problem space, early and often.
flakiness 2y ago
The heads of the research once wrote about that. They called it a "Hybrid Approach to Research" (as other comments pointed out). https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/38149.pdf https://static.googleusercontent.com/media/research.google.c...
- moandcompany 2y ago
  The "Hybrid Approach to Research" paper describes how "Google Research" first started when Google was mostly, if not entirely, about Search and "Research" was part of the Search organization. In these days, there were no "pure research" roles, nor were there formal designations for "research scientists" as a career ladder at Google. There were "SWEs" and in some cases "Members of Technical Staff." Since then, "Research" became its own organization or "Product Area" at Google (i.e. the equivalent of a company division). "Google Brain" was also created. Deepmind was acquired. All of these existed simultaneously, however Deepmind remained as an organizationally separate entity. In this era, the "Research Scientist" role was created, which generally existed exclusively within "Google Research." A large span of this era had John Giannandrea ("JG") at the helm of the Google Research org; (note: Giannandrea left to head and build Apple's "AI/ML" organization, which includes Siri, a few years ago. After JG's departure, Google Brain and Google Research were brought together under the common leadership of Jeff Dean, as an organization called still called "Google Research" with a branch still called "Google Brain." For perspective, it may be useful to consider too that the size of "Google Research" in staff headcount here measured in the several-thousands. This configuration existed for the last few years, with the latest changes being the merging of "Google Research" and Deepmind into "Google Deepmind." - I am a Xoogler, formerly from this product area. One of the things I and at least a few others observed was that "Research" was becoming defacto synonymous with "Machine Learning / AI," yet not all of Google's storied research accomplishments, or problem areas, are limited to Machine Learning and AI. In the last few years, Google made its public statements of being an "AI-first," previously "mobile-first," company in recognition that it would be incorporating and leveraging ML and AI technology across all of its products and services. This raised a significant question: What should "Google Research" or Research at Google be if product areas across Google began full incorporation of AI/ML technology and methods in their products? What if they incorporated their own AI/ML teams? If Google was truly successful at becoming AI-first, how should "Google Research" define and focus its organizational purpose, research portfolio, and show its value when Moonshots/X also exists within Alphabet? Over time, there were many parts of "Google Research" and research at large across Alphabet that felt that their purpose, or at least their individual reason for joining, was to do "pure research," yet this is not how the organizations started at all in the beginning. Many researchers and teams also knew that for practical reasons (e.g. promotion) that they generally needed to present and align their work with things like product launches with partner organizations. I suppose we are seeing some of the answer to this with Google DeepMind stating that they will be aligning more strongly with creating AI products, but in addition to the question of what happens to foundational research (for AI), what happens to foundational research in non-AI areas for Google and Alphabet?

radicaldreamer 2y ago

Why? Attach seasoned product teams from Google to the research org and have experienced PMs paired with experienced EMs launch products. Trying to transition a research org into a product org is going to be needlessly painful, especially since the research org needs to be firing on all cylinders in this hyper-competitive space.

advael 2y ago
God, yea. I've flipped between R&D and product development a few times in my career, sometimes at the same company, and it's a really rough transition even for an individual experienced in both. I can't imagine trying to flip a whole research team to make products is going to go well, especially when the products are getting a ton of well-deserved bad press and a lot of those researchers were coming from academia rather than elsewhere in industry in the first place
gaogao 2y ago
Agreed. As an example of that, Meta's kept its research org, FAIR, still doing fundamental research. Research orgs are great at demos, but actual productionalization takes a different mindset.
- nomad_horse 2y ago
  FAIR is considerably downscaled from what it was before, in eg 2022.
- fooker 2y ago
  Fun anecdote: some folks from FAIR reached out to a friend, asked her to apply, and then rejected her without an interview!
  - htrp 2y ago
    Facebook's recruiting funnel is super broken after they fired a ton of their HR teams
  - bsilvereagle 2y ago

curious_cat_163 2y ago

> While no one is getting as much computing power as they want, the supply is tighter for teams engaged in pure research, say the former employee and others familiar with the lab. Good! Maybe they will focus on researching how to make these things more compute efficient.

caycep 2y ago
true. I wonder how much energy in food/farming to develop a 6 yr old human is required vs. the amount required to run a hojillion GPUs running the latest generative algorithms
- dontlikeyoueith 2y ago
  Assuming dollar cost is a relevant metric, the 6yr old human is far cheaper.
- whamlastxmas 2y ago
  The training costs of the 6 year old are millions of years of evolution and suffering of billions of people.
  - lupire 2y ago
    Irrelevant, as that's already been paid.
    - FactKnower69 2y ago
      sunk cost fallacy
- Izikiel43 2y ago
  But can a 6 year old answer millions upon millions of queries? You need a lot of 6 year olds.
  - DrScientist 2y ago

dinobones 2y ago

Overall probably a good move for Google. They were were spending 100s of millions of dollars a year to train RL agents to get good at playing Qwop for close to a decade.

29athrowaway 2y ago
Or chess, go, shogi, arimaa, StarCraft II, etc.
- summerlight 2y ago
  In a PR perspective, at least AlphaGo did a prominent job for Google. It failed to keep its prestigious status but at least it's a leadership/product side issue, not DeepMind's.
  - hot_gril 2y ago
    That stuff gave Google the appearance of "nerds playing with their toys." Sure it's worthwhile research, but it's not great how many things Google announced that close to 0 people could use. They're trying to be more user-oriented now, and because of Cloud, their users are businesses.
    - FactKnower69 2y ago
      No. AlphaGo et al gave the appearance of "world class researchers achieving state of the art on problem classes that humans have been devoting lifetimes of study for thousands of years". the current desperate LLM scramble, including stuffing shitty, hallucinating, half-baked paraphrase spam to the top of every Google search result page, gives the appearance of "panicked flailing and tacit admission that high level decisionmaking has been captured by terrified MBA types"
      - hot_gril 2y ago
        There's a good long middle ground. Search results do seem desperate now, but they got into this position in the first place by failing to execute when they had the advantage. None of Google's customers have ever cared how well an AI can play Go. If there's one place the bragging could've translated to profits, it'd be Tensorflow dominance, which didn't happen.

light_triad 2y ago

___

HWR_14 2y ago
What's the issue with large companies plowing their profits into pure research?
- light_triad 2y ago
  ___
- viscanti 2y ago
  It seems to be difficult to turn the pure research back into new products. Apple famously got lots of ideas for free from Xerox PARC. Google researchers wrote the Attention Is All You Need paper and they're now desperately playing catchup because they couldn't convert it to any kind of product. There's nothing wrong with companies investing in pure research, but these large companies sometimes are unable to take advantage of the research. The people running the business want to keep doing what got them successful, not some new experimental thing that might not work.
  - chasd00 2y ago
    Yeah being first doesn’t mean you win automatically. There’s a story about the Ramones playing a show at a famous club in NYC and everyone in the crowd went home and started bands that became way more successful and famous than who they were trying to be like. …I think blondie was one of the bands that came out of that crowd.
    - n4r9 2y ago
      You might be thinking of the Sex Pistols gig whose audience of 30-40 included Morrissey, Mark E Smith, the Buzzcocks and Lower Broughton: https://www.bbc.co.uk/manchester/content/articles/2006/05/11/110506_sex_pistols_gig_feature.shtml https://www.bbc.co.uk/manchester/content/articles/2006/05/11... The docudrama 24 hour party people is good to watch about this era.

deleted 2y ago

[deleted]

karmasimida 2y ago

AI product factory seems like an odd choice of phrasing ...

kevinventullo 2y ago
It’s MBA-speak. “So we put in researchers, and products and money come out. This slide deck is gonna get me promoted.”

ruraljuror 2y ago

> In May, the lab released a new version of AlphaFold, a landmark tool for predicting protein structures. Hassabis says it could develop into a $100 billion business, but some people at Google have questioned whether he should be dedicating so much time to it. Wonder what the timeframe on that speculative return is?

prithvi24 2y ago

> Researchers inside the AI unit have told colleagues they’re proud of their advances on Gemini, such as its “context window,” the amount of information the system can analyze at once. This is particularly useful to a company whose enormous amount of data is one of its key competitive advantages. what does a large context window have anything to do with google's data moat?

gradus_ad 2y ago
It's the sort of careless, superficially meaningful statement that an LLM would make...
mitthrowaway2 2y ago
My reading is that the large context window makes Gemini useful as a tool to Google.
seanhunter 2y ago
I suppose superficially, for retrieval augmented generation use cases, the more data you have (and the better you are at retrieval), the more useful extra space in the context window is because you put things from retrieval into the context of the model to do the generation. That said, literally everyone has more than enough data to completely dwarf the context window of any of the existing models so it seems true but irrelevant. One thing about gemini that may be a benefit here is not just the size of the window, but the fact that the context window seems to be better utilised by the model. GPT-4 seems to have a characteristic where the start and end of the context window are much more important to the model than anything in the middle, meaning that if you stuff the window with retrieved data, things in the middle of the context get ignored by the model. Istr that is not the case with gemini, which takes more notice of things in the middle of the window. Maybe attention is all you need.[1] [1] Sorry for the pun but I couldn't resist. Any case if you search "Perplexity over long sequences" in the gemini 1.5 tech report it explains this effect and shows their results https://storage.googleapis.com/deepmind-media/gemini/gemini_v1_5_report.pdf https://storage.googleapis.com/deepmind-media/gemini/gemini_...

ethbr1 2y ago

> Hassabis says that he’s learning more about introducing products and that Google’s product teams, in turn, are dealing with the novel challenges of generative AI, which has the potential to behave unusually when placed in the hands of the general public. This part isn't rocket science. Step 1) Post on 4chan and SomethingAwful "What is the worst thing you could do with genAI? Go." Step 2) Test your beta product against all the answers you get.

Barrin92 2y ago
the tricky part with systems like these isn't to find and fix the worst things that people can come up with on 4chan because they're by definition obvious. The much trickier part is finding the little problems that way more people run into and that most people might not even immediately recognize or report. And that is a very complicated science in particular with something that can be as fuzzy and intransparent as generative AI.
- eitland 2y ago
  This has been going on since long before[1] the recent AI craze. IMNSHO it seems Google just cannot miss an opportunity to mess up the basics in the quest for amazing and then fail at amazing or cancel it just as they are about to achieve it. And, ironically this has transformed their search engine from unbeatable leader in its field to something much closer to what it replaced. [1]:This is from 5 years ago: https://erik.itland.no/more-fun-with-google-mixing-images-from-different-sources https://erik.itland.no/more-fun-with-google-mixing-images-fr...
- robertlagrant 2y ago
  > the worst things that people can come up with on 4chan because they're by definition obvious If they're finding your flag through star patterns and flying drones at it to set it on fire, I think they go a bit deeper than "obvious".
cloudking 2y ago
I think the challenge is you can't QA every edge case, because there's unlimited edge cases.

therobots927 2y ago

Hadn’t these two AI orgs within Google been fighting over resources for a long time? At the end of the day that’s just counterproductive. A merger was all but guaranteed and it’s clear given current stock market sentiment why the product team was chosen. Doesn’t mean I don’t feel bad for the Deepmind researchers impacted. The genAI hype is sparing no one, not even the foremost AI labs in the country.

banish-m4 2y ago

Meta needs to emulate this because they're sinking tens of billions without being focused enough on delivering profits with all that hardware they're spending treasure on.

fhub 2y ago
Meta did $12.4B profit in Q1 2024 which was 116.7% increase year-over-year. They have a lot of treasure to spend and the treasure chest keeps getting bigger.
aprilthird2021 2y ago
Pretty untethered take. Meta has seen one of the largest growths in profit in the past few years. Their improvements in AI have made far more profitable their AI ads targeting business

nelsonic 2y ago

Let's not forget that Demis Hassabis (DeepMind CEO) created Theme Park so he knows how to create products. I have full confidence in his leadership. Buy more Alphabet (GOOG) shares! Ref: https://en.wikipedia.org/wiki/Demis_Hassabis#Bullfrog https://en.wikipedia.org/wiki/Demis_Hassabis#Bullfrog

stephen_cagle 2y ago
...and (burying the lead) wrote it while he was under 18! But, that is one of the odder takes for why he would be good at building a product?
- nelsonic 2y ago
  Demis understands the “customer” and can use everything he has learned in the last 20 years to build something incredible. If he can build a great/successful game with low resources, he will smash a consumer product with unlimited resources and excellent people.
  - seanhunter 2y ago
    I definitely don't think that follows at all.
pixelpoet 2y ago
Saw him briefly at my first job at Lionhead Studios, and also worked with Alex Evans (Media Molecule cofounder, coauthor of InstantNGP, legendary demoscener, ...) there. Pretty amazing how much talent was buzzing around there.

nabla9 2y ago

Hassabis moves from fundamental AI research into app development. (alternative title)

chucke1992 2y ago

Essentially Google has no idea how to leverage their AI as Gemini for search just does not work. Apple went with deep AI integration into OS in hope to sell more devices and Microsoft went full blown corporate + windows devices. Google can try to integrate it maybe with Chrome OS to sell more devices? They are also trying with various providers (like Samsung) but nature of Android is that people might just go with basic apps and stuff.

nolist_policy 2y ago
Don't forget Google Docs, Drive, Photos, GMail and Chrome.
- chucke1992 2y ago
  The problem is that none of Google's products are unified into a fully used ecosystem. For example with Apple they integrated everything together seamless into the OS - granted I am not sure if people are using their email app or calendar that often. But with AI they integrated it all together at least. With Microsoft they benefit from their tight integration between Office suite, Outlook, teams (and calendar integration between outlook and teams is quite convenient) etc. They only have issues with consumer products as they are unable to achieve the same level of integrations as they achieve within the corporate - corporate Windows instances with laptops and stuff are corporate to Apple products for consumers. Microsoft does not have user facing products, but their enterprise solutions are nicely connected to each. And new services like Loop or Copilot are just naturally expanded on that. But Google? I literally use Gmail but only for emails. Chrome for browsing but I have no integrations between Chrome and Gmail aside the account overall in my flow. They have their streaming service with Youtube Premium but it is not really that connected to overall other infra or services - unlike for example Apple, that is offering their Apple One subscription. App Stores? Google Play exists in its own universe that has no relation to other google services either. And that's without AI stuff. There is something missing between google services.
  - blueboo 2y ago
    I dunno. Android, Chrome, ChromeOS, Workspace. There’s a lot there that’s knit together. Compared to what, Safari, Pages and Messages? Teams, Word, and Outlook? They all have their issues. Maybe the crux of it is chat. If your work is integrated into your chat — the day to day online social space — it’ll feel “integrated”

amunozo 2y ago

IMO, older DeepMind research was much more exciting and original than nowadays. We do not need more LLMs, we need creativity.

a_bonobo 2y ago

Looking back, I feel like the AlphaFold 3 launch a month ago was a precursor to this move. The public-facing side of AlphaFold 3 ('AlphaFold Server') is severely constrained; if you want the novel parts around drug binding prediction you need to pay Isomorphic Labs instead. https://blog.google/technology/ai/google-deepmind-isomorphic-alphafold-3-ai-model/#drug-discovery https://blog.google/technology/ai/google-deepmind-isomorphic... I expect other developments to follow suite: a bit of R&D with a lot of hype and commercialisation.

deleted 2y ago
[deleted]

vladsanchez 2y ago

http://archive.today/zsnps http://archive.today/zsnps

iamleppert 2y ago

Good on them for cracking the whip on those intellectuals and extracting value out of them. Even smart people don't get a pass when it comes to driving shareholder value and fast ROI.

theGnuMe 2y ago

This is most likely a tax thing.

rldjbpin 2y ago

people aka shareholders got what current trends want. but i personally don't think they needed to restructure research division for this.