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Google search was 1998. Google Maps was 2005. Gmail was 2004. Android was 2008. Youtube was 2005. Chrome was 2008. Docs was 2006. Translate was 2006. Ye

Google search was 1998. Google Maps was 2005. Gmail was 2004. Android was 2008. Youtube was 2005. Chrome was 2008. Docs was 2006. Translate was 2006. Yet in the last decade, they really haven't had many successes (perhaps with the exception of Google Photos - 2015) One would imagine that with nearly 200,000 employees at least one of them would have a good enough idea for a new product people like. But management and culture, with 'more wood behind fewer arrows', is no longer conducive to the good ideas getting launched.

danpalmer 3y ago
This is a common meme, but it depends how you define "product". There are companies with millions in VC backing that would just be a feature on a Google (or other big tech company) product as most people define them. I would argue that taking a product from 100m to 1bn users is a whole new level of success, and that has been done multiple times in the last decade.
- water-your-self 3y ago
  Why should scaling matter? I thought google tried to solve problems regardless of scale? Or maybe youre commending google for its ability to more effectively commodify datacenter labour in the past decade?
  - danpalmer 3y ago
    I don't think we can expect businesses to solve problems without any business upside. I don't hold that against any company. That means needing some amount of scale in order to justify the work and opportunity cost.
  - londons_explore 3y ago
    'free' ad supported products usually have engineering costs greater than compute costs, even up to billions of users. Compute scales with the userbase. Engineering scales with the product featureset. That means a small userbase in general cannot support much engineering and therefore cannot have much complexity/features if it wants to be profitable. That in turn puts big companies at a massive advantage. And in fact we see that - the vast majority of my time using the web is spent on big products (google, youtube, reddit, twitter), and only a small fraction on small sites (perhaps HN being the one exception here). Those big products won the battle for my attention.
fizigura 3y ago
If you compare the Android from 2008 and the Android from 2023 then you'd soon agree that within these 15 years, the whole thing was re-invented multiple times. And I'm not talking the UX, which has already changed substantially, but I mean the underpinnings.
- londons_explore 3y ago
  Sure. But as far as the user is concerned, it is much the same. Touchscreen apps, app store, camera, wifi and phone abilities, app switcher and back button. The user doesn't care that the wheel has been reinvented 3 times along the way... There hasn't been any revolutionary new features in android since shortly after launch really. There have been revolutions in apps. For example, pre 2017 I couldn't just tap a button and get an Uber. Or tap a button and have food delivered. Or do a video call with all my friends. But the OS can't really claim credit for most of that innovation.
  - fizigura 3y ago
    > There hasn't been any revolutionary new features in android since shortly after launch really. Not visibly. But the tech stack has changed substantially. I'd find it quite an achievement if the UX has largely stayed the same while things under the hood got modernized over and over again and went with the times, subtly bringing innovations to the UX as well without people realizing. It's a feature that things don't look substantially different every two years.
    - saalweachter 3y ago
      Android Auto was 2015.
      - londons_explore 3y ago
        Hasn't really seen widespread acceptance. I bet a sample of 100 cars on the freeway, perhaps only 25% would have carplay or android auto connected in the USA, and outside the USA adoption is far lower.
layer8 3y ago
> perhaps with the exception of Google Photos Which is somewhat offset by Google dropping Picasa.
ajross 3y ago
> Google search was 1998. Google Maps was 2005. Gmail was 2004. Android was 2008. Youtube was 2005. Chrome was 2008. Docs was 2006. > Yet in the last decade, they really haven't had many successes I don't think this kind of analysis is really giving a good answer. I mean, by these standards, look what a disaster of a dinosaur legacy vendor Apple Computer is! Haven't had a successful product launch since the iPad 13 years ago! (Perhaps with the exception of Apple Watch - 2015).
VirusNewbie 3y ago
K8s, TPU Colab Tensorflow hmmm.
- londons_explore 3y ago
  Oh yes - google still has great technology - but they aren't consumer products.
docandrew 3y ago
Also Maps, Android and YouTube were started by other companies which were acquired.
systemBuilder 3y ago
You have the wrong impression of Google Translate. Translate was started in 2006 and it sucked. 60% accuracy at best. Janky incoherent sentences. Translate revolutionized the entire field of language translation in 2016. Seriously. Went to 94% accuracy when Jeff Dean joined the project and spurred them to train against all languages at once. It revolutionized the whole research field of language translation. Translate is now better than most high school students after several years of study. I consider Translate to be one of the top-5 accomplishments that Google ever had: https://translatepress.com/is-google-translate-correct/ https://translatepress.com/is-google-translate-correct/ Another breakthrough is picture recognition. Did you know you can type in "motorcycles" and do an image search and there is ZERO text associated with many of those pictures of motorcycles? They really are mapreducing those pictures and running image recognition against a 17M open-source image library to assess "motorcycle-ness" of all those pictures! They started talking about picture recognition in the early 2000's but it really began happening in the late 2010's after they hired fei fei li, the mother of image recognition ... https://profiles.stanford.edu/fei-fei-li https://profiles.stanford.edu/fei-fei-li
- nvm0n2 3y ago
  Translate did not suck in 2006, it was a big leap over the competitors at the time. It was really the first time a company had launched productized statistical machine translation at all. Before that there was the Altavista Babelfish which was rules based. Going neural definitely made a big difference but Translate was called "statml" by the infrastructure internally for years, maybe still is, because just using statistics and having training at all was a big deal back then.

danpalmer 3y ago

This is a common meme, but it depends how you define "product". There are companies with millions in VC backing that would just be a feature on a Google (or other big tech company) product as most people define them. I would argue that taking a product from 100m to 1bn users is a whole new level of success, and that has been done multiple times in the last decade.

water-your-self 3y ago
Why should scaling matter? I thought google tried to solve problems regardless of scale? Or maybe youre commending google for its ability to more effectively commodify datacenter labour in the past decade?
- danpalmer 3y ago
  I don't think we can expect businesses to solve problems without any business upside. I don't hold that against any company. That means needing some amount of scale in order to justify the work and opportunity cost.
- londons_explore 3y ago
  'free' ad supported products usually have engineering costs greater than compute costs, even up to billions of users. Compute scales with the userbase. Engineering scales with the product featureset. That means a small userbase in general cannot support much engineering and therefore cannot have much complexity/features if it wants to be profitable. That in turn puts big companies at a massive advantage. And in fact we see that - the vast majority of my time using the web is spent on big products (google, youtube, reddit, twitter), and only a small fraction on small sites (perhaps HN being the one exception here). Those big products won the battle for my attention.

fizigura 3y ago

If you compare the Android from 2008 and the Android from 2023 then you'd soon agree that within these 15 years, the whole thing was re-invented multiple times. And I'm not talking the UX, which has already changed substantially, but I mean the underpinnings.

londons_explore 3y ago
Sure. But as far as the user is concerned, it is much the same. Touchscreen apps, app store, camera, wifi and phone abilities, app switcher and back button. The user doesn't care that the wheel has been reinvented 3 times along the way... There hasn't been any revolutionary new features in android since shortly after launch really. There have been revolutions in apps. For example, pre 2017 I couldn't just tap a button and get an Uber. Or tap a button and have food delivered. Or do a video call with all my friends. But the OS can't really claim credit for most of that innovation.
- fizigura 3y ago
  > There hasn't been any revolutionary new features in android since shortly after launch really. Not visibly. But the tech stack has changed substantially. I'd find it quite an achievement if the UX has largely stayed the same while things under the hood got modernized over and over again and went with the times, subtly bringing innovations to the UX as well without people realizing. It's a feature that things don't look substantially different every two years.
  - saalweachter 3y ago
    Android Auto was 2015.
    - londons_explore 3y ago
      Hasn't really seen widespread acceptance. I bet a sample of 100 cars on the freeway, perhaps only 25% would have carplay or android auto connected in the USA, and outside the USA adoption is far lower.

layer8 3y ago

> perhaps with the exception of Google Photos Which is somewhat offset by Google dropping Picasa.

ajross 3y ago

> Google search was 1998. Google Maps was 2005. Gmail was 2004. Android was 2008. Youtube was 2005. Chrome was 2008. Docs was 2006. > Yet in the last decade, they really haven't had many successes I don't think this kind of analysis is really giving a good answer. I mean, by these standards, look what a disaster of a dinosaur legacy vendor Apple Computer is! Haven't had a successful product launch since the iPad 13 years ago! (Perhaps with the exception of Apple Watch - 2015).

VirusNewbie 3y ago

K8s, TPU Colab Tensorflow hmmm.

londons_explore 3y ago
Oh yes - google still has great technology - but they aren't consumer products.

docandrew 3y ago

Also Maps, Android and YouTube were started by other companies which were acquired.

systemBuilder 3y ago

You have the wrong impression of Google Translate. Translate was started in 2006 and it sucked. 60% accuracy at best. Janky incoherent sentences. Translate revolutionized the entire field of language translation in 2016. Seriously. Went to 94% accuracy when Jeff Dean joined the project and spurred them to train against all languages at once. It revolutionized the whole research field of language translation. Translate is now better than most high school students after several years of study. I consider Translate to be one of the top-5 accomplishments that Google ever had: https://translatepress.com/is-google-translate-correct/ https://translatepress.com/is-google-translate-correct/ Another breakthrough is picture recognition. Did you know you can type in "motorcycles" and do an image search and there is ZERO text associated with many of those pictures of motorcycles? They really are mapreducing those pictures and running image recognition against a 17M open-source image library to assess "motorcycle-ness" of all those pictures! They started talking about picture recognition in the early 2000's but it really began happening in the late 2010's after they hired fei fei li, the mother of image recognition ... https://profiles.stanford.edu/fei-fei-li https://profiles.stanford.edu/fei-fei-li

nvm0n2 3y ago
Translate did not suck in 2006, it was a big leap over the competitors at the time. It was really the first time a company had launched productized statistical machine translation at all. Before that there was the Altavista Babelfish which was rules based. Going neural definitely made a big difference but Translate was called "statml" by the infrastructure internally for years, maybe still is, because just using statistics and having training at all was a big deal back then.