3 ms·

One might assume, though, that Google could've applied more homegrown ML to the same problem and achieved significant savings as well.

ACow_Adonis 10y ago
Indeed. One of the "elephant in the room" parts of all of these corporate/pr press releases dressed up as news/revenue reports is that they never report or investigate opportunity cost: say how much could google have saved with a simple algorithm, homegrown solution, or 4 heuristic if/then/else statements. I've been involved with similar multi-million dollar projects that were reported to be bringing in XX million in revenue/savings over three years. What isn't reported is that the revenue was just being moved from another project that was canned, and a guy in an office for a week looking at a spreadsheet could have found similar savings without the expense/complexity. (Not that I'm saying that's what's happening in google s case, but the fluff peices are so universally fluffy, you aren't given enough information to know that it isn't)
- ben_jones 10y ago
  I wonder what the opportunity cost is for the various departments that get put into overdrive for any acquisition: business analysts doing number crunching, legal doing legal, engineers doing various integrations, executives doing lunches. Countless (tens of?) thousands of hours of work before any productivity is yielded, and then when it finally is yielded its propped up by all kinds of dubious accounting to seem like more of a success then it probably was..
- Godel_unicode 10y ago
  Deep mind is needed for other things (e.g. search results). Effectively, the cost of developing it is paid for by search et al, and the only cost core infrastructure has is adapting the existing technology to work on power data as well. This is that "synergy" thing we always snicker at when people in suits say it. It just happens to be true here. Sidebar: the sour grapes in this thread about what Google has apparently accomplished here is amazing. If any other company said they used machine learning to save that much money people would be singing their praises and begging for it to be open-sourced. This thread effectively reads as "pics or it didn't happen"
  - hueving 10y ago
    >begging for it to be open-sourced. This thread effectively reads as "pics or it didn't happen" Likely because it won't be open sources and because there are almost no details at all compared to how this would have worked with other ML techniques. It's nothing but a fluff piece to feed to investors wondering about the large purchase.
    - Godel_unicode 10y ago
      While I agree that this is fluffy, I would submit that: 1 There are a number of other organizations with serious ML chops 2 Knowing that something is possible is frequently the biggest aid to making it happen 3 This solution is likely tightly coupled with Google's infrastructure
  - argonaut 10y ago
    On the contrary, my experience with HN is that people are across-the-board far too accepting, credulous, and unskeptical of machine learning posts, especially given how most commenters have little ML experience and given how incredibly easy in machine learning it is to create "amazing" results that are actually worthless. This is particularly unique to the field of AI/ML - it's pretty hard to bullshit a new programming language you've developed, or a new mobile app you've published.
xbmcuser 10y ago
Google already used neural networks earlier to get efficiency improvements earlier these improvement are on top of that. Another thing google for years has been working on producing the cheapest and most efficient servers possible from the ground up so something improving on that is a win for google I have started feeling that most people and governments don't realise how big machine and deep learning can become and the jobs its likely going to effect.
bemmu 10y ago
They could also have just licensed DeepMind for this particular purpose, without having to buy the entire company.

ACow_Adonis 10y ago

Indeed. One of the "elephant in the room" parts of all of these corporate/pr press releases dressed up as news/revenue reports is that they never report or investigate opportunity cost: say how much could google have saved with a simple algorithm, homegrown solution, or 4 heuristic if/then/else statements. I've been involved with similar multi-million dollar projects that were reported to be bringing in XX million in revenue/savings over three years. What isn't reported is that the revenue was just being moved from another project that was canned, and a guy in an office for a week looking at a spreadsheet could have found similar savings without the expense/complexity. (Not that I'm saying that's what's happening in google s case, but the fluff peices are so universally fluffy, you aren't given enough information to know that it isn't)

ben_jones 10y ago
I wonder what the opportunity cost is for the various departments that get put into overdrive for any acquisition: business analysts doing number crunching, legal doing legal, engineers doing various integrations, executives doing lunches. Countless (tens of?) thousands of hours of work before any productivity is yielded, and then when it finally is yielded its propped up by all kinds of dubious accounting to seem like more of a success then it probably was..
Godel_unicode 10y ago
Deep mind is needed for other things (e.g. search results). Effectively, the cost of developing it is paid for by search et al, and the only cost core infrastructure has is adapting the existing technology to work on power data as well. This is that "synergy" thing we always snicker at when people in suits say it. It just happens to be true here. Sidebar: the sour grapes in this thread about what Google has apparently accomplished here is amazing. If any other company said they used machine learning to save that much money people would be singing their praises and begging for it to be open-sourced. This thread effectively reads as "pics or it didn't happen"
- hueving 10y ago
  >begging for it to be open-sourced. This thread effectively reads as "pics or it didn't happen" Likely because it won't be open sources and because there are almost no details at all compared to how this would have worked with other ML techniques. It's nothing but a fluff piece to feed to investors wondering about the large purchase.
  - Godel_unicode 10y ago
    While I agree that this is fluffy, I would submit that: 1 There are a number of other organizations with serious ML chops 2 Knowing that something is possible is frequently the biggest aid to making it happen 3 This solution is likely tightly coupled with Google's infrastructure
- argonaut 10y ago
  On the contrary, my experience with HN is that people are across-the-board far too accepting, credulous, and unskeptical of machine learning posts, especially given how most commenters have little ML experience and given how incredibly easy in machine learning it is to create "amazing" results that are actually worthless. This is particularly unique to the field of AI/ML - it's pretty hard to bullshit a new programming language you've developed, or a new mobile app you've published.

xbmcuser 10y ago

Google already used neural networks earlier to get efficiency improvements earlier these improvement are on top of that. Another thing google for years has been working on producing the cheapest and most efficient servers possible from the ground up so something improving on that is a win for google I have started feeling that most people and governments don't realise how big machine and deep learning can become and the jobs its likely going to effect.

bemmu 10y ago

They could also have just licensed DeepMind for this particular purpose, without having to buy the entire company.