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michael_nielsen's profile
michael_nielsen
michael_nielsen
michael_nielsen
@michael_nielsen

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michael_nielsen

@michael_nielsen

Searching for the numinous. Co-purveyor of https://quantum.country/ 

San Francisco, CA
michaelnielsen.org
Joined July 2008

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    1. OpenAI‏Verified account @OpenAI 16 May 2018
      • Report Tweet

      AI and Compute: Our analysis showing that the amount of compute used in the largest AI training runs has had a doubling period of 3.5 months since 2012 (net increase of 300,000x):https://blog.openai.com/ai-and-compute/ 

      26 replies 472 retweets 1,116 likes
      Show this thread
    2. OpenAI‏Verified account @OpenAI Nov 7
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      We've analyzed compute used in major AI results for the past decades and identified two eras in AI: 1) Prior to 2012 - AI results closely tracked Moore's Law, w/ compute doubling every two years. 2) Post-2012 - compute has been doubling every 3.4 months https://openai.com/blog/ai-and-compute/#addendum …pic.twitter.com/ILN5MRrWYH

      24 replies 298 retweets 683 likes
      Show this thread
    3. Grady Booch‏Verified account @Grady_Booch Nov 7
      • Report Tweet
      Replying to @OpenAI

      Where would Deep Blue and Watson fit on this chart? They are - surprisingly - missing.

      1 reply 1 retweet 15 likes
    4. Jack Clark‏ @jackclarkSF Nov 7
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      Replying to @Grady_Booch @OpenAI

      We plotted Deep Blue on this early on in the analysis, but took it out of the chart as these results are ones which predominantly use ML. I'm not sure if there was enough info in the Watson papers to do a compute calc.

      2 replies 0 retweets 2 likes
    5. Jack Clark‏ @jackclarkSF Nov 7
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      Replying to @jackclarkSF @Grady_Booch @OpenAI

      Here is the deep blue number & method, hope helpful!pic.twitter.com/iQVqN4GKhW

      1 reply 0 retweets 0 likes
    6. girish sastry‏ @girishsastry Nov 7
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      Replying to @jackclarkSF @Grady_Booch @OpenAI

      Yep, note that this was an initial cut at deep blue and makes some assumptions re: utilization and “thinking time”. As jack said, for this particular analysis we looked at learning systems in particular

      1 reply 0 retweets 2 likes
    7. michael_nielsen‏ @michael_nielsen Nov 7
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      Replying to @girishsastry @jackclarkSF and

      Where did the 11 GF / sec number come from? IIRC, the papers says they could evaluate ~200 mill positions per second, and were calculating ~8,000 features per position. That makes it at least 1 TF / sec, and probably at least an order of magnitude higher.

      2 replies 0 retweets 0 likes
    8. michael_nielsen‏ @michael_nielsen Nov 7
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      Replying to @michael_nielsen @girishsastry and

      michael_nielsen Retweeted michael_nielsen

      I checked the numbers. Deep Blue (1997) appears comparable to the 2012 systems:https://twitter.com/michael_nielsen/status/1192667888840142848 …

      michael_nielsen added,

      michael_nielsen @michael_nielsen
      Interesting to add Deep Blue to this graph. The 1997 system achieved ~8 Teraflops / sec, according to IBM's paper. I don't know how long it ran in the Kasparov match, but it was many hours, maybe tens of hours. So it's between 10^-3 and 10^-2 PF days, above DQN, below AlexNet. https://twitter.com/OpenAI/status/1192481690741903360 …
      Show this thread
      1 reply 2 retweets 3 likes
    9. Grady Booch‏Verified account @Grady_Booch Nov 7
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      Replying to @michael_nielsen @girishsastry and

      Fantastic!

      1 reply 0 retweets 1 like
    10. michael_nielsen‏ @michael_nielsen Nov 7
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      Replying to @Grady_Booch @girishsastry and

      A caveat: as a commenter points out, the Deep Blue numbers aren't Flops, but a somewhat different kind of operation. Still, it's pretty clearly in the 2012 ballpark.

      1 reply 0 retweets 1 like
      michael_nielsen‏ @michael_nielsen Nov 7
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      Replying to @michael_nielsen @Grady_Booch and

      Amusing: if you extrapolate back to Deep Blue's 1997 performance, then the doubling time becomes... roughly every 2 years.

      9:12 PM - 7 Nov 2019
      • 1 Like
      • Julián Bravo Ⓥ
      1 reply 0 retweets 1 like
        1. Grady Booch‏Verified account @Grady_Booch Nov 7
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          Replying to @michael_nielsen @girishsastry @jackclarkSF

          pic.twitter.com/7hPzboFkWw

          0 replies 0 retweets 0 likes
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