Wiktor Sierociński

@wsieroci

Software Engineer @ 9LivesData - working on automated machine learning platform for predictive modeling

Warsaw, Poland
Joined April 2015
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  1. Retweeted
    Sep 26

    Things money can't buy: 1) happiness 2) love 3) product market fit

    37 replies 710 retweets 2,403 likes
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  2. Retweeted
    Sep 6

    Tesla, software and disruption

    1 retweet
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  3. Retweeted
    Aug 13

    People confuse decentralization as a governance goal, and decentralized computing as an implementation choice. You can use decentralized protocols to build highly centralized power structures, and inversely you can use centralized tools to build orgs where power is distributed

    6 replies 106 retweets 333 likes
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  4. May 27

    1 like
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  5. Retweeted
    Apr 10

    Productivity:

    50 replies 379 retweets 1,265 likes
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  6. Retweeted
    Mar 19

    You can be wrong on a lot of decisions if you are really right on a few huge ones. Optimize for the magnitude of your good decisions, not the percentage of the time you are right.

    71 replies 1,502 retweets 4,346 likes
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  7. Retweeted
    Feb 14

    "Deep Reinforcement Learning Doesn't Work Yet" great read, hits a lot of points I've also come to realize over last ~2 years. 70% is a vast understatement.

    22 replies 652 retweets 1,551 likes
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  8. Retweeted
    Feb 8

    When approaching a new problem, by focusing on easy wins you can sometimes deliver 20% of the results with 1% of the effort. The trap is to extrapolate that the problem will be fully solved if you work on it just 5x longer. Widely applicable to AI successes...

    17 replies 255 retweets 801 likes
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  9. Retweeted
    Jan 24

    My raw video of the Falcon Heavy static-fire at Kennedy Space Center. Come for the cloud plumes, stay for the sound. A French space reporter just yelled "It's like the 4th of July!"

    367 replies 4,471 retweets 15,970 likes
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  10. Retweeted
    Jan 8

    I'd say ML is both overhyped and underrated. People overestimate the intelligence & generalization power of ML systems (ML as a magic wand), but underestimate how much can be achieved with relatively crude systems, when applied systematically (ML as the steam power of our era)

    42 replies 1,105 retweets 2,775 likes
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  11. Retweeted
    11 Nov 2017

    New blog post: "Software 2.0"

    59 replies 1,174 retweets 2,248 likes
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  12. Retweeted
    4 Nov 2017

    A thing I learned advising startups that generalizes: people get the most upset when you tell them true things they wish were false.

    119 replies 1,178 retweets 3,828 likes
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