Kazuki
@kazuki
Cofounder of Glasp. I collect ideas and stories worth sharing 📚
San Francisco, CA
Joined Oct 9, 2020
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www.youtube.com/watch?v=hGK1yraNeXU&ab_channel=MichaelSimmons
Apr 14, 2022
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jamesclear.com/delayed-gratification
Apr 14, 2022
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jamesclear.com/habits
Apr 14, 2022
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medium.com/@ericmigi/why-pebble-failed-d7be937c6232
Apr 13, 2022
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www.youtube.com/watch?v=-tADdvQv_RE&ab_channel=MichaelSimmons
Apr 13, 2022
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jarche.com/2022/03/knowledge-flows-at-the-speed-of-trust/
Apr 12, 2022
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medium.com/@kazuki_sf_/learning-in-public-the-most-effective-way-to-learn-e14564d611b
Apr 12, 2022
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medium.com/accelerated-intelligence/how-one-life-hack-from-a-self-made-billionaire-leads-to-exceptional-success-48610e7a292
Apr 12, 2022
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glasp.co/articles/growth-handbook
Apr 9, 2022
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www.nateliason.com/notes/pragmatic-thinking-learning-andy-hunt
Apr 9, 2022
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www.youtube.com/watch?v=zqVILfmi0kQ&ab_channel=MichaelSimmons
Apr 8, 2022
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www.failory.com/blog/pre-seed-funding
Apr 8, 2022
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medium.com/accelerated-intelligence/the-number-one-predictor-of-career-success-according-to-network-science-be7fcc8e9558
Apr 7, 2022
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www.nateliason.com/blog/self-education
Apr 6, 2022
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medium.com/accelerated-intelligence/memory-learning-breakthrough-it-turns-out-that-the-ancients-were-right-7bbd3090d9cc
Apr 5, 2022
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medium.goodnotes.com/three-pitfalls-to-avoid-when-studying-with-a-highlighter-2aa345e1e6eb
Apr 5, 2022
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theviewinside.me/what-is-your-ikigai/
Apr 5, 2022
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medium.com/@jack/authority-merit-80ad140f990b
Apr 5, 2022
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commoncog.com/blog/tacit-knowledge-is-a-real-thing/
Apr 3, 2022
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maggieappleton.com/programmatic-notes
Apr 3, 2022
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infolab.stanford.edu/~backrub/google.html
Apr 2, 2022
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dkb.io/post/google-search-is-dying
Apr 2, 2022
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roambrain.com/building-the-global-knowledge-graph/
Apr 1, 2022
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dkb.io/post/organize-the-world-information
Apr 1, 2022
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www.buzzfeednews.com/article/annehelenpetersen/millennials-burnout-generation-debt-work
Apr 1, 2022
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nesslabs.com/metacognition
Mar 31, 2022
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nesslabs.com/thinking-in-maps
Mar 31, 2022
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mixergy.com/interviews/goodreads-otis-chandler/
Mar 29, 2022
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lithub.com/elizabeth-khuri-chandler-tells-the-origin-story-of-goodreads/
Mar 29, 2022
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hbr.org/2016/09/know-your-customers-jobs-to-be-done
Mar 29, 2022
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www.readthegeneralist.com/briefing/10-lessons
Mar 28, 2022
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www.gq.com/story/how-feelings-help-you-think
Mar 26, 2022
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www.reforge.com/blog/marketing-is-more-than-growth
Mar 25, 2022
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nesslabs.com/productivity-addiction
Mar 24, 2022
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backlinko.com/link-building
Mar 24, 2022
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glasp.substack.com/p/why-do-people-collect-things?s=w
Mar 23, 2022
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medium.com/accelerated-intelligence/while-most-people-fight-to-learn-in-demand-skills-smart-people-are-secretly-learning-rare-skills-f9b26856c9d6
Mar 22, 2022
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backlinko.com/keyword-research
Mar 21, 2022
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debliu.substack.com/p/what-is-the-best-piece-of-advice?s=r
Mar 21, 2022
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nocategories.net/ephemera/highlighters/
Mar 20, 2022
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In 1994, one of the first web search engines, the World Wide Web Worm (WWWW) [McBryan 94] had an index of 110,000 web pages and web accessible documents. As of November, 1997, the top search engines claim to index from 2 million (WebCrawler) to 100 million web documents (from Search Engine Watch).
In March and April 1994, the World Wide Web Worm received an average of about 1500 queries per day. In November 1997, Altavista claimed it handled roughly 20 million queries per day.
Our main goal is to improve the quality of web search engines.
One of our main goals in designing Google was to set up an environment where other researchers can come in quickly, process large chunks of the web, and produce interesting results that would have been very difficult to produce otherwise.
The citation (link) graph of the web is an important resource that has largely gone unused in existing web search engines.
Academic citation literature has been applied to the web, largely by counting citations or backlinks to a given page. This gives some approximation of a page's importance or quality. PageRank extends this idea by not counting links from all pages equally, and by normalizing by the number of links on a page.
PR(A) = (1-d) + d (PR(T1)/C(T1) + ... + PR(Tn)/C(Tn))
PageRank can be thought of as a model of user behavior. We assume there is a "random surfer" who is given a web page at random and keeps clicking on links, never hitting "back" but eventually gets bored and starts on another random page. The probability that the random surfer visits a page is its PageRank. And, the d damping factor is the probability at each page the "random surfer" will get bored and request another random page. One important variation is to only add the damping factor d to a single page, or a group of pages. This allows for personalization and can make it nearly impossible to deliberately mislead the system in order to get a higher ranking.
Currently, the predominant business model for commercial search engines is advertising. The goals of the advertising business model do not always correspond to providing quality search to users.