posted 1 day ago on pinboard
Something I've been working on the last couple of weeks – a totally new approach to building UIs

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posted 1 day ago on pinboard
WHO MADE THIS?! 😂😂😂

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posted 1 day ago on pinboard
Holy Moley.

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posted 1 day ago on pinboard
WHO MADE THIS?! 😂😂😂

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posted 1 day ago on pinboard
This clip is astounding. Tens of millions of Americans believe these same things.

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posted 1 day ago on pinboard
Here are my notes from last week’s secret meeting of the secret conspiracy, AKA Bay Area Tech Solidarity:

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posted 1 day ago on pinboard
This, from a friend who didn't wish to be named as they're tired of the very abuse they describe here, is perfect:

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posted 1 day ago on pinboard
"Well they just don't understand the values of #Agile..." Yeah, because companies are selling this.

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posted 1 day ago on pinboard
"how many layers of agile are you on?" "like maybe 5 or 6 right now, we use trello, do standup" "you are like a lit…

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posted 1 day ago on pinboard
WHO MADE THIS?! 😂😂😂

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posted 1 day ago on pinboard
hmmm, i lied, twitter is actually good

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posted 1 day ago on pinboard
Holy Moley.

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posted 1 day ago on pinboard
There are an awful lot of stock photos for virtual reality that just consist of people wearing headphones incorrect…

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posted 1 day ago on pinboard
WHO MADE THIS?! 😂😂😂

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posted 1 day ago on pinboard
Here are my notes from last week’s secret meeting of the secret conspiracy, AKA Bay Area Tech Solidarity:

Read More...
posted 2 days ago on pinboard
Something I've been working on the last couple of weeks – a totally new approach to building UIs

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posted 2 days ago on pinboard
How Google Is Challenging AWS Amazon won round one of the cloud wars; now Google is trying to change the rules

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posted 2 days ago on pinboard
Okay, people can believe what they want about Clinton, but I'd vote Goldman Sachs if those are my only two options.

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posted 2 days ago on pinboard
Neural networks have the rather uncanny knack for turning meaning into numbers. Data flows from the input to the output, getting pushed through a series of transformations which process the data into increasingly abstruse vectors of representations. These numbers, the activations of the network, carry useful information from one layer of the network to the next, and are believed to represent the data at different layers of abstraction. But the vectors themselves have thus far defied interpretation. In this blog post I put forward a possible interpretation of these vectors. I argue we shouldn't take these vectors literally, but rather as an encoding for a simpler, sparse data structure. This gives rise to a simple technique (the -SVD) for reverse engineering this data structure, and gives us the tools to decode the vectors' meaning.

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