Quotes About Algorithm

Which meant gait metrics were unavailable, and facial recognition was notoriously bad at handling skin tones darker than a typical whitebread silicon valley bro. (It went all the way back to the color cards used to optimize photographic film stock for white-skinned targets in the 1950s: algorithms embodied the prejudices and biases of their designers.)

So everything is an algorithm now. And just as every Google search uses its algorithms to produce a different result for each person searching, so can algorithms customize products for their consumers. For

Algorithms are great, but they're very limited in what they can do as far as playing songs and playing a mood.

Engagement is the most important thing about Instagram, and you can lose it if you miss a day.

The Target algorithm hadn't produced a superhuman leap of logic, but a very human one: it figured out exactly what you or I or anyone else would also have figured out, given the same information.

As an algorithm the protocol is unbiased and capable of auditing, authenticating, validating, approving, and transferring integer values along a ledger that is distributed to tens of thousands of computers (called mining machines) that are located around the world. 

If you really care about Facebook likes, don't just post your stuff to Twitter and then rely on it being republished automatically to Facebook. In my sample size of one, Facebook penalizes you significantly for that and shows that content to far fewer people.

Somebody writing a subroutine is unbelievable boring.

Humans were biology. They lived for the dopamine rush. They could get it either by putting the relevant chemicals directly into their bodies or by partaking of some clickbait that had been algorithmically perfected to make brains generate the dopamine through psychological alchemy. It was not a way to live long or to prosper, but it was a way of being as ineradicable, now, as the ragweed that flourished in the roadside ditches.

It is written in Lisp, which is the only computer language that is beautiful.

Where a CPU would feed an algorithm many pieces of data, one after the other, a GPU could process multiple pieces of data simultaneously. To learn to recognize images of cats, a CPU would process pixel after pixel, while a GPU could "look" at many pixels at once. So the time needed to train a computer to recognize cats decreased dramatically.

possible to run any AI algorithm on a general-purpose CPU, but the scale of computation required for AI makes using CPUs prohibitively

With supervised learning, an algorithm is presented with a set of inputs along with their desired outputs (also called labels). The goal is to discover a rule that enables the computer to essentially break down and learn what the input is, which technically is called mapping the input to the output.

At the level of the microcode, physical and abstract meet. The

The universe computes its own destiny.

Where folks like Google have fallen down is in just putting a little review box up, then closing their eyes and letting the algorithm take care of itself. Yelp is a technology company, but also a company that understands how people want to connect with one another.

Just because you listen to The National, Spotify might tell you that you want to listen to The Lumineers' music. Well, maybe you don't.

The nervous system and the automatic machine are fundamentally alike in that they are devices, which make decisions on the basis of decisions they made in the past.

Because we take certain things about the world for granted when we encounter new data, we accept it or reject it based in large part on whether it corresponds with or contradicts what we think we already know. This is what I had said earlier. This is being increasingly reinforced by the so-called bubble or silo effect in which computer algorithms channel our online behavior so that we rarely encounter views with which we disagree

Over time,[*] the Google algorithm created something that had never previously existed: a consensus about the shared understanding of everything.

We don't use the word 'intelligence' with software. We regard that as a naive idea. We say that it's 'complex.' Which means that we don't always understand what it's doing.

Think like a machine instead of a boy.

If a psychosis was just some synapses misfiring why wouldnt you simply get static? But you dont. You get a carefully crafted and fairly articulate world never seen before. Who's doing this? Who is it who is running around hooking up the dangling wires in new and unusual ways. Why is he doing it? What is the algorithm he follows? Why do we suspect there is one?

a table and diagram showing exactly how the algorithm would be fed into the computer, step by step, including two recursive loops. It was a numbered list of coding instructions that included destination registers, operations, and commentary—something that would be familiar to any C++ coder today.