Top 132 Algorithms Quotes & Sayings - Page 2

For his major contributions to the analysis of algorithms and the design of programming languages, and in particular for his contributions to the "art of computer programming" through his well-known books in a continuous series by this title.

There are lots of different ways that algorithms can go wrong, and what we have now is a system in which we assume because it's shiny new technology with a mathematical aura that it's perfect and it doesn't require further vetting. Of course, we never have that assumption with other kinds of technology.

Finding your way doesn't mean surviving, just as pleasing an audience doesn't mean twisting your editorial around search engine optimization and Facebook algorithms.

Just as divine authority was legitimised by religious mythologies and human authority was legitimised by humanist ideologies, so high-tech gurus and Silicon Valley prophets are creating a new universal narrative that legitimises the authority of algorithms and Big Data.

As the border between physical and digital gets more permeable, a new kind of literacy emerges. And that literacy is built on a foundation of code - whether it's the codes of letters and words, or the code of bits and algorithms.

In popular books and articles, information technology writer Carr has worried over the ways that algorithms like those employed by Google are reshaping the ways we think.

Facebook has become the richest and most powerful publisher in history by replacing editors with algorithms - shattering the public square into millions of personalised news feeds, shifting entire societies away from the open terrain of genuine debate and argument while they make billions from our valued attention.

AIs are only as good as the data they are trained on. And while many of the tech giants working on AI, like Google and Facebook, have open-sourced some of their algorithms, they hold back most of their data.

Scientists need the infrastructure for scientific search to aid their research, and they need it to offer relevancy and ways to separate the wheat from the chaff - the useful from the noise - via AI-enabled algorithms. With AI, such an infrastructure would be able to identify the exact study a scientist needs from the tens of thousands on a topic.

AI does not keep me up at night. Almost no one is working on conscious machines. Deep learning algorithms, or Google search, or Facebook personalization, or Siri or self driving cars or Watson, those have the same relationship to conscious machines as a toaster does to a chess-playing computer.

So much of the language that surrounds us - from things like economics, management theory, and the algorithms built into computer systems - appears to be objective and neutral. But in fact, it is loaded with powerful, and very debatable, political assumptions about how society should work and what human beings are really like.

Once you succeed in writing the programs for [these] complicated algorithms, they usually run extremely fast. The computer doesn't need to understand the algorithm, its task is only to run the programs.

Algorithms diminish public safety in this country. They ask us to pretend that lengthy arrest records and violent crimes don't matter. They ask police to scoop up the bad guys only for the courts to immediately release them. They turn us into a bad joke.

Competitors argue that Google rigs its search algorithms to demote listings for competing search engines. Many of the allegations of demotion come generally from sites of pretty questionable quality, such as Nextag and Foundem. Some of Google's primary competitors in 'specialized search' clearly place well in search results - Amazon and Yelp.

Many [business] people focus on what is static, black and white. Yet great algorithms can be rewritten. A business process can be defined better. A business model can be copied. But the speed of execution is dynamic within you and can never be copied. When you have an idea, figure out the pieces you need quickly, go to market, believe in it, and continue to iterate.

The single greatest business opportunity that is now emerging in the global marketplace is the ability to analyze digital log data to trace digital actions and from those traces to develop algorithms that can predict future outcomes with greater accuracy.

The classes of problems which are respectively known and not known to have good algorithms are of great theoretical interest. [...] I conjecture that there is no good algorithm for the traveling salesman problem. My reasons are the same as for any mathematical conjecture: (1) It is a legitimate mathematical possibility, and (2) I do not know.

We do know that we can set certain algorithms for machines to do certain things - now that may be a simple task. A factory robot that moves one object from here to there. That's a very simple top-down solution. But when we start creating machines that learn for themselves, that is a whole new area that we've never been in before.

One of my optimistic prophecies is based on the assumption that machines could have the best algorithms in the universe, but it will never have purpose. And the problem for us to explain purpose to a machine is because we don't know what our purpose is. We have the purpose, but we still ... When we look at this global picture, a universal picture, to understand what is our purpose being here on this planet? We don't know.

But for me, true art can't be created by accident. There are boundaries to the reach of algorithms. Limits to what can be quantified. Among all of the staggeringly impressive, mindboggling things that data and statistics can tell me, how it feels to be human isn't one of them.

Algorithms learn by being fed certain images, often chosen by engineers, and the system builds a model of the world based on those images. If a system is trained on photos of people who are overwhelmingly white, it will have a harder time recognizing nonwhite faces.

When The Daily Muse initially wanted to launch a job board, our first ideas were insanely (and needlessly) complex. We wanted to integrate with social networks, gather rich personal data to build predictive algorithms, and put together numerous cool visualization tools before launching out to the world. We were just sure users would love it!

You invent things like algorithms to take care of some of the changes you want to make. The changes aren't detectable. There's all kinds of things happening as I play.

Facebook Algorithms have got us all screwed up, where we only listen and talk to people with the same views as us, and I think it's not helping us as a culture to grow.

Mathematics my foot! Algorithms are mathematics too, and often more interesting and definitely more useful.

Good SEO work only gets better over time. It's only search engine tricks that need to keep changing when the ranking algorithms change.

I am worried that algorithms are getting too prominent in the world. It started out that computer scientists were worried nobody was listening to us. Now I'm worried that too many people are listening.

Imagine life without any algorithms at all, you wouldn't be able to do anything. This is already completely encompassing. We have a habit of over-trusting what mathematics or computer scientists tell us to do, without questioning it, too much faith in the magical power of analysis.

Quite a lot has been written, including by me, about the effect of social media on politics, and in particular the way in which the algorithms built into Facebook and YouTube are more likely to spread angry, extremist and deliberately provocative political language.

I'm not anti conceptual art. I don't think painting must be revived, exactly. Art reflects life, and our lives are full of algorithms, so a lot of people are going to want to make art that's like an algorithm. But my language is painting, and painting is the opposite of that. There's something primal about it. It's innate, the need to make marks. That's why, when you're a child, you scribble.

The word deepfake has become a generic noun for the use of machine-learning algorithms and facial-mapping technology to digitally manipulate people's voices, bodies and faces. And the technology is increasingly so realistic that the deepfakes are almost impossible to detect.

I don't like the idea that Facebook controls how people express themselves and changes it periodically according to whatever algorithms they use to figure out what they should do or the whim of some programmer or some CEO. That bothers me a great deal.

Despite the metadata attached to each tweet, and despite trails of retweets and 'favorite' tweets, the Twitter corpus lacks the latticework of hyperlinks that makes Google's algorithms so potent. Twitter's famous hashtags - #sandyhook or #fiscalcliff or #girls - are the crudest sort of signposts, not much help for smart searching.

Some people have set up sort of "gotcha" algorithms that apparently crawl through psychology articles and look for fraudulent p-values [a measure of the likelihood that experimental results weren't a fluke]. But they're including rounding errors that don't change the significance levels of the results, and they're doing it anonymously.

There is a calculus, it turns out, for mastering our subconscious urges. For companies like Target, the exhaustive rendering of our conscious and unconscious patterns into data sets and algorithms has revolutionized what they know about us and, therefore, how precisely they can sell.

Enchanting is not the word that would immediately spring to mind when describing a play that deals with fractal geometry, iterated algorithms, chaos theory and the second law of thermodynamics, but it is a perfect fit for Tom Stoppard's astonishing 1993 play, which is as beautiful as it is brilliant. This is one Stoppard drama that you don't have to be Einstein to understand -- you can feel it as well as think it. (...) Breathtaking, exhilarating and deeply satisfying.

Jurisdictions across the U.S. are snapping up algorithms as tools to help judges make bail and bond decisions. They're being sold as race- and gender-neutral assessments that allow judges to use science in determining whether someone will behave if released from jail pending trial.

There are no algorithms for content moderation in place. All 8chan moderation relies on human volunteers and one automated 'bot' account to remove illegal content or spam, automated or human, based only on keywords.

Fantasy sports went a long way toward developing the sabermetrics formulas used not only by oddsmakers but general managers in hiring players. So the amateur fantasists ended up creating some of the algorithms that Oakland GM Billy Bean's statisticians used to win games with less salary money available for star players.

The government adoption of AI will not bring about a government being run by robots. Instead, our government will continue to be run by people, with help from algorithms dramatically improving government services for all Americans.

We have a lot of argument about laws but none of it solves the problem. Let's examine what happened, why did we miss the Tsarnaev brothers, why did we miss the San Bernardino couple? It wasn't because we had stopped collected metadata it was because, I think, as someone who comes from the technology world, we were using the wrong algorithms.

On a strategic level, employers really are behaving stupidly. Look at how they do recruiting: this automated process under which they will publish a job description chock full of so-called "key words", and then have software algorithms that attempt to match applicants to the resumes against those key words. So where in the key word collection do we capture institutional knowledge? No one advertises for that. Of course they don't.

When designing algorithms as a business owner, your incentive is your profit, something for your business, it's not an incentive to maximise something for the individual.

The key to a solid foundation in data structures and algorithms is not an exhaustive survey of every conceivable data structure and its subforms, with memorization of each's Big-O value and amortized cost.

The invisible pieces of code that form the gears and cogs of the modern machine age, algorithms have given the world everything from social media feeds to search engines and satellite navigation to music recommendation systems.

I know how models are built, because I build them myself, so I know that I'm embedding my values into every single algorithm I create and I am projecting my agenda onto those algorithms.

Leibniz endeavored to provide an account of inference and judgment involving the mechanical play of symbols and very little else. The checklists that result are the first of humanity's intellectual artifacts. They express, they explain, and so they ratify a power of the mind. And, of course, they are artifacts in the process of becoming algorithms.

Is any job safe? I was hoping to say 'journalist,' but researchers are already developing algorithms that can gather facts and write a news story. Which means that a few years from now, a robot could be writing this column. And who will read it? Well, there might be a lot of us hanging around with lots of free time on our hands.

We want people doing white hat search engine optimization (or even no search engine optimization at all) to be free to focus on creating amazing, compelling web sites. As always, we’ll keep our ears open for feedback on ways to iterate and improve our ranking algorithms toward that goal.

Google helps us sort the Internet by providing a sense of hierarchy to information. Facebook uses its algorithms and its intricate understanding of our social circles to filter the news we encounter. Amazon bestrides book publishing with its overwhelming hold on that market.

We don't let a car company just throw out a car and start driving it around without checking that the wheels are fastened on. We know that would result in death; but for some reason we have no hesitation at throwing out some algorithms untested and unmonitored even when they're making very important life-and-death decisions.

As a digital technology writer, I have had more than one former student and colleague tell me about digital switchers they have serviced through which calls and data are diverted to government servers or the big data algorithms they've written to be used on our e-mails by intelligence agencies.

We're trying to evolve a lot away from YouTube because YouTube is awesome - they have a huge audience, and we started there - but then you're at the mercy of their algorithms a lot, too. They can change anything, and it's really up to them, and you can't say anything about it.

Randomness has an incredibly powerful place in our culture. If you think about it, you can see it driving the algorithms that run our information economy, patterns that make up the traffic of our cities, and on over to the way the stars and galaxies formed.

Netflix will know everything. Netflix will know when a person stops watching it. They have all of their algorithms and will know that this person watched five minutes of a show and then stopped. They can tell by the behavior and the time of day that they are going to come back to it, based on their history.

Genetic algorithms (GAs) are defined as search procedures based on the mechanics of natural selection and genetics, and we think we know what innovation is - at least in some sort of qualitative way - but what does one have to do with the other?

Nothing will ever replace the experience of wandering haphazardly through a great bookstore, no matter how many algorithms are developed to find matches for our tastes. That's because not only is there no accounting for taste, there is no predicting it either.

With recidivism algorithms, for example, I worry about racist outcomes. With personality tests [for hiring], I worry about filtering out people with mental health problems from jobs. And with a teacher value-added model algorithm [used in New York City to score teachers], I worry literally that it's not meaningful. That it's almost a random number generator.

The algorithms that orchestrate our ads are starting to orchestrate our lives.

I just thought making machines intelligent was the coolest thing you could do. I had a summer internship in AI in high school, writing neural networks at National University of Singapore - early versions of deep learning algorithms. I thought it was amazing you could write software that would learn by itself and make predictions.