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The Singularity Approaches!

Discussion in 'The Tavern' started by Paul Bellow, May 18, 2017.

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Seagrim Level 18 (Magician) LitRPG Author Citizen

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A simulator that can simulate a subreddit.

*snerk*

-----------------------------------------

John Newton

Paraphrase of G.K. Chesterton

Fairy tales do not tell children that dragons exist. They already know that.

Fairy tales tell children that dragons can be defeated.

La Jodaso Stiana

Seagrim, Jan 12, 2018

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How artificial intelligence is creating new ways of storytelling

Can a computer write a great novel or a script for a movie? Artificial intelligence (AI) is manna from heaven for sci-fi writers.

We've seen a sentient computer called HAL wreak quiet havoc in 2001: A Space Odyssey. We've watched a robot girl's will to survive in 2015's Ex Machina. Most recently we’ve seen an AI-meets-the-wild-west scenario in TV series Westworld.

Writers do a great job of making AI entertaining, but does it work the other way around? Can AI itself create, develop and write storylines, scripts and other art forms?

AI is spreading into every corner of human existence. So it should come as no surprise that it’s helping authors, journalists and writers to create in ever more inventive ways.
Click to expand...

http://www.techradar.com/news/how-artificial-intelligence-is-creating-new-ways-of-storytelling

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Paul Bellow, Jan 13, 2018

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MrPotatoMan, Jan 21, 2018

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The Entrepreneur Trying to Democratize Law with a Free Chatbot

Joshua Browder created DoNotPay to help people fight parking tickets, and hopes to make the platform a resource for all kinds of legal issues.

Two years ago, Joshua Browder was learning to drive around his home in the UK and racking up parking tickets in the process. “I was a really terrible driver,” he told me in a phone conversation. “I got about 30 parking tickets in two years.” He had to figure out a way to fight these tickets without blowing his whole teenage budget on legal fees.

He started pouring through archives and documents looking for the most common reasons parking tickets were dismissed, and realized quickly that it’s pretty easy to turn the city’s messy regulations and ticket-administering against itself. Before long, Browder became a master at battling traffic tickets. He made a website to help his friends and family fight them, too.

That’s what ultimately inspired DoNotPay, a chatbot Browder designed to take on all the annoying little (and sometimes life-altering) legal issues that come up in life, like parking tickets (the bot has successfully fought 160,000 fines and counting). The website acts as a free resource for people looking for more information on their legal options: Just enter your problem in the text field, and a bot walks you through choices depending on your location and situation.

Building on its origins as a a ticket fighter, Browder is now expanding DoNotPay to help walk people through the steps to sue Equifax after a security breach leaked the personal information of just about everyone in the county. It’s currently available in the US, Canada, and the UK.
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https://motherboard.vice.com/en_us/...trying-to-democratize-law-with-a-free-chatbot

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Paul Bellow, Jan 25, 2018

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Paul Bellow, Jan 25, 2018

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Paul Bellow, Jan 30, 2018

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Artificial Intelligence Takes a Crack at Decoding the Mysterious Voynich Manuscript

The Voynich Manuscript has baffled cryptographers ever since the early 15th-century document was rediscovered by a Polish book dealer in 1912. The handwritten, 240-page screed, now housed in Yale University’s Beinecke Rare Book & Manuscript Library, is written from left to right in an unknown language. On top of that, the text itself is likely to have been scrambled by an unknown code. Despite numerous attempts to crack the code by some of the world’s best cryptographers, including Alan Turing and the Bletchley Park team, the contents of the enigmatic book have long remained a mystery. But that hasn’t stopped people from trying. The latest to give it a stab? The Artificial Intelligence Lab at the University of Alberta.

Bob Weber at the Canadian Press reports that natural language processing expert Greg Kondrak and grad student Bradley Hauer have attempted to identify the language the manuscript was written in using AI. According to a press release, the team originally believed that the manuscript was written in Arabic. But after feeding it to an AI trained to recognize 380 languages with 97 percent accuracy, its analysis of the letter frequency suggested the text was likely written in Hebrew.

“That was surprising,” Kondrak says. They then hypothesized that the words were alphagrams, in which the letters are shuffled and vowels are dropped. When they unscrambled the first line of text using that method they found that 80 percent of the words created were found in the Hebrew dictionary. The research appears in the journal Transactions of the Association of Computational Linguistics.

Neither of the researchers are schooled in ancient Hebrew, so George Dvorsky at Gizmodo reports they took their deciphered first line to computer scientist Moshe Koppel, a colleague and native Hebrew speaker. He said it didn’t form a coherent sentence. After the team fixed some funky spelling errors and ran it through Google Translate, they came up with something readable, even if it doesn’t make much sense: “She made recommendations to the priest, man of the house and me and people.”

Weber reports that a translation of another 72-word section included the words “farmer,” “light,” “air” and “fire.”
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https://www.smithsonianmag.com/smar...rack-mysterious-voynich-manuscript-180967983/

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Paul Bellow, Feb 1, 2018

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Paul Bellow, Feb 1, 2018

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AI and Deep Learning in 2017 – A Year in Review

The year is coming to an end. I did not write nearly as much as I had planned to. But I’m hoping to change that next year, with more tutorials around Reinforcement Learning, Evolution, and Bayesian Methods coming to WildML! And what better way to start than with a summary of all the amazing things that happened in 2017? Looking back through my Twitter history and the WildML newsletter, the following topics repeatedly came up. I’ll inevitably miss some important milestones, so please let me know about it in the comments!
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http://www.wildml.com/2017/12/ai-and-deep-learning-in-2017-a-year-in-review/

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Paul Bellow, Feb 7, 2018

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Google debuts AdSense ‘auto ads’ with machine learning to make placement and monetization choices

Google is today unveiling a new ad unit for AdSense that taps into the company’s big push to add more artificial intelligence into its business, and to potentially bring on more publishers who might consider ramping up their advertising efforts but don’t have the time or other resources to manage them.

Google is debuting “Auto Ads” — not commercials for cars, but a new ad format that uses machine learning to “read” a page to detect and place what kinds of ads might be appropriate to place there, including where to place them, and how many to run. Publishers activate Auto Ads with a single line of code on the page.

The service was actually quietly announced and launched in a limited beta September 2017, and now it is live for everyone. Google tells us that “publishers participating in the beta saw an average revenue lift of 10 percent with revenue increases ranging from five to 15 percent.”

For those who track or use AdSense, you know that there is already a fair degree of automation in the service. The product is used by tens of millions of web publishers to indicate where to place ads (banners and other units); with those ads then selected by Google based on a crawl of the page to figure out which ad might be most relevant. It already comprises a significant proportion of parent company Alphabet’s ad revenues, which accounted for $27 billion of its $32 billion of revenues in the most recent quarter.
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https://techcrunch.com/2018/02/21/g...g-to-make-placement-and-monetization-choices/

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Paul Bellow, Feb 26, 2018

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What an AI's Non-Human Language Actually Looks Like

Bob: i can i i everything else . . . . . . . . . . . . . .
Alice: balls have zero to me to me to me to me to me to me to me to me to
Bob: you i everything else . . . . . . . . . . . . . .
Alice: balls have a ball to me to me to me to me to me to me to me
Bob: i i can i i i everything else . . . . . . . . . . . . . .
Alice: balls have a ball to me to me to me to me to me to me to me
Bob: i . . . . . . . . . . . . . . . . . . .
Alice: balls have zero to me to me to me to me to me to me to me to me to
Bob: you i i i i i everything else . . . . . . . . . . . . . .
Alice: balls have 0 to me to me to me to me to me to me to me to me to
Bob: you i i i everything else . . . . . . . . . . . . . .
Alice: balls have zero to me to me to me to me to me to me to me to me to

https://www.theatlantic.com/technol...on-human-language-actually-looks-like/530934/

I had to deal with FB ad support today with the new ads manager interface. I teased them about their AI. Heh.

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Paul Bellow, Feb 28, 2018

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Fake news 2.0: personalized, optimized, and even harder to stop

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Paul Bellow, Mar 28, 2018

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Watch a Computer Learn to Play ‘Doom’ Inside a Dream

Researchers got deep learning models to train inside their own hallucinated ideas of the world.

The ability to practice real-world skills inside a dream and then use those skills in waking life is part bong water fantasy and part scientific enigma. Dr. Daniel Erlacherat the University of Bern in Switzerland, for example, has conducted numerous studies on the effects of practicing activities like squatting and dart throwing in a lucid dreaming state—the “waking dream” phenomenon—and then trying them in real life.

The research for humans continues, but computers are definitely able to dream up their own version of the world and learn skills inside it. Case in point: Researchers David Ha (of Google Brain, the search giant’s machine learning wing) and Jürgen Schmidhuber were able to get a machine to “hallucinate,” as they put it, its own idea of what the 1993 video game Doom looks like. Then, they got a virtual agent to play its own dream version of Doom to learn how to play the real thing.

You can see what this looks like on a webpage the researchers put up on Tuesday. If you need a description, imagine someone filming a game of Doom off of a CRT computer monitor with a glob of Vaseline smeared on the lens.
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Watch a Computer Learn to Play ‘Doom’ Inside a Dream

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Paul Bellow, Mar 31, 2018

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https://singularityhub.com/2018/04/05/dungeons-and-dragons-not-chess-and-go-why-ai-needs-roleplay/

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Paul Bellow, Apr 5, 2018

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Elon Musk warns that AI could become an 'immortal dictator'

Authoritarianism is nothing new.

But at least Mussolini and Hitler died. In the age of artificial intelligence, we could create "an immortal dictator from which we would never escape," says Elon Musk in the new documentary Do You Trust This Computer?

It's the latest from filmmaker Chris Paine, who met the Tesla co-founder while making 2006's Who Killed The Electric Car?

This time around Paine explores the promise and peril of AI — a subject Musk has been very vocal about. In 2017, he warned that AI could start World War III. Later that year, he called artificial intelligence "the greatest risk we face as a civilization" and suggested the government regulate it.

In Do You Trust This Computer?, Musk mentions a terrifying possibility: the AI built by authoritarian governments could outlast individual leaders or parties, creating a permanent structure of oppression.
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Paul Bellow, Apr 6, 2018

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Paul Bellow, Apr 6, 2018

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Paul Bellow, Apr 6, 2018

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Paul Bellow, Apr 6, 2018

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The rise of robo-writers

It sounds like the start of a bad joke: How can you tell the difference between what a human wrote and what a robot wrote?

The punchline isn't particularly funny: You might not be able to.

Here's a snippet of a story that The Washington Post published in November 2016, on a close game between two local high school football teams:

Keeney seemed to be at a loss until the game's final minutes. Coming off four consecutive 300-plus-yard performances, Keeney completed just 10 of 20 pass attempts for 125 yards, two interceptions and one touchdown Friday.

And here's a sample from another high school football game write-up that the Post published less than a year later, in September 2017:

The game began with a scoreless first quarter.

In the second quarter, The Patriots' Paul Dalzell was the first to put points on the board with a two-yard touchdown reception off a pass from quarterback William Porter.

The first section is written by Nick Eilerson, a high school sports reporter for The Washington Post. The second one is the work of Heliograf, the Post's artificial intelligence system. You know, a robot.
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The rise of robo-writers

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Paul Bellow, Apr 10, 2018

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How the Enlightenment Ends

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Paul Bellow, May 19, 2018

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