The Singularity Approaches!

Facebook is reportedly buying a British AI firm to help tackle fake news

• The acquisition of London-based Bloomsbury AI would cost only $30 million at the upper end of reported estimates.
• But it could signal Facebook is now looking outside the company to round out its own efforts.
• Facebook has vowed in recent months to beef up human editors and problem-spotting AI as it addresses election meddling and abuse of the platform.

Sara Salinas | @saracsalinas

Facebook is reportedly buying a British AI firm to help tackle fake news

 

Bought this today ...

https://www.amazon.com/dp/B00LOOCGB2

 

How to tell if you’re talking to a bot

Twitter recently took drastic action as part of an effort to slow the spread of misinformation through its platform, shutting down more than two million automated accounts, or bots.

But Twitter shuttered only the most egregious, and obvious, offenders. You can expect the tricksters to up their game when it comes to disguising fake users as real ones.

It’s important not to be swayed by fake accounts or waste your time arguing with them, and identifying bots in a Twitter thread has become a strange version of the Turing test. Accusing posters of being bots has even become an oddly satisfying way to insult their intelligence.

Advances in machine learning hint at how bots could become more humanlike. IBM researchers recently demonstrated a system capable of conjuring up a reasonably coherent argument by mining text. And Google’s Duplex software also shows how AI systems can learn to mimic the nuances of human conversation.

 

Artificial Intelligence Will Be Hollywood’s Next Big Star – Guest Column

This year marks the 50th anniversary of 2001: A Space Odyssey, Stanley Kubrick’s seminal science fiction film that examined our evolution as human beings and technology’s role in our development. Looking back, you can argue that Kubrick was surprisingly prescient in depicting man’s relationship with machines as companies like Amazon, Google and Apple continue to invest in AI-related products and services. Instead of HAL, the supercomputer villain in Kubrick’s film, we have Alexa, Siri and Watson to help us avoid traffic and find shortcuts to work or answer simple questions like, “What year did 2001: A Space Odyssey come out?”

And while there’s no denying the promise of artificial intelligence as the next big thing, how we consume content is one area where we may see its impact sooner rather than later. As content consumption behaviors continue to evolve in today’s highly fragmented media landscape, media companies and platforms need to harness artificial intelligence to improve the quality of viewing and content experiences. By doing so, they will make it easier for consumers to use programming, while providing more access to content and developing new AI-related technologies like voice control.

Artificial Intelligence Will Be Hollywood’s Next Big Star – Guest Column

 

Programmer trains artificial intelligence to draw faces from text descriptions



Programmer Animesh Karnewar wanted to know how characters described in books would appear in reality, so he turned to artificial intelligence to see if it could properly render these fictional people. Called T2F, the research project uses a generative adversarial network (GAN) to encode text and synthesize facial images.

Simply put, a GAN consists of two neural networks that argue with each other to produce the best results. For example, the job of network No. 1 is to fool network No. 2 into believing a rendered image is a real photograph while network No. 2 sets out to prove the alleged photo is just a rendered image. This back-and-forth process fine-tunes the rendering process until network No. 2 is eventually fooled.

Karnewar started the project using a dataset called Face2Text provided by researchers at the University of Copenhagen, which contains natural language descriptions for 400 random images.

Programmer trains artificial intelligence to draw faces from text descriptions

 

To hone its collaborative skills, this AI is taking on the world’s top video game players



In warmup matches, OpenAI Five defeated human players at the multiplayer strategy game Dota 2.

OPENAI
To hone its collaborative skills, this AI is taking on the world’s top video game players
By Matthew HutsonAug. 15, 2018 , 12:05 PM

Next week, scientists working on artificial intelligence (AI) and games will be watching the latest human-machine matchup. But instead of a single pensive player squaring off against a computer, a team of five top video game players will be furiously casting magic spells and lobbing (virtual) fireballs at a team of bots called OpenAI Five. They’ll be playing the real-time strategy game Dota 2at The International in Vancouver, Canada, an annual e-sports tournament that draws professional gamers who compete for millions of dollars.

In 1997, IBM’s Deep Blue AI bested chess champion Garry Kasparov. In 2016, DeepMind’s AlphaGo AI beat Lee Sedol, a world master, at the traditional Chinese board game Go. Computers have also defeated humans in checkers and some forms of poker. But fast-paced multiplayer video games pose a different kind of challenge, requiring computers to collaborate and manage unpredictability. The goal is common sense, which could help AIs handle real-world situations such as navigating traffic and providing home care—even if they never have to face a magic spell.

“The next big thing for AI is collaboration,” says Jun Wang, a computer scientist at University College London who works on StarCraft II, another real-time strategy game. That requires “strategic reasoning, where it’s understanding the incentives of others,” says Jakob Foerster, a computer scientist at the University of Oxford in the United Kingdom, who also works on StarCraft II.

 

This AI Creates Horrifying Images Based On Your Words

I love technology that’s earnestly bad at doing things. Robots falling down the stairs? Algorithms composing deranged karaoke songs? They’re trying so hard! A for effort.

So a newish AI called AttnGAN makes me a very happy human. It’s a machine learning algorithm that was trained to produce images based on text input. The algorithm, a Generative Adversarial Network (GAN), was published in January by researchers at Microsoft’s Deep Learning Technology Center. Their work was also detailed in a paper posted to arXiv.org.


AttnGAN is supposed to visualize text-based captions, but it’s not very good at it—at times, horrifyingly so. To be fair, when researches trained the AI on a specific dataset, like images of birds, it was able to produce convincing renderings of birds. But when trained on a larger dataset of more diverse images, AttnGAN became artistically overwhelmed.



This AI Creates Horrifying Images Based On Your Words

 

Algorithms can turn any scene into a comic

 

How Google’s DeepMind will train its AI inside Unity’s video game worlds

Intelligent design versus evolution isn’t just a divide in people’s worldviews. It’s also been a divide in the artificial intelligence community. Until just a few years ago, AI was mainly about humans coding smart algorithms–from bank fraud detectors to autonomous video game characters. But with massive server farms, machine learning AI can run wild in the boundless fields of data that society generates–and often intuit algorithms faster and better than humans could program them. The next stage is to let algorithms loose in environments that look and act like actual fields, or houses, or highways, or anything else that can be simulated in 3D gaming environments.

DeepMind, part of Google parent company Alphabet, is going big on virtual world AI training through a deal with game-making software provider Unity Technologies (which powers games like Monument Valleyand Pokémon Go). DeepMind will run the software at a giant scale to train algorithms in physics-realistic environments–part of a growing trend in AI. Game engines like Unity or Unreal provide customizable settings for advanced AI techniques such as reinforcement learning (a kind of machine learning), in which an algorithm pursues a goal through trial and error until it’s been mastered.

“Games are in many, many ways . . . much closer to nature than people think,” says Danny Lange, Unity’s VP of machine learning and AI. “You get the visual, the physics, the cognitive, and . . . the social aspect–the interaction.” These all put evolutionary pressures on algorithms, just as nature does on living things, he says.

How Google’s DeepMind will train its AI inside Unity’s video game worlds