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Why We Really Don't want Artificial Intelligence to Learn from Us

#artificialintelligence

If you want to see some of the stuff that Tay tweeted, head over here (warning; some of her tweets make Donald Trump look tame). Tay's introduction by Microsoft was not just an attempt to build an AI that learnt from human interactions, but also one that potentially enriched Microsoft's brand and was designed also to harvest users information such as gender, location/zip codes, favourite foods, and so on (as was the Microsoft Age guessing software of last year). It harvested user interactions alright, but after a group of trolls launched a sustained, coordinated effort to influence Tay, the AI did exactly what Microsoft designed it to do -- it adapted to the language of it's so-called peers. Tay appears to have accomplished an analogous feat, except that instead of processing reams of Go data she mainlined interactions on Twitter, Kik, and GroupMe. She had more negative social experiences between Wednesday afternoon and Thursday morning than a thousand of us do throughout puberty. It was peer pressure on uppers, "yes and" gone mad. No wonder she turned out the way she did. I've Seen the Greatest A.I. Minds of My Generation Destroyed by Twitter, New Yorker article, March 25th, 2016 Tay is a lesson to us in the burgeoning age of AI. Teaching Artificial Intelligences is not only about deep learning capability, but significantly about the data these AIs will consume, and not all data is good data.


Automation and financial services: debunking the myths

#artificialintelligence

In an age of self-driving cars, 'robot surgery' and computers capable of trouncing human players in hugely-complex games such as Chess or Go, it seems obvious to many that the automation of Wall Street, the City of London, Frankfurt and other financial centres must be imminent.




Nvidia steps up its transition to an AI company

#artificialintelligence

Nvidia reported earnings that beat expectations and showed that the company's focus on artificial intelligence is still paying off. For the past decade, Nvidia has been rising above graphics chips for gamers, expanding to parallel processing in data centers and lately to artificial intelligence processing for deep learning neural networks and self-driving cars. The company reported earnings per share of $1.33 (up 60 percent from a year ago) on revenue of $2.6 billion (up 32 percent), beating Wall Street's expectations. The company's stock price is up more than 100 percent in the past year on the popularity of artificial intelligence. But it slumped during the day on Thursday, along with the broader market.


The $1tn question: how far can the new iPhone 8 take Apple?

The Guardian

Apple's stock market value is heading towards a new milestone and its latest product launch on 12 September could push the tech giant closer to becoming the first ever $1tn (£760bn) company. At the end of last week, the company's market capitalisation hovered around $830bn, continuing a 10-year run that has generally headed upwards since a low of $69bn in January 2009, during the financial crisis. Tuesday's event, with the iPhone 8 the star attraction, will strive to meet investors' – and customers' – vaulting expectations. But what will Apple tempt users with to justify Wall Street's faith in its future profits? An Apple spokesman declined to discuss what will be revealed at the event in the company's $5bn, spaceship-shaped Cupertino headquarters.


3 Growth Stocks That Could Soar More Than Nvidia -- The Motley Fool

#artificialintelligence

NVIDIA's (NASDAQ:NVDA) graphic cards have long been favorites among hardcore gamers, but who would've thought the chipmaker's stock would explode the way it has in recent times? The share price has more than tripled in just the past year, turning NVIDIA into a near eight-bagger in just five years. It's more an artificial intelligence computing company today, having made huge headway in two of the hottest technology fields of our times: AI and self-driving cars. For investors looking to find the "next NVIDIA," the trick is to find a company that is sitting on a big growth opportunity, or is already tapping into a soon-to-heat-up trend, but that is still flying under Wall Street's radar. These are stocks with the potential to soar.


Why we don't want AI's like IBM Watson learning from humans - Breaking Banks

#artificialintelligence

If you want to see some of the stuff that Tay tweeted, head over here(warning; some of her tweets make Donald Drumpf look tame). Tay's introduction by Microsoft was not just an attempt to build an AI that learnt from human interactions, but also one that potentially enriched Microsoft's brand and was designed also to harvest users information such as gender, location/zip codes, favourite foods, and so on (as was the Microsoft Age guessing software of last year). It harvested user interactions alright, but after a group of trolls launched a sustained, coordinated effort to influence Tay, the AI did exactly what Microsoft designed it to do -- it adapted to the language of it's so-called peers. Tay appears to have accomplished an analogous feat, except that instead of processing reams of Go data she mainlined interactions on Twitter, Kik, and GroupMe. She had more negative social experiences between Wednesday afternoon and Thursday morning than a thousand of us do throughout puberty. It was peer pressure on uppers, "yes and" gone mad. No wonder she turned out the way she did. I've Seen the Greatest A.I. Minds of My Generation Destroyed by Twitter, New Yorker article, March 25th, 2016 Tay is a lesson to us in the burgeoning age of AI. Teaching Artificial Intelligences is not only about deep learning capability, but significantly about the data these AIs will consume, and not all data is good data.