Gigi Peccolo is the Content Manager at OneReach, where she is focused on creating content enabling companies to offer effective, meaningful customer support over text message. Gigi is a skilled writer, having served as News Editor at her college newspaper. Gigi received her BA in Journalism Studies and Spanish from the University of Denver, where she graduated with Distinction in Journalism Studies.

Program could be used for personal assistants and weather analysis Artificial intelligence has won Jeopardy, mastered Go and will now predict the winner of a popular Chinese reality TV show. Developed by Alibaba Cloud, 'Ai' will choose a champ on'I'm a Singer' this Friday using social computing and emotional perception.

It's a word that we like to think is constrained to unsavory websites and isn't approved of in polite society. Just as with many other technology developments that can be misused, 3-D printing and robot technology have enabled the construction of, if you will, android sex dolls. There are few legal constraints on this, and we can probably expect see it escalate quite a bit before social forces learn how to deal with it in a positive way. The Particle Debris standout article of the week is from Wired. "The Scarlett Johansson Bot Is the Robotic Future of Objectifying Women."

If you've seen the movie Her, or perhaps Iron Man, you'll know what the future of tech looks like. AI is coming and it's coming in a big way. It's here to make our lives easier and simpler, or at least, that's what all the big tech giants would have us believe. AI is nothing new, IBM has been experimenting with Watson for a couple of years. But powerful, enormous tech such as Watson is far removed from the lives of everyday people like you or me.

You know what movie is seriously pretty fun? You no doubt saw it last year--probably multiple times--and your initial reaction was likely either "OH MAN, BEST MOVIE OF ALL TIME, FINN HEART POE 4-EVA" or "Enh, it's totally fine, too many New Hope nods, Rey is cool tho." Those were the prevailing online attitudes about the movie throughout its winter-long, record-disintegrating box-office run, and they made perfect sense: This was the first Star Wars movie in a decade, and it needed to not only restore what had become a robotic-feeling franchise to greatness, but to also re-energize the base of (admittedly somewhat older) Star Wars devotees who felt the series had already peaked decades ago. The Force Awakens had to be a million different things to a gazillion different fans, including myself, and that may be why, on first viewing, I wasn't overjoyed or underwhelmed. But after a bunch of re-viewings, and a few scene-specific replays upon last week's home-video release, it became clear that, when removed from the suffocating context of huge expectations and attention, The Force Awakens is all it needs to be: Namely, a really good Star Wars movie, with zippy dog-fighting sequences and sly Solo one-liners and some really dope menswear.

In an age when technology companies routinely introduce new forms of everyday magic, one problem that remains seemingly unsolved is that of long-form transcription. Sure, voice dictation for documents has been conquered by Nuance's Dragon software. Our phones and smart home devices can understand fairly complex commands, thanks to self-teaching recurrent neural nets and other 21st century wonders. However, the task of providing accurate transcriptions of long blocks of actual human conversation remains beyond the abilities of even today's most advanced software. When solved on a broad scale, it is a problem that might unlock vast archives of oral histories, make podcasts easier to consume for speed-readers (tl;dl), and be a world-changing boon for journalists everywhere, liberating precious hours of sweet life.

In an age when technology companies routinely introduce new forms of everyday magic, one problem that remains seemingly unsolved is that of long-form transcription. Sure, voice dictation for documents has been conquered by Nuance's Dragon software. Our phones and smart home devices can understand fairly complex commands, thanks to self-teaching recurrent neural nets and other 21st century wonders. However, the task of providing accurate transcriptions of long blocks of actual human conversation remains beyond the abilities of even today's most advanced software. When solved on a broad scale, it is a problem that might unlock vast archives of oral histories, make podcasts easier to consume for speed-readers (tl;dl), and be a world-changing boon for journalists everywhere, liberating precious hours of sweet life.

Text analysis startup Aylien, which uses deep learning and NLP algorithms to parse text and extract intel from documents for its customers, has launched a new tool specifically focused on analyzing written news content. "The idea for the News API is to give access to the news content that is out there enriched and in real-time to developers and data scientists," says co-founder Parsa Ghaffari. The Dublin-based startup says it's utilizing core text analysis tech powering its existing text API product, which launched back in February 2014 -- but this time it's focusing exclusively on news content and also doing a little more of the analytical heavy lifting for its customers. "We decided to simplify the use case a little bit by collecting and analyzing the news documents on our end, rather than giving them the tools to do that themselves. So this was born out of that," says Ghaffari.

Apart from fighting web spam, credit card fraud and many more curious applications, machine learning is being widely used in the field of art to generate stuff. We collected a few open source projects and papers which help you understand how machine learning can be used in the field of music.

Where is humanity going, and what will we be like when we get there? Do we really have less than 15 years before computers match the intellectual and emotional capabilities of humans, and less than 30 years before artificial intelligence surpasses humanity? Join us for the Season 7 premiere of StarTalk Radio as Neil deGrasse Tyson examines futurist Ray Kurzweil's predictions about "the Singularity" with the help of guest neuroscientist Dr. Gary Marcus and co-host Chuck Nice. Find out why Ray thinks that we'll be able to directly link our neocortexes to the cloud, yielding an increase in brainpower the likes of which we haven't seen since humans developed our frontal cortex millions of years ago. Ponder the possibilities of nanobot computers the size of blood cells, preloaded with information, that can enter our brains through capillaries and make us smarter.