AI: One Giant Leap for Technology

It’s inhabited the role of some of pop culture’s most iconic villains. The mere utterance of these two words have caused some of our greatest minds to worry about the global consequences, and the possibility—however small—of ending the human race. I’m talking about Artificial Intelligence, or “AI” for short. What could be the next key in new, long-term scientific discoveries also rests upon machine intelligence. But of course, a world such as ours inundated with stories like The Terminator, 2001: A Space Odyssey, etc. makes many skeptical of whether or not we’ll be capable to keep such machines “in check.” For this blog, I wish not to dwell on worries but how new technologies in this field may shape what lies ahead in 2017.

One of the most expected fields is in the sciences. What’s been a trend as of late is the decline sole scientist “eureka!” moments; by this I mean: the notion of seeing these Einsteins, Newtons, Hawkings type of stories isn’t precisely the world we’re in. That’s not to suggest we’re getting less geniuses. Perish the thought! Rather, we’re at this time where such momentous discoveries rely on stretched amounts of time and more people in simply acquiring the necessary data in testing a hypothesis. And for what could be decades-long research, AI’s promises of collecting and filtering that data appears to be where mankind’s next big breakthroughs may lie (1).

Another potential area for advancement comes with their general ‘connectedness’ with humans, either emotionally or linguistically. One fascinating example of this happening last year was with IBM’s Watson. The marketing team behind the film Morgan decided to utilize “his” help in making a trailer by watching the entire film, assessing the ups and downs, and crafting a two-ish minute trailer all alone. While the road ahead is an arduous one (2), many AI researchers will likely bring up language as another forefront in AI’s advancement throughout this year and the coming years.

Another leap in the AI field is called generational adversarial networks, or also termed dueling neural networks. The conceit is as follows: “systems consisting of one network that generates new data after learning from a training set, and another that tries to discriminate between real and fake data. By working together, these networks can produce very realistic synthetic data (3).” There’s been a lot of neat ways in which this technology has started being used. From cleaning up video games, real-time streaming, and more (4), it’s already been put to use in some neat ways. Experts in the field of machine learning appear to be quite hyped about this approach due to utilizing a way for computers to learn from unlabeled data. Translation: this could very well be the “missing link of artificial intelligence.” (5)

These are just a few of the ways AI is displaying promises of advancing in 2017. I truly hope that this short, scratch-of-the-surface blog has inspired you to check out some more prestigious sites, catalogs, etc. on this subject. Although there’s still scientists (6) (7) in other fields positing legitimate worries of where this might lead long-term, the advancements being made in the field today are nothing short of extraordinary and may reshape our everyday lives in untold ways.

Links:

1. https://www.google.com/#q=A...
2. https://www.technologyrevie...
3. https://www.technologyrevie...
4. https://www.technologyrevie...
5. https://www.technologyrevie...
6. http://www.bbc.com/news/tec...
7. https://www.ted.com/talks/s...