In just two years, the Artificial Intelligence technologies available through IBM Watson has exploded. Artificial Intelligence is a rapidly growing field.
The New York Times has an interesting article that provides a background to the business behind Watson.
Also new for today is an article at the Mac Observer about Apple’s AI intentions.
Rather than take up more screen real estate with a new button, we repurposed an existing function in Lumberyard. Previously, any logged Keyword Range less than 5 seconds long was ignored. We figured anything that short was a mistake. Now it creates a Marker.
The Marker will be named using the Keyword as the name, but it will be applied at the starting point as a single frame Marker.
Tim Cook – Apple’s CEO – has said in a new interview with BuzzFeed, that Augmented Reality (AR) will be more important than Virtual Reality (VR). Virtual Reality creates a new environment that is immersive for the viewer. Augmented Reality overlays computer generated data on the real word (as captured by a camera).
While VR is undoubtedly going to be a significant technology in the future, I think it will mostly enhance games, exhibits and remote presence rather than everyday activities. AR can overlay translated text over foreign signage. AR can create geotagged games like the recent Pokemon Go.
I can see how AR will become part of everyday life. I’m not sure I see the same for VR.
As you probably all know, I have two day jobs heading Intelligent Assistance Software and Lumberjack System. We’re very proud of the work we’ve done through both companies. We make a decent income from them for sure, but what makes us particularly happy when our tools get people’s work done faster. They get to go home to their families earlier and production has less drudgery.
So it pleases us greatly when that gets recognized, as it did this trip.
In this episode we discuss the future of Avid and how AI will affect post production. Only one subject has a positive looking future!
Comments off · Posted by Philip in Artificial Intelligence
Indirectly – by forming the Partnership on AI – Facebook, Amazon, Google, IBM and Microsoft to promote “best practices” in Artificial Intelligence. I just hope that includes not wanting to wipe out humans!
The full name of the new partnership is: The Partnership on Artificial Intelligence to Benefit People and Society. That’s a worthy goal. Here’s hoping they go a measure toward achieving it.
Over recent years, I’ve read a lot on Apple* but only during the flight back did I start reading anything on Google: In the Plex by Steven Levy. While I’m not yet finished it struck me the fundamental difference between Google and Apple is “who’s in control”.
With Google, engineers rule. Data rules. Everyone else is in the service of the engineers.
At Apple, designers rule. (Design in the full sense of how something operates and feels, not just how it looks).
And right there is the difference between the two companies. All else leads from that fundamental focus.
*Becoming Steve Jobs Brent Schlender & Rick Tetzeli
Design Crazy Max Chafkin
Insanely Simple Ken Segall
Inside Apple Adam Lashinsky
Steve Jobs Walter Isaacson
Comments off · Posted by Philip in Machine Learning
It seems the smartest way to make money right now is to have a startup in speech recognition, machine learning, neural networks or other Artificial Intelligence related startup.
TechCrunch reported late last week the Apple had acquired another machine learning company:
Presumably to beef up its efforts in AI and machine learning across the company.
Not to be left behind, Google:
…said that it’s acquired API.ai, a startup with tools for speech recognition and natural language understanding….
In addition to its developers tools, Api.ai offers a conversational assistant app with more than 20 million users.
I would expect the purchase is to beef up their speech recognition in its AI assistant Google Now.
Google have open sourced it’s Show and Tell model for automatically captioning images. This is an excellent example of how neural networks work: train the model with examples – in this case human captioned images – and then let it loose on new images. From the Venture Beat article:
Google trains Show and Tell by letting it take a look at images and captions that people wrote for those images. Sometimes, if the model thinks it sees something going on in a new image that’s exactly like a previous image it has seen, it falls back on the caption for the caption for that previous image. But at other times, Show and Tell is able to come up with original captions. “Moreover,” Shallue wrote, “it learns how to express that knowledge in natural-sounding English phrases despite receiving no additional language training other than reading the human captions.”
As the article points out, there are many more players looking to do the same thing. Imagine how much easier life would be in editorial if all the B-roll came in organized like this.
In this latest episode of The Terence and Philip Show Terry and I discuss metadata, my citizenship, smart APIs, Artificial Intelligence and more.