- In the HBO show Silicon Valley, an app is pitched to some credulous VCs called SeeFood that’s “like Shazam for food.”
- Weeks later, Pinterest announced that exact functionality for its own app, and now, less than a month after SeeFood’s initial parody of tech culture, we have a Shazam for cars: Blippar.
- The app can recognize any car made after the year 2000, and show you the make, model, and year of the car, along with customer reviews, a 360 panorama of the interior, and a price quote.
- But specific car recognition is nice addition to the app’s skill set, and probably a lot easier to monetize.
- To that end, the company is also launching an API, so other companies can add Blippar’s object-identification tech to their apps.
In the HBO show Silicon Valley, an app is pitched to some credulous VCs called SeeFood that’s “like Shazam for food.” Weeks later, Pinterest announced that exact functionality for its own app, and…
Continue reading “Blippar’s car-identifying app is like SeeFood for cars”
As customers become accustomed to AI-powered solutions, they’ll expect the same from their local businesses.
Continue reading “Why Small Business Should Be Paying Attention to Artificial Intelligence”
- A Canadian startup called Lyrebird has announced that it has developed a platform capable of mimicking human voice with a fraction of the audio samples required by other platforms such as Google DeepMind and Adobe Project VoCo.
- The Lyrebird synthesis software requires only 60 seconds of sample audio to produce it’s synthetic sample.
- We hope that everyone will soon be aware that such technology exists and that copying the voice of someone else is possible.
- James Vincent at The Verge neatly summarizes the worrying outcomes of the combination of trick biometric software, 3D mapping and voice synthesizers.
- We already know that synthetic voice generators can trick biometric software used to verify identity.
Realistic voice synthesis combined with trick biometric software and 3D mapping gives us a realistic video of Trump announcing that the US is bombing North Korea
Continue reading “AI Voice Cloning & Perceived Reality – Fake News Has A New Friend”
- Called “AutoML” for “auto-machine learning,” it allows one A.I. to become the architect of another, and direct its development without the need for input from a human engineer.
- In essence, AutoML’s strategy of using neural networks to design other neural networks is familiar; making programs to edit the code of other programs is the definition of machine learning.
- In a blog post about the project, Google CEO Sundar Pichai said that, “We hope AutoML will take an ability that a few Ph.D.s have today and will make it possible in three to five years for hundreds of thousands of developers to design new neural nets for their particular needs.”
- In theory, the AutoML approach should be able to design more efficient neural nets, if only for simple problems right now, but in being more efficient those A.I. creations could also be more inscrutable to humans.
- The sheer difficulty of coding neural networks is becoming a problem for an industry that runs on abundant talent; AutoML is a bid to lower the bar to entry for the coming generation of prospective machine learning students, at least for the simplest and most common applications.
Google’s latest machine learning breakthrough seems like it could push humans out of A.I. development. Google thinks it could save them.
Continue reading “Google Reveals Automatic Machine Learning: A.I. Can Create Itself”
Researchers have successfully given AI a curiosity implant, which motivated it to explore a virtual environment.
Continue reading “Researchers Have Created an AI That Is Naturally Curious”
I am briefly sharing a video from the last TensorFlow Dev Summit in February 2017. My choice has fallen to a presentation by François Chollet of the deep learning library API Keras and its integration with TensorFlow. As Dr. Chollet explains, Keras integrated with TensorFlow promises to streamline deep learning frameworks in ways that will…
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- With a higher capacity for unbiased, constructive problem solving, an AI president could potentially prove to be a better leader than our human ones.
- Others have pushed the idea of an AI president before, with one group even fighting for Watson, IBM’s AI, to run for the position in 2016.
- The president could be programmed to follow conservative or liberal agendas, or instead of electing an AI designed to reflect one political party or another, we could just vote on various issues that would then be considered by our unbiased AI leader.
- As AI systems take on tasks traditionally held by human doctors, lawyers, and even songwriters, considering an AI president isn’t so far-fetched.
- AI can now even be used to create better AI, so it might be time for us to consider a future in which our political leaders are smarter, fairer, and, well, less human.
Some think we might be better off with an AI president than a human one.
Continue reading “Could an AI Ever Be Elected President?”