Lifeboat Foundation

DeepMind’s use of neural networks to synthesize speech could finally make computers sound more human.

Google has announced WaveNet, a speech synthesis program that uses AI and deep learning techniques to generate speech samples better than current technologies. By analyzing samples 16,000 a second, it can generate human-like speech and even its own music compositions.

If you’ve ever been lost in the maze of Youtube videos you may have stumbled on clips of computers reading news articles. You’d recognize that staccato, robotic nature of the voice. We’ve come a long way from “Danger! Will Robinson!,” but it there is yet to be a computer that can seamlessly mimic a human voice.

Now, there’s a new contender, brought to you by the brilliant minds behind DeepMind. Google has announced a new voice synthesis program in WaveNet, powered by deep neural AI.

Continue reading “At Last, Google’s DeepMind AI Can Make Machines Sound Like Humans” »

Google’s DeepMind unit, which is working to develop super-intelligent computers, has created a system for machine-generated speech that it says outperforms existing technology by 50 percent.

U.K.-based DeepMind, which Google acquired for about 400 million pounds ($533 million) in 2014, developed an artificial intelligence called WaveNet that can mimic human speech by learning how to form the individual sound waves a human voice creates, it said in a blog post Friday. In blind tests for U.S. English and Mandarin Chinese, human listeners found WaveNet-generated speech sounded more natural than that created with any of Google’s existing text-to-speech programs, which are based on different technologies. WaveNet still underperformed recordings of actual human speech.

Elon Musk blew our minds when he suggested that it’s highly likely we’re all living in a computer simulation. Seriously? Why would he think this, and how could we tell if it’s true?

Scientists at the University of Wisconsin-Madison have shown for the first time that transistors fashioned out of carbon nanotubes are actually twice as efficient as regular silicon varieties. This comes after decades of research regarding how carbon nanotubes can be used to design the next generation of computers. Speaking about the breakthrough, recently published in the Science Advances journal, Michael Arnold, a member of the team, said:

Making carbon nanotube transistors that are better than silicon transistors is a big milestone. This achievement has been a dream of nanotechnology for the last 20 years.

Continue reading “Carbon Nanotube Transistors Twice As Efficient As Silicon, Study Shows” »

When this hits in 2017, we’re going to see more momentum around accelerating the adoption of a QC in mainstream devices across all areas of business and consumers. China has definitely accelerated the efforts around migrating the net to a Quantum secured net.

Nice.

“We’ve managed to put quantum-based technology that has been used in high profile science experiments into a package that might allow it to be used commercially.”

Random number generators are crucial to the encryption that protects our privacy and security when engaging in digital transactions such as buying products online or withdrawing cash from an ATM. For the first time, engineers have developed a fast random number generator based on a quantum mechanical process that could deliver the world’s most secure encryption keys in a package tiny enough to use in a mobile device.

Continue reading “New Quantum Chip Could Bring Highest Level of Encryption to Any Mobile Device” »

As I mentioned 4 months ago when an article came out stating that this type of concept of a scalable quantum chip was at least 15 years away was bunk; this is again one more example where contributors really need to do their homework and make sure they are speaking to the real folks on the frontlines of QC.

Quantum-based random number generators are now small enough that they could fit in mobile devices.

Imagine a five-year-old watching Mum talking to Siri, and Dad talking to Alexa, on a daily basis — what must she think of such interactions? Children nowadays witness computers that seem like they have a mind of their own — and even a personality with which to engage. It can be taken for granted that their perception of machines, and thus of the world itself, differs a lot from our own.

Artificial intelligence is one of the most promising areas of tech today, if not even the one that is likely to entail the most striking changes in our way of living, the way our economy works and how society functions. Thanks to enormous amounts of data, coupled with compute power to analyze it, technology companies are making strides in AI that resembles something of a gold rush.

New approaches, including use of deep neural networks, have led to groundbreaking achievements in AI, some of which weren’t predicted to happen for another decade. Google defeating the world champion at the ancient game of Go is just one prominent example. Many more are to be expected, including advances in deep learning combined with reasoning and planning — or even emulating creativity and artwork.