Personal Assistant Systems
What is The Artificial Intelligence (AI) We're Living With
Artificial Intelligence has always been a hot topic. The problem of creating a machine that can think, make its own decisions and at the same time lacks human limitations, has always aroused controversies. We all remember what the infamous Skynet has done to our planet in Terminator series, right? We can also recall this nasty feeling of a cold shiver running down our spines when Neo has woken up from the Matrix. After watching such films, we can wonder why our scientists want to build intelligent machines in a first place. One would ask: why putting humanity at risk?
Five surprising ways AI could be a part of our lives by 2030
Artificial intelligence (AI) has gradually become an integral part of modern life, from Siri and Spotify's personalized features on our phones to automatic fraud alerts from our banks whenever a transaction appears suspicious. Defined simply, a computer with AI is able to respond to its environment by learning on its own--without humans providing specific instructions. A new report from Stanford University in Palo Alto, California, outlines how AI could become more integrated into people's lives by 2030, and recommends how best to regulate it and make sure its benefits are shared equally. Here are five examples--some from this report--of AI technology that could become a part of our lives by 2030. Smart traffic lights using artificial intelligence technology to learn and adapt to traffic patterns in real time could make intersections safer and more efficient.
Noisy Inductive Matrix Completion Under Sparse Factor Models
Soni, Akshay, Chevalier, Troy, Jain, Swayambhoo
Inductive Matrix Completion (IMC) is an important class of matrix completion problems that allows direct inclusion of available features to enhance estimation capabilities. These models have found applications in personalized recommendation systems, multilabel learning, dictionary learning, etc. This paper examines a general class of noisy matrix completion tasks where the underlying matrix is following an IMC model i.e., it is formed by a mixing matrix (a priori unknown) sandwiched between two known feature matrices. The mixing matrix here is assumed to be well approximated by the product of two sparse matrices---referred here to as "sparse factor models." We leverage the main theorem of Soni:2016:NMC and extend it to provide theoretical error bounds for the sparsity-regularized maximum likelihood estimators for the class of problems discussed in this paper. The main result is general in the sense that it can be used to derive error bounds for various noise models. In this paper, we instantiate our main result for the case of Gaussian noise and provide corresponding error bounds in terms of squared loss.
Google's DeepMind AI fakes some of the most realistic human voices yet
WaveNet, as the system is called, generates voices by sampling real human speech and directly modeling audio waveforms based on it, as well as its previously generated audio. In Google's tests, both English and Mandarin Chinese listeners found WaveNet more realistic than other types of text-to-speech programs, although it was less convincing than actual human speech. The alternative is parametric text to speech -- building a completely computer-generated voice, using coded rules based on grammar or mouth sounds. Google's system is still based on real voice input.
Google's DeepMind AI fakes some of the most realistic human voices yet
Google's DeepMind artificial intelligence has produced what could be some of the most realistic-sounding machine speech yet. WaveNet, as the system is called, generates voices by sampling real human speech and directly modeling audio waveforms based on it, as well as its previously generated audio. In Google's tests, both English and Mandarin Chinese listeners found WaveNet more realistic than other types of text-to-speech programs, although it was less convincing than actual human speech. If that weren't enough, it can also play the piano rather well. Text-to-speech programs are increasingly important for computing, as people begin to rely on bots and AI personal assistants like Apple's Siri, Microsoft's Cortana, Amazon's Alexa, and the Google Assistant.
Google DeepMind gets closer to sounding human
Artificial intelligence researchers at DeepMind have created some of the most realistic sounding human-like speech, using neural networks. Dubbed WaveNet, the AI promises significant improvements to computer-generated speech, and could eventually be used in digital personal assistants such as Siri, Cortana and Amazon's Alexa. The technology generates voices by sampling real human speech from both English and Mandarin speakers. In tests, the WaveNet generated speech was found to be more realistic than other forms of text-to-speech programs but still falling short of being truly convincing. In 500 blind tests, respondents were asked to judge sample sentences on a scale of one to five (five being most realistic).
You can remove Cortana from Windows 10, but it's tricky
Travis wanted Cortana, Microsoft's personal assistant for Windows 10, out of his PC once and for all. He's probably not alone, so I figured I'd detail exactly how to perform a Cortana-ectomy. This procedure was done on the latest build of Windows 10, which is 1607 (the Anniversary Update). Once complete you'll have a regular search bar like in previous versions of Windows. Big kudos to this forum, where I unearthed these tips.
Artificial Intelligence โ Why Now? - Welcome To SogetiLabs, the research and innovation community of Sogeti.
Artificial intelligence is making a lot of promises for even the near future. We already have access to digital assistants like Microsoft's Cortana and Apple's Siri. It has already made great improvements in the healthcare industry. AI can even compose music, dream, and beat us at complex games like Go. All of these advancements are incredible, but why did they start appearing recently, and how far will we be able to push AI? Modern AI has been a thought since the first digital computer was created around the 1940s.
Innovation in Tech Evolves in New Ways
Early reviews of Apple Inc. AAPL -2.26 % 's new iPhone 7 were, in a word, "meh." Pundits praised the many improvements in the device, but a consensus emerged that Apple had not given existing iPhone owners a compelling reason to upgrade. Why are the iPhone, and other computing devices like PCs and tablets, not changing as quickly as they once did? There are many reasons, but the central issue is this: It is harder than ever--more technically difficult, more expensive and more time consuming--to advance the state of the art. Our devices are so complicated that, at their most fundamental level, advancing them further pushes against the boundaries of physics.
Still ringing bells
APPLE's events have often been compared to religious worship. Evangelical fans watch as the company's darkly-clad boss--first Steve Jobs, now Tim Cook--presents shiny new iSomethings in front of a screen showing colourful slides reminiscent of stained glass. Yet Apple's latest event, on September 7th, was a less rapturous affair. The iPhone 7, the firm's new smartphone, will come with a better camera, a faster chip and a brighter display, but will otherwise not be much of an improvement. The main novelty is that it no longer has a conventional jack for headphones, which have to plug into the charging port or be wireless (conveniently, Apple also introduced new untethered "AirPods", which will cost 160 a pair).