The move comes as Toyota nears a self-imposed deadline of 2020 for selling cars capable of piloting themselves on freeways. The company will be led by James Kuffner, now the chief technology officer at Toyota Research Institute in California. Toyota joins a string of car makers that have sought to separate their self-driving units to attract top software engineers who might not otherwise work for a traditional auto maker. Car makers have long complained that they face difficulties in attracting engineers with the appropriate software skills. Toyota is scouting for locations in Tokyo for office space and said employees of the company would speak English--another measure to widen its pool of job applicants.

IBM Corp.'s Watson is heading to space, specifically the International Space Station, in the form of an 11-pound, artificially intelligent smiling orb. The orb, dubbed CIMON, short for Crew Interactive Mobile Companion, will be taken to the ISS in June by German astronaut and scientist Alexander Gerst. It has been designed as an experimental assistance system to support astronauts in performing routine work. Complete with an "expressive digital face," CIMON will initially assist Gerst in running a series of tests, including an experiment with crystals, solving a Rubik magic cube based on videos, and a complex medical experiment. "CIMON's digital face, voice and use of artificial intelligence make it a'colleague' to the crew members," IBM said in a blog post Monday.

TOKYO (Reuters) - Toyota Motor Corp and group suppliers Denso Corp and Aisin Seiki Co said on Friday they would form a joint venture for researching and developing automated-driving technology, investing more than 300 billion yen ($2.8 billion).

This month's senate intelligence meeting is probably the most important two-hour video you should make time to watch this week, especially if you are interested in the intersection between AI, DI, and national security. Also some important cautions about Internet of Things (IOT) security. Admiral Mark Rogers: "Clearly I think we are not where need to be…the challenge I think is that we have [multiple areas of knowledge and insight within the federal government and within the private sector, how do we bring this together and create and integrated team, with some real-time flow back and forth." Admiral Mark Rogers: "I wonder how bad does this have to get before we realize that we have to do something fundamentally differently…[IOT will]…get, much much worse, exponentially from a security perspective." Senator Richard Burr: "The widespread proliferation of artificial intelligence is expected to prompt new national security concerns" General Ashley: " …when you think about artificial intelligence, our near-peer competitors are pursuing this…when you look at the volume in big data and what's available…artificial intelligence will be integral to that….it's Mark Rogers: "We are victims of our own success..the ability to access data at increased levels brings its own set of challenges…[China] there clearly is a national strategy designed to harness the power of artificial intelligence to generate strategic outcomes…to generate positive outcomes…" Mark Rogers: "…with the power of machine learning, artificial intelligence and big data analytics…data concentrations are a target….

This is driving as it exists in most cars today.

Social dilemmas, where mutual cooperation can lead to high payoffs but participants face incentives to cheat, are ubiquitous in multi-agent interaction. We wish to construct agents that cooperate with pure cooperators, avoid exploitation by pure defectors, and incentivize cooperation from the rest. However, often the actions taken by a partner are (partially) unobserved or the consequences of individual actions are hard to predict. We show that in a large class of games good strategies can be constructed by conditioning one's behavior solely on outcomes (ie. one's past rewards). We call this consequentialist conditional cooperation. We show how to construct such strategies using deep reinforcement learning techniques and demonstrate, both analytically and experimentally, that they are effective in social dilemmas beyond simple matrix games. We also show the limitations of relying purely on consequences and discuss the need for understanding both the consequences of and the intentions behind an action.

Thanks to the growing availability of spoofing databases and rapid advances in using them, systems for detecting voice spoofing attacks are becoming more and more capable, and error rates close to zero are being reached for the ASVspoof2015 database. However, speech synthesis and voice conversion paradigms that are not considered in the ASVspoof2015 database are appearing. Such examples include direct waveform modelling and generative adversarial networks. We also need to investigate the feasibility of training spoofing systems using only low-quality found data. For that purpose, we developed a generative adversarial network-based speech enhancement system that improves the quality of speech data found in publicly available sources. Using the enhanced data, we trained state-of-the-art text-to-speech and voice conversion models and evaluated them in terms of perceptual speech quality and speaker similarity. The results show that the enhancement models significantly improved the SNR of low-quality degraded data found in publicly available sources and that they significantly improved the perceptual cleanliness of the source speech without significantly degrading the naturalness of the voice. However, the results also show limitations when generating speech with the low-quality found data.

We consider linear models where $d$ potential causes $X_1,...,X_d$ are correlated with one target quantity $Y$ and propose a method to infer whether the association is causal or whether it is an artifact caused by overfitting or hidden common causes. We employ the idea that in the former case the vector of regression coefficients has 'generic' orientation relative to the covariance matrix $\Sigma_{XX}$ of $X$. Using an ICA based model for confounding, we show that both confounding and overfitting yield regression vectors that concentrate mainly in the space of low eigenvalues of $\Sigma_{XX}$.

Patients at Beth Israel Deaconess Medical Center in Boston soon will use high-tech assistants to help them navigate their hospital stays. They could use Google Home to page a nurse, request spiritual care, or find out when their doctor is scheduled to arrive. Already, Beth Israel Deaconess has tested how both the Alexa and Google Home ambient listening devices might work with inpatients. The medical center is also considering how these technologies could be used to help physicians with tasks such as accessing patient data without having to click through electronic files. Such applications could be just the start of advances ushered in by consumer tech giants, says John D. Halamka, MD, MS, chief information officer for Beth Israel Deaconess and dean for technology at Harvard Medical School.

To some Chinese, it seems their movements, habits and thoughts can be tracked by a government with unchecked power. So is a digital dictatorship all powerful? That's a question that author Wang Lixiong set out to answer in his dystopian novel "Ceremony." Released by Taiwan's Locus Publishing in December, "Ceremony" describes a China in 2021 that isn't far off from how the nation is today. The leader wants to stay in office beyond mandated term limits and uses an anticorruption campaign to vanquish rivals.