If you are bored with Google Assistant and want to try a new Artificial Intelligence (AI) based app, then make up your plans for buying the next powerful smartphone from Samsung, because the company is working to add its AI app on its upcoming device. Yes, the Galaxy S8 will come with Samsung's own artificial intelligence service. According to the details, the South Korean smartphone manufacturer will add a voice-assistant called "Viv" into the Galaxy S8. The users will be able to control their home appliances and wearables by using this app. Moreover, this AI will let the users order food, add appointments to the calendar, set the alarm, and do a lot of other things on their Galaxy S8.

SoftBank also sells the Pepper human-shaped companion robot for homes and businesses, and runs a solar energy business in Japan, highlighting a critical stance against nuclear energy that has spread since the 2011 Fukushima disaster. Its investment empire encompasses financial technology and ride-booking services.

Samsung Electronics said Sunday it will offer an artificial intelligence assistant service in the upcoming flagship smartphone, as the South Korean firm seeks recovery from its global smartphone recalls. The Galaxy S8 will let users order food or perform other tasks without going through a third-party application but by simply asking the phone's virtual assistant, Samsung said in a statement. The artificial intelligence service will also be made available in Samsung's other consumer electronics products, such as refrigerators. The company declined to disclose what specific tasks the S8 phone will perform through its artificial intelligence feature. Samsung is expected to unveil the next iteration for its flagship Galaxy device in spring as it has typically done in the past.

Experts with the Word Economic Forum (WEF) say that there will be seven million less jobs available in 2020 than now. Oxford University experts warn that 20 years from now 39 percent of people will lose their jobs. Industrial workers will be the next to be phased out by the onslaught of intelligent robots. WEF experts insist that the loss of jobs in some sectors will made up for by new jobs available on other economic sectors. According to them, there will be 2 million more high-tech jobs available four to five years from now.

The Commonwealth Scientific and Industrial Research Organisation (CSIRO) has signed on for a pair of Nvidia DGX-1 3U boxes to serve as a platform for applying machine learning to its science. Angus Macoustra, acting deputy CIO and executive manager for Scientific Computing at CSIRO, said the boxes would be used for medical image analysis, nano-material modelling, genome analysis, astronomy, and space science. In the realm of space science, Macoustra said machine learning can help with hunting for the signature of pulsars. "Two thirds of all known pulsars discovered in the world have actually been observed on the Parkes radio telescope, and CSIRO holds close to 40 years of data collected from that instrument," Macoustra said during the GTCx Australia conference on Tuesday. "Machine learning gives us mechanisms to interrogate that data and it is the belief of our scientists that there are still a number of unknown pulsars locked up in these data sets that span the past 40 years."

Two crucial questions in discussions about the risks of artificial superintelligence are: 1) How much more capable could an AI become relative to humans, and 2) how easily could superhuman capability be acquired? To answer these questions, I will consider the literature on human expertise and intelligence, discuss its relevance for AI, and consider how an AI could improve on humans in two major aspects of thought and expertise, namely mental simulation and pattern recognition. I find that although there are very real limits to prediction, it seems like an AI could still substantially improve on human intelligence, possibly even mastering domains which are currently too hard for humans. In practice, the limits of prediction do not seem to pose much of a meaningful upper bound on an AI's capabilities, nor do we have any nontrivial lower bounds on how much time it might take to achieve a superhuman level of capability. Takeover scenarios with timescales on the order of mere days or weeks seem to remain within the range of plausibility. As AI systems become more advanced, there is the possibility of them reaching superhuman levels of intelligence, eventually breaking out of human control (Bostrom 2014). The answers to these questions will influence the urgency of dealing with questions of superintelligent AI, as well as the correct means of it. If AI systems can rapidly achieve strong capabilities, becoming powerful enough to take control of the world before any human can react, then that implies a very different approach than one where AI capabilities develop gradually over many decades, never getting substantially past the human level (Sotala & Yampolskiy, 2015). Views on these questions vary. Authors such as Bostrom (2014) and Yudkowsky (2008) argue for the possibility of a fast leap in intelligence, with both offering hypothetical example scenarios where an AI rapidly acquires a dominant position over humanity. On the other hand, Anderson (2010) and Lawrence (2016) appeal to fundamental limits on predictability – and thus intelligence – posed by the complexity of the environment. 'Practitioners who have performed sensitivity analysis on time series prediction will know how quickly uncertainty accumulates as you try to look forward in time. There is normally a time frame ahead of which things become too misty to compute any more. Further computational power doesn't help you in this instance, because uncertainty dominates. Reducing model uncertainty requires exponentially greater computation. We might try to handle this uncertainty by quantifying it, but even this can prove intractable.

Have you ever been in a situation where knowing another language would have come in handy? I remember standing on the platform at Tokyo Station watching my train to Nagano -- the last train of the day -- pulling away without me on it. What ensued was a frustrating hour of gestures, confused smiles, and head-shaking as I wandered the station looking for someone who spoke English (my Japanese is unfortunately nonexistent). It would have been really helpful to have a bilingual pal along with me to translate. Bilingual pals can be hard to find, but Google's new translation software may be an equally useful alternative.

At MIT's 2016 Open House last spring, more than 100 visitors took rides on an autonomous mobility scooter in a trial of software designed by researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL), the National University of Singapore, and the Singapore-MIT Alliance for Research and Technology (SMART). The researchers had previously used the same sensor configuration and software in trials of autonomous cars and golf carts, so the new trial completes the demonstration of a comprehensive autonomous mobility system. A mobility-impaired user could, in principle, use a scooter to get down the hall and through the lobby of an apartment building, take a golf cart across the building's parking lot, and pick up an autonomous car on the public roads. The new trial establishes that the researchers' control algorithms work indoors as well as out. "We were testing them in tighter spaces," says Scott Pendleton, a graduate student in mechanical engineering at the National University of Singapore (NUS) and a research fellow at SMART.

Rokid Corporation, Ltd., an artificial intelligence (AI) and robotics company, today announced that it has raised in excess of $50 million in Series B funding at a post-funding valuation of $450 million. Rokid is a smart home device featuring advanced AI and deep learning that enriches a consumer's life by delivering information on-demand and performing tasks via voice and visual interactions. Rokid's superior engineering and elegant design makes it an essential family companion. This latest infusion builds upon a successful Series A round raised in 2015, and will be used for product development and to expand its world-class team, with an emphasis on research, hardware/software development, design, and user experience in U.S. and China. This round was led by Advantech and existing investors, IDG Capital Partners and Walden International.

Given that Sinovation Ventures founder Dr. Kai-Fu Lee has around 50 million followers on Chinese social networks, he has become an oracle when it comes to predicting the future of tech in China. Kai-Fu Lee talked about the most important trends in Chinese startups at TechCrunch Beijing 2016. Sinovation Ventures recently raised the equivalent of $675 million in total across a Chinese and an American fund, and the firm has over 300 companies in its portfolio. "We can invest up to $15 million per company now," Kai-Fu Lee said. And by far, the most important area for future Sinovation Ventures investments will be artificial intelligence.