Andrew Ng, one of the world's leading artificial intelligence researchers, said in a Medium post that he is resigning as the head of AI initiatives at Baidu Corp., one of China's largest Internet companies. Ng said he said he will "continue to shepherd" the growth of AI in society, but provided few clues about what might come next. He portrayed his departure from Baidu as amicable, saying: "the team is stacked up and down with talent; I am confident AI at Baidu will continue to flourish." Ng has held a multitude of high-profile positions in Silicon Valley in the past decade, serving as a computer science professor at Stanford University, as head of the Google Brain project, and as chairman of Coursera, an online-education company that he co-founded with Stanford faculty colleague Daphne Koller. I've completed a new book called "You Can Do Anything: The Surprising Power of a Useless Liberal Arts Education."

SHANGHAI (Reuters) - Baidu Inc chief scientist Andrew Ng said on Wednesday he will resign from the Chinese search engine company after three years of leading its drive into artificial intelligence (AI) and augmented reality (AR) projects.

"90% of the world's supercomputers run on Intel technology," Diane Bryant tells me at SxSW. "And 95% of artificial intelligence solutions run on Intel Xeon and Xeon Phi processors." Bryant is an Intel veteran who joined the semiconductor giant right after getting an electrical engineering degree from U.C. Davis. Starting a a microprocessor design engineer, she quickly worked her way up the ranks, spending 4 years as Intel's CIO before moving on to lead their Data Center Group. With recent acquisitions of Nervana and Mobileye, Intel is building a solid position in the A.I. wars. Every major tech company in Silicon Valley, along with every automotive giant from Detroit, is battling to gain ground in self-learning and self-driving technologies.

The chief scientist helping drive Baidu Inc.'s push into artificial intelligence is quitting the Chinese search giant, putting at risk its efforts to put AI at the center of a business revival. Andrew Ng, a Stanford University academic who worked on deep learning at Alphabet Inc. before joining Baidu in 2014, said he's leaving the business next month. Ng doesn't plan to join another technology company and will seek to bring AI into sectors such as health care and education around the world. The departure comes at a crucial point for the Beijing-based company as it attempts to revive its fortunes by embracing machine intelligence across all of its business units. His decision to leave comes after Qi Lu was hired in January as Baidu's group president and chief operating officer with a mandate to reshape the business, whose online-ad business is under threat from rivals including Alibaba Group Holding Ltd. and Tencent Holdings Ltd. Prior to joining, Lu was an executive at Microsoft Corp. leading efforts to develop artificial intelligence.

I will be resigning from Baidu, where I have been leading the company's AI Group. Baidu's AI is incredibly strong, and the team is stacked up and down with talent; I am confident AI at Baidu will continue to flourish. After Baidu, I am excited to continue working toward the AI transformation of our society and the use of AI to make life better for everyone. I joined Baidu in 2014 to work on AI. Since then, Baidu's AI group has grown to roughly 1,300 people, which includes the 300-person Baidu Research.

Dipayan Dev Dipayan Dev has completed his M.Tech from National Institute of Technology, Silchar with a first class first and is currently working as a software professional in Bengaluru, India. He has extensive knowledge and experience in non-relational database technologies, having primarily worked with large-scale data over the last few years. His core expertise lies in Hadoop Framework. Dr. Hadoop has recently been cited by Goo Wikipedia in their Apache Hadoop article. Apart from that, he registers interest in a wide range of distributed system technologies, such as Redis, Apache Spark, Elasticsearch, Hive, Pig, Riak, and other NoSQL databases.

NEC's artificial intelligence platform is mixing data, bus telematics, and human observation to determine whether a bus driver in Singapore is likely to cause an accident in the next three months. NEC, in partnership with Singapore public transport service provider SMRT Corporation, is using artificial intelligence (AI) to prevent bus accidents on the city-state's roads. The Japanese giant is taking historical data from a bus driver's work records, telematics data produced by each bus, and observations made by on-board data scientists to determine whether a driver is likely to cause an accident in the next three months, and intervene before SMRT has to deal with the costly and potentially life-threatening aftermath. Here's what Samsung's latest budget phones may tell us about the Galaxy S9 Addressing the Tech Leaders Forum 2017 on Monday, Mervyn Cheah, head and vice president of NEC Laboratories Singapore, explained that once an at-risk driver is identified, they are sent for further training. Buses on the road, sometimes they do create accidents and actually they will always react when they have an accident, you'll send them for training, he said.

Low paying jobs seem to be more at risk of a robot takeover, but a new developed has suggests that not even highly paid Wall Street jobs are safe. Goldman Sacs has published a job posting seeking a software developer to build a'robot adviser' that provides mass affluent clients with'detailed information on their financial portfolio and analytics'. The move comes as Goldman is looking at ways to broaden its customer base outside the super wealthy, including making deeper inroads into new consumer-focused businesses. Goldman Sacs has published a job posting seeking a software developer to build a platform that gives mass affluent clients'detailed information on their financial portfolio and analytics' According to the job posting, Goldman Sachs wants to leverage'a global technology platform offering an integrated suite of tools and applications to service clients. 'Digital innovations to shape client experience and enable our Institutional and Third-Party Distribution (TPD) salesforce with the tools required to best serve our clients,' the listing reads.

Representing documents is a crucial component in many NLP tasks, for instance predicting aspect ratings in reviews. Previous methods for this task treat documents globally, and do not acknowledge that target categories are often assigned by their authors with generally no indication of the specific sentences that motivate them. To address this issue, we adopt a weakly supervised learning model, which jointly learns to focus on relevant parts of a document according to the context along with a classifier for the target categories. Derived from the weighted multiple-instance regression (MIR) framework, the model learns decomposable document vectors for each individual category and thus overcomes the representational bottleneck in previous methods due to a fixed-length document vector. During prediction, the estimated relevance or saliency weights explicitly capture the contribution of each sentence to the predicted rating, thus offering an explanation of the rating. Our model achieves state-of-the-art performance on multi-aspect sentiment analysis, improving over several baselines. Moreover, the predicted saliency weights are close to human estimates obtained by crowdsourcing, and increase the performance of lexical and topical features for review segmentation and summarization.