The same can be said about the world of science, which witnessed some of the biggest breakthroughs in decades, even as it provided several grim reminders about the impact of climate change on planet Earth. One hundred years ago, Albert Einstein predicted that the collision of massive objects such as black holes and neutron stars can create "ripples" in the curvature of space-time. Earlier this year, scientists associated with the Laser Interferometer Gravitational-Wave Observatory (LIGO) discovered these distortions. "The achievement fulfilled a 100-year-old prediction, opened up a potential new branch of astronomy, and was a stunning technological accomplishment," the journal Science, which was one of the many publications that termed the discovery of gravitational waves "Breakthrough of the Year," said in a recent statement. Currently, all we know about the cosmos is what we have gathered from electromagnetic radiation such as radio waves, visible light, infrared light, X-rays and gamma rays.

Baidu is demonstrating some of its most recent tech advancements in novel ways, including a partnership with KFC China (yes, the fried chicken KFC). The search giant sometimes referred to as the'Google of China' partnered with KFC to open a new "smart restaurant" in Beijing, which employs facial recognition to make recommendations about what customers might order, based on factors like their age, gender and facial expression. The restaurant also offers up augmented reality games via table stickers, but these are also deployed at 300 other KFC locations in Beijing. The facial recognition tech is unique to this one location, though Baidu has previously worked with KFC on another type of smart restaurant at a pilot location in Shanghai, where a robot customer service agent can listen for and recognize orders made by customers using natural language input. Baidu's tech in this new restaurant, however, is all about guessing what you want before you can even ask; image recognition hardware installed at the KFC will scan customer faces, seeking to infer moods, and guess other information including gender an age in order to inform their recommendation.

Object recognition is one of the most exciting areas in machine learning right now. Computers have been able to recognize objects like faces or cats reliably for quite a while, but recognizing arbitrary objects within a larger image has been the Holy Grail of artificial intelligence. Maybe the real surprise is that human brains recognize objects so well. We effortlessly convert photons bouncing off objects at slightly different frequencies into a spectacularly rich set of information about the world around us. Machine learning still struggles with these simple tasks, but in the past few years, it's gotten much better.

We learn a lot about objects by manipulating them: poking, pushing, prodding, and then seeing how they react. We obviously can't do that with videos -- just try touching that cat video on your phone and see what happens. But is it crazy to think that we could take that video and simulate how the cat moves, without ever interacting with the real one? Researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) have recently done just that, developing an imaging technique called Interactive Dynamic Video (IDV) that lets you reach in and "touch" objects in videos. Using traditional cameras and algorithms, IDV looks at the tiny, almost invisible vibrations of an object to create video simulations that users can virtually interact with.

Artificial Intelligence: New Tool To Create Cancer-Killing Drugs. DAEJEON, SOUTH KOREA - NOVEMBER 5: An employee of the Korea Institute of Science and Technology Information checks the supercomputers at the research institute November 5, 2004 in Daejeon, South Korea. South Korea's Information and Communication Ministry organized a presentation on'Ubiquitous Digital Life' to promote its policy of turning the country into a'Ubiquitous Society' where computers and the internet are available anytime and everywhere. With a rapid development of supercomputers, application of artificial intelligence to all fields of life is becoming the norm. In the field of science health, an introduction of artificial intelligence can revolutionize how diseases are being treated.

Ambar presses her hand to her forehead, nose crinkled in concentration as she considers the question on her screen: how many sevens in 91? The ten-year-old has been grappling with it for about a minute when she smiles: "13!". Her tutor responds by posting a large smiley cat picture on her screen – the virtual equivalent of a pat on the back. He is sitting on the other side of the world in an online tutoring centre in India. Ambar, who attends Pakeman primary school in north London, is one of nearly 4,000 primary school children in Britain signed up for weekly one-to-one maths sessions with tutors based in India and Sri Lanka.

IDC predicts that 35 percent of leading organizations in logistics, health, utilities, and resources will explore the use of robots to automate operations by 2019. What does the future hold for robotics? It's hard to say, given the rapid pace of change in the field as well as in associated areas such as machine learning and artificial intelligence. But one thing seems certain: Robots will play an increasingly important role in business and life in general. Research firm International Data Corp's (IDC) Manufacturing Insights Worldwide Commercial Robotics program recently unveiled its top 10 predictions for worldwide robotics for 2017 and beyond.

NEC Corporation has established a new company that promotes the development and application of therapeutic cancer peptide vaccines using advanced Artificial Intelligence (AI) technology. The new company, CYTLIMIC Inc. (CYTLIMIC), will use NEC the WISE AI technologies combined with machine learning and experimentation to produce a unique "immune function prediction technology" that is able to efficiently discover peptides that are potential vaccines in a short period of time and at a low cost. NEC has been engaged in collaborative research since 2014 with Yamaguchi University and Kochi University, and in clinical research with Yamaguchi University, resulting in the discovery of a peptide vaccine that promises to be effective in the treatment of hepatoma and esophageal cancer and is compatible with the genetic profile of approximately 85 percent of Japan's population. Currently, it is also advancing its application as a new cancer drug through CYTLIMIC, by developing investigational use formulations of the discovered peptide vaccine, confirming its safety and efficacy through nonclinical and clinical tests, and investigating its commercialization with pharmaceutical companies. In recent years, advances in life science have been accompanied by advances in elucidating the human immunity mechanism, and new cancer therapies that utilize immunity are being administered.

In his regular courses at Georgia Tech, the computer science professor had at most a few dozen students. But his online class had 400 students -- students based all over the world; students who viewed his class videos at different times; students with questions. Maybe 10,000 questions over the course of a semester, Goel says. It was more than he and his small staff of teaching assistants could handle. "We were going nuts trying to answer all these questions," he says.

The study was published in Oncotarget on 22nd of December, 2016. The study represents the proof of concept for applying Generative Adversarial Networks (GANs) to drug discovery. The authors significantly extended this model to generate new leads according to multiple requested characteristics and plan to launch a comprehensive GAN-based drug discovery engine producing promising therapeutic treatments to significantly accelerate pharmaceutical R&D and improve the success rates in clinical trials. Since 2010 deep learning systems demonstrated unprecedented results in image, voice and text recognition, in many cases surpassing human accuracy and enabling autonomous driving, automated creation of pleasant art and even composition of pleasant music. GAN is a fresh direction in deep learning invented by Ian Goodfellow in 2014.