Discovering a new drug is no easy task. Once scientists have isolated or synthesized a particular compound, they then have to figure out what it's good for. To make sure it works, they conduct experiments in petri dishes, then in mice, then in larger mammals, and eventually in humans--a (pricey) gauntlet that just 6 percent of drugs pass through. Big data analytics company In Silico Medicine wants to change all that. Using a deep learning technique that can analyze how compounds affect cells, the researchers can not only determine what new drugs could be used to treat, but also its dose and possible side effects on other parts of the body.

In the future, the development of artificial intelligence (AI) will accelerate beyond anything we have previously imagined. It will offer limitless possibilities – changing our experiences, transforming every area of life and redefining how we interact with technology. Yet AI is not just future fantasy. It is here and now, gaining momentum through advances in machine learning, neural networks and big data. These are exciting times and the UK is right at the heart of it.

Wipro HOLMES – Artificial Intelligence Platform is a rich set of cognitive computing services for the development of digital virtual agents, predictive systems, cognitive process automation, visual computing applications, knowledge virtualization, robotics and drones.

Since presidential campaigns have incorporated social media into their strategic messaging, it has become more challenging for journalists to cover the election in depth, because of the large amount of data generated by candidates and the public every day. Journalists tend to focus on single quotes or tweets rather than providing analysis and reporting on the aggregate of messages on social media. But single tweets may not give people a full appreciation for the style of campaigning or the substance of the rest of the tweets. In order to get a sense of what the candidates and public are actually saying and how candidates communicate over time, we have taken a computational approach to predict categories of candidate-produced tweets and posts (as described in a blog post introducing the Illuminating 2016 project). We have been working on a system that automatically classifies each message into a category based on what the message is trying to do: urge people to act, change their opinions through persuasion, inform them about some activity or event, honoring or mourning people or holidays, or on Twitter having a conversation with members of the public.

Sports analytics has been successfully applied in sports like baseball and basketball. However, its application in soccer has been limited. There is a need to find out if the application of Machine Learning can bring better and more insightful results in soccer analytics. In this thesis, we perform descriptive as well as predictive analysis of soccer matches and player performances. In soccer, it is popular to rely on ratings by experts to assess a player's performance.

Bots, done right, are the cutting-edge form of interactive communications that captivate and engage users. But what kind of potential do they have for sales, customer support and the bottom line? Tobias Goebel, Aspect Software's Director of Emerging Technologies, weighed in at our recent VB Live event. Recently, I had the opportunity to exchange thoughts and opinions on artificial intelligence, machine learning in general, and chatbots in particular with Ron Brachman from Cornell Tech and Akhil Aryan from Haptik. It was all part of a VB Live event hosted by VentureBeat.

Connected baggage, robots, virtual reality, big data, and drones will be part of your travels soon. Just how will they, along with other technology trends, create a better experience for travelers? Robotics combined with artificial intelligence You can already experiment with robots that deliver room service, guide passengers to departure gates, or provide translation assistance. But would they be able to understand informal language such as slang, idioms, local dialects or irony? Combining their capabilities with Artificial Intelligence (AI) so they are able to recognize emotions, group behaviors, and proactively respond to unexpected situations, give them the potential to provide the next generation of customer service.

Since the nineteenth century, the primary tool used to identify cells has always been the microscope but the report, by the Harvard team, identified many problems with this system. Using this technique they were able to make the AI accurate in 92 per cent of diagnosis and decrease the human rate of error by 85 per cent. Importantly, the errors made by the deep learning system did not generally correlate with the errors made by humans. The report concluded: "Although the pathologist alone is currently superior to our deep learning system alone, combining deep learning with the pathologist produced a major reduction in pathologist error rate."

Since the nineteenth century, the primary tool used to identify cells has always been the microscope but the report, by the Harvard team, identified many problems with this system. Using this technique they were able to make the AI accurate in 92 per cent of diagnosis and decrease the human rate of error by 85 per cent. Importantly, the errors made by the deep learning system did not generally correlate with the errors made by humans. The report concluded: "Although the pathologist alone is currently superior to our deep learning system alone, combining deep learning with the pathologist produced a major reduction in pathologist error rate."

Self driving cars which seemed like fiction in not so recent past, have become a hot topic in the auto and tech industry. New players like Google, Baidu, Tesla are jumping into this sector has heated up competition and as of current day, almost all car manufacturers have announced their development efforts towards autonomous driving. It is now broadly clear that vision sensing elements like cameras, LIDAR ( like Velodyne's LIDAR seen on top of Google's self driving cars), RADARs, SONARs, night vision systems, proximity sensors, etc. are the most important enabling elements for self driving technology. These sensors are mounted across the vehicle body to form real time 3D image of the surroundings. These images are then compared to already existing 3D maps and intelligent algorithms are able to take the appropriate action to drive the car without any manual intervention.