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Using Virtual Reality at the IBM Watson Image Recognition Hackathon

Using Virtual Reality at the IBM Watson Image Recognition Hackathon

Using Virtual Reality at the IBM Watson Image Recognition Hackathon

Five teams of developers gathered at the Silicon Valley Virtual Reality (SVVR) headquarters in California last month to learn about the new features of IBM Watson’s Visual Recognition service, like the ability to train and retrain custom classes on top of the stock API, that allow the service to have new and interesting use cases in VR when combined with the Watson Unity SDK. Staff from IBM, NVIDIA and SVVR were on-site for the event to help developers gain the best experience.

The Watson Developer Cloud Unity SDK makes it easy for developers to take advantage of modern AI techniques through a set of cloud-based services with a simple REST APIs. These APIs can be accessed from the Unity development environment by using the Watson Unity SDK, available on GitHub, so anyone can take the code and improve upon it.

This was the first experience building training sets for image recognition for many of the developers, but the Watson API made things relatively simple. Teams were able to get started within a few minutes.

After two days of hacking, the winning team was Watson and Waffles, an intriguing adventure game which required the player to sketch game objects using the Vive controller. Watson identified the objects, and then the game manifested them for the player to use.

Using Virtual Reality at the IBM Watson Image Recognition Hackathon

Using Virtual Reality at the IBM Watson Image Recognition Hackathon

The game was innovative — combining VR adventuring with room scale sketching using motion controllers. The winning team received an NVIDIA TITAN X GPU and an HTC Vive VR setup.

“It was fantastic to experiment with the new AI image recognition technologies in all new ways in VR, and now my mind is running wild with ideas of how AI could become an essential part of a game developer’s toolbox — allowing us to rapid prototype things that would otherwise require hours of entangled webs of logic,” said Michael Jones, developer on the Watson and Waffles team.

The runner-up teams built a game based around recognizing playing cards with the Vive’s front-facing camera and a VR panoramic photo viewing application that allowed uses to take a virtual journey through their memories.

“I really wanted to do a Watson VR hackathon focusing on a single service — in this case visual recognition — to see what creative and interesting new use cases developers could come up with, and thanks to the high quality of participants and the support of great partners like NVIDIA, HTC and SVVR, we were blown away by the results,” said Michael Ludden, Product Manager, Developer Relations at IBM Watson who also mentioned they have plans of hosting similar hackathons in the future.

Watson uses GPU-acceleration to power components of the image recognition API. Image recognition can be used in a variety of Virtual and Augmented reality applications, and besides being able to recognize images, Watson has services for interactive speech, natural language processing, translation, speech-to-text, text-to-speech and data analytics, among others.

IBM Watson Chief Technology Officer Rob High to Speak at GPU Technology Conference

IBM Watson Chief Technology Officer Rob High to Speak at GPU Technology Conference

IBM Watson Chief Technology Officer Rob High to Speak at GPU Technology Conference

Highlighting the key role GPUs will play in creating systems that understand data in human-like ways, Rob High, IBM Fellow, VP and chief technology officer for Watson, will deliver a keynote at our GPU Technology Conference, in Silicon Valley, on April 6.

Five years ago, Watson grabbed $1 million on Jeopardy!, competing against a pair of the TV quiz show’s top past winners. Today, IBM’s Watson cognitive computing platform helps doctors, lawyers, marketers and others glean key insights by analyzing large volumes of data.

High will join a lineup of speakers at this year’s GTC that includes NVIDIA CEO Jen-Hsun Huang and Toyota Research Institute CEO Gill Pratt, who will all highlight how machines are learning to solve new kinds of problems.

Fueling an AI Boom

Watson is among the first of a new generation of cognitive systems with far-reaching applications. It uses artificial intelligence technologies like image classification, video analytics, speech recognition and natural language processing to solve once intractable problems in healthcare, finance, education and law.

GPUs are at the center of this artificial intelligence revolution (see “Accelerating AI with GPUs: A New Computing Model”). And they’re part of Watson, too.

IBM announced late last year that its Watson cognitive computing platform has added NVIDIA Tesla K80 GPU accelerators. As part of the platform, GPUs enhance Watson’s natural language processing capabilities and other key applications. (Both IBM and NVIDIA are members of the OpenPOWER Foundation. The open-licensed POWER architecture is the CPU that powers Watson.)

GPUs are designed to race through a large number of tasks at once, something called parallel computing. That makes them ideal for many of the esoteric mathematical tasks that underpin cognitive computing, such as sparse and dense matrix math, graph analytics and Fourier transforms.

NVIDIA GPUs have proven their ability to accelerate applications on everything from PCs to supercomputers using all these techniques. Bringing the parallel computing capabilities of GPUs to these compute-intensive tasks allows more complex models to be used, and used quickly enough to power systems that can respond to human input.

Rob High, IBM Fellow, VP and chief technology officer for Watson, will speak at our GPU Technology Conference

Rob High, IBM Fellow, VP and chief technology officer for Watson, will speak at our GPU Technology Conference

Understanding Language

The capabilities brought to Watson from GPUs are key to understanding the vast sums of data people create every day — a problem that High and his team at IBM set out to solve with Watson.

With structured data representing only 20 percent of the world’s total, traditional computers struggle to process the remaining 80 percent of unstructured data. This means that many organizations are hampered from gathering data from unstructured text, video and audio that can give them a competitive advantage.

Cognitive systems, like Watson, set out to change that by focusing on understanding language as the starting point for human cognition. IBM’s engineers designed Watson to deal with the probabilistic nature of human systems.

Dive in at Our GPU Technology Conference

Our annual GPU Technology Conference is one of the best places to learn more about Watson and other leading-edge technologies, such as self-driving cars, artificial intelligence, deep learning and virtual reality.

AI invasion will allow workers to empathise

Jobs for the bots: robots will take on mundane work, enabling humans to focus on interpersonal tasks.

Jobs for the bots: robots will take on mundane work, enabling humans to focus on interpersonal tasks.

There’s a clue to the future of work in the relief you feel when your phone call to a big corporation is answered by, of all things, a human.

It makes sense. People are replete with empathy and compassion, like to solve problems and enjoy communicating through stories. And these profoundly human traits are the areas where artificial intelligence (AI) trails humans. Because they are our strengths they point to the future of the office and to our workplace relationships with robots and AI.

In the future, people will spend more time dealing with other people rather than investing their energy in spreadsheets, machinery and computer screens. Rote decision making, repetitive tasks and data management will be owned by our silicon-chip workmates.

You can already glimpse this labour allocation in action – there are accounting apps that extract the information from photographs of receipts and automatically compile end-of-month reports. Meanwhile, the accelerating capability of AI to understand spoken human language will cause immense disruption. “Will we ultimately be able to replace most telephone operators? Yes,” says Paul Murphy, chief executive of voice technology company Clarify.io. “In fact I’d say speech recognition and understanding has the potential to eliminate any job where the role of the human is that of intermediary.”

Meanwhile, we will be employed to tell stories, empathise, see the big picture, solve complex problems and adapt fast to changing situations.

Rather than displacing humans, AI will augment human strengths. This will lead to the invention of new roles, which fall into three categories.

Thinking differently

AI and robots excel at following pre-set rules. People will thrive when they learn to harness machines for data insights, which they can use for problem-solving and innovation. An architect, for example, will be able to work much faster than today because of the range of technologies available, such as augmented reality visualisation and virtual reality headsets. But providing a solution that fits within the constraints of space, planning restrictions, budget and aesthetic style would be nigh-on impossible to automate.

Thinking bigger

Computers can’t see the context, connection and patterns that humans can, despite crunching vast amounts of data at speed. For example, an automated ad-buying program might be brilliant at buying online advertising space for the right audience at the right price, but it might fail to realise that the day after an air accident would be the wrong day to advertise certain products or certain taglines. The future will involve people who oversee machine decision-making.

Social interaction

The analytical powers of robots enable them to suggest decisions in healthcare, financial investment and other areas based on huge quantities of data. IBM’s Watson computer, for example, can monitor a vast array of data inputs to identify possible medical problems and propose courses of treatment. But the communication of advice and the contextualised understanding of the best course of action for a specific patient is best handled by humans. As with medicine, so with finance: the role of the specialist human will be to mediate between the wonders of automation and the needs and desires of the patient or customer.



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My name is Sayed Ahmadreza Razian and I am a graduate of the master degree in Artificial intelligence .
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Related topics such as image processing, machine vision, virtual reality, machine learning, data mining, and monitoring systems are my research interests, and I intend to pursue a PhD in one of these fields.

جهت نمایش صفحه معرفی و رزومه کلیک کنید

My Scientific expertise
  • Image processing
  • Machine vision
  • Machine learning
  • Pattern recognition
  • Data mining - Big Data
  • CUDA Programming
  • Game and Virtual reality

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