Today, Microsoft’s top researchers shared their personal predictions for the future. Microsoft researchers including the United States, China, and Europe shared their thoughts on what we might see in the next 10 years. Their expectations range from artificial intelligence, machine learning, DNA storage, speech recognition, security research, and a lot more. Here’s a quick list of some of their expectations:
- What will be the key advance in speech and natural language processing in 2017? Kalika Bali (Researcher at Microsoft Research India): Our speech and language technology applications will be increasingly multilingual in 2017. That doesn’t just mean that we will add more languages to our offering. We will do that, but we also will have systems that understand, process and generate the language that an English-Spanish or a French-Arabic or a Hindi-English speaker uses when she effortlessly switches from one language to another, within the same conversation, chat and sometimes even within the same sentence.
- What will be the key advance in algorithms for machine learning in 2017? Jennifer Chayes (Distinguished Scientist and Managing director of Microsoft’s New England and New York City research labs): Deep learning is transforming many aspects of our technology, however, deep learning algorithms today are still largely heuristic, based on the experience and intuition of leaders in the field. In 2017, we will develop a more principled understanding of deep learning and hence more robust algorithms. The insights here will come from many fields, including the intersection of statistical physics and computer science.
- What will be the key advance or topic of virtual reality in 2027? Mar Gonzalez Franco (Researcher at Microsoft Research Redmond): By 2027 we will have ubiquitous virtual reality systems that will provide such rich multisensorial experiences that will be capable of producing hallucinations which blend or alter perceived reality. Using this technology, humans will retrain, recalibrate and improve their perceptual systems. In contrast to current virtual reality systems that only stimulate visual and auditory senses, in the future, the experience will expand to other sensory modalities including tactile with haptic devices.
- What will be the key advance or topic of discussion in artificial intelligence and machine learning in 2027? Katja Hofmann (Researcher, Microsoft Research lab at Cambridge): AI is progressing very rapidly. It has great potential to empower people and help us tackle key global challenges. To me, the most important topic of discussion is how to ensure that by 2027 these advances and great potential translate into AI technology that results in the greatest possible benefit to society.
- What will be the key advance in mathematics and cryptography in 2017? Kristin Lauter (Principal Researcher at Microsoft Research Redmond): New mathematical solutions allowing for computation on encrypted data will be deployed to protect the privacy of medical and genomic data for patients and hospitals. The new homomorphic encryption schemes will secure the data while allowing the cloud to compute on it to make useful risk predictions and provide analysis and alerts. Homomorphic encryption will be deployed soon in the financial sector to protect sensitive banking data.
- What will be the key advance or topic of discussion in programming languages and software engineering in 2027? Kathryn S. McKinley (Principal Researcher at Microsoft Research Redmond) By 2027, the majority of software engineers will be facile in programming systems that reason about estimates and produce models with statistical methods. This sea change will deliver applications that seamlessly integrate sensors, machine learning, and approximation to interact with human beings in entirely new, meaningful and correct ways.
- What will be the key advance in mobile computing in 2017? Oriana Riva (Researcher at Microsoft Research Redmond): In 2017, systems will increasingly re-architect themselves to support interactions without a graphical user interface. We’ll see fewer users installing apps on their devices and more apps turning into behind-the-scenes services for chatbots and personal digital assistants.
- What will be the key advance in hardware and devices in 2017? Karin Strauss (Senior Research at Microsoft Research Redmond): Moore’s Law has been slowing down. It is getting too expensive to scale general purpose, silicon-based processors and capacitive memories at the same pace as before. As a result, in 2017 we will see a number of new custom hardware accelerators, mostly on FPGA fabrics, proliferate in the cloud to improve performance and lower costs, instead of simply relying on Moore’s Law. Of course, general purpose processors will continue to improve, just at a slower rate. The result will be more interesting, responsive and secure services backed by the cloud. We also will see more virtual reality and augmented reality devices and accessories, both cheap and expensive, come to market. This will result in a number of new applications experimenting with these platforms, as well as interesting developments in content creation for virtual and augmented reality, including 360-degree video recording and similar devices.
- What will be the key advance or topic of discussion in computer vision in 2027? Xiaoyan Sun (Lead researcher at Microsoft Research Asia): By 2027 the ability for computers to “see” will be ubiquitous as we will have highly developed imaging devices, powerful computing resources and combined deep and wide learning techniques. Advances in these techniques will lead to ubiquitous vision “eyes” that can “see” and empower humans in daily life and all kinds of professions, from manufacturing and health care to finance and security.
- What will be the key advance in data analytics and vision in 2017? Dongmei Zhang (Principal Research Manager at Microsoft Research Asia): In 2017, the key technology advance of data analytics and visualization will be in smart data discovery, with interactive, intuitive and instant insights at its core. Such insights will be generated automatically and recommended to users based on their analysis context. The insight generation and recommendation will take into account user response, thus creating an effective and fast feedback loop. Users will be able to complete their analytic tasks more quickly and with less effort.
