Editor’s note: This post and its research are the collaborative efforts of our team, which includes Andrew Ilyas (opens in new tab) (PhD Student, MIT), Logan Engstrom (opens in new tab) (PhD Student, MIT), Aleksander Mądry (opens in new tab) (Professor at MIT), Ashish Kapoor…
With over 50 papers from Microsoft accepted at this year’s International Conference on Machine Learning (ICML 2020) (opens in new tab), a number of which were presented in virtual workshops, Microsoft researchers are in full summer swing when it comes to advancing machine learning in…
Reinforcement learning (RL) provides exciting opportunities for game development, as highlighted in our recently announced Project Paidia (opens in new tab)—a research collaboration between our Game Intelligence group at Microsoft Research Cambridge and game developer Ninja Theory. In Project Paidia, we push the state of…
While there has been a focus in the quantum computing industry on growing the number of qubits in a quantum computer, the reality is there are many important factors when building an overall system to bring quantum solutions to fruition. Hardware scaling, temperature control, software…
All around us, biochemical systems are regulating a variety of natural processes, from our body’s ability to protect our skin through the timely production of melanin to plants’ ability to convert carbon dioxide into carbohydrates and oxygen using sunlight. Replicating and programming such complex systems—essentially…
Mental health experiences vary widely from individual to individual. Because of this, effective treatment is about identifying the unique set of tools that will help a person manage their mental health productively. And that rarely happens overnight. People experiencing symptoms of depression, anxiety, or other…
Editor’s note, Feb. 14, 2024 – The Project Freta analysis web portal is no longer publicly accessible. Please contact project-freta@microsoft.com. “Sunlight is said to be the best of disinfectants.” ―Louis D.…
The ability to see and navigate is a critical operational requirement for robots and autonomous systems. For example, consider autonomous rescue robots that are required to maneuver and navigate in challenging physical environments that humans cannot safely access. Similarly, building AI agents that can efficiently and…
In machine learning, adversarial examples usually refer to natural inputs plus small, specially crafted perturbations that can fool the model into making mistakes. In recent years, adversarial examples have been repeatedly discovered in deep learning applications, causing public concerns about AI safety. An illustration of…
The 2020 EMEA and Latin America PhD Award recipients are undertaking research central to advancing today’s technology—training artificial agents to learn faster in new situations, designing new scalable machine learning algorithms for continual and federated learning, and several other compelling projects. Not only is the…
The amount of visual data we accumulate around the world is mind boggling. However, not all the images are captured by high-end DSLR cameras, and very often they suffer from imperfections. It is of tremendous benefit to save those degraded images so that users can…
Since AlexNet was invented in 2012, there has been rapid development in convolutional neural network architectures in computer vision. Representative architectures (Figure 1) include GoogleNet (2014), VGGNet (2014), ResNet (2015), and DenseNet (2016), which are developed initially from image classification. It’s a golden rule that…
