Microsoft Research Blog

Artifical intelligence

  1. Leveraging blockchain to make machine learning models more accessible 

    July 12, 2019 | Justin D. Harris

    Significant advances are being made in artificial intelligence, but accessing and taking advantage of the machine learning systems making these developments possible can be challenging, especially for those with limited resources. These systems tend to be highly centralized, their predictions are often sold on a…

  2. Microsoft makes AI debugging and visualization tool TensorWatch open source 

    June 25, 2019

    The rise of deep learning is accompanied by ever-increasing model complexity, larger datasets, and longer training times for models. When working on novel concepts, researchers often need to understand why training metrics are trending the way they are. So far, the available tools for machine…

  3. Reliability in Reinforcement Learning 

    June 6, 2019 | Romain Laroche

    Reinforcement Learning (RL), much like scaling a 3,000-foot rock face, is about learning to make sequential decisions. The list of potential RL applications is expansive, spanning robotics (drone control), dialogue systems (personal assistants, automated call centers), the game industry (non-player characters, computer AI), treatment design…

  4. a person sitting at a table using a laptop computer

    A phonetic matching made inˈhɛvən 

    June 6, 2019 | Matthew Dixon

    Recently, Microsoft Research Montréal open sourced a phonetic matching component used previously in Maluuba Inc.'s natural language understanding platform. The library contains string comparison utilities that operate on a phoneme level as opposed to a character level. This allows upstream systems to utilize personalized and…

  5. a man standing in front of a building

    Provably efficient reinforcement learning with rich observations 

    June 3, 2019 | Akshay Krishnamurthy

    Reinforcement learning, a machine learning paradigm for sequential decision making, has stormed into the limelight, receiving tremendous attention from both researchers and practitioners. When combined with deep learning, reinforcement learning (RL) has produced impressive empirical results, but the successes to date are limited to simulation…