IBM Research launches new AI Experiments hub featuring prototypes of tools and resources that will unleash the power of AI.
Here I describe an approach to efficiently train deep learning models on machine learning cloud platforms (e.g., IBM Watson Machine Learning) when the training dataset consists of a large number of small files (e.g., JPEG format) and is stored in an object store like IBM Cloud Object Storage (COS). As an example, I train a […]
In a previous post we explained how to write a probabilistic model using Edward and run it on the IBM Watson Machine Learning (WML) platform. In this post, we discuss the same example written in Pyro, a deep probabilistic programming language built on top of PyTorch. Deep probabilistic programming languages (DPPLs) such as Edward and […]
Edward is a deep probabilistic programming language (DPPL), that is, a language for specifying both deep neural networks and probabilistic models. DPPLs draw upon programming languages, Bayesian statistics, and deep learning to ease the development of powerful AI applications. Probabilistic languages let the user express a probabilistic model as a program with an intuitive formalism […]
Recent years have brought a tremendous proliferation of hardware acceleration and computation devices such as GPUs and FPGAs to address the ever-increasing need for computational power. Deep learning, which requires the processing of large volumes of data through computationally intensive neural networks, has both been enabled by and driven the development of advanced computational hardware. […]
If you want to teach a child what an elephant looks like, you have an infinite number of options. Take a photo from National Geographic, a stuffed animal of Dumbo, or an elephant keychain; show it to the child; and the next time he sees an object which looks like an elephant he will likely […]
Search the two million mobile games on the app store, and you won’t find another quite like Hello Quantum.
Recent years have seen tremendous advances in the development of artificial intelligence (AI). Modern AI systems achieve human-level performance on cognitive tasks such as recognizing objects in images, annotating videos, converting speech to text, or translating between different languages. Many of these breakthrough results are based on Deep Neural Networks (DNNs). DNNs are complex machine […]
Real life is taking a step closer to The Sims video game series. This week at SuperComputing 17 in Denver, Colorado, the Japan Science and Technology Agency (JST) is introducing series of demos, including new research from IBM scientists in Japan which can simulate social situations such as shopping at the mall or an emergency […]
Since our bio-inspired machine learning technology “Dynamic Boltzmann Machine (DyBM)” debuted in the fall of 2015, we received many comments on the music demo and human evolution image that we used to show how an artificial neural network learns about different topics in different formats. Many developers expressed interest in using the code to let […]
In June last year I reported here the open sourcing of Amalgam8 – a microservice fabric first to provide a central control over layer 7 routing across a mesh of microservices that constitutes a cloud app. The value of Amalgam8 is in removing the burden and complexity of integrating the smaller microservices that comprise an […]