HOY, UN HUMANO AÚN HA PODIDO SUPERAR AL COGNITIVE COMPUTING, ¿HASTA CUÁNDO?

March 13th, 2016|

Hoy, el surcoreano Lee Sedol, campeón mundial del juego de mesa GO, ha logrado su primera victoria contra la aplicación de “Cognitive Computing” AlphaGo  de Google. Ha sido en la cuarta de las cinco partidas de las que consiste el torneo que se realiza en Seúl (Corea del Sur). Lee Sedol, en realidad, ya perdió el torneo después de que AlphaGo ganara las tres primeras partidas, pero el hecho que hoy Lee haya ganado al sistema es noticia. Si les apeteciera, el próximo martes pueden seguir en directo la final en YouTube. Según un tweet de Demis Hassabis,  CEO y cofundador de DeepMind (compañía de inteligencia artificial inglesa adquirida por Google en 2014), el sistema AlphaGo se confundió y no se dio cuenta que había cometido un error hasta diez movimientos después. Pero [...]

Distributed TensorFlow Has Arrived

March 13th, 2016|

The landscape of Deep Learning was impacted in November, 2015, with the release of Google's TensorFlow, what is now the most popular open source machine learning library on Github by a wide margin. Some researchers showed their dissatisfaction with the project because the lack of distributed training capabilities (because such capabilities were directly alluded to in the accompanying whitepaper's title). However, the distributed TensorFlow has arrived, few week ago [*] Google announced an update to its deep learning library and TensorFlow now supports distributed training. The distributed version of TensorFlow is supported by gRPC, which is a high performance, open source RPC framework for inter-process communication (the same protocol used by TensorFlow Serving). Remember that the second most-starred machine learning project of Github is Scikit-learn, the de [...]

Google launched TensorFlow Serving

February 18th, 2016|

Google launched TensorFlow Serving, that helps developers to take their TensorFlow machine learning models (and, even so, can be extended to serve other types of models) into production.  TensorFlow Serving is an open source serving system (written in C++) now available on GitHub under the Apache 2.0 license. What is the difference between TensorFlow and TensorFlow Serving?  While in TensorFlow is easier for the developers to build machine learning algorithms and train them for certain types of data inputs, TensorFlow Serving specializes in making these models usable in production environments.  The idea is that developers train their models using TensorFlow and then they use TensorFlow Serving’s APIs to react to input from a client. This allows developers to experiment with different models in a large scale that change over time based on real-world data, and maintain a [...]

INTERNATIONAL PHD IN DEEP LEARNING & HPC FOR COMPUTER VISION

February 7th, 2016|

The Research Group Autonomic Systems and eBusiness Platforms at Barcelona Supercomputing Center (BSC), invites outstanding candidates to apply for a full-time PhD position under "Becas de posgrado de La Caixa"  grants (link) or "International PhD Program Fellowship BSC La Caixa" grants (link). The PhD work will focus on Deep Learning and High Performance Computing for computer vision. PhD project description Deep learning has changed the scape of computer vision and artificial intelligence. Current research in these areas has shown the possibility of creating tools that are able to recognize thousands of objects, or automatically describe the content in an image. For example, Google Brain approach to automatic captioning is able to reliably describe many complex images using this basic queues. However, human understanding of images is far more elaborated. Humans do not [...]

Barcelona Supercomputing Center starts to work on Deep Learning

June 26th, 2014|

What is Deep Learning? We can consider Deep Learning as a new area of Machine Learning research with the objective of moving Machine Learning closer to Artificial Intelligence (one of its original goals).  Our research group has been working in Machine Learning for a long time thanks to Ricard Gavaldà who introduced us in this wonderful world. It was during the summer of 2006, also with Toni Moreno, Josep Ll. Berral, Nico Poggi. Unforgettable moments! However, after 8 years we will make a step forward and start to work with Deep Learning. It was during a group retreat held last September when I realise that "Deep Learning"  was an interesting topic thank you to  Jordi Nin. Deep Learning comes from Neural nets conceived in the 1940s, inspired by the [...]