Deep Learning Summer Seminar at UPC is full!

May 26th, 2016|

Deep Learning at UPC with Oriol Vinyals & Joan Bruna

May 23rd, 2016|

The Machine Learning Summer School 2016

May 21st, 2016|

Seminar on Deep Learning at UPC with Oriol Vinyals and Joan Bruna

May 14th, 2016|

We (UPC, TelecomBCN, FIB, CFIS and BSC) are proud to invite you to our first seminar on Deep Learning organized at UPC, next May 23th at 11:00, with the talks of two outstanding speakers: Joan Bruna (UC Berkeley) and Oriol Vinyals (Google DeepMind). Do not miss this great event happening in Barcelona.  And if you are interested in Deep Learning, we are also preparing  a Deep Learning for Computer Vision Summer Seminar  in Barcelona next 4-8 July 2016 ( more info at  http://TelecomBCN.DeepLearning.Barcelona). UPDATE: Photographs of the event here When: Monday  May 23, 11:00-13:00 Place: Aula Màster -  A3 building - UPC Campus Nord - Barcelona Talks: 11:00: Convolutional Neural Networks against the Curse of Dimensionality by Joan Bruna (UC Berkeley).  Convolutional Neural Networks are a powerful class of non-linear representations that have shown through numerous [...]

CaixaBank y el BSC investigarán la aplicación de la computación cognitiva a la innovación financiera

May 7th, 2016|

Esta semana en el BSC-CNS hemos podido materializar un primer acuerdo de colaboración con CaixaBank para promover conjuntamente el desarrollo de sistemas High-Performance Big-Data Analytics basados en Deep Learning para mejorar el servicio a sus clientes y optimizar la eficiencia operativa en sus servicios bancarios. Estoy extremadamente contento, es mi primer proyecto gestionado con mi rol de Senior Innovation Advisor del BSC-CNS. Espero contarles desde este blog futuros avances en los que podamos ganar todos. De momento más detalle lo pueden encontrar en nuestra nota de prensa.  

New release of TensorFlow with distributed computing support

April 13th, 2016|

Few hours ago Google announced his TensorFlow 0.8 that includes distributed computing support. As we already presented in this blog, distributed TensorFlow is powered by the high-performance gRPC library, which supports training on hundreds of machines in parallel according Google post. It complements the recent announcement of Google Cloud Machine Learning, which enables us to use the Google Cloud Platform. The post also announces that they have published a distributed trainer for the Inception image classification neural network in the TensorFlow models repository. The distributed trainer also enables us to scale out training using a cluster management system like Kubernetes from Google. Furthermore, once we have trained our model, we can deploy to production and speed up inference using TensorFlow Serving on Kubernetes. Beyond distributed Inception, the 0.8 release includes new libraries for defining our own distributed models. Using the distributed trainer, they trained the Inception network to 78% accuracy [...]

Aprender TensorFlow en Salamanca

March 31st, 2016|

Hace unos días unos alumnos de la Facultad de Ciencias de la USAL pertenecientes al  capítulo de la ACM se pusieron en contacto conmigo a propósito del libro TensorFlow y en especial por una de sus ilustraciones.  Uno de sus intereses es el campo de la inteligencia artificial y las redes neuronales artificiales, así que desde que fundaron la asociación han venido organizando anualmente workshops con esta temática [1][2]. Ahora organizan un seminario introductorio al aprendizaje automático con redes neuronales y TensorFlow. Me han mostrado su github que han preparado para el curso y sin duda va a ser impresionante, tratando temas  como las LSTM que no contiene mi libro. Les pregunté que debería contar a mis alumnos para animarlos a asistir a este seminario en Salamanca. Aquí va: "La verdad es que estudiar en Salamanca es toda una [...]

¡Google ofrece más Machine Learning a los desarrolladores!

March 24th, 2016|

Google acaba de anunciar en su blog nuevas herramientas de Machine Learning para  desarrolladores disponibles como un servicio más en su plataforma Google Cloud  a través de APIs. En el blog se indica que es exactamente la misma tecnología que está detrás de productos como Google Now o Google Photos, permitiendo a los desarrolladores construirse potentes modelos Machine Learning usando TensorFlow, además de ofrecer modelos preentrenados a través de Google Translate API,  Cloud Vision API o Google Cloud Speech API. Si juntamos esto con su servicio Cloud Dataproc que permite la gestión de procesos tanto de Hadoop como de Spark,  realmente los desarrollador e investigadores tenemos ahora mismo una potente y completa plataforma de procesado Big Data. Si tienen dos minutos les recomiendo este video insertado en su blog, para hacerse una idea a través de un simple robot realizado con una Raspberry Pi :

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 [...]