"Thinking Machines"

Jul 2015

13 Mon

14 Tue

15 Wed

16 Thu 08:30 AM – 06:35 PM IST

17 Fri 08:30 AM – 06:30 PM IST

18 Sat 09:00 AM – 06:30 PM IST

19 Sun

Make a submission

NIMHANS Convention center

Machine Learning, Distributed and Parallel Computing, and High-performance Computing are the themes for this year’s edition of Fifth Elephant.

The deadline for submitting a proposal is 15th June 2015

We are looking for talks and workshops from academics and practitioners who are in the business of making sense of data, big and small.

Track 1: Discovering Insights and Driving Decisions

This track is about general, novel, fundamental, and advanced techniques for making sense of data and driving decisions from data. This could encompass applications of the following ML paradigms:

Statistical Visualizations
Unsupervised Learning
Supervised Learning
Semi-Supervised Learning
Active Learning
Reinforcement Learning
Monte-carlo techniques and probabilistic programming
Deep Learning

Across various data modalities including multi-variate, text, speech, time series, images, video, transactions, etc.

Track 2: Speed at Scale

This track is about tools and processes for collecting, indexing, and processing vast amounts of data. The theme includes:

Distributed and Parallel Computing
Real Time Analytics and Stream Processing
MapReduce and Graph Computing frameworks
Kafka, Spark, Hadoop, MPI
Stories of parallelizing sequential programs
Cost/Security/Disaster Management of Data

HasGeek believes in open source as the binding force of our community. If you are describing a codebase for developers to work with, we’d like it to be available under a permissive open source license. If your software is commercially licensed or available under a combination of commercial and restrictive open source licenses (such as the various forms of the GPL), please consider picking up a sponsorship. We recognize that there are valid reasons for commercial licensing, but ask that you support us in return for giving you an audience. Your session will be marked on the schedule as a sponsored session.

Workshops

If you are interested in conducting a hands-on session on any of the topics falling under the themes of the two tracks described above, please submit a proposal under the workshops section. We also need you to tell us about your past experience in teaching and/or conducting workshops.

Hosted by

The Fifth Elephant

The Fifth Elephant - known as one of the best data science and Machine Learning conference in Asia - has transitioned into a year-round forum for conversations about data and ML engineering; data science in production; data security and privacy practices. more

All submissions

This submission has been added to the schedule

"Thinking Machines"

Submitted Jul 8, 2015

Section: Keynote Technical level: Advanced

To explore the key building blocks of Artificial Intellgence: “Understanding”, “Learning”, “Thinking”, and “Creativity”.

Outline

Ever since the dawn of civilization humans have been trying to “extend” themselves through “machines” - tools to hunt animals stronger than us, telescopes to see farther than our eyes, cranes to lift more than our hands, cars to move faster than our legs, and computers to store and process more information than ever before. The epitome of this “extension”, the dream (or nightmare) of Artificial Intelligence, is to create a “Thinking Machine” that replicates or even surpasses our brain’s ability to:

(a) “Understand” the data it receives,

(b) “Learn” compositional and causal structures in it,

(d) “Create” new data using the “model” of the world it has learnt.

Such a machine could, for example, have a human like conversation, solve complex problems, predict the next scene in a video, find a cure for cancer, prove Fermat’s last theorem, or even create art or poetry some day. Advances made in machine learning, natural language understanding, speech recognition and synthesis, computer vision, and deep learning have brought us to the brink of such a possibility! We can already see glimpses of such “thinking machines” - the self driving cars, the jeopardy winning Watson, and the recent “paintings” created from deep vision networks (http://googleresearch.blogspot.in/2015/06/inceptionism-going-deeper-into-neural.html).

In this talk, we will explore both the philosophical and algorithmic aspects of building such a “Thinking Machine”. More specifically, we will explore some hypothese on how we:

(a) learn, represent, and disambiguate senses of words without knowing the grammar of a language?

(b) analyze knowledge from langauge and synthesize language from knowledge?

(d) can build better machine translation and conversation systems using some of these building blocks?