NASHVILLE, Tenn., Nov. 12, 2018 /PRNewswire/ -- Lucd, a provider of
an end to end Enterprise AI Platform will announce a breakthrough
implementation of Reservoir Computing capability for next
generation Artificial Intelligence at SC18.
Lucd has implemented a key approach to Reservoir Computing,
called Echo State Neural Networks,
using its patent pending Distributed Optimistic System.
Reservoir computing (RC) is an alternative to Deep Learning
Recurrent Neural Networks (RNNs), which are critical to
breakthroughs in applications such as natural language
processing. RC has the added benefit of greatly reduced
computation required in the hidden layers of the network.
Lucd's distributed implementation has been tested on tens of
thousands of processors to demonstrate the scalability of RNNs
containing millions of neurons.
As an alternative to Deep Learning, Reservoir Computing is
transforming artificial intelligence (AI) because it takes less
time to train highly accurate models. Today, practitioners
are hampered by the long training times of RNNs, and the need to
refresh training on a regular basis. Organizations with tens
or hundreds of existing models require large-scale compute
resources just to maintain the models they have. Lucd's
distributed approach solves this problem by reducing training times
to minutes, while also enabling models of nearly unbounded width
and depth. Neural nets that are millions of inputs wide and
thousands of layers deep can now be trained in minutes, rather than
months, and provide magnitudes of greater accuracy.
"Training hidden layers is just too slow. Today's systems
were developed with parallel processing as an afterthought.
In our experience, attempting to parallelize existing
libraries almost never works well. We believe parallelization
must be considered at the outset of the development of any new
library. By starting with our scalable distributed optimistic
system, we rapidly developed a large-scale echo state model that,
out of the box was able to scale to thousands of processors.
Our approach to neural network modeling requires a fraction
of the time of classic training algorithms," said Justin LaPre, Ph.D., Director of Distributed
Computing at Lucd.
The anticipated impact of this approach will be the further
democratization of machine learning by reducing requirements for
large amounts of highly specialized computing resources; the
ability to train and retrain models of nearly any size within
minutes; and to perform online training of models in
production.
"At Lucd, we continue to push the envelope so more businesses
can easily integrate AI into their processes. The compute
resource challenge of training deep neural networks risks
bifurcating Enterprise AI into the haves and have nots. Our
approach to reservoir computing offers to change all that. By
exploiting the massive reduction in computational effort needed for
model development, Lucd empowers all industries with faster
training and greater accuracy on any infrastructure," said
David Bauer, Ph.D., CTO and
co-founder at Lucd. "In the coming months we will be working
with select business partners to develop networks of echo state
networks to develop higher order reasoning across hundreds or even
thousands of lower level AI."
"Artificial Intelligence needs computational breakthroughs to
continue a successful trajectory. Demonstrating scalability
of large-scale Reservoir Computing models is a game changer in the
field," noted Chris Carothers,
Ph.D., Director, Center for Computational Innovations and
Professor, Computer Science at Rensselaer
Polytechnic Institute and Lucd Board of Advisors member.
Lucd is at booth #3775 and will be showcasing its Reservoir
Computing results.
About Lucd. By unleashing the power of data, the
Lucd Enterprise end to end AI platform allows all businesses to
conduct machine learning in a responsible way. Lucd builds
Competitive Digital Advantage through leveraging data assets;
Digital ROI; and providing the ability to exploit market knowledge.
Lucd develops pioneering capabilities in AI, Big Data, Data
Fusion and Machine Learning. Visit Lucd online at:
https://www.lucd.ai/
About SC18
SC18, the International Conference for High-Performance
Computing (sc18.supercomputing.org), sponsored by ACM and IEEE-CS,
offers a complete technical education program and exhibition to
showcase the many ways high-performance computing, networking,
storage, and analysis lead to advances in scientific discovery,
research, education, and commerce. This premier international
conference includes a globally attended technical program,
workshops, tutorials, a world-class exhibit area, demonstrations,
and opportunities for hands-on learning.
Photos:
https://www.prlog.org/12739635
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SOURCE Lucd