Our Experience Sets Us Apart
Statement of Corporate Responsibility
Vyasa operates in accordance with a strong sense of corporate responsibility and expects that each member of the Vyasa team does so as well. In particular, at Vyasa, we are driven by the values of Service, Humility, Integrity, Excellence, Love and Diversity. We believe that these are values that enhance all human interactions and are also essential for building and operating a well-respected, successful business that provides top-tier interactions, services and solutions for our clients and partners.
Vyasa is the name of a central and revered figure in the Hindu dharma. As the key compiler and storyteller of sacred Hindu texts, Vyasa brought together knowledge across many sources. Our CEO, Christopher Bouton lived in India for four years as a boy and has great respect for the many belief systems and writings from the deep and rich tapestry of knowledge and thought that are part of the Hindu and broader Indian culture. He believes that our data today has the ability to tell us important, valuable stories and that novel technologies such as deep learning can act as an approach toward gaining greater insight into these stories.
Why we’re excited about deep learning
Hype, especially in our 24/7 driven media age, can often distort the perceived importance of any given technological development. There is no doubt that artificial intelligence (AI) and the deep learning algorithms that underpin these AI approaches are currently the subject of such a hype cycle.
While it will take time for the wheat to be separated from the chaff, what will emerge is a set of technological advances that do in fact have novel capabilities that will fundamentally enhance our ability to utilize computational approaches in some of humanity’s most critical pursuits.
At the heart of these advances is the notion that machines can now learn to recognize patterns, objects and outcomes without being given a priori rule sets to operate on. While this may seem a radical notion, it is not without precedence. There is a computer that has been around for as long as we’ve been around: the human brain – in particular the brain’s cortical architecture -which operates in a very similar manner. Our brains, however, are limited by the amount of information that they can ingest and consider at any given time. This is not the case for artificial intelligence approaches, which can incorporate far more variables for learning and thus, can provide deeper insights based on an understanding of the complexity and interconnectedness of variables that far surpasses what humans are capable of.
These types of capabilities are highly relevant in areas such as the life sciences and healthcare, where many complex variables across disparate information sources need to be brought to bear for insight generation and effective decision making. Fundamental to that capability, though, is the need to securely provide deep learning systems with enterprise data at scale.
Vyasa Cortex is an enterprise-scale deep learning platform, built from the ground up with consideration for Big Data-scale data handling and provision to a range of deep learning approaches. Cortex handles disparate structured and unstructured data as chunks, or statements, and instead of attempting to model or format that content, utilizes a novel deep learning methodology called Neural Concept Recognition developed by Vyasa to identify the concepts latent in the content. Cortex can then enable the application of a pipeline of AI approaches on the concepts identified in the system.
At Vyasa, we see a future in which AI-driven approaches enable humans to elevate the nature of our work beyond the rote activities so often inherent in our current processing of digital content. It is exciting to imagine what will be possible when we are able to apply these approaches across large pools of content to help advance our understanding and capabilities across a wide array of pursuits. Hyped or not, AI technologies are here to stay. They are powerful and they are game changing for those enterprises that can apply them effectively at scale.