Announces Partnership with Supermicro Computer
Cortical.io, a leader in AI-based Natural Language Understanding (NLU) solutions, announced the debut of a new class of high-performance enterprise applications based on “Semantic Supercomputing.” Semantic Supercomputing combines Cortical.io AI-based NLU software inspired by neuroscience with hardware acceleration to create new solutions to understand and process streams of natural language content at massive scale in real time.
“The demand for real-time AI services has never been greater and, together with Cortical.io and Supermicro, we’re excited to be building a solution for solving the incredible processing challenges of real-time Natural Language Understanding on a massive scale”
“Ever-increasing unstructured data is overwhelming the world and the available processing power and current statistical approaches to deal with it,” said Francisco Webber, co-founder and CEO of Cortical.io. “We are taking the concept of supercomputing to the next level with the introduction of Semantic Supercomputing and the ability to deliver real-time processing of semantic content.”
First Application of Semantic Supercomputing Tackles Enterprise Messaging
The first application of Semantic Supercomputing, a Messaging Classification Appliance that can filter, classify and route streams of messages in real time by understanding the semantic content – the meaning and intent of the messages was unveiled today at Xilinx Developer Forum (XDF) Europe keynote session at the Xilinx, Inc. developer conference held November 12-13 in The Hague.
Building on the strategic relationship announced with Xilinx at last month’s at XDF Americas in San Jose, Cortical.io is developing this first of a series of FPGA-based appliances powered by Xilinx Alveo accelerator cards. Cortical.io also announced it is partnering with Supermicro (SMCI), a global leader in enterprise computing, storage, networking solutions and green computing technology, to deliver the email solution on a pre-loaded server. The appliance will enable enterprises to filter and route massive volumes of email messages in real time with high precision and recall based on the meaning of the message. The product will be available in Q1 2020.
“The goal is to reduce the wasted efforts of handling irrelevant or misdirected emails by first line business operations – including support, sales, purchasing,” said Cortical.io CMO Steve Levine. “The appliance will be able to handle a massive volume of messages daily in real time.”
Enterprise system administrators will be able to train the system and customize the filtering and routing based on a small number of sample emails. Once trained, the appliance works across multiple languages (English, Spanish, German, Portuguese, Cantonese, Arabic, French, Italian, Mandarin Chinese, Dutch).
“The demand for real-time AI services has never been greater and, together with Cortical.io and Supermicro, we’re excited to be building a solution for solving the incredible processing challenges of real-time Natural Language Understanding on a massive scale,” said Adam Scraba, director of marketing, Data Center Group, at Xilinx.
“Supermicro’s proven and extensive server portfolio when combined with Xilinx Alveo accelerators and the Cortical.io AI-based NLU software, delivers a sophisticated enterprise platform to address the growing data explosion, especially email,” said Don Clegg, senior vice president, Worldwide Sales, Supermicro.
This is just the first instance of using the power of Semantic Supercomputing. Cortical.io CEO Webber stressed, “Our goal is to make possible the broad implementation and deployment of AI solutions for automating business processes and solving the most challenging use cases that depend on human understanding, decision making and execution.”
The unique Cortical.io approach to NLU is inspired by the latest findings on the way the brain processes information. This approach provides advantages over traditional machine learning methods and helps businesses solve many open NLU challenges like meaning-based filtering of terabytes of unstructured text data, real-time topic detection in social media, or semantic search over millions of documents across languages.