Deep learning applications are the future and these 14 companies are ahead of the curve

By Mike Thomas  |  November 19, 2018

Deep learning is a complicated process that’s fairly simple to explain. A subset of machine learning, which is itself a subset of artificial intelligence, DL is one way of implementing machine learning (automated data analysis) via what are called artificial neural networks — algorithms that effectively mimic the human brain’s structure and function. And while it remains a work in progress, there is unfathomable potential.

“We may someday reach the point where AI and deep learning will help us achieve superintelligence or even bring on the singularity (runaway technological growth),” Conversica chief scientist Dr. Sid J. Reddy has explained. “But our challenge, and duty, as artificial intelligence professionals today is to ensure that deep learning applications live up to their billing and deliver benefits to users and society.”

Here are 14 innovative ways deep learning is being used today. 

 

deep learning applications
descartes labs

Descartes Labs

Location: Santa Fe, N.M.

How it’s using deep learning: Descartes Labs has created what it refers to as a  “data-refinery on a cloud-based supercomputer for the application of machine intelligence to massive data sets.” The process, which involves deep learning, enables companies to “better apply insights from data” — their own and external. Applications include disease control, disaster mitigation, food security and satellite imagery. 

Industry impact: Descartes Labs government programs director Steven Truitt recently told Quartz his company “plans to discuss a super-computing platform for the intelligence community and ‘defense information awareness missions’” at a late-November tech gathering hosted by the Army Research Lab, the Project Maven team and the U.S. Department of Defense’s Joint Artificial Intelligence Center. 

 

deep learning applications
Boxx

Boxx 

Location: Austin, Texas

How it’s using deep learning: Boxx builds high-performance workstation development platforms for a variety of deep learning frameworks, including Tensorflow and PyTorch. Its mission, according to vice president of marketing Bill Leasure, is to “accelerate workflows, expedite decision-making processes and facilitate customer success.”

Industry impact: Boxx recently showcased its new APEXX Neutrino W deep learning development workstation at Supercomputing 2018 in Dallas, Texas.

 

deep learning applications
clusterone

ClusterOne

Location: Seattle

How it’s using deep learning: ClusterOne is a deep learning platform for AI and machine language development whose goal is “to take the pain out of AI programming” by enabling the running of multiple concurrent experiments and managing “scalable deep learning infrastructure, including runtime environment, data and networking.”

Industry impact: In early 2018, ClusterOne — founded by ex-Google employees — moved its headquarters from California to Seattle to join a startup incubator program at the Allen Institute for Artificial Intelligence.

 

deep learning applications
twosense.ai

TwoSense.AI

Location: New York

How it’s using deep learning: A mobile SaaS security product that “invisibly authenticates users by their behavior,” biometrics company TwoSense employs machine (and deep) learning to eliminate authentication challenges and prevent fraudulent activity. Its deep neural networks analyze various data streams, from device location to length of stride, to create unique user profiles. 

Industry impact: The company’s CEO, Dawud Gordon, recently spoke about the use of behavior biometrics in deception tech (a subset of cybersecurity that strategically employs decoys and content to stop threats early) at the 2018 DerbyCon security conference in Louisville, Ky.

 

deep learning applications
salesforce

Salesforce

Location: San Francisco

How it’s using deep learning: Cloud software maker Salesforce created a platform called Einstein to simplify artificial intelligence and “deliver smarter, personalized and more predictive customer experiences.” With attributes that include advanced machine learning, deep learning and predictive analytics, Einstein is employed to “automatically discover relevant insights, predict future behavior and proactively recommend best next actions, and even automate tasks.” 

Industry impact: The company recently open-sourced Einstein so other companies can access it to solve data science issues. 

 

deep learning applications
clarifai

Clarifai

Location: New York

How it’s using deep learning: Clarifai lets computers “see” and understand visual content in a way that’s similar to how the human brain processes images. The company’s technology, which involves deep learning, can be applied to a variety of disparate businesses — from e-commerce stores and content management platforms to real estate firms.  

Industry impact: Clarifai partnered with RichRelevance to, per a report on martechadvisor.com, “deliver a comprehensive, full-spectrum suite of AI personalization strategies” that will enable “digital leaders to tap into deep learning and visual AI to deliver new, innovative digital shopping experiences that incorporate visual inputs and concepts to drive engagement and revenue growth.”

 

deep learning applications
h2o

H2O.ai

Location: Mountain View, Calif.

How it’s using deep learning: H2O.ai created the H2O Driverless AI platform “to make it easier, faster and cheaper to deliver expert data science as a force multiplier for every enterprise.” The company’s ultimate goal is to democratize artificial intelligence.  

Industry impact: According to a Smart Industry report, Stanley Black & Decker now uses H2O’s Driverless AI to “develop AI-enabled manufacturing processes aimed at reducing product-development time.” SBD might also apply Driverless AI to other company projects. 

 

deep learning applications
voysis

Voysis

Location: Boston

How it’s using deep learning: Voysis employs deep learning and other high-tech tools in its development and refining of voice AI for the consumer and business sectors. One example is its work on the WaveNet speech synthesis system, which processes raw audio. 

Industry impact: Voysis recently announced the launch of its product Voysis Embedded WaveNet (ViEW), which makes WaveNet technology available on all cloud mobile devices and requires no cloud connectivity.

 

deep learning applications
ifm tech

IFM Tech

Location: Evergreen Park, Ill.

How it’s using deep learning: IFM, which stands for Intelligent Flying Machines, uses deep learning and computer vision “to make humans more efficient than robots” via the company’s Onetrack.AI platform that “connects the physical to the digital world” and optimizes workforces. 

 

deep learning applications
gamalon

Gamalon

Location: Boston

How it’s using deep learning: Gamalon’s natural language processing technology enables robots to learn from less data, which allows them to more quickly adapt to new challenges and environments. As the company’s CEO put it, “Gamalon’s mission is to accelerate human understanding by combining human and machine learning. It’s easy enough for a business analyst to get started providing return on investment right away. When Gamalon’s Idea Learning technology reads large amounts of text, and forms ideas, the AI becomes an extension of you — allowing you to read and respond to huge volumes of messages.” 

Industry impact: A recent $20 million infusion from investors is going toward R&D as well as the expansion of marketing and sales efforts.

 

deep learning applications
neurala

Neurala

Location: Boston

How it’s using deep learning: The company’s product, Neurala Brain, employs proprietary algorithms called Lifelong-DNN “to emulate the way biological brains see the world and continuously learn from it.” Neurala claims that learning is possible with less data and training time.

Industry impact: With its goal of enhancing AI skills domestically and globally, Neurala recently made its Brain Builder platform available to educators in the U.S. and China.

 

deep learning applications
cora

Cora

Location: Chicago

How it’s using deep learning: Cora users can simultaneously search hundreds of furniture websites “to easily find shoppable products” based on favorite images. The process, aided by deep learning, involves uploading an original photo or one from the company’s library and letting Cora work its computer vision magic. 

 

deep learning applications
aiera

Aiera

Location: Boston

How it’s using deep learning: An adaptive deep learning platform, Aiera provides “institutional investors with advanced, self-learning models, augmented with human insight, on a secure and scalable infrastructure.” Some benefits include “real-time full-featured analysis across individual equities, industry categories and key investor themes.” Company founder Ken Sena: "What we’re trying to do with a product like Aiera is help the fundamental analyst with some of these advances in data and compute. As we look to the next two to five years, I think the industry is going to be very different."

Industry impact: Sena founded Aiera in mid-2018 with former Amazon Alexa AI guru Bryan Healey. As Bloomberg recently wrote, Aiera’s “system now covers more than a thousand stocks and makes hundreds of recommendations with one- to three-month durations.” 

 

deep learning applications
robbie.ai

Robbie.AI 

Location: Boston

How it’s using deep learning: Robbie.AI’s cloud-based technology scours photos and video footage to provide facial recognition services and analyze/predict human emotions in real time. Actionable data insights are provided via a customized dashboard on a wide variety of connected devices. 

Industry impact: Robbie.AI recently partnered with SureID to develop a nationwide biometrics (realistic authentication) gathering system for a wide variety of applications in the U.S.

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