Novetta is using deep learning to automate advanced analytic pipelines for our customers. These new capabilities identify important pieces of information across large text, image, and video data sets, a challenge faced by many of our Defense and Intelligence Community customers. We developed Argo, a standardized, Docker-based model training and deployment pipeline, to enable rapid evaluation and deployment of state-of-the-art deep learning models. Argo enables models to be deployed as endpoints and, when used with Amazon SageMaker, it forms the foundation for us to deploy, scale, and manage our deep learning models. Simplifying infrastructure setup through Docker and AWS allows…
20% Accuracy Bump in Text Classification with ME-ULMFiT
Introduction In a previous post, we discussed an enhanced method of passing additional data to the ULMFiT1 algorithm for unstructured text classification, which improved accuracy by up to 9%. In follow-on experiments, we have demonstrated that this approach – in which we prepend metadata to the text to provide more information to the model – increased accuracy by up to 20%, in relative terms. This improvement required just a few lines of Python, such that the performance boost comes at essentially no cost. This blog post explains the findings of this more-detailed evaluation, where we have compared how the following…
Training an ML Model on the Show Floor: Rapid Prototyping at AWS PSS
AWS PSS attendees interact with Novetta’s Machine Learning Prototype demo on the show floor. Introduction In our previous blog post, Sharpening the Edge with IoT, ML, and Homomorphic Encryption, we discussed our prototype application with the following functionality: Identify when a simulated license plate (alphanumeric characters on a white card) appeared in a live video stream Extract text from the license plate card using Amazon Rekognition Securely search an encrypted watchlist for this text Return any matches to the user Novetta and Enveil demonstrated this prototype at AWS Public Sector Summit, June 11-12. This blog post is an…
Sharpening the Edge with IoT, ML, and Homomorphic Encryption
An interactive demo at AWS Public Sector Summit • Washington, D.C. June 11-12
Edge compute capabilities are central to many of our customers’ missions, and are only growing in importance. For complex workloads like field forensics or digital media triage, we are seeing an increasing need to use machine learning models to process data where it is being collected. Novetta is pairing our advanced analytics, machine learning, and IoT capabilities with Enveil’s ZeroReveal™ technology through a strategic alliance. Using homomorphic encryption, Enveil’s technology allows sensitive information to be securely processed in unsecure environments, allowing data to be searched or analyzed while it is still encrypted. The data security startup’s core technology was developed…
Enveil and Novetta Partner to Deliver Secure Data Processing at the Tactical Edge
Strategic partnership and technology integration unlocks field-ready capabilities for mission-critical applications in the government market.
WASHINGTON, D.C., June 4, 2019 – Enveil, the pioneering data security company protecting Data in Use, and Novetta, a leader in advanced analytics technology, today announced a strategic partnership and technology integration to enable trusted compute at the tactical edge. The collaboration pairs Enveil’s ZeroReveal™ technology with Novetta’s tailored machine learning models to deliver unmatched capabilities for government customers whose mission requires operating on sensitive data in hostile or untrusted environments. Building on their unique national security heritage and mission experience, Novetta and Enveil are exceptionally positioned to deliver capabilities in support of the nation’s highest priority challenges. As a result…
Deep Learning for Language Identification on Audio Signals
Introduction Speech-to-text transcription is an important tool for mission analytics and many natural language processing tasks. In most cases, a language is manually preset before speech-to-text transcription can be applied. For scenarios where data is being aggregated in large quantities in various languages, automatic language detection capabilities would greatly streamline data processing. Novetta has developed a technique, Language Identification For Audio Spectrograms (LIFAS), that uses spectrograms of raw audio signals as input to a convolutional neural network (CNN) to be used for language identification. This approach requires minimal pre-processing, as raw audio signals are input into the neural network and…
2019 Strata Data Conference New York
Novetta is a premier exhibitor at Strata Data Conference in New York on September 23-26, 2019. Visit us in Booth #1534 to discuss our entity resolution and machine learning capabilities. Strata Data Conference is where cutting-edge science and new business fundamentals intersect—and merge. It’s a deep dive into emerging techniques and technologies. You’ll dissect case studies, develop new skills through in-depth tutorials, share emerging best practices in data science, and imagine the future. Formerly known as Strata + Hadoop World, the conference was created in 2012, when O’Reilly and Cloudera brought together their two successful big data conferences. This event…
Introducing Metadata Enhanced ULMFiT
Introduction Since its release in 2018, Novetta’s Machine Learning Center of Excellence has evaluated the performance of Universal Language Model Fine-Tuning (ULMFiT)1 against many customer use cases. We have found that automated labeling of unstructured text helps analysts be more efficient, freeing them up to focus on higher-value tasks. We have been so impressed with its accuracy that we have deployed ULMFiT against a dataset in a production system, with plans to expand it to dozens of other datasets. While ULMFiT’s performance has been impressive on all the datasets we’ve tested, we thought it could do more. Our first use…
State of the Art Text Classification with ULMFiT
Novetta’s Matt Teschke spoke at ODSC East – Boston in the session,”State of the Art Text Classification with ULMFiT” on May 2, 2019. The rise of the internet has led to a faster flow of information, where news posted to a relatively obscure blog can be shared on social media and reach national publications within hours. The volume of information is such that humans alone cannot filter out noise, identify important new viewpoints, and determine how messaging trends are changing over time. At Novetta, we are constantly evaluating advances in deep learning to help our customers…
2019 AWS Public Sector Summit
On June 11-12, 2019, global leaders from government, education, and nonprofit organizations came together for the tenth annual AWS Public Sector Summit in Washington, DC. Novetta participated in two speaking sessions. On Wednesday, June 12th, Chris Doty from AWS, introduced Novetta’s Steve Adelman and Matt Johannesson when they presented: From Unattended Ground Sensors (UGS) to Installations; Leveraging AWS IoT for Effective, Flexible Sensing. The session was recorded and is available for screening here: In Novetta’s both, our subject matter experts demonstrated: Novetta Entity Analytics Natural Language Processing CloudTracker And an interactive demo using a Novetta machine learning prototype, running on…
