Welcome to the July 2020 BASELINE, Novetta’s Machine Learning Newsletter, where we share thoughts on important advances in machine learning technologies likely to impact our customers. This is another special month, as we invited additional members of our 2020 intern class to share their latest findings. They selected topics covering: Fairness and bias in ML New methods for interacting with tabular data Information extraction from forms Preprocessing for deepfake detection models Algorithmic Injustices As more questions arise concerning the ethical implications of machine learning (ML) usage, prominent conferences, such as NeurIPS, are beginning to ask contributors to evaluate and disclose…
Machine Learning Explainability
Novetta applies machine learning models to help customers make better decisions across a wide range of use cases. Increasingly, decision makers want to understand why a model makes the decisions that it does. Model explanations help our customers gain an understanding of how our models function, while enabling us to debug our models and assess them for bias and fairness. In this blog post, we describe the tools and techniques we use to generate explanations from the predictions of our machine learning models. Interpretable Models Selecting an inherently interpretable “white-box” model is an obvious way to gain insights on how…
BASELINE – June 2020
An ML Newsletter from Novetta
Welcome to the June 2020 installment of BASELINE, Novetta’s Machine Learning Newsletter, where we share thoughts on important advances in machine learning technologies likely to impact our customers. This is a special month, as we invited members of our 2020 intern class to provide their thoughts. They selected topics covering: New methods for training image models with less data Open source audio datasets A new approach for translating between programming languages Faster word embeddings Training GANs with Limited Data Training high-quality Generative Adversarial Networks (GANs) typically requires a large number of images whose collection may be costly or time-consuming. To…
BASELINE – May 2020
An ML Newsletter from Novetta
Welcome to the May 2020 installment of BASELINE, Novetta’s Machine Learning Newsletter, where we share thoughts on important advances in machine learning technologies likely to impact our customers. This month’s topics include: New open source translation models Synthetic audio generation Resources for learning about advances in machine learning Open Source Machine Translation To understand world events, analysts can’t rely solely on English-language news and social media. While the large cloud service providers (Amazon Web Services, Google Cloud Platform, Microsoft Azure) provide high-quality, easy-to-use translation APIs, the costs of API calls can add up. That is why we are excited about…
BASELINE – April 2020
An ML Newsletter from Novetta
Welcome to the April 2020 installment of BASELINE, Novetta’s Machine Learning Newsletter, where we share thoughts on important advances in machine learning technologies likely to impact our customers. This month’s topics include: Creative applications of synthetic data to improve model accuracy How deep learning may speed development of a COVID-19 vaccine A new deep learning approach to tabular data classification Kaggle Bengali competition winner Kaggle is a data science competition site that often sees competitors advance the state-of-the-art in different domains. We have found that Kaggle is one of the best places to identify creative new approaches to problems, and…
Redefining the Disaster Response Landscape with AWS
by Matt Johannessen Over the last six months, Novetta has had the privilege of collaborating closely with the AWS Snow Family and AWS Disaster Response teams. Working with AWS, we have integrated Novetta’s mission proven C4ISR solution, called Ageon ISR. With emerging IoT and Machine Learning capabilities, Ageon ISR is deployed on the rugged AWS Snowball Edge Compute Optimized device. The device acted as a computing and storage hub at the temporary incident command center at two different massive disaster response events. Novetta used the Snowball Edge device to successfully track the location personnel, vehicles, and equipment involved in the…
BASELINE – March 2020
An ML Newsletter from Novetta
Welcome to the March 2020 installment of BASELINE, Novetta’s Machine Learning Newsletter, where we share thoughts on important advances in machine learning technologies likely to impact our customers. This month’s topics include: AdaptNLP, an open source framework for state-of-the-art Natural Language Processing (NLP) A new competition for geospatial AI applications corresponding with the release of a Synthetic Aperture Radar (SAR) dataset A new and improved way of training language models StanfordNLP gets a new coat of paint Research into training large ML models with CPUs A new tool designed for rapid prototyping quantum machine learning models AdaptNLP At Novetta, we…
BASELINE – February 2020
An ML Newsletter from Novetta
Welcome to the February 2020 installment of BASELINE, Novetta’s Machine Learning Newsletter, where we discuss important advances in machine learning technologies and their potential impact on our IC / Defense customers. This month’s topics include: New breakthroughs in language models, including conversational AI Concise APIs that simplify model implementation Promising new approaches in computer vision and graph neural networks Meet Google’s Meena Google’s Meena has raised the bar for open-domain chatbots, achieving near-human-like interactions. Meena is a conversational model designed to chat sensibly about nearly any topic while taking into account the context of the conversation. In addition to Meena,…
BASELINE – January 2020
An ML Newsletter from Novetta
Welcome to the January 2020 installment of BASELINE, Novetta’s Machine Learning Newsletter, where we share thoughts on important advances in machine learning technologies likely to impact our customers. This month’s topics include: New software tools that improve the process of developing machine learning models Improvements in language models, with some research showing that synthetically generated text can fool human reviewers The “What-If Tool” and Manifold While the primary goal for most machine learning models is high accuracy, we also need to understand why the model is making certain predictions. We’ve recently been working with the What-If Tool from the Google…
IoT & Edge Computing for Disaster Response
by Matt Johannessen Recently, I had the opportunity to lead a Novetta team tasked with demonstrating how C4ISR, IoT, Machine Learning, and edge computing technologies can improve situational awareness for disaster response operations. Through our partnership, Amazon Web Services invited Novetta to participate in an event called Operation Convergent Response (OCR). OCR is an event hosted annually by Verizon & Nokia at the Guardian Centers facility in Perry, GA. The primary objective of OCR is to bring solution providers and first responder organizations together to demonstrate how emerging technologies can save lives. Unlike traditional technology trade shows, OCR is centered…
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