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Webinar: Using External Data to Accelerate Business in a Post-Vaccinated World

Join this webinar to learn how companies are developing insights to better prepare for growth opportunities, improve business performance and mitigate risk in a post-pandemic economy. Wednesday, June 24th, 2021 at 11:00 AM PT (2:00 PM ET)

AI Under the Hood: Object Detection Model Capable of Identifying Floating Plastic Beneath the Surface of the Ocean

A group of researchers, Gautam Tata, Sarah-Jeanne Royer, Olivier Poirion, and Jay Lowe, have written a new paper “DeepPlastic: A Novel Approach to Detecting Epipelagic Bound Plastic Using Deep Visual Models.” The workflow described in the paper includes creating and preprocessing a domain-specific data set, building an object detection model utilizing a deep neural network, and evaluating the model’s performance.

Mastercard’s Five Pillars of AI

Businesses are rushing to adopt AI — but they need to consider ethics right off the bat if they want to build trust and future-proof their business. This special report from Brighterion highlights how more than 60% of consumers consider brands more trustworthy if they think their use of AI is ethical — meaning today’s businesses must be able to demonstrate responsible AI as the technology becomes critical to the future of work.

2021 MLOps Platforms Vendor Analysis Report

The Neuromation team has just published a new report on the state of Machine Learning Operations Platforms in 2021. MLOps was defined as a separate discipline only recently when the ML practitioners moved from university labs to corporate boardrooms. AI and ML leaders today already have a better understanding of the MLOps lifecycle and the procedures and technology required for deploying new models into production and subsequently scaling them.

Video Highlights: Supercharging our Data Scientists’ Productivity at Netflix

In this talk sponsored by Tecton, Jan Forjanczyk, Senior Data Scientist, Netflix and Ravi Kiran Chirravuri, Software Engineer, Netflix, working in Content Demand Modeling, present one of the challenges that they faced earlier this year. This is used as a backdrop to present the human-centric design principles that govern the design of Metaflow and its internals.

Video Highlights: Challenges of Operationalizing ML

In the panel discussion below, the focus is on the main challenges of building and deploying ML applications. The discussion includes common pitfalls, development best practices, and the latest trends in tooling to effectively operationalize. The presentation comes from apply(): The ML Data Engineering Conference sponsored by Tecton.

Why 3D is the Key to Unlocking Vital Video Surveillance Data

In this contributed article, Srinath Kalluri, CEO of Oyla, suggests that by blending AI, 3D and video analytics, businesses will be able to bring better information to big data and enable smarter and safer ways of working.

Quantum Machine Learning – An Introduction to QGANs

In this contributed article, data scientists from Sigmoid discuss quantum machine learning and provide an introduction to QGANs. Quantum GANs which use a quantum generator or discriminator or both is an algorithm of similar architecture developed to run on Quantum systems. The quantum advantage of various algorithms is impeded by the assumption that data can be loaded to quantum states. However this can be achieved for specific but not generic data.

Despite Data’s Importance, More than a Third of Business Leaders Don’t Use It for Critical Decisions

Talend (NASDAQ: TLND), a global leader in data integration and integrity, released the results of a survey1 that highlighted the challenges businesses face in becoming data-driven organizations and the solutions to these challenges. It’s clear that business leaders know how important data is — two-thirds report that they use data every day.

Best of arXiv.org for AI, Machine Learning, and Deep Learning – April 2021

In this recurring monthly feature, we will filter all the recent research papers appearing in the arXiv.org preprint server for subjects relating to AI, machine learning and deep learning – from disciplines including statistics, mathematics and computer science – and provide you with a useful “best of” list for the month.