Accelerating ML within CNN

At CNN, our mission is to inform, engage, and empower the world in a way that is trusted, timely, and transparent. This mission is more critical than ever as we face some of the most challenging times of our generation. As the world is becoming increasingly digital in nature, we are relentlessly focusing our mission to directly connect with our audience, understand what they care about most, and reach them in a way that is most accessible for their lifestyle. Our Data Intelligence team, in particular, leverages data and machine-learning capabilities to build innovative experiences for our audience and provides scalable solutions to CNN’s operations. As the world’s largest digital news destination, we averaged more than 200 million unique global visitors every month of 2020. Our catalog of raw audio and video footage also goes back several decades. Clearly, we have a lot of data!

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Why Board Directors And CEOs Need To Learn AI Knowledge Foundations: Building AI Leadership Brain Trust Is A Business Imperative: Are You Ready?

Why Fortune 1000 Leaders need to build AI Brain Trust? In reviewing over 200 board of director compositions on the Fortune 1000, many of them do not have sufficient technology depth and knowledge expertise. The majority have operations knowledge particular in finance, legal and have often held a CEO or high profiled leadership role in a prior company. The major of larger companies all have a technology strategy and risk committee working with their CIO and Cybersecurity or Risk officers, but if you look across the broader board director skill knowledge on the depth of AI and digital transformation leadership skills and solid execution experiences, you will find less relevant and current knowledge know-how.

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Exscientia nets $225 million in latest funding round


Exscientia, a clinical stage pharmatech company using artificial intelligence (AI) to design patient-based drugs, announced that it has completed a $225 million Series D funding round. SoftBank Vision Fund 2i led the Series D and was joined by previous round lead investors, Novo Holdings and funds managed by Blackrock. Other investors included Mubadala Investment Company, Farallon Capital, Casdin Capital, GT Healthcare Capital, Marshall Wace, Pivotal bioVenture Partners, Laurion Capital, Hongkou and Bristol-Myers Squibb. In addition, SoftBank is providing an additional $300 million equity commitment that can be drawn at the Company’s discretion.

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Reinforcement Learning for 3D Molecular Design

In this blog post, we will outline how we combine ideas from reinforcement learning and quantum chemistry to catalyse the search for new molecules. We will explain how we can push the boundaries of the type of molecules we can build by representing the atoms directly in Cartesian coordinates. Finally, we will demonstrate how we can exploit symmetries of the design process to efficiently train a reinforcement learning agent for molecular design.

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10 teams selected to receive funding for MVP phase of 2021 Nittany AI Challenge

Ten student teams will be funded to compete in the final phase of the 2021 Nittany AI Challenge. Each team will be awarded $1,500 from a prize pool of $50,000 to further develop solutions that address real-world challenges in education, environment, health and humanitarianism and create a minimum viable product (MVP).

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How Merck works with Seeqc to cut through quantum computing hype

Merck - Seeqc lab

When it comes to grappling with the future of quantum computing, enterprises are scrambling to figure just how seriously they should take this new computing architecture. Many executives are trapped between the anxiety of missing the next wave of innovation and the fear of being played for suckers by people overhyping quantum’s revolutionary potential. That’s why the approach to quantum by pharmaceutical giant Merck offers a clear-eyed roadmap for other enterprises to follow.

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Abbott’s new coronary imaging platform powered by Artificial Intelligence launches in Europe

Coronary imaging

To give clinicians a quick, cross-sectional look into potential blockages of the heart’s major arteries, Abbott has combined digital imaging technology with artificial intelligence to build an automated system for cardiac procedures. he company’s Ultreon software relies on catheters equipped with optical coherence tomography, which uses laser light to scan the interior of a blood vessel and the immediately surrounding tissues to detect calcium and plaque deposits, while also instantly measuring the diameter of an artery.

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AppTek Expands its workbench Data Labeling and Annotation Platform to include Labeling for Computer Vision and Multimodal AI Models at Scale

Apptek platform

AppTek, a leader in Artificial Intelligence (AI), Machine Learning (ML), Automatic Speech Recognition (ASR), Neural Machine Translation (NMT), Text-to-Speech (TTS) and Natural Language Processing / Understanding (NLP/U) technologies, today announced the expansion of its Workbench data labeling and annotation platform to include video labeling capabilities for computer vision models, in addition to its industry-leading ASR, NMT, TTS, and NLP/U data services.

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Europe – commission legal framework on Artificial Intelligence could impact Talent Acquisition and Assessment

European Union

The European Commission is proposing the first ever legal framework on Artificial Intelligence, which addresses the risks of AI and aims to develop an ecosystem of trust around AI. The proposal is based on EU values and fundamental rights and aims to give people the confidence to embrace AI-based solutions, while encouraging businesses to develop them.

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This new tool can track the Environmental Cost of your Machine Learning Model


Energy consumption is a major factor to plan for when implementing a long-term project or service that uses large-scale machine learning algorithms. Now, a team of researchers from Georgia Tech has created an interactive tool called EnergyVis that allows users to compare energy consumption across locations and against other models. 

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