Google powers YouTube with its own Video-Transcoding Chips

Google AI chip

YouTube is the world’s most popular video-sharing platform. Keeping it going was once thought to be difficult before Google purchased it in 2006. Since then, Google has fought hard to keep the site’s costs down, often reinventing Internet technology and copyright to do so. The primary infrastructure issue that YouTube must address for end-users today is delivering content optimized for your platform and bandwidth while ensuring efficiency.

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Google announces the general availability of Vertex AI to expedite the development and maintenance of Artificial Intelligence (AI) Models

Google Vertex

Data scientists, every day, face manually stitching together Machine Learning point solutions and finding anomalies, resulting in a lag in model creation and experimentation, hence reducing the production level. To address these issues, Google announced Vertex AI, a managed machine learning platform meant to expedite the development and maintenance of artificial intelligence (AI) models to be generally available.

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Project Starline by Google promises to usher in a new era of Video Conferencing with 3D Display

Project Starline - 3D display

Human beings are social animals who like to connect with their counterparts in one way or another. While we have reached significant milestones in the arena of technology, communication remains a considerable roadblock. An entire plethora of video conferencing platforms like Zoom, Google Meet, Teams, among significant others, have been made available to the masses and are in constant use, especially due to the pandemic. However, all of them are far behind the actual face-to-face talking experience, thereby offering only limited connectivity.

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[Paper] Facebook AI releases Dynaboard: A New Evaluation platform for NLP Models

Last year, Facebook AI released Dynabench, a platform that radically rethinks benchmarking in AI, starting with natural language processing (NLP) models. Going forward, they have now announced a new evaluation-as-a-service platform for comprehensive, standardized evaluations of NLP models called Dynaboard. Dynaboard can perform apples-to-apples comparisons dynamically without common issues from bugs in evaluation code, inconsistencies in filtering test data, backward compatibility, accessibility, and several other reproducibility issues.

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Europe’s Technology Industry saw a rise of 26.76% in Artificial Intelligence deal activity in Q1 2021

EU brain

Led by $1.6bn acquisition of Yandex, Europe’s technology industry saw a rise of 26.76% in artificial intelligence deal activity during Q1 2021, when compared to the last four-quarter average, according to GlobalData’s deals database. A total of 212 artificial intelligence deals worth $5.05bn were announced for the region during Q1 2021, against the last four-quarter average of 167.25 deals.

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[Paper Summary] Researchers From Allen Institute for AI releases AI2-THOR 3.0


The Allen Institute for AI (AI2) announces the release of AI2-THOR 3.0, which is an embodied AI framework. Embodied Artificial Intelligence is a sub-specialty of artificial intelligence at the intersection of robotics, computer vision, and natural language processing and is an emerging area of interest for researchers.

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[Paper Summary] Researchers at ETH Zurich and UC Berkeley Propose Deep Reward Learning by Simulating The Past (Deep RLSP)

In a new research paper, a research team from ETH Zurich and UC Berkeley have proposed ‘Deep Reward Learning by Simulating the Past’ (Deep RLSP). This new algorithm represents rewards directly as a linear combination of features learned through self-supervised representation learning. It enables agents to simulate human actions “backward in time to infer what they must have done.

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Researchers from DeepMind and Alberta University propose policy-guided Heuristic search Algorithm

DeepMind’s AlphaGo and its successors previously demonstrated that the policy and heuristic function is formulated upon the PUCT (Polynomial Upper Confidence Trees) search algorithm. This algorithm can be quite effective for guiding search in adversarial games. However, PUCT is computationally inefficient and lacks guarantees on its search effort. Though other methods such as LevinTS provide guarantees on search steps, they do not use a heuristic function.

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Google AI introduces a new system for Open-Domain Long-Form Question Answering (LFQA)


Open-domain long-on answering (LFQA) form questions a fundamental challenge in natural language processing (NLP) that involves retrieving documents relevant to a given query and using them to generate a detailed paragraph-length answer. 

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[Paper Summary] Researchers at the University Of Genoa and AWS analyze techniques to Make Machine Learning (ML) Models fairer

AI fair or unfair

This research on algorithmic fairness provides three main approaches, i.e., pre-processing data, post-processing an already learned ML model, and in-processing, which consists of enforcing fairness notions by imposing specific statistical constraints on the learning phase of the model.

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Applying Machine Learning-anchored computation to Enhance Drug discovery and development

Drug development AI console

Valo Health is a drug development company headquartered in Boston, Massachusetts, the United States, which uses human-centric data and machine learning to strengthen and boost the process of drug discovery and its development to promote intelligent health. The Opal Computational Platform by utilizes…

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Utilizing AI for the Protection of Service Members and Civilians through unmanned Self-Driving Software

Autonomous console

Shield AI is a California-based startup employing artificial intelligence to develop products that offer protection for service members and civilians. It is primarily a defense technology organization that uses self-driving software, enabling the unmanned systems to operate smoothly even without the availability of GPS or any other form of communication.

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