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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This Washington-Based AI Startup offers an Acceleration Platform

Octo ML Acceleration platform

OctoML is a Washington-based startup that offers an acceleration platform for deploying machine learning models and algorithms on the hardware. This platform primarily helps the engineering teams deploy the machine learning models seamlessly and with increased accuracy. The platform is built on an open-source Apache TVM compiler framework project. In the recent Series B funding rounds, OctoML raised $28 million, which takes the company’s total capital to around $47 million.

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

ManipulaThor

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 from NVIDIA, Stanford University and Microsoft Research propose Efficient Trillion-Parameter Language Model Training on GPU Clusters

In a paper by NVIDIA, Stanford University, and Microsoft Research, a research team has proposed a new parallelization schedule that improves throughput by more than 10 percent with a comparable memory footprint. The paper demonstrated that such strategies could be composed to achieve high aggregate throughput when training large models with nearly a trillion parameters. 

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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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[Paper Summary] Google AI proposes a Machine Learning Algorithm for teaching Agents to solve new tasks

Google algorithm graph

Google AI suggests an alternative, example-based control, which aims at teaching agents how to solve new tasks by providing examples of success. This is termed as recursive classification of examples (RCE). It does not rely on formulated reward functions, distance functions, or features. It instead just uses the examples of success.

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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)

Attention

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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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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Intel’s AI is helping NFL hopefuls to reach their full potential

Athlete

EXOS is piloting the use of Intel’s 3D Athlete Tracking (3DAT) technology to help the next generation of professional footballers reach their full potential. This year’s hopefuls risk feeling unprepared after coming off such a disruptive year and will need all the help they can get to achieve their goals. 3DAT is a computer vision […]

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Google AI, DeepMind and the University of Toronto introduce DreamerV2

dreamer-v2

It is the first Reinforcement Learning (RL) agent based on the world model to attain human-level success on the Atari benchmark. It includes the second generation of the Dreamer agent who learns behaviors entirely within a world model’s latent space […]

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Georgia Tech and Facebook AI researchers devise a new Tensor…

A recent study conducted jointly by the Georgia Institute and Facebook AI researchers has opened the door to a new method called TT-Rec (Tensor-Train for DLRM). If employed successfully, this method would be a leap forward in the arena of deep learning as it will significantly reduce the size of the Deep Learning Recommendation Models […]

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Biotech company combines Single Cell Genomics with Machine Learning

Immunai

Immunai is a biotech company using machine learning algorithms that combine single-cell genomics to empower the human immune system’s high-resolution profiling. Based out of New York, this company was established merely three years ago, but it is growing at a breakneck pace with the largest dataset in the world for single-cell immunity characteristics.

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Allen Institute For AI (AI2) Launches The 2.7.0 Version of AI2-THOR That Enables Users To Reduce Their Training Time Dramatically

AI2-THOR

Allen Institute for AI (AI2) has recently announced the 2.7.0 release of AI2-THOR. AI2-THOR is an open-source interactive environment for training and testing embodied AI. The 2.7.0 version of AI2-THOR contains several performance enhancements that can provide dramatic training time reductions. The new version introduces improvements to the IPC system between Unity/Python and serialization/deserialization format. It includes new actions that are much better to control the metadata. 

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