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 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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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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Using Algorithms derived From Neuroscience research, Numenta demonstrates 50x speed improvements on Deep Learning Networks

Numenta has made some advances by applying a principle of the brain called sparsity. It compared sparse networks and dense networks by running its algorithms on Xilinx FPGAs (Field Programmable Gate Array) for a speech recognition task that used the Google Speech Commands (GSC) dataset.

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Embold: Static Code Analyzer uses AI to help Developers analyze and improve their code

Embold is a simple but efficient AI-based static code analyzer that can help developers analyze and improve their code. The feature that truly makes it stand apart is its ability to analyze source code across four dimensions: code issues, design issues, metrics and duplication, and surface issues that impact stability, robustness, security, and maintainability.

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Intel to acquire SigOpt, an AI Hyperparameter Optimization Platform

Intel has confirmed that it is buying SigOpt Inc., an artificial intelligence startup developing software platforms to optimize AI models. Several private firms and research groups such as OpenAI use these software platforms to boost their AI models’ performance.

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Microsoft introduces Lobe: A free Machine Learning application that allows you to create AI Models without coding

Microsoft has released Lobe, a free desktop application that lets Windows and Mac users create customized AI models without writing any code. Several customers are already using the app for tracking tourist activity around coral reefs, the company said.

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