What is DrQ Algorithm by NYU & Facebook AI Research

New York University (NYU) & Facebook Artificial Intelligence Research (FAIR) researchers, including Denis Yarats, Rob Fergus, Alessandro Lazaric, Lerrel Pinto, have introduced DrQ-v2, a model-free reinforcement learning (RL) algorithm for visual continuous control. DrQ-v2 is an upgraded version of DrQ, an off-policy actor-critic approach that uses data augmentation to learn directly from pixels. 

 

Read more: https://analyticsindiamag.com/what-is-drq-algorithm-by-nyu-facebook-ai-research/

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What is DrQ Algorithm by NYU & Facebook AI Research
Otho  Hagenes

Otho Hagenes

1619511840

Making Sales More Efficient: Lead Qualification Using AI

If you were to ask any organization today, you would learn that they are all becoming reliant on Artificial Intelligence Solutions and using AI to digitally transform in order to bring their organizations into the new age. AI is no longer a new concept, instead, with the technological advancements that are being made in the realm of AI, it has become a much-needed business facet.

AI has become easier to use and implement than ever before, and every business is applying AI solutions to their processes. Organizations have begun to base their digital transformation strategies around AI and the way in which they conduct their business. One of these business processes that AI has helped transform is lead qualifications.

#ai-solutions-development #artificial-intelligence #future-of-artificial-intellige #ai #ai-applications #ai-trends #future-of-ai #ai-revolution

Aileen  Jacobs

Aileen Jacobs

1597245602

Researchers Claim Inconsistent Model Performance In Most ML Research

The process of benchmarking is considered to be one of the most crucial assets for the progress of AI and machine learning research. The benchmark datasets are usually fixed sets of data, which are manually, semi-automatically as well as automatically generated to form a representative sample for these specific tasks to be solved by a model.

Recently, researchers from the Institute for Artificial Intelligence and Decision Support, Vienna claimed that the considerable part of metrics currently used to evaluate classification AI benchmark tasks might be inconsistent. It may result in a poor reflection in the performance of a classifier, especially when used with imbalanced datasets.

For the research, they analysed the present aspect of performance metrics that are based on data covering more than 3500 ML model performance results from a web-based open platform.

#developers corner #ai research benchmark #ai research papers #benchmark #benchmarking ai #bias in ml research #inconsistent benchmark

AI Algorithm From Facebook Can Play Chess & Poker With Equal Ease

The researchers at Facebook believe that this algorithm will have real-world applications, including dealing with negotiations, fraud detection, and even #cybersecurity
https://zcu.io/Fhs6

#chess #poker #facebook #research #technews #ai

Alice Cook

Alice Cook

1614750304

How can I create a Poll on Facebook?

How do I start or create or post a Poll on Facebook? Know the ways to add options or make a poll on Facebook Page or Messenger.

make a poll on Facebook
add options to Facebook Poll

#how can i create a poll on facebook #create a poll on facebook #how to make a poll on facebook #how to do a poll on facebook #poll on facebook #create poll on facebook

Elton  Bogan

Elton Bogan

1602338400

Facebook Is Giving Away This Speech Recognition Model For Free

Researchers at Facebook AI recently introduced and open-sourced a new framework for self-supervised learning of representations from raw audio data known as wav2vec 2.0. The company claims that this framework can enable automatic speech recognition models with just 10 minutes of transcribed speech data.

Neural network models have gained much traction over the last few years due to its applications across various sectors. The models work with the help of vast quantities of labelled training data. However, most of the time, it is challenging to gather labelled data than unlabelled data.

The current speech recognition systems require thousands of hours of transcribed speech to reach acceptable performance. There are around 7,000 languages in the world and many more dialects. It can be said that the availability of the transcribed speech for a vast majority of languages is still negative.

To mitigate such issues, researchers open-sourced the wave2vec framework. The framework has the capability to make efficient development in Automatic Speech Recognition (ASR) for the low-resource languages.).

#developers corner #facebook ai #facebook ai research #speech recognition algorithm