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Artificial intelligence (AI, also machine intelligence, MI) is intelligence demonstrated by machines, in contrast to the natural intelligence (NI) displayed by humans and other animals. In computer science AI research is defined as the study of “intelligent agents”: any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals. Colloquially, the term “artificial intelligence” is applied when a machine mimics “cognitive” functions that humans associate with other human minds, such as “learning” and “problem solving”.

Math shows neurons work in organized ‘cliques’

A new mathematical method can detect geometric structure in neural activity in the brain. “Previously, in order to understand this structure, scientists needed to relate neural activity to some specific external stimulus,” says Vladimir Itskov, associate professor of mathematics at Penn State. “Our method is the first to be able to reveal this structure without [...]

Open sourcing TRFL: a library of reinforcement learning building blocks

Today we are open sourcing a new library of useful building blocks for writing reinforcement learning (RL) agents in TensorFlow. Named TRFL (pronounced ‘truffle’), it represents a collection of key algorithmic components that we have used internally for a large number of our most successful agents such as DQN, DDPG and the Importance Weighted Actor [...]

Relational inductive biases, deep learning, and graph networks

Artificial intelligence (AI) has undergone a renaissance recently, making major progress in key domains such as vision, language, control, and decision-making. This has been...

Introducing the Azure Blockchain Development Kit

Over four decades, we’ve lowered barriers to development with developer tooling, enterprise integration, DevOps, PaaS, and SaaS. Today, serverless offerings from Functions and Logic Apps to Azure DevOps and IoT Central remove friction for development in the cloud. This morning, we’re excited to announce the initial release of the Azure Blockchain Development Kit which is [...]

TensorFlow AutoGraph

Google open sources BERT, an NLP pre-training technique

Google open-sourced Bidirectional Encoder Representations from Transformers (BERT) last Friday for NLP pre-training. Natural language processing (NLP) consists of topics like sentiment analysis, language translation, question answering, and other language-related tasks. Large datasets for NLP containing millions, or billions, of annotated training examples is scarce. Google says that with BERT, you can train your own [...]

BabyAI: A research platform for grounded language learning with human in...

Last week, researchers from the University of Montreal, University of Oregon, and IIT Bombay published a paper, titled, ‘BabyAI: First Steps Towards Grounded Language Learning With a Human In the Loop’ that introduces, BabyAI platform. This platform provides a heuristic expert agent for the purpose of simulating a human teacher and also supports humans in [...]

TGM: PyTorch Geometry

Documentation The PyTorch Geometry package is a geometric computer vision library for PyTorch. It consists of a set of routines and differentiable modules to solve generic...

OpenAI launches Spinning Up, a learning resource for potential deep learning...

OpenAI released Spinning Up yesterday. It is an educational resource for anyone who wants to become a skilled deep learning practitioner. Spinning Up has many examples in reinforcement learning, documentation, and tutorials. The inspiration to build Spinning Up comes from OpenAI Scholars and Fellows initiatives. They observed that it’s possible for people with little-to-no experience [...]