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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”.

Simple, Distributed, and Accelerated Probabilistic Programming

Simple, Distributed, and Accelerated Probabilistic Programming This directory contains reference code for the NIPS 2018 paper, "Simple, Distributed, and Accelerated Probabilistic Programming". It's organized as follows: *.py: Edward2, an implementation of the idea. Companion.ipynb: Jupyter notebook which expands on the paper's code snippets and examples. no_u_turn_sampler/: Example implementation of the No-U-Turn Sampler. The implementation, Edward2, [...]

The trouble with Smart Contracts

The government of Tennessee now officially recognizes Smart Contracts. That’s great news if we speak in terms of the publicity blockchain will receive. By virtue of such events, the Blockchain technology and all that’s related to it are drawing closer to becoming a standard way of how things work. However, the practice shows that the [...]

Facebook launches Horizon, its first open source reinforcement learning platform for...

Facebook launched Horizon, its first open source reinforcement learning platform for large-scale products and services, yesterday. The workflows and algorithms in Horizon have been built on open source frameworks such as PyTorch 1.0, Caffe2, and Spark. This is what makes Horizon accessible to anyone who uses RL at scale. “We developed this platform to bridge [...]

DeepMind open sources TRFL, a new library of reinforcement learning building...

The DeepMind team announced yesterday that they’re open sourcing a new library, named TRFL, that comprises useful building blocks for writing reinforcement learning (RL) agents in TensorFlow. The TRFL library was created by the research engineering team at DeepMind. TRFL library is a collection of key algorithmic components that are used for a large number [...]

Stable version of OpenZeppelin 2.0, a framework for smart blockchain contracts,...

Early last month, the team at OpenZepplin announced their first release candidate ‘OpenZepplin 2.0 RC1’. Yesterday, the team released a completely stable, audited, and fully tested package of this framework. OpenZeppelin is an open-source framework to build secure smart contracts for Ethereum and other EVM and eWASM blockchains. This framework provides well tested and audited code [...]

Knowledge representation and reasoning

Knowledge representation and reasoning (KR, KR², KR&R) is the field of artificial intelligence (AI) dedicated to representing information about the world in a form...

Multi-agents environments and adversarial self-play in Unity

There are various novel training strategies that we can employ with multiple agents and/or brains in an environment, from adversarial and cooperative self-play to imitation and curriculum learning. In this tutorial, we will look at how to build multi-agent environments in Unity as well as explore adversarial self-play. This tutorial is an excerpt taken from [...]

Microsoft showcases its edgy AI toolkit at Connect(); 2017

At the ongoing Microsoft Connect(); 2017, Microsoft has unveiled their latest innovations in AI development platforms. The Connect(); conference this year is all about developing new tools and cloud services that help developers seize the growing opportunity around artificial intelligence and machine learning. Microsoft has made two major announcements to capture the AI market. Visual [...]