Tag: Technical blogs

Bayesian Online Meta-Learning (BOML) for continual & gradual learning

April 19, 2021 ResearchTechnical blogs

New project aims to create AI that can continually acquire knowledge in different domains as well as utilize past experiences to quickly adapt to new unseen tasks. 

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GoodAI enters into research collaboration to progress meta-learning and combinatorial generalization

April 14, 2021 ResearchTechnical blogs

Self-improving artificial intelligence that can learn new tasks from small amounts of data is a crucial step for the advancement of strong artificial intelligence.

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Creating a new framework for multi-agent AI systems

April 12, 2021 ResearchTechnical blogs

Current artificial intelligence is limited in its scope and is far from human-level intelligence. One of the key components missing is learning to pursue multiple goals, ones that are dynamic, changing, and that depend on knowledge acquired from previous tasks.

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A new kind of open-ended environment for a new kind of artificial intelligence

April 08, 2021 ResearchTechnical blogs

If we are to develop artificial intelligence (AI) capable of learning as humans do, it needs to be tested in complex environments just like humans are.

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My experiments with the evolutionary dynamics of sexual selection

January 11, 2021 ResearchTechnical blogs

GoodAI CEO Marek Rosa has been experimenting with the evolutionary dynamics of sexual selection. In this blog, he outlines some of his findings.

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Nature article – Artificial intelligence finds surprising patterns in Earth’s biological mass extinctions

December 09, 2020 ResearchTechnical blogs

The idea that mass extinctions allow many new types of species to evolve is a central concept in evolution, but a new study using artificial intelligence to examine the fossil record finds this is rarely true.

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Learning in Badger experts improves with episodic memory

October 23, 2020 ResearchTechnical blogs

AI agents often operate in partially observable environments, where only part of the environment state is visible at any given time. An agent in such an environment needs memory to compute effective actions from the history of its actions.

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Benefits of modular approach – generalization

August 09, 2020 ResearchTechnical blogs

One of the properties of the Badger architecture is modularity: instead of using one big neural network, the Badger should be composed of many small Experts which solve the whole task in a collaborative manner.

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Workshop on Collective Meta-Learning and the Benefits of Deliberation

June 08, 2020 ResearchTechnical blogs

GoodAI recently hosted a virtual workshop with a number of external collaborators in order to address some of the crucial open questions related to our Badger Architecture.

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Trainability of Badger – Why is Badger so hard to train?

To understand why Badger is hard to train, we need to understand first how Badger learns, using a toy task. We try to understand the plateaus, what happens during this period, and why the plateaus are there.

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