Facebook to Create a Dataset to Train Dialogue AI

The dataset includes 5 million characters and 700 million dialogues
19 September 2018   506

Researchers from Facebook created a set of training data to improve the effectiveness of neural networks training, specializing in communicating with live users. It includes 5 million characters and 700 million dialogues.

Persona-based network architecture
Persona-based network architecture

In the basis of the software, developers have put a set of PERSONA-CHAT, developed jointly by Facebook experts and scientists from the Montreal Institute of Learning Algorithms. First of all, the increase in the volume of data is notable - the basic data-set contained only about a thousand personalities. But researchers are paying attention to a more important aspect. The PERSONA-CHAT content was created artificially, and the new set was formed on the basis of the Reddit user dialogues.

An interactive neural network, trained on a new set of data, leads more engaging dialogues than networks that did not have access to a collection of personalities. Moreover, the training of systems based on the characters is faster.

Choosing the right data set for learning artificial intelligence is one of the key tasks for developers. The accuracy and productivity of the software being created depends on it. In September 2018, Google in the test mode launched a special tool to find suitable collections.

OpenAI to Create Fake News Creating Algorithm

On the basis of one or two phrases that set the theme, it is able to “write” a fairly plausible story
18 February 2019   165

The GPT-2 algorithm, created by OpenAI for working with language and texts, turned out to be a master in creating fake news. On the basis of one or two phrases that set the theme, it is able to “compose” a fairly plausible story. For example:

  • an article about scientists who have found a herd of unicorns in the Andes;
  • news about pop star Miley Cyrus caught on shoplifting;
  • artistic text about Legolas and Gimli attacking the orcs;
  • an essay on how waste recycling harms the economy, nature, and human health.

The developers did not publish the source code of the model entirely, fearing abuse by unscrupulous users. For fellow researchers, they posted on GitHub a simplified version of the algorithm and gave a link to the preprint of the scientific article. The overall results are published on the OpenAI blog.

GPT-2 is a general purpose algorithm. The developers taught it to answer questions, “understand” the logic of a text, a sentence, finish building phrases. In this case, the algorithm worked worse than the model of a specific purpose. Researchers suggest that the indicators can be improved by expanding the training datasets and choosing computers more efficiently.