Summary: Researchers in China have developed a new neural network that generates high-quality bird images from textual descriptions using common-sense knowledge to enhance the generated image at three different levels of resolution, achieving competitive scores with other neural network methods. The network uses a generative adversarial network and was trained with a dataset of bird images and text descriptions, with the goal of promoting the development of text-to-image synthesis.

Source: Intelligent Computing.

In an effort to generate high-quality images based on text descriptions, a group of researchers in China built a generative adversarial network that incorporates data representing common-sense knowledge.

An exploration of Machine Natural Selection and the potential of an AI Apocalypse.

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In a paper published in March, artificial intelligence (AI) scientists at Stanford University and Canada’s MILA institute for AI proposed a technology that could be far more efficient than GPT-4 — or anything like it — at gobbling vast amounts of data and transforming it into an answer.

Also: What is GPT-4? Here’s everything you need to know

Known as Hyena, the technology is able to achieve equivalent accuracy on benchmark tests, such as question answering, while using a fraction of the computing power. In some instances, the Hyena code is able to handle amounts of text that make GPT-style technology simply run out of memory and fail.

A recent study conducted at the University of Turku in Finland shows that different people have similar brain activity when perceiving social situations. Researchers discovered an extensive neural network in the human brain that effectively processes various social information.

Social interaction is central to all aspects of human life. Interaction requires the perception and interpretation of the social environment as well as flexible reacting to other people’s behavior. The human brain is capable of such perception and decision-making automatically and rapidly. However, the social information processing mechanisms of the brain remain unresolved.

The study conducted at the Turku PET Centre revealed an extensive neural network in the human brain that processes various social information. The study showed that the social perceptual world of humans consists of a limited set of main dimensions, such as antisocial behavior, sexual or affiliative behavior, and communication. These social dimensions are processed in various brain regions located mainly in the back of the brain, more specifically in the occipital and temporal lobes.

Microsoft has been secretly developing the chips since 2019.

Microsoft is reportedly working on its own AI chips to train complex language models. The move is thought to be intended to free the corporation from reliance on Nvidia chips, which are in high demand.

Select Microsoft and OpenAI staff members have been granted access to the chips to verify their functionality, The Information reported on Tuesday.