Fast-Tracking the Fight Against Covid: Researchers Validate AI-Generated Antivirals, Paving the Way for Rapid Drug Development in Future Crises

A recent study conducted by researchers at IBM and Oxford University revealed a breakthrough in antiviral drug development. The researchers utilized generative artificial intelligence (AI) to design novel molecules that have the potential to block the SARS-CoV-2 virus, which causes Covid-19. This approach proved successful, as the team identified four potential Covid-19 antivirals in a…

Read More

Researchers from the University of Toronto Introduce scGPT: A Foundation Model for Single-Cell Biology based on Generative Pre-Trained Transformer Across a Repository of Over 33 Million Cells

Natural language processing and computer vision are only examples of the fields where generative pre-trained models have succeeded incredibly. In particular, a viable strategy for constructing foundation models is to combine varied large-scale datasets with pre-trained transformers. The study investigates the feasibility of foundation models to further research in cellular biology and genetics by drawing…

Read More

Driven to driverless | MIT News

When Cindy Heredia was choosing an MBA program, she knew she wanted to be at the forefront of the autonomous driving industry. While doing research, she discovered that MIT had a unique offering: a student-run driverless team. Heredia applied to MIT to join the team, hoping to get hands-on experience. “My hope is that we’re…

Read More

Researchers from the University of Wisconsin and ByteDance Introduce PanoHead: The First 3D GAN Framework that Synthesizes View-Consistent Full Head Images with only Single-View Images

In computer vision and graphics, photo-realistic portrait image synthesis has been constantly emphasized, with a wide range of downstream applications in virtual avatars, telepresence, immersive gaming, and many other areas. Indistinguishable from genuine images, recent developments in Generative Adversarial Networks (GANs) have shown a remarkably high image synthesis quality. Contemporary generative methods, however, don’t model…

Read More

Scaling audio-visual learning without labels | MIT News

Researchers from MIT, the MIT-IBM Watson AI Lab, IBM Research, and elsewhere have developed a new technique for analyzing unlabeled audio and visual data that could improve the performance of machine-learning models used in applications like speech recognition and object detection. The work, for the first time, combines two architectures of self-supervised learning, contrastive learning…

Read More

Princeton Researchers Introduce InterCode: A Revolutionary Lightweight Framework Streamlining Language Model Interaction for Human-Like Language-to-Code Generation

ChatGPT, the latest chatbot developed by OpenAI, has been in the headlines ever since its release. This GPT transformer architecture-based model imitates humans by answering questions accurately just like a human, generates content for blogs, social media, research, etc., translates languages, summarizes long textual paragraphs while retaining the important key points, and even generates code…

Read More

UCLA Researcher Develops a Python Library Called ClimateLearn for Accessing State-of-the-Art Climate Data and Machine Learning Models in a Standardized and Straightforward Way

Extreme weather conditions have become a typical occurrence, especially in recent years. Climate change is the main factor to blame for such extreme weather-related phenomena, from the torrential downpours seen in Pakistan that have submerged large portions of the country under water to the exceptional heat waves that have fueled wildfires throughout Portugal and Spain….

Read More

This Artificial Intelligence-Based Protein Language Model Unlocks General-Purpose Sequence Modelling

The way people study the language of life has been fundamentally altered by comparing the syntax-semantics of natural languages and the sequence function of proteins. Although this comparison has inherent value when seen as a historical milestone that helped improve NLP’s application to the domain of proteins (such as language models), results from the area…

Read More