A new technique for maximizing control over animations has been developed by researchers at MIT. The technique offers animators the ability to mold the movements and image of characters in 2D and 3D animations to their individual requirements, through the use of barycentric coordinates, mathematical functions that determine how shapes flex, bend and move in…
MIT researchers have leveraged the power of deep learning, a branch of artificial intelligence (AI), to discover a class of compounds that can potentially kill methicillin-resistant Staphylococcus aureus (MRSA). The discovery, described in a paper published in the journal Nature, saw the use of AI to predict the antibiotic potency of various molecules, an insight…
In 2023, MIT had an eventful year, including the inauguration of President Sally Kornbluth and a Commencement address by Mark Rober, as well as Professor Moungi Bawendi winning a Nobel Prize for research on quantum dots. Researchers were also involved in several scientific breakthroughs, such as a study on a dying star consuming a planet,…
Neuroscientists at MIT, assisted by an artificial language network, have discovered that complex sentences with unusual grammar or unexpected meaning, stimulate the brain's key language processing centres more effectively. Interestingly, both straightforward sentences and nonsensical sequences of words had minimal engagement in these regions.
The findings were part of a study led by MIT graduate…
Cohere AI, a leading enterprise AI platform, recently announced the release of the Cohere Toolkit intended to spur the development of AI applications. The toolkit integrates with a variety of platforms including AWS, Azure, and Cohere's own network and allows developers to utilize Cohere’s models, Command, Embed, and Rerank.
The Cohere Toolkit comprises of production-ready applications…
Scientific Machine Learning (SciML) is an emerging discipline that leverages machine learning (ML), data science, and computational modeling, thereby ushering in a new era of scientific discovery. Offering rapid processing of vast datasets, SciML drives innovation by reducing the time between hypothesis generation and experimental validation. This greatly benefits fields such as pharmacology where the…
Large Language Models (LLMs) are a critical component of several computational platforms, driving technological innovation across a wide range of applications. While they are key for processing and analyzing a vast amount of data, they often face challenges related to high operational costs and inefficiencies in system tool usage.
Traditionally, LLMs operate under systems that activate…
The 2024 Zhongguancun Forum in Beijing introduced Vidu, an advanced AI model developed by ShengShu-AI and Tsinghua University. Vidu is capable of generating 16-second 1080p video clips from a simple prompt, marking a notable milestone in generative AI technologies coming from China. This innovative AI model is poised to compete with OpenAI's Sora.
Vidu uses Universal…
Reinforcement Learning (RL) is a method of learning that engages an agent with its environment to gather experiences and maximize received rewards. Given the policy rollouts necessary in the experience collection and improvement process, this is known as online RL. However, these online interactions required by both on-policy and off-policy RL can be impractical due…
Training vision-language models (VLMs) traditionally requires centralized aggregation of large datasets, a process that raises issues of privacy and scalability. A recent solution to this issue is federated learning, a methodology allowing models to train across a range of devices while maintaining local data. However, adapting VLMs to this framework presents its challenges. Intel Corporation…
Large Language Models (LLMs) are integral to the development of chatbots, which are becoming increasingly essential in sectors such as customer service, healthcare, and entertainment. However, evaluating and measuring the performance of different LLMs can be challenging. Developers and researchers often struggle to compare capabilities and outcomes accurately, with traditional benchmarks often falling short. These…
Researchers at the Massachusetts Institute of Technology (MIT) have developed a technique that enables digital artists more versatility in how they move their animations of 2D and 3D shapes. Traditionally, artists had limited choices when it came to defining movements using mathematical functions known as barycentric coordinates.
The researchers suggest that existing solutions are rigid and…
