CSAIL (Computer Science and Artificial Intelligence Laboratory) is a research laboratory located at the Massachusetts Institute of Technology (MIT) in Cambridge, Massachusetts, USA. It is one of the largest and most prestigious computer science research centers in the world, with over 1,000 researchers, faculty members, and students.
CSAIL is dedicated to advancing the field of computer science and artificial intelligence through cutting-edge research, innovation, and education. It conducts research in a wide range of areas, including robotics, machine learning, natural language processing, computer vision, and cybersecurity.
On SciTechDaily.com, you can find the latest news and breakthroughs in computer science and artificial intelligence research conducted by CSAIL researchers, such as advancements in robotics, new breakthroughs in natural language processing, and the latest developments in machine learning.
“Lightning” system connects photons to the electronic components of computers using a novel abstraction, creating the first photonic computing prototype to serve real-time machine-learning inference…
SoftZoo is a soft robot co-design platform that can test optimal shapes and sizes for robotic performance in different environments. Since the term “soft robotics”…
MIT researchers develop “FrameDiff,” a computational tool that uses generative AI to craft new protein structures, with the aim of accelerating drug development and improving…
This AI system only needs a small amount of data to predict molecular properties, which could speed up drug discovery and material development. Discovering new…
MIT’s new system analyzes the likelihood that an attacker could thwart a certain security scheme to steal secret information. Researchers have created a system to…
By applying a language model to protein-drug interactions, researchers can quickly screen large libraries of potential drug compounds. Huge libraries of drug compounds may hold…
Using insights into how people intuit others’ emotions, researchers have designed a model that approximates this aspect of human social intelligence. When interacting with another…
Selecting the right method gives users a more accurate picture of how their model is behaving, so they are better equipped to correctly interpret its…
Researchers develop an algorithm that decides when a “student” machine should follow its teacher, and when it should learn on its own. Someone learning to…
The system they developed eliminates a source of bias in simulations, leading to improved algorithms that can boost the performance of applications. MIT researchers have…
By mapping the volumes of objects, rather than their surfaces, a new technique could yield solutions to computer graphics problems in animation and CAD. MIT…
Researchers find that models trained using common data-collection techniques judge rule violations more harshly than humans would. Machine-learning models often make harsher judgments than humans…
A new method developed by researchers uses multiple models to create more complex images with better understanding. With the introduction of DALL-E, the internet had…
MIT researchers unveil the first open-source simulation engine capable of constructing realistic environments for deployable training and testing of autonomous vehicles. Since they’ve proven to…
Robots manipulate soft, deformable material into various shapes from visual inputs in a new system that could one day enable better home assistants. Many of…
The system rapidly scans the genome of cancer cells and could help scientists find targets for new drugs. Cancer cells can have thousands of DNA…
Q&A: MIT’s Neil Thompson on Computing Power and Innovation Innovation in many industries has been fueled by rapid increases in the speed and power of…
According to a new study, explanation methods that help users determine whether to trust machine-learning model predictions can be less accurate for disadvantaged subgroups. Machine-learning…
