Archives des Computer Science and Artificial Intelligence Laboratory (CSAIL)

Using generative AI to diversify virtual training grounds for robots
9 Oct
AI maps how a new antibiotic targets gut bacteria
9 Oct
Responding to the climate impact of generative AI
9 Oct
New AI system could accelerate clinical research
9 Oct
What does the future hold for generative AI?
9 Oct
How to build AI scaling laws for efficient LLM training and budget maximization
9 Oct
Machine-learning tool gives doctors a more detailed 3D picture of fetal health
9 Oct
A greener way to 3D print stronger stuff
9 Oct
MIT researchers develop AI tool to improve flu vaccine strain selection
9 Oct
Researchers glimpse the inner workings of protein language models
9 Oct
MIT tool visualizes and edits “physically impossible” objects
9 Oct
New algorithms enable efficient machine learning with symmetric data
9 Oct
Robot, know thyself: New vision-based system teaches machines to understand their bodies
9 Oct
A new way to edit or generate images
9 Oct
The unique, mathematical shortcuts language models use to predict dynamic scenarios
9 Oct
Can AI really code? Study maps the roadblocks to autonomous software engineering
9 Oct
AI shapes autonomous underwater “gliders”
9 Oct
Study could lead to LLMs that are better at complex reasoning
9 Oct
Using generative AI to help robots jump higher and land safely
9 Oct
Researchers present bold ideas for AI at MIT Generative AI Impact Consortium kickoff event
9 Oct
Unpacking the bias of large language models
9 Oct
Envisioning a future where health care tech leaves some behind
9 Oct
Teaching AI models what they don’t know
9 Oct
Teaching AI models the broad strokes to sketch more like humans do
9 Oct
AI learns how vision and sound are connected, without human intervention
9 Oct
Study shows vision-language models can’t handle queries with negation words
9 Oct
Hybrid AI model crafts smooth, high-quality videos in seconds
9 Oct
Novel AI model inspired by neural dynamics from the brain
9 Oct
Making AI models more trustworthy for high-stakes settings
9 Oct
The MIT-Portugal Program enters Phase 4
9 Oct
“Periodic table of machine learning” could fuel AI discovery
9 Oct
3D modeling you can feel
9 Oct
Making AI-generated code more accurate in any language
9 Oct
Training LLMs to self-detoxify their language
9 Oct
New method efficiently safeguards sensitive AI training data
9 Oct
Could LLMs help design our next medicines and materials?
9 Oct
New method assesses and improves the reliability of radiologists’ diagnostic reports
9 Oct
For this computer scientist, MIT Open Learning was the start of a life-changing journey
9 Oct
At the core of problem-solving
9 Oct
Robotic helper making mistakes? Just nudge it in the right direction
9 Oct
Like human brains, large language models reason about diverse data in a general way
9 Oct
AI model deciphers the code in proteins that tells them where to go
9 Oct

Using generative AI to diversify virtual training grounds for robots

AI maps how a new antibiotic targets gut bacteria

Responding to the climate impact of generative AI

New AI system could accelerate clinical research

What does the future hold for generative AI?

How to build AI scaling laws for efficient LLM training and budget maximization

Machine-learning tool gives doctors a more detailed 3D picture of fetal health

A greener way to 3D print stronger stuff

MIT researchers develop AI tool to improve flu vaccine strain selection

Researchers glimpse the inner workings of protein language models

MIT tool visualizes and edits “physically impossible” objects

New algorithms enable efficient machine learning with symmetric data

Robot, know thyself: New vision-based system teaches machines to understand their bodies

A new way to edit or generate images

The unique, mathematical shortcuts language models use to predict dynamic scenarios

Can AI really code? Study maps the roadblocks to autonomous software engineering

AI shapes autonomous underwater “gliders”

Study could lead to LLMs that are better at complex reasoning

Using generative AI to help robots jump higher and land safely

Researchers present bold ideas for AI at MIT Generative AI Impact Consortium kickoff event

Unpacking the bias of large language models

Envisioning a future where health care tech leaves some behind

Teaching AI models what they don’t know

Teaching AI models the broad strokes to sketch more like humans do

AI learns how vision and sound are connected, without human intervention

Study shows vision-language models can’t handle queries with negation words

Hybrid AI model crafts smooth, high-quality videos in seconds

Novel AI model inspired by neural dynamics from the brain

Making AI models more trustworthy for high-stakes settings

The MIT-Portugal Program enters Phase 4

“Periodic table of machine learning” could fuel AI discovery

3D modeling you can feel

Making AI-generated code more accurate in any language

Training LLMs to self-detoxify their language

New method efficiently safeguards sensitive AI training data

Could LLMs help design our next medicines and materials?

New method assesses and improves the reliability of radiologists’ diagnostic reports

For this computer scientist, MIT Open Learning was the start of a life-changing journey

At the core of problem-solving

Robotic helper making mistakes? Just nudge it in the right direction

Like human brains, large language models reason about diverse data in a general way

AI model deciphers the code in proteins that tells them where to go