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From fish to machines: The natural ‘control law’ of fish was embedded in swarms of robotic cars, drones, and boats (Credit: Christian Ziegler/Max Planck Institute of Animal Behavior).
CSAIL article

Fish are masters of coordinated motion. Schools of fish have no leader, yet individuals manage to stay in formation, avoid collisions, and respond with liquid flexibility to changes in their environment. Reproducing this combination of robustness and flexibility has been a long-standing challenge for human engineered systems like robots. Now, using virtual reality for freely-moving fish, a research team based in Konstanz has taken an important step towards that goal.

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Ray and Maria Stata Center exterior
External articles

"The net effect [of DeepSeek] should be to significantly increase the pace of AI development, since the secrets are being let out and the models are now cheaper and easier to train by more people." ~ Associate Professor Phillip Isola

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alt="Daniela Rus, Director of CSAIL and MIT EECS Professor, was recently named a co-recipient of the 2024 John Scott Award by the Board of Directors of City Trusts (Credit: Rachel Gordon/MIT CSAIL)."
CSAIL article

Daniela Rus, Director of CSAIL and MIT EECS Professor, was recently named a co-recipient of the 2024 John Scott Award by the Board of Directors of City Trusts. This prestigious honor, steeped in historical significance, celebrates scientific innovation at the very location where American independence was signed in Philadelphia, a testament to the enduring connection between scientific progress and human potential.

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The MIT researchers developed an AI-powered simulator that generates unlimited, diverse, and realistic training data for robots. The team found that robots trained in this virtual environment called “LucidSim” can seamlessly transfer their skills to the real world, performing at expert levels without additional fine-tuning (Credit: Mike Grimmett/MIT CSAIL).
CSAIL article

For roboticists, one challenge towers above all others: generalization – the ability to create machines that can adapt to any environment or condition. Since the 1970s, the field has evolved from writing sophisticated programs to using deep learning, teaching robots to learn directly from human behavior. But a critical bottleneck remains: data quality. To improve, robots need to encounter scenarios that push the boundaries of their capabilities, operating at the edge of their mastery. 

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Figure 1: Schematic overview of the framework for on-road evaluation of explanations in automated vehicles (Credit: MIT CSAIL and GIST).
CSAIL article

The Proceedings of the ACM on Interactive, Mobile, Wearable, and Ubiquitous Technologies (IMWUT) Editorial Board has awarded MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) and the Gwangju Institute of Science and Technology (GIST) researchers with a Distinguished Paper Award for their evaluation of visual explanations in autonomous vehicles’ decision-making.

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alt="MIT CSAIL researchers helped design a new technique that can guarantee the stability of robots controlled by neural networks. This development could eventually lead to safer autonomous vehicles and industrial robots (Credits: Alex Shipps/MIT CSAIL)."
CSAIL article

Neural networks have made a seismic impact on how engineers design controllers for robots, catalyzing more adaptive and efficient machines. Still, these brain-like machine-learning systems are a double-edged sword: Their complexity makes them powerful, but it also makes it difficult to guarantee that a robot powered by a neural network will safely accomplish its task.

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Researchers from MIT and elsewhere designed a communication framework that enables academics to ask for research help on social media using meronymous communication, in which the asker only reveals certain verified aspects of their identity. They found that meronymous communication encouraged people to ask questions they otherwise might not have for fear of judgment from more senior scientists (Credits: MIT News; iStock).
CSAIL article

Have you ever felt reluctant to share ideas during a meeting because you feared judgment from senior colleagues? You’re not alone. Research has shown this pervasive issue can lead to a lack of diversity in public discourse, especially when junior members of a community don’t speak up because they feel intimidated.