New Tool Makes Generative AI Models More Likely to Create Breakthrough Materials
Zach Winn | MIT News
With SCIGEN, researchers can steer AI models to create materials with exotic properties for applications like quantum computing.
Photonic Processor Could Enable Ultrafast AI Computations with Extreme Energy Efficiency
Adam Zewe | MIT News
This new device uses light to perform the key operations of a deep neural network on a chip, opening the door to high-speed processors that can learn in real-time.
AI Method Radically Speeds Predictions of Materials’ Thermal Properties
Adam Zewe | MIT News
The approach could help engineers design more efficient energy-conversion systems and faster microelectronic devices, reducing waste heat.
A New Way to Let AI Chatbots Converse All Day without Crashing
Adam Zewe | MIT News
Researchers developed a simple yet effective solution for a puzzling problem that can worsen the performance of large language models such as ChatGPT.
Technique Enables AI on Edge Devices to Keep Learning Over Time
Adam Zewe | MIT News
With the PockEngine training method, machine-learning models can efficiently and continuously learn from user data on edge devices like smartphones.
Memristive Crossbar Arrays for Analog In-Memory Computing and Neuromorphic Engineering
Wednesday, October 11, 2023 | 12:00 - 1:00pm ET
Hybrid
Grier A (34-401A)
50 Vassar Street Cambridge, MA
Helping Computer Vision and Language Models Understand What They See
Adam Zewe | MIT News
Researchers use synthetic data to improve a model’s ability to grasp conceptual information, which could enhance automatic captioning and question-answering systems.
Building Tools To Learn Human Brain Processes
Imagination + AI, MIT CSAIL, Forbes
The CSAIL Imagination in Action @ MIT Symposium aimed to educate and motivate entrepreneurs on building successful AI-focused companies, attracting a diverse audience passionate about AI's transformative potential.
Machine-learning System Based on Light Could Yield More Powerful, Efficient Large Language Models
Elizabeth A. Thomson | Materials Research Laboratory
MIT system demonstrates greater than 100-fold improvement in energy efficiency and a 25-fold improvement in compute density compared with current systems.
Systematic Modeling and Design of Sparse Tensor Accelerators
Friday, May 05, 2023
Nellie Wu, MIT