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Found 7 papers, 4 papers with code
How GPT learns layer by layer
Understanding how LLMs build internal world models is key to developing agents capable of consistent, adaptive behavior across tasks.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry
Here, we present the outcomes from the second Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry, which engaged participants across global hybrid locations, resulting in 34 team submissions.
Contrastive learning of cell state dynamics in response to perturbations
We illustrate the features and applications of DynaCLR with the following experiments: analyzing the kinetics of viral infection in human cells, detecting transient changes in cell morphology due to cell division, and mapping the dynamics of organelles due to viral infection.
14 Examples of How LLMs Can Transform Materials Science and Chemistry: A Reflection on a Large Language Model Hackathon
Recent studies suggested that these models could be useful in chemistry and materials science.
Open Arms: Open-Source Arms, Hands & Control
Open Arms is a novel open-source platform of realistic human-like robotic hands and arms hardware with 28 Degree-of-Freedom (DoF), designed to extend the capabilities and accessibility of humanoid robotic grasping and manipulation.
Design of an Affordable Prosthetic Arm Equipped with Deep Learning Vision-Based Manipulation
This paper lays the complete outline of the design process of an affordable and easily accessible novel prosthetic arm that reduces the cost of prosthetics from $10, 000 to $700 on average.
A Neuro-Symbolic Humanlike Arm Controller for Sophia the Robot
We outline the design and construction of novel robotic arms using machine perception, convolutional neural networks, and symbolic AI for logical control and affordance indexing.
