When it comes to the role of AI in our lives, the conundrum we have to crack is if—and how consciously—we inhabit our own minds.
As embodied AI moves from demos to deployment, my personal view is that the future will follow the evolutionary path. It better matches how technologies scale, how businesses work, and how our ...
Most polymers don’t mix—and that’s the point. Polymer alloys succeed by engineering the interface: use thermodynamics to predict separation, processing to sculpt morphology, and compatibilizers to ...
Abstract: Over the past decades, extensive research has been conducted on adversarial attacks and defense mechanisms in deep learning, particularly in real-world applications such as autonomous ...
EvoToolkit is a Python library that leverages Large Language Models (LLMs) to evolve solutions for optimization problems. It combines the power of evolutionary algorithms with LLM-based solution ...
ABSTRACT: Multi-objective optimization remains a significant and realistic problem in engineering. A trade-off among conflicting objectives subject to equality and inequality constraints is known as ...
ABSTRACT: Mathematical optimization is a fundamental aspect of machine learning (ML). An ML task can be conceptualized as optimizing a specific objective using the training dataset to discern patterns ...
Abstract: Problem transformation-based multiobjective evolutionary algorithms (MOEAs) face the risk of losing optimal solutions when transforming a large-scale multiobjective optimization problem into ...
A new evolutionary technique from Japan-based AI lab Sakana AI enables developers to augment the capabilities of AI models without costly training and fine-tuning processes. The technique, called ...
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