We’re committed to advancing the field of artificial intelligence through focused research on Spike Neural Networks (SNNs), YOLOv7, and Deep Reinforcement Learning (DRL).
Our team is exploring Spike Neural Networks (SNN), the latest advancement in neural network technology. Unlike traditional neural networks, SNN operate on a time-based mechanism which can potentially lead to more energy-efficient and faster processing. Our goal is to understand how to leverage SNN for tasks where time is a critical factor, like signal processing or real-time decision-making.
With YOLOv7, object detection is getting faster and more accurate. Our researchers are working to enhance this tool, making it more adaptable for practical applications. We’re pushing its limits to see how and where YOLOv7 can be integrated, from enhancing security systems to improving autonomous navigation.
Deep Reinforcement Learning (Deep RL) sits at the core of our quest to develop AI that can learn and adapt. Our work focuses on algorithms that can learn from their environment to make decisions, mimicking a level of decision-making closer to human cognition. We’re exploring how Deep RL can solve complex problems that require a strategic thought process.
As a research-driven startup, we’re not tied down by production demands. This freedom allows us to dive deep into AI research and develop prototypes and software that can lead to breakthroughs in the field.
We believe in collaboration and are always looking to partner with like-minded individuals and organizations. By sharing our findings and learning from others, we aim to contribute to a future where AI is more efficient, ethical, and accessible.
Keep an eye on our site for updates on our latest developments and insights into AI research.
Research on Spike Neural Networks, YOLOv7, Deep reinforcement learning
