Hi all. This is thank you for joining my talk. Today I am discuss human AI sym robotics, which is revolutionizing the precision in collaborative systems with datadriven advancements. The human ai Symbi Robotics is transforming the collaborative systems through continuous feedback loops that enhances both the human creativity and the artificial intelligence capabilities. Today, I'm going to present that explores how these revolutionized. Systems which is has high impact on high position fields such as surgery. And it also helps in integrating the multimodal perception. It helps in our medical predictions. It helps in the bidirectional interfaces and physical actuation. In this topic, we'll examine the measurable improvements in these surgical outcomes, challenges in the implementations, and the future potential of these technologies which spans across various domains. Coming to the next slide, today we are going to discuss about the architecture of the human AI symbiotic systems. It's on the kind of pial structure where we have shown the, a diagram there is multimodal perception which is the advanced sensor fusion technologies. And then there comes the AI prediction engines. Machine learning algorithms. There is physical actuators, which has the precision mechanical response systems, and there comes the bidirectional interfaces, which consist of the seamless human AI communication channels. The foundation of these symbiotic robotics reached on these four integrated subsystems. Advanced sensor fusion helps in collecting the environmental data while the machine learning gets the feedback from the real time data. It helps in making the computational decisions into physical actions and also increases the accuracy up to 94.2. We have given a use case for applications here. We have used the different parameters in terms of the metrics the decision latency reduction it helps in the faster surgical making decisions, thereby increasing the productivity up to almost 58.4%. Then there comes the position improvement where we are dealing with the enhanced tissue MA manipulation accuracy, and that comes around almost 29 7% accuracy. And then there is also the complication reduction and we are seeing a significant reduce in the minor surgical complications. And that will be around 41.2%. And also there is average reduction in the patient stay duration. So almost eight. So these surgical platforms based on the AI has demonstrated significant improvements in the clinical outcomes. The it also enhances the surgical capabilities by providing the real time guidance and precision instrument control. Therefore it helps in the just technological and for the better experience from the patient perspective. We have given some diagram, which consist of different parameters unnecessary movements total. Cognitive load and task performance. We have just try to give this metrics. So these symbiotic systems practically improve workflow efficiency across multiple dimensions. Almost 25% reduction in unnecessary instrument movements coupled with around almost 19.3% decrease in the total demonstrates how AI optimization streamlines technical execution. These systems reduces the cognitive load by almost 28.4%. This gives these a lot of help in terms of the critical decision making rather than mechanical execution of the routine task. This use case helps in achieving the superhuman position. But there are also human limitations these surgeons are facing. Like a lot of issues in the terms of the micro surgeries. There can be a natural hand framer or there is like induced position degradation. Visual perception limitations, and when this system integrate with the ai the, basically the AI robotic capabilities enhances this limitations. There are barriers, tre filtering and the motion scaling. There is enhanced visual feedback with the magnification. Then submillimeter positions consistently are maintained in the most demanding microsurgical applications. AI assisted robotic systems have demonstrated capabilities that exceed expert human performance. These position enables the surgical possibilities which are previously considered too risky and for the patients. These AI robotic capabilities help since it's numerous on in this surgery field. There are also lot of technical challenges. We have to deal with latency management intent prediction and safety. Though it has really advanced the systems uht around 5,200 milliseconds in terms of the critical performance in the critical applications we, in order to reduce these, we have, we need further innovations in terms of the communication protocol and the com computational architecture. So in case of the intent prediction, our current algorithms achieve almost 94.2% accuracy in predictable scenarios, but struggle with noble situations and expert level technique that devi from different training patterns and safety verification perspective, formal verification of the. Systems remains challenging here, so we have to add up the AI human collaborative systems. Bidirectional learning. I have some here. There are different forms like human expertise which provides intuition creativity and the judgment capabilities. Then it'll be the human learning. Hydrogen again, various insights from the previous decision making AI capabilities. Then the AI enhancements also comes into picture. So the system improves precision and the Integr collective expertise. Then the knowledge transfer, so the techniques are already captured and encoded into the AI models. So these systems continuously help in the bidirectional learning where the humans and the AI both are mutually improving. And surgeon also teach the system their techniques. While also gathering the necessary feedback in terms of the AI capabilities. So this is basically a bidirectional learning capabilities. Both the AI and the are collaborating with. So there are various multimodal communication interfaces there. One is voice control which consists of the natural language commands and confirmations. Then there is gauge tracking. So the eye movement monitoring for attention based control. Helps in the gauge tracking and then there is the gesture recognition. Hand and the body movement interpretation falls under this and the he haptic feedback. This will be basically the force and the tactile sensation delivery. So these channels has drastically reduced in terms of the in cognitive workload almost reduction around 32.6%. And around improvement of 28% in the tax performance. These interfaces create more in, I. By leveraging the natural communication modes and the providing ens feedback. The most effective systems here adapt to the different users and preferences and needs. This helps in switching, the multimodal communication interface, which is. Then there comes the ethical framework for the integration here, the autonomy and the control. Establishing clear boundaries for ai, decision making authority while maintaining the meaningful human oversight. And then there is data privacy. In these developing protocols for responsible collection and use of surgical data while ensuring appropriate patient consent and the revolution responsibility attribution it'll help in creating the frameworks for. Determining the accountability when the outcomes involve the human AI collaborative decisions the access and the equity addressing disparities in availability of advanced surgical technologies across healthcare systems and geographical regions to prevent the quality gaps. But we have to consider this in terms of the ethical guidance to see whether this integration will be ethically integrate into this AL practice. It'll create the trust among the patients and the practitioners and the regularity bodies. We can also use in different applications apart from surgery. We can use this in the different domains like industrial manufacturing which always need the precision. And it's a complex environment, so it's basically needs the flexibility. We also can explain this use case in the, space exploration which art space, latency compensation with the remote operations and the disaster response. So in case of any difficult environment intervention with the human judgment and then there comes this scientific research so micro nanoscale manipulation with the, human creativity. So these principles and the technologies developed for the surgical applications are finding new homes across diverse domains, each feel presence, unique challenges for these human AI collaborations. But all can be made mutually beneficial. And these applications can be span across multiple domains. It's a multi-billion dollar industries, but. In major kit takeaway from this top the symbiotic future. So it's miserable impact human AI symbiotic systems have demonstrated ative, improvements in this iCal outcomes almost the precision increased to almost 30% and the complication reductions to almost 32%. And it's actually continuous evolving. We are just doing the ongoing research in the bidirectional learning and the multimodal interface in terms of the latency and intent prediction. And there is also complement capabilities. So the most successful implementations leverage the strengths of the human intuition and the machine precisions. And we can be on the surgical settings. We can expand this to the different domains like space industry disaster management had the human judgment and the mission positions must seamlessly combine. Here our goal is not to replace human with ai, but just key takeaway is to combine the human in the AI symbiotic robotics. And it is needs to be a collaborative environment. So where the, humans or nations could accomplish anything independently. Thank you all.