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Introduction What is a Humanoid Anyway? History of Humanoid Robot Why to Develop Humanoids? Challenges in Humanoids Human Evolution Legged Locomotion Humanoid Robot Applications Social Aspects Conclusion Introduction Robotics deals with robots Recent enhancement in robotics - Humanoid robots Humanoid robots - having human characteristics or form Resemble human both in appearance and behaviour “Elektro” is the first Humanoid Robot History of Humanoid Robot Integration of scientific and engineering fields, has a social dimension WASEDA University- leading research sites First usable robot by HONDA in 1996 HONDA Humanoid robots-brief history First high profile humanoid robot-Honda’s ASIMO-2000 What is a Humanoid Anyway? Humanoid refers to any being whose body structure resembles that of a human: head, torso, legs, arms, hands. But it is also a robot made to resemble a human both in appearance and behaviour. The difference between a robot and android is only skin-deep, looks exactly like humans on the outside, but with internal mechanics of humanoid robot. More rational reasons They can work in human environment without a need to adapt themselves or to change the environment Our environment and our tools are adapted for us Why adapt all to robots? It is easier for a human being to interact with a human-like being Connect with me or follow me at https://www.facebook.com/aakash416/ https://github.com/aakash416 https://www.linkedin.com/in/aakash-ra... https://twitter.com/aakashraj416 https://www.youtube.com/channel/UCzy-... https://plus.google.com/u/0/b/1028832...

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Effective data discovery is crucial for maintaining compliance and mitigating risks in today's rapidly evolving privacy landscape. However, traditional manual approaches often struggle to keep pace with the growing volume and complexity of data. Join us for an insightful webinar where industry leaders from TrustArc and Privya will share their expertise on leveraging AI-powered solutions to revolutionize data discovery. You'll learn how to: - Effortlessly maintain a comprehensive, up-to-date data inventory - Harness code scanning insights to gain complete visibility into data flows leveraging the advantages of code scanning over DB scanning - Simplify compliance by leveraging Privya's integration with TrustArc - Implement proven strategies to mitigate third-party risks Our panel of experts will discuss real-world case studies and share practical strategies for overcoming common data discovery challenges. They'll also explore the latest trends and innovations in AI-driven data management, and how these technologies can help organizations stay ahead of the curve in an ever-changing privacy landscape.

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The presentation explores the development and application of artificial intelligence (AI) from its inception to its current status in the modern world. The term "artificial intelligence" was first coined by John McCarthy in 1956 to describe efforts to develop computer programs capable of performing tasks that typically require human intelligence. This concept was first introduced at a conference held at Dartmouth College, where programs demonstrated capabilities such as playing chess, proving theorems, and interpreting texts. In the early stages, Alan Turing contributed to the field by defining intelligence as the ability of a being to respond to certain questions intelligently, proposing what is now known as the Turing Test to evaluate the presence of intelligent behavior in machines. As the decades progressed, AI evolved significantly. The 1980s focused on machine learning, teaching computers to learn from data, leading to the development of models that could improve their performance based on their experiences. The 1990s and 2000s saw further advances in algorithms and computational power, which allowed for more sophisticated data analysis techniques, including data mining. By the 2010s, the proliferation of big data and the refinement of deep learning techniques enabled AI to become mainstream. Notable milestones included the success of Google's AlphaGo and advancements in autonomous vehicles by companies like Tesla and Waymo. A major theme of the presentation is the application of generative AI, which has been used for tasks such as natural language text generation, translation, and question answering. Generative AI uses large datasets to train models that can then produce new, coherent pieces of text or other media. The presentation also discusses the ethical implications and the need for regulation in AI, highlighting issues such as privacy, bias, and the potential for misuse. These concerns have prompted calls for comprehensive regulations to ensure the safe and equitable use of AI technologies. Artificial intelligence has also played a significant role in healthcare, particularly highlighted during the COVID-19 pandemic, where it was used in drug discovery, vaccine development, and analyzing the spread of the virus. The capabilities of AI in healthcare are vast, ranging from medical diagnostics to personalized medicine, demonstrating the technology's potential to revolutionize fields beyond just technical or consumer applications. In conclusion, AI continues to be a rapidly evolving field with significant implications for various aspects of society. The development from theoretical concepts to real-world applications illustrates both the potential benefits and the challenges that come with integrating advanced technologies into everyday life. The ongoing discussion about AI ethics and regulation underscores the importance of managing these technologies responsibly to maximize their their benefits while minimizing potential harms.

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