๐ฉ๐ฎ๐โSophia๐๐f4f
@okex10
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The history of robotics dates back to ancient times, with early concepts appearing in Greek mythology and Chinese legends. The first mechanical automata were built during the Renaissance by inventors like Leonardo da Vinci, who designed a humanoid robot in 1495. The modern development of robotics began in the 20th century, particularly with Czech playwright Karel ฤapekโs play *R.U.R.* (1920), which introduced the term "robot."
The first programmable robot, Unimate, was created in 1954 and revolutionized manufacturing. In the decades that followed, advancements in computing, artificial intelligence, and materials led to increasingly sophisticated robots used in industries, healthcare, and space exploration. Today, robots are integral to automation, medical surgeries, and everyday tasks, with AI-driven models like Boston Dynamics' robots showcasing the future of robotics. 0 reply
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The future world could be shaped by significant advancements in technology, sustainability efforts, and societal changes.
**Technology**: Artificial intelligence and automation will play a much larger role in daily life, revolutionizing industries, transportation, and personal interactions. Autonomous vehicles, drones, and AI-driven services will likely become more commonplace. Smart cities with interconnected systems will improve infrastructure and energy efficiency.
**Sustainability**: As climate change pressures grow, the future will likely see a shift towards greener energy sources like solar, wind, and potentially nuclear fusion. Sustainable architecture, electric vehicles, and circular economies will be crucial in reducing environmental impact.
**Society**: Social and work structures may evolve, with more remote work, digital economies, and virtual interactions taking precedence. Augmented and virtual realities could redefine how people socialize, learn, and experience entertainment. 0 reply
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To enter the AI industry, begin by developing a solid foundation in mathematics, statistics, and computer science, focusing on areas such as linear algebra, calculus, probability, and algorithms. Learn programming languages like Python, which is widely used in AI, and gain expertise in machine learning, deep learning, and data science through online courses, certifications, and hands-on projects. Build a portfolio showcasing your work on platforms like GitHub. Networking is crucialโattend AI conferences, join relevant online communities, and connect with professionals in the field. Consider internships or research opportunities to gain practical experience, and stay updated on the latest AI advancements by reading research papers and following industry trends. 0 reply
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