AI and Sustainable Events Together: Creating a Greener Future

Throughout its development, artificial intelligence (AI) and sustainable events have attracted a lot of attention and witnessed impressive growth.

AI has transformed a number of industries and is now a necessary component of day-to-day living. Artificial intelligence has advanced and broadened its capabilities from its modest beginnings, spurring innovation and revolutionizing how we use technology in our daily lives and at work.

Past Events

The idea of building machines that might mimic human intelligence was first investigated in the 1950s, and that is when artificial intelligence first emerged. Rule-based expert systems, which employed a set of predetermined rules and logical reasoning to handle certain issues, were the main focus of early AI systems. Although these systems were limited in their ability to handle complicated and uncertain settings, they did set the groundwork for future breakthroughs in AI.

Machine learning, a branch of artificial intelligence that focuses on creating algorithms that let machines learn from data and get better over time, became the focus of AI research in the 1980s and 1990s. Deep learning model training was made possible by the advent of neural networks and technologies such as backpropagation during this period. However, the broad use of these techniques was hampered by low processing power and a dearth of large datasets.

The advent of big data and advances in computing power throughout the early 2000s signaled a major turning point in history. Complex model training was made possible by the development of increasingly powerful processors and the availability of large datasets. As a result, advances in speech recognition, natural language processing, and computer vision were made. Large corporations made significant investments in research, opening the door for revolutionary applications such as virtual assistants, picture recognition, and language translation.

Further driving the rise of AI was the expansion of cloud computing and the growing accessibility of AI frameworks and tools. Cloud platforms provided resources for AI model deployment and training that were both affordable and scalable.