A generative AI summit will be held in Athens, Greece between February 29th and March 2nd with the participation of dozens of experts from around the world.
The summit, which will be held at Eugenides Foundation, will delve into AI’s capabilities and its transformative impact across sectors of public policy, legal, consulting, and finance.
It will also explore how generative AI can inspire creativity and innovation in product, healthcare, food/nutrition, and fashion industries as well as its role in education, marketing, people, and customer experience by enhancing communication, creativity, and collaboration.
In July 2020, the hype and buzz around GPT was brand new. In just under four years since that time, GPT is no longer an alien term, and generative AI is pretty much everywhere. Since 2020, large-scale commercialization of AI, driven by OpenAI and its founder Sam Altman, spurred the likes of Google, Meta, Microsoft, Amazon, and other tech majors to double down on AI.
Many doubted it at first, but GenAI is now well and is truly the future.
A panel of experts from Microsoft, Google, LinkedIn, Nvidia, and Trible will discuss how generative AI can facilitate product design, prototyping, user interface, user experience, testing, and feedback. This track reveals how generative AI can help product managers and developers create innovative and user-friendly products with tools and techniques.
Another panel will explore how generative AI can enhance content creation, customer segmentation, personalization, and social media marketing. It will demonstrate how generative AI can help investors and financial institutions make better and informed decisions and optimize performance with insights and tips.
Please follow the link for the full agenda of the summit.
What is generative AI?
Generative AI is a type of artificial intelligence technology that can produce various types of content, including text, imagery, audio, and synthetic data. The recent buzz around generative AI has been driven by the simplicity of new user interfaces for creating high-quality text, graphics, and videos in a matter of seconds.
The technology, it should be noted, is not brand-new. Generative AI was introduced in the 1960s in chatbots. However, it was not until 2014 with the introduction of generative adversarial networks, or GANs, a type of machine learning algorithm, that generative AI could create convincingly authentic images, videos, and audio of real people.
On the one hand, this newfound capability has opened up opportunities that include better movie dubbing and rich educational content.
It also unlocked concerns about deepfakes, or digitally forged images and videos, and harmful cybersecurity attacks on businesses, including nefarious requests that realistically mimic an employee’s boss.
Related: Top Scientists Selected to Advance Artificial Intelligence in Greece
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