Generative AI refers to models or algorithms that create brand-new output, such as text, photos, videos, code, data, or 3D renderings, from the vast amounts of data they are trained on. The models 'generate' new content by referring back to the data they have been trained on, making new predictions.
The purpose of generative AI is to create content, as opposed to other forms of AI, which might be used for different purposes, such as analyzing data or helping to control a self-driving car.
The term generative AI is causing a buzz because of the increasing popularity of generative AI programs, such as OpenAi's conversational chatbot ChatGPT and the AI image generator DALL-E. Continue reading from ZDNET
Generative AIs, such as ChatGPT, have revolutionized how we interact with and view AI. Activities like writing, coding, and applying for jobs have become much easier and quicker. With all the positives, however, there are some pretty serious risks.
A major concern with AI is trust and security, which have even caused some countries to completely ban ChatPT as a whole or to reconsider policy around AI to protect users from harm.
According to Gartner analyst Avivah Litan, some of the biggest risks of generative AI concern trust and security and include hallucinations, deepfakes, data privacy, copyright issues, and cybersecurity problems. Continue reading from ZDNET
Generative AI (LinkedIn Learning)
What Is Generative AI? (McKinsey & Company)
What Is Generative AI: Everything You Need to Know (TechTarget)
Generative AI Defined (Tech Republic)
What Is Generative AI and Why Is It Suddenly Everywhere? (Vox)
The Generative AI Revolution Has Begun-How Did We Get Here? (Ars Technica)
The Promise and Peril of Generative AI: Experts Weigh In (Advanced Science News)
How Generative A.I. and ChatGPT Will Influence Jobs at All Professional Levels (CNBC)
