Artificial Intelligence (AI) systems are about to revolutionize everything and already greatly impacts our lives. It refers to machines’ mimicking capabilities of human brain, such as learning and problem-solving. Since the early days of the AI-history, some computer scientists have strived to make machines as intelligent as humans. Since its inception in 1950s, AI has come a long way. Based on the recent advancements and the significant increases in investment, we should expect AI technology to become even more powerful in the years and decades to come.
The language and image recognition capabilities of AI systems have developed very rapidly, as just 10 years ago, no existing machine was able to reliably provide language or image recognition at a human level. Over the past few years, AIs producing language have impacted our world in many ways: Emails get auto-completed, translation-as-a-service products nowadays translate massive amounts of online texts, reports and essays get auto-generated, school children use language models to do their homework, and the list continues. AI is no longer a technology of the future or part of Hollywood Science Fiction.
Investment in generative AI surged during the early 2020s. Generative AI models use neural networks to identify patterns within existing data to generate new content such as text, images, sounds, animation, 3D models, or other. Nvidia points to three critical requirements needed to build a successful generative AI model. These are High Quality Samples, Mode Coverage Diversity, and Fast Sampling.
As an evolving space, generative models are still considered to be early stages and face several challenges such as the scale of compute infrastructure, lack of high-quality data, etc. Moreover, there are also many concerns about the potential misuse of generative AI, including cybercrime or creating fake news.