NVIDIA AI experts predict rapid transformations across industries as companies accelerate AI rollouts and begin to build best practices for adopting generative AI.
Move over, Merriam-Webster: Enterprises this year found plenty of candidates to add for word of the year. “Generative AI” and “generative pretrained transformer” were followed by terms such as “large language models” and “retrieval-augmented generation” (RAG) as whole industries turned their attention to transformative new technologies.
Generative AI started the year as a blip on the radar but ended with a splash. Many companies are sprinting to harness its ability to ingest text, voice and video to churn out new content that can revolutionize productivity, innovation and creativity.
Enterprises are riding the trend. Deep learning algorithms like OpenAI’s ChatGPT, further trained with corporate data, could add the equivalent of $2.6 trillion to $4.4 trillion annually across 63 business use cases, according to McKinsey & Company.
Yet managing massive amounts of internal data often has been cited as the biggest obstacle to scaling AI. Some NVIDIA experts in AI predict that 2024 will be all about phoning a friend — creating partnerships and collaborations with cloud service providers, data storage and analytical companies, and others with the know-how to handle, fine-tune and deploy big data efficiently.
Large language models are at the center of it all. NVIDIA experts say advancements in LLM research will increasingly be applied in business and enterprise applications. AI capabilities like RAG, autonomous intelligent agents and multimodal interactions will become more accessible and more easily deployed via virtually any platform.
