Russell Wald, director of the Stanford Institute for Human-Centered AI, sounds off on'The Story.' OpenAI CEO Sam Altman says the age of the giant artificial intelligence model is already over. "I think we're at the end of the era where it's going to be these, like, giant, giant models," he told an audience at the Massachusetts Institute of Technology over Zoom last week. "We'll make them better in other ways." During the same event, Altman also confirmed that his company is not developing Chat GPT-5. "An earlier version of the letter claimed OpenAI is training GPT-5 right now," he said, referencing a letter from billionaire Elon Musk and Apple co-founder Steve Wozniak.

The stunning capabilities of ChatGPT, the chatbot from startup OpenAI, has triggered a surge of new interest and investment in artificial intelligence. But late last week, OpenAI's CEO warned that the research strategy that birthed the bot is played out. It's unclear exactly where future advances will come from. OpenAI has delivered a series of impressive advances in AI that works with language in recent years by taking existing machine-learning algorithms and scaling them up to previously unimagined size. GPT-4, the latest of those projects, was likely trained using trillions of words of text and many thousands of powerful computer chips.

By now it's evident that artificial intelligence (AI) is the singular most definitive technology of this generation, and it's powering broad industrial transformation across critical use cases. Ronald van Loon is a NVIDIA partner and had the opportunity to apply his expertise as an industry analyst to explore the implications of MLPerf benchmarking results on the next generation of AI. Enterprises are facing an unprecedented moment as they strive to leverage AI for competitive advantage. This means optimizing training and inferencing for AI models to gain differentiating benefits, like significantly improved productivity for their data science teams and achieving faster time to market for new products and services. However, AI is advancing incredibly quickly and AI model size is dramatically increasing in such areas as Natural Language Processing (NLP), which has grown 275 times every two years using the Transformer neural network architecture.