“Nvidia’s multi-million-token context window is an impressive engineering milestone, but for most companies, it’s a solution in search of a problem,” said Wyatt Mayham, CEO and cofounder at Northwest AI Consulting. “Yes, it tackles a real limitation in existing models like long-context reasoning and quadratic scaling, but there’s a gap between what’s technically possible and what’s actually useful.”
Helix Parallelism helps fix LLMs’ big memory problem
Large language models (LLMs) still struggle to stay focused in ultra-long contexts, experts point out.
“For a long time, LLMs were bottlenecked by limited context windows, forcing them to ‘forget’ earlier information in lengthy tasks or conversations,” said Justin St-Maurice, technical counselor at Info-Tech Research Group.
This story originally appeared on Computerworld
