As a techno-journalist who's seen more AI buzzwords than bad sci-fi plots, I have to say Rama Ramakrishnan's latest from MIT Sloan hits the sweet spot. In a world where executives are drowning in promises of AI magic, this piece cuts through the fluff with 10 straight-up questions about large language models (LLMs) that every forward-thinking leader should have bookmarked. It's not about turning you into a coder overnight—it's about arming you with just enough insight to avoid those 'oops, the AI just invented a policy' moments.
Take the first one: how does an LLM decide to wrap up its rambling response? Ramakrishnan simplifies it beautifully—no, the model isn't pondering life's mysteries; it's more like a DJ dropping the mic when it hits a special 'end' token or maxes out on words. Think of it as your verbose uncle at Thanksgiving finally passing the potatoes. For businesses building custom apps, tweaking these rules can mean the difference between concise reports and endless novella drafts, saving time and sanity.
And hallucinations? Oh boy, the article's pragmatic nod here is gold. You can't zap them away like bugs at a picnic, but layering in tricks like retrieval-augmented generation (RAG)—basically, feeding the AI a targeted info snack instead of the whole buffet—can dial down the nonsense. I chuckle at the irony: we're handing machines god-like knowledge, yet they still fib like politicians. Ramakrishnan's advice to mix human checks with AI 'judges' (another LLM playing referee) feels refreshingly real—innovation thrives when we treat AI as a clever sidekick, not an infallible oracle.
What I love most is how this encourages critical thinking without the doomscroll. Sure, LLMs won't update on the fly from your corrections or spit out identical answers every time (unless you cache like a digital hoarder), but understanding these quirks lets businesses innovate smarter. Imagine ditching blind trust for pragmatic pilots: test RAG on your expense reports before letting it loose on board decisions. It's pro-innovation without the fairy dust—because in the end, the best AI strategies are the ones that don't crash and burn spectacularly. Source: How LLMs Work: Top 10 Executive-Level Questions | Rama Ramakrishnan
