We require a new vocabulary to keep up with the evolution of AI

Terminology has fallen behind the trajectory of this technology but clarity is crucial for sensible investments to be made in it

- NILESH JASANI

The artificial intelligence (AI) news flow does not stop, and it's becoming increasingly obscure and pompous. China's MiniMax just spiked efficiency and context length, but we are not gasping. Elon Musk says Grok will "redefine human knowledge," but is that a new algorithm or just hot air? Andrej Karpathy's "Software 3.0" sounds clever but lacks real-world bite. Mira Murati bet $2 billion on "custom models," a term so vague it could mean anything. And only by testing Kimi AI's "Researcher" did we get why it's slick and different.

Technology now sprints past our words. As machines get smarter, our language lags. Buzzwords, recycled slogans and podcast quips fill the air but clarify nothing. This isn't just messy, it's dangerous. Investors chase vague terms, policymakers regulate without definitions and the public confuses breakthroughs with sci-fi.

We're in a tech revolution with a vocabulary stuck in the dial-up days. We face a generational shift in technology without a stable vocabulary to navigate it.

This language gap is not a side issue. It is a core challenge that requires a new discipline: a fierce skepticism of hype and a deep commitment to the details. The instinct to simplify is a trap. Once, a few minutes was enough to explain breakthrough apps like Google or Uber. Now, innovations in robotics or custom silicon resist such compression. Understanding OpenAI's strategy or Nvidia's product stack requires time, not sound-bites.