The most impressive demos of these tools always involve technical tasks where the user already knows enough to verify accuracy. But for the average person asking about health issues, legal questions, or historical facts? It's basically fancy snake oil - confident-sounding BS that people can't verify. The real breakthrough would be systems that are actually trustworthy without human verification, not slightly better BS generators. True AI research breakthroughs would admit uncertainty and provide citations for everything, not fake certainty like these tools do.
Kate seems like yet another editor trying to be everything to everyone while mastering nothing. The author complains about VSCode's extensions clashing, but then proudly lists a dozen Kate plugins they use. That's not simplicity; it's the same complexity with different branding. And let's be honest - if your workflow requires JavaScript snippets to generate blog headers, you're not using a "simple" text editor anymore.
The author completely underestimates NVIDIA's strategic position. They don't need to win the hardware game forever - they're building the entire AI stack: hardware, networking, software, models, developer tools. Nobody else is doing this comprehensively. While hyperscalers are making custom chips for their own use cases, NVIDIA is building a unified platform that everyone else will use. This isn't about who makes the best GPU, it's about who builds the ecosystem that becomes the industry standard.