I'm not sure that we disagree, but perhaps we're understanding "launching" in the metaphor somewhat differently. I think the key point about the interstellar pr

I'm not sure that we disagree, but perhaps we're understanding "launching" in the metaphor somewhat differently. I think the key point about the interstellar probe example is it's assumed that once it's launched, it's not going to improve on the very long flight to Alpha Centauri. Maybe this isn't actually fair -- if you design a solar sail, pushed by a giant laser that stays in our system, you could likely upgrade the laser while the probe is in flight, but your probe can't build itself a new larger sail, or develop itself a fusion drive. I think research is rapidly building off the prior generation of techniques, but this improvement doesn't show up in the economic impact the article author is complaining about. Actual productivity changes are going to come when large organizations integrate AI models to replace or improve key systems or human-performed functions. This is slow, expensive, and probably a minority of transformations like this are even started, let alone showing fruit, and I think it's rational for a lot of companies to defer starting this work until the tech improves further. There's also a possibly prolonged intermediate phase where some stuff is being done both by an AI-centered system and either a human or a legacy system while the organization measures how well the AI version does (and how stable/reliable any associated vendors are), and during this period, productivity may even take a measurable hit.