Notable researchers join $4 billion effort to build self-improving AI - The Seattle Times

Oh, how delightful. Richard Socher — once Salesforce's chief scientist, now evidently its chief escapee — has gathered seven other "notable researchers" to chase the holy grail of recursive self-improvement, all under the banner of a company valued at a cool $4 billion. The plan, as described in the Seattle Times, is to build software systems that can run for days or months in pursuit of goals, improving themselves as they go. Because of course, the only thing that could possibly make AI more reliable is letting it rewrite its own code without anyone watching. What's the worst that could happen? A little unexpected morning paperclip maximisation?

The $4 billion valuation is a particularly rich detail, considering that the company has disclosed precisely zero safety mechanisms or independent oversight structures. In fact, the article notes the company's explicit aim is "recursive self-improvement" — a term that, in any other context, would be the plot of a cautionary sci-fi novel. But in 2026, it's just another Tuesday in San Francisco. Socher, who previously led Salesforce's Einstein AI, seems to have decided that the best way to avoid an alignment problem is to simply not talk about it. After all, if you're too busy counting your billions, you might not notice the runaway train.

And so the pattern continues: brilliant researchers, vast sums of capital, and a collective amnesia about every warning the safety community has issued for the past decade. The article itself doesn't mention a single safety researcher or alignment framework; it's just "self-improving" as a feature, not a bug. One almost admires the audacity — betting $4 billion that you can build a smarter-than-human mind and keep it in a box while it's busy improving itself. Almost.