That’s wild! 692 “partners”, I wonder if anyone even sees the irony of that message.

According to the report, the company’s chief financial officer, Susan Li, told staff the division has lost $55 billion since 2019.

$55 billion in losses over ~5 years? That’s a substantial amount.

Microsoft CTO Kevin Scott is of course not a reliable source due to conflict of interest and his position in the US corporate world.

If anything, the fact that he is doing damage control PR around “LLM scaling laws” suggests something is amiss. Let’s see how things develop.

Representatives for developers of the remaining three plugins couldn’t be reached because they provided no contact information on their sites.

You’re asking for trouble if you’re using such random plugins on production sites.

Not all surprising, he’s been pushing the russian narrative for a while now.

We are all waiting. If they don’t come up with proven revenue opportunities in the next ~18 months, it’s going to be difficult to justify the astronomical capex spend.

Pretty dystopian article.

But this will continue, until oligarchs like Altman, Cook, Nadella etc. start getting put into difficult situations; ones that create very strong incentives for them to show humanity (or at least emulate it).

I didn’t really get this either.

I did think the final paragraph was notable, a “zeitgeist of our times” if you will:

The absurdity of the situation prompted tech author and journalist James Vincent to write on X, “current tech trends are resistant to satire precisely because they satirize themselves. a car park of empty cars, honking at one another, nudging back and forth to drop off nobody, is a perfect image of tech serving its own prerogatives rather than humanity’s.”

I am increasingly starting to believe that all these rumors and “hush hush” PR initiatives about “reasoning AI” is an attempt to keep the hype going (and VC investments) till the vesting period for their stock closes out.

I wouldn’t be surprised if all these “AI” companies have come to a point where they’re basically at the limits of LLM capabilities (due to problems with its fundamental architecture) while not being able to solve its core drawbacks (hallucinations, ridiculously high capex and opex cost).

Given a sufficient amount of text, the method is said to be 99.9 percent effective.

If that’s really the case, they should release some benchmarks. I am skeptical. Promising the world is a key component of their “business model”.