I disagree with the claim that its sticky, but this is the wrong response. Reductive and doesn't take into account the obvious things (UX, network effects, barrier to entry to use the product). All 3 of these are much better with Muse than they with are similar products.
UX is not a moat, especially in the era of AI software replication. I disagree that there are network effects for MUSE, maybe there will be at some point (e.g. vendors or something sign up for it) but I would love to hear why its better to be on muse when more people use it? Barrier to entry is somewhere they have an advantage, but not more of an advantage than google, or really anyone who has an app installed on your phone already.
How do you get around this? Literally every bank, brokerage, etc... is hell bent on you using your phone for everything from 2FA to passkeys, etc... They dont even imagine people have computers anymore or want two+ physical devices/controls on what can be done with which factors
It requires collective action. Ideally with laws to force interoperability, so folks can move among platforms with ease. Then standards will arise to keep that feasible for app makers.
Without regulation markets coalesce as the winners eat each other like a game of snake. It's a miracle Apple hasn't yet eliminated Android. Although I suppose for some institutions there is only iPhone.
Certainly you can use those, but they're not mandatory (here in Canada at least). Can easily get a card and use physical bank and ATM to do everything, and website logins use email as 2fa.
> There was never any plausible explanation for why this wouldn’t happen.
What a nice post hoc revision of history. Distillation is still an active area of research, that you can distill models as easily as you can it genuinely interesting and absolutely not something that was taken for granted even 12 months ago.
Even 6 months ago this idea that 'using model outputs as training examples' was listed as the reason that all models would fail in the near future due to some spooky circular training catastrophe.
I think you’re being overly combative. It’s intuitively quite obvious that it’s incredibly easy to implement and the circular training catastrophe was only ever a conjecture. It’s kind of like releasing a crypto primitive without knowing a proof. Like… maybe it works, but you can’t assume that just because you don’t know how to break it. You have to remember that 100s of billions of enterprise valuation rely on frontier models being moats. The burden of proof is on those raising valuations assuming they will capture the full market.
I agree that hindsight is doing work here, but DeepSeek R1 from Jan 2025 seemed to heavily leverage distillation, and 18 months is an eternity in this climate.
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