Plus, China’s market opens just as it closes, and narrative responsive design on the web
Open AI’s capped returns
OpenAI announced yesterday
that they are going to be offering a “capped return” security for
investors as part of the for-profit/non-profit split the organization is
creating:
As mentioned above, economic returns for
investors and employees are capped (with the cap negotiated in advance
on a per-limited partner basis). Any excess returns go to OpenAI
Nonprofit. Our goal is to ensure that most of the value (monetary or
otherwise) we create if successful benefits everyone, so we think this
is an important first step. Returns for our first round of investors are
capped at 100x their investment (commensurate with the risks in front
of us), and we expect this multiple to be lower for future rounds as we
make further progress.
I candidly don’t understand
this structure at all. For venture capitalists — and particularly
early-stage investors — returns are driven by one, maybe two, and
extremely rarely three startups in a portfolio (that would be Benchmark’s 2011 fund,
which includes Uber, Snap, and WeWork). That one outlier investment may
drive a majority of all fund returns. If OpenAI were to be that
investment, how you could you possibly relinquish the remaining upside?
Maybe you could prospectively sort of accept this, but how would you
explain to LPs that “ah, yes, seven years ago we decided to give up that
next 150x” or whatever.
OpenAI
LP (the for-profit entity) is trying to target more mission-oriented
investors, who presumably value incentive alignment but not (huge)
profits. That’s fine, but the idea of capping a return as a mechanism to
capture run-away value creation seems really off to me and should be
discouraged.
My colleague Devin Coldewey also had a negative take, but sort of in the opposite direction — that OpenAI “may not be quite so open going forward” and is going to focus more on profits than science. That’s a fair criticism as well, although I think the profit motive will get us to AGI faster.
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Eliot Peper and “narrative responsive design” on the web
A few years ago, Peper published True Blue,
a short story about discrimination in which people’s life outcomes are
determined by the color of their eyes. It’s a parable to our own world,
infested with the kind of speculative details that Peper is known for.
One
of the counterintuitive lessons we learned was how powerful it is to
obscure certain details, letting readers bring more of their imagination
to the story. Specifically, we discovered that detailed lines often
trigger the sense of something being depicted for you, so we smudged and
faded and shadowed until we felt the right balance of detail and
suggestion. This philosophy carried through to design — which so often
aims to reduce tension by making experiences simple, intuitive, and
convenient. But stories thrive on conflict, and Peter challenged himself
to use design to evoke tension instead of erasing it.
He even
engineered a new tool that cropped images so that they adapted to
different devices and screen sizes not only by changing size, but
actually changing image composition to preserve narrative content and
emotional impact. When I told him about the project over a slice of
Arizmendi pizza, author/friend/media experimenter Robin Sloan coined a term for this new technique: Narrative Responsive Design.