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Technology-driven Medicare advisor improving how seniors choose health coverage. Visit us: https://t.co/M0mwwxUMJU

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Chapter
Chapter@askchapter·
Simply the best.
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Chad Byers 🦍
Chad Byers 🦍@chadbyers·
Susa co @askchapter raised $100m at ~$3B. We have ~15% of Susa III dollars invested in Chapter. 3x-5x more than a typical fund would have in a single company. It's very easy for investors to claim they have high conviction in a company, but the truth is always in the data. How concentrated are they in that single name? We led the seed and have invested in every round. When you work with founders like Cobi and the team he's built around him, you go all in. h/t @SethGB pulse2.com/chapter-100-mi…
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The Information
The Information@theinformation·
An AI-driven startup with 90% gross margins is scaling fast while keeping staffing lean, challenging how traditional Medicare brokers operate. Read more in today's AI Agenda newsletter: thein.fo/4t8UKf2
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Chapter
Chapter@askchapter·
Just raised our Series E, announcement below. We're just getting started.
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Chapter@askchapter·
@DouthatNYT Reinventing the core KPIs of Judaism from first principles
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Ross Douthat
Ross Douthat@DouthatNYT·
Put it on a bumper sticker: "Two things are important now, deep learning and fertility." x.com/JesusFerna7026…
Jesús Fernández-Villaverde@JesusFerna7026

I concluded my Henry Family lecture at the University of Miami last Thursday by saying: “Two things are important right now in life: deep learning and fertility. Everything else is noise.” We are only starting to glimpse what these two forces will do to global life over the next fifty years. And they interact: deep learning will reshape demographics, and demographic collapse will reshape automation. Nearly all my posts on X (except some parochial commentary on Spanish economic policy) revolve around these two facts. So does most of my current research. Even work that does not seem directly connected turns out to be, once you look carefully. My papers on geoeconomics and international macro are about figuring out some of the consequences of deep learning and fertility. For example, my work on China focuses on its abysmal demographic future and how the U.S. is positioning itself (rightly or wrongly) to address it. And my work on political polarization and the welfare state is about the consequences of decades of low fertility in Western Europe. When people talk about political change in Western Europe, they are talking about low fertility, whether they know it or not. It is not clear that modern representative democracy can survive sustained fertility rates of 1.3. I do not say that with glee. The reason I decided to spend my life on academic work in economics is that I realized, when I was much younger, that daily events are irrelevant. The things that concern the media and 99 percent of commentary on X are largely irrelevant. One political party does better or worse in the next electoral cycle because of internal fights or a good campaign. At a fundamental level, none of it matters: the political outcome 25 years from now will not depend on those accidents. As Alexander Gerschenkron said, Clio is not a tidy housewife. The rise of any political movement is always full of advances and retreats. Social change waxes and wanes. But at the end of the day, as my favorite historian Fernand Braudel put it: “The events of history are merely surface disturbances, crests of foam that the tides of history carry on their strong backs.” or in the much better original: “Les événements de l’histoire ne sont que des agitations de surface, des crêtes d’écume que les marées de l’histoire portent sur leur dos puissant.” The tides of history today are deep learning and fertility.

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Matthew Yglesias
Matthew Yglesias@mattyglesias·
@MattZeitlin What do you need to know about China other than that the word for crisis combines the characters for crisis and opportunity?
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Matthew Zeitlin
Matthew Zeitlin@MattZeitlin·
Anyone else feel like all the time they’ve spent reading about Europe was a complete waste and they should have been chinamaxxing the whole time
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Chapter
Chapter@askchapter·
Another great conversation. Link below.
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Chapter@askchapter·
Great conversation, thanks @Ajuggles. Link below.
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Chapter@askchapter·
@devahaz The Medalmogging of the Stanfoid Traitor Gu by State School Patriot Liu
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Deva Hazarika
Deva Hazarika@devahaz·
Eileen Gu growing up in Sea Cliff and being the villain and Alysa Liu growing up in Richmond and being the hero is perfect scriptwriting
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Chapter
Chapter@askchapter·
Announcing you left xAI today? Come work on interesting real world AI applications with us at Chapter!
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Michael Sanislo
Michael Sanislo@the_sigh_op2·
@mattyglesias @KelseyTuoc True story: during a recent open enrollment, I was trying to help someone switch from Medicare Advantage back to Original Medicare because they had provider issues with the former. The medicare agent I spoke with kept trying to push other Medicare Advantage plans instead.
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Chapter
Chapter@askchapter·
We agree with @FastCompany that you should get to know us.
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Chapter@askchapter·
@mattyglesias Honestly a world in which they treat us like dopey children/adorable pets is probably the best case scenario
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Auren Hoffman
Auren Hoffman@auren·
new World of DaaS pod with Chapter CEO @CobiBGantz on why medicare was more broken than you think (and hopefully is not getting better): * 24,000 plans across the country * $100B+ annual fraud * lifetime penalties for missing enrollment * CMS keeps hiring Accenture (despite knowing it will fail)
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Chapter
Chapter@askchapter·
@Jimmyking35 This is what it feels like to speak with one of our licensed advisors about Medicare
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Jimmy King
Jimmy King@Jimmyking35·
Someone is flying around City Hall tail whipping in a little buggy to Olivia Dean’s ‘Man I Need’. Philadelphia is the best city in the world and you can’t convince me otherwise
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