Y Combinator recently published their latest Top Companies list online, listing the top 137 YC portfolio startups in descending order of valuation. The headline statistics are impressively shocking:

$300B+ combined valuation

125+ companies valued at $150 million+

60K+ jobs created

Since Rebel Fund’s job is to select and invest in the top 3–4% of YC startups in each new batch, we carefully study past YC startup successes to help us identify patterns that could be predictive of tomorrow’s unicorns. …

When I moved to San Francisco in 2012, it was the place to start a venture-backed technology startup. Everyone knew that Silicon Valley attracted the best software developers, the best entrepreneurs, the best venture capitalists, and all the other A-players necessary for a thriving startup ecosystem. Getting accepted into Y Combinator that year and raising millions of dollars for my YC startup from top-tier VCs validated my decision to move to this startup mecca.

While Silicon Valley still attracts many of the world’s best and brightest, I’ve watched its dominance slowly erode over the years, a trend that has only…

At Rebel Fund, one of our ‘unfair advantages’ when it comes to investing in seed-stage Y Combinator startups is a proprietary machine learning algorithm we developed called Rebel Theorem.

Developed for Rebel by the brilliant MIT-trained computer scientist Ajay Saini, this algorithm uses machine learning techniques to score and screen startups based on their exit probability and forecasted ROI. It’s adapted from a predecessor machine learning model that Ajay developed as his graduate school thesis and ultimately published in the paper “Picking Winners: A Framework for Venture Capital Investment” along with two MIT co-authors.

Since data-driven investing is a hot…

I’ve long been a fan of Tim Urban’s brilliant blog Wait Buy Why. His recent post A Sick Giant is the latest in a long series on how human individuals and societies process information and make decisions. While Tim published this post in January, before coronavirus entered the world stage, his theories about why recent social and technological changes have lead to unprecedented political polarization can also, in my opinion, explain the world’s reaction to this pandemic.

The question that I’ve found most fascinating related to coronavirus is why, in 2020, did the world almost universally ‘lockdown’ to slow the…

If there’s been a common thread amongst the dozen or so posts that I’ve published related to COVID-19 over the past several months, it’s been that the public perception and policy reaction of this virus has not been at all proportional to its objective threat. In my post On coronavirus vs the flu pandemic of 1968 I explored why that might be the case, and most of my hypotheses can be traced back to a single root cause: an extreme media environment causing what I’ll dub a reality distortion field

Thanks to digital communication technologies, we live in a time…

Today I’d like to explore some statistics around potential COVID-19 fatalities and the various ways that Americans typically die. This can help us understand exactly how afraid we should be of this novel virus at every age.

As anyone who reads my posts knows, I’m pretty obsessed with quantifying risk. Spending the last 20+ years of my professional career knee-deep in data as a market researcher, entrepreneur, and investor made me this way and gave me the necessary statistical skills.

What prompted this post was a simple personal question: How worried should I be about COVID-19 compared to all the…

My family is facing a conundrum.

My grandfather is 94 years old and due to strict lockdown policies in his assisted living facility, his quality of life has deteriorated. He’s not allowed to leave the building and can only interact with visitors through a pane of glass. Community meal service has been suspended and he must stay 6 feet away from other residents at all times. He can’t visit his ‘ladyfriend’ and can no longer volunteer as a mediator. He’s essentially imprisoned in his own home.

Should we stage a jailbreak or keep him there, safely out of harm from…

This post was inspired by a recent article published by the AIER titled Woodstock Occurred in the Middle of a Pandemic.

The author reports that a flu pandemic spread from Hong Kong to the United States, arriving here in December 1968 and peaking a year later, ultimately killing 100,000 Americans. Also according to the author, “we might be looking at a quarter million deaths today from this virus” accounting for population increases and health/demographic changes since then.

He also speaks to how this flu pandemic barely made an imprint on American psyche or society at the time. Schools weren’t closed…

As anyone who has read my previous posts knows, I try to think like a scientist, analyzing data on everything from COVID-19 vs seasonal flu fatality rates to the factors predicting how early-stage venture capital will fare in a time of crisis. My background in statistics and market research coupled with 20+ years as an entrepreneur taught me to think skeptically, objectively and quantitatively, skills which have proven valuable in an environment of hyper-sensationalism and hyper-polarization.

But now we’re entering a new phase, a brave new post-covid world which I believe will be qualitatively different than the pre-covid world in…

Let me preface this post by making clear that COVID-19 isn’t the flu. It seems to spread much faster, is likely more fatal, and clearly can wreak more havoc on hospitals. That said, for the purpose of establishing some perspective, I do think it’s sometimes helpful to compare something novel to something familiar, especially in a time of crisis and panic.

To that end, I’ve pulled and analyzed data from the US National Center for Health Statistics, a division of the CDC, which conveniently reports weekly statistics on COVID-19, influenza, and all-cause fatality in the US by age range.

My…

Jared Heyman

Techie and investor. Founder at Rebel Fund and previously Pioneer Fund. Chairman of Infosurv/Intengo and CrowdMed (YC W13). Former Bain consultant. Data nerd.

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