How F1 got the data crunched for its new race car – ClearTips

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friend! Hello and thanks for leaving. Today we have a lot of our usual fare: funding rounds to digest, some data on the startup market (thanks, DocSend), and so on. But we’re starting with our passion: racing.

The exchange has made several jokes this year about technology finding money’s way into the world of Formula One. Companies like Splunk and Webex and Microsoft and Zoom and Oracle and others are sponsoring the teams, races and leagues themselves.

One particular F1 partner of note is Amazon. For example, its public cloud project, AWS, has powered on-screen graphics for games. Sure, sometimes fans wonder how the group’s Compute Cluster is coming up with certain metrics, but AWS’s notes on tire wear are useful and timely.

However, it turns out that behind the scenes Amazon has been more active in the F1 world than ever before. In short, the technology and F1 money story we discussed was just one piece of a bigger puzzle. how so? It turns out that AWS was key to the design process of F1’s new 2022 car.

it looks like this:

image credit: formula One

Very neat, yes?

I’m sure you must be wondering why this is such a swoon. The answer is that the car is designed with some very specific aerodynamic goals in mind. Like a diminutive of something called “dirty air”, a phenomenon when air blowing from behind an F1 car causes the car to struggle to stay on track.

Today’s F1 Cars — We are in the middle of last season with the current generation of Formula One hardware; Let’s go Lando! – Generate a lot of dirty air. Which makes for some awkward racing because the cars on the track can’t get very close to each other for fear of losing their all-important downforce. You know, the stuff that keeps the cars on the tarmac and not in the wall.

In order to design a base car that did what F1 wanted for its next era of competition, namely to cut down on dirty air and allow more close racing, a lot of computing effort had to go into computational fluid dynamics, or CFD. And it turns out that AWS took over the computing needs of the racing group.

The exchange got on Amazon Chime – our first time on the platform, might we add – to chat with F1’s Rob Smedley, its director of data systems, about how it all came together. According to a former engineer at Ferrari and Williams, the racing organization and Amazon have been working on the new car project since 2018. F1 has a lot of in-house brains to handle its side of the matter, while Amazon has provided thousands of cores to do all that. difficult math.

According to Smedley, if his team had used the same computing power that individual F1 teams are allowed – the sport of Formula One racing to help keep teams somewhat on the same level, or to hold Mercedes back The design is chock full of rules, depending on your perspective — it would have taken four days per computation cycle to model two new cars driving one after the other.

But with Amazon providing 2,500 compute cores, the data boffins on the Smedley and F1 can accomplish the same task in six or eight hours. This means the group can run more simulations and design a better car. Sometimes he absorbed even more computation, the data director told The Exchange, adding that at one point last year his team was simultaneously running simulations over a dozen iterations. This was made possible by approximately 7,500 cores powering the data work. The simulation run took 30 hours.

Just to say that yes, there is a lot of technical money in Formula One to help teams do their jobs and stay financially secluded. But F1’s real guts and bolts also have a load of technology. And as an F1 dweeb, it makes me very happy to see my intersecting passion with work.

Now, back to our more regular fare.

The Midwest’s Latest Unicorn

M1 Finance is one such company that continues to grow in my reporting life. Mostly because it keeps raising money and announcing new performance metrics. This week the company entered a $150 million round at a valuation of $1.45 billion. The latest funding for consumer fintech SuperApp was led by SoftBank’s Vision Fund 2.

So, why do we care? Well the funniest thing about the M1 is that the company told us how to track its revenue growth over time. At the beginning of my coverage of the startup its CEO said that it expects to generate about 1% of its assets under management (AUM) as revenue. Therefore, we can track the revenue growth of the company to see how quickly it increases AUM.

And the company keeps on issuing the AUM number. (PR folks, providing longitudinal data is a great way to get us interested in startups!)

Here is a brief overview of M1’s AUM over time:

On its 1% target, they work to target run rates of $14.5 million, $20 million, $35 million and $45 million. Or the company effectively tripled its revenue from last June. That’s great and that’s the kind of growth that investors want to get back. Hence the present day. And the new Unicorn price tag of the M1.


Remember Truvata? We have talked about it before, when it was revealing its plans. Former Microsoft executive Terry Myerson is part of the team, and since I used to cover Microsoft for a living, I looked back on the early days of the startup. As we said last time, Truvata, as a reminder, seeks to “collect a lot of data from healthcare providers, anonymize it, aggregate it and make it available for research to third parties.”

Well, this week the startup announced new partnerships and $95 million in funding. This is a great test! The startup now has 17 partner health groups to boot.

By bringing together a lot of data in one place, the startup hopes to help make the medical world better and more equitable. And now he has billions of rupees to go after that goal. Let’s see what can be done.

other important things

To save marginally on word count and avoid putting the hard brakes on c0py editing here on ClearTips [ed. note: done broke], here’s what else is important that we couldn’t find in other parts:

Cambridge Savings Bank (CSB) forays into FinTech: Remember how Goldman launched Marcus, a digital bank for the masses? It is not alone in the effort. Now CSB has created and launched its own digital-first bank named Ivy. To be honest, I liked the idea: Take a bank that has a long history of operations and a classic tech stack and service suite. Then build something right next to it that is more modern. This is probably a better solution than trying to force the old bank to learn new tricks. Also, if more banks do this, it undermines Neobanks to some extent, doesn’t it?

Code-X Raises $5 Million, Proves You Can Share Your Valuation And Not Burst In Fire: A small note that Code-X, a Florida-based startup that built a “lattice-based data protection platform,” is now worth $40 million thanks to its latest capital raise. No, I don’t know what a “lattice-based data protection platform” is. but i know that code-x announced it Evaluation as part of a primary stage Round. It deserves praise. Good on Code-X.

Finally, the data from DocSend: The document sending company with a somewhat literal name dropped some new data this week that I was chewing on. Here’s the core bit:

[N]ew Q2 2021 data from DocSend’s Startup Index shows a 41% year-over-year (YOY) increase in investor interest and engagement (a proxy for demand) with the startup pitch deck. Actively fundraising links by founders with their pitch deck (an indicator of supply) was up 36% YOY in Q2 2021.

Why is this fun? Demand exceeds supply! Ha! It really says it all.

We’ve been digging into the enterprise world’s Q2 results for weeks, and have somehow failed to summarize. Why Is Startup Valuation Rising? Why Are startups picking up more, and faster? Because among venture-backed companies, investor demand far exceeds startup supply.

In short, 2021.

You are amazing and delightful and look great today!

Next week we’ll have notes on two battery-focused SPACs, namely the Evonix and SES. When it comes to battery technology, energy density and the future of wellbeing, there’s a lot to talk about. and money.

your friends,


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