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Two Standard Cognition Founders on Changing the Face of Retail — And Reclaiming Humanity’s Most Precious Resource

How many hours have you spent standing in line so far this year — and what could you do if you got those hours back? For the team at Standard Cognition, making in-person shopping seamless means not just removing friction from your next trip to the grocery store, but fundamentally changing the way people spend their time. Below, co-founders Jordan Fisher (CEO) and Michael Suswal (COO) explain the challenges their team is tackling, how they think about automation and the ethics of computer vision, what makes them grateful to be competing with Amazon, and why they believe transforming retail is just the beginning.

First, give us your vision for the future. How will the world be different if Standard Cognition succeeds?

Jordan: Ultimately, we’re building towards reclaiming literally billions of hours people spend waiting in lines every year collectively. It’s crazy that we’re wasting that much time — it’s our most precious resource. I think getting it back will be a windfall for humanity.

Of course, it will also change the time and manpower we expend on retail work. We’ve been through similar changes in the past — before the Industrial Revolution, three-fourths of the population worked in agriculture; now it’s about 2%. I think we’re better off today and will ultimately be even better off because of automation. But it’s important to understand that transitions like this are really rough for a lot of people, and we need to get there as responsibly as we can. No one has answers yet, but the first step is to talk about it, openly and honestly. That’s the thinking behind the automation pledge we’re writing — companies like us have a duty to be part of that conversation.

Co-founders Jordan Fisher (CEO) and Michael Suswal (COO). All photos provided by Standard Cognition.

Michael: Something we also believe we can help with in the long term is making things easier for smaller retailers. It’s incredibly challenging to run a shop without a large workforce. Store owners are staying open 24/7 but can’t afford the staff — it’s such a brutal business.

Above left: Standard Cognition team members and their families enjoying some San Francisco sun during last year’s summer picnic. Above right: From left to right: Ricketta Carson (Standard Store Manager), Rebekah Huggins (Data Implementation Lead ), Rob Ferguson (VP, Engineering), and Kylin Ellison (Technical Recruiting Manager) representing Standard Cognition at AfroTech 2019.
Above left: Chintan Maniar (left, Head of Retail Experience) and Evan Shiue (right, VP, Strategy & Finance) at a baby shower celebrating their newest family members. Above right: Located in a restored historic building in SoMa, Standard Cognition’s San Francisco office offers lots of light-filled space to gather. From the People Team: “We eat together as a reminder to everyone that taking breaks and knowing your peers is just as important as the work you do every day.”
Above left: San Francisco team members at an impromptu happy hour — a common employee-driven effort. Above right: From left to right: Ricketta Carson (Standard Store Manager), Mike Lee (Technical Program Manager), Yvonne Ho (Office Manager & Executive Assistant), and Wasif Islam (Research Engineer) enjoying a Lunch Roulette — a company initiative intended to help employees build relationships with folks they may not work with on a daily basis. Every month, Standard employees are randomly sorted into small groups to share a company-sponsored lunch outing. With Lunch Roulettes currently paused due to Covid-19, the company now uses Donut to facilitate virtual coffees.

How did you and your co-founders decide on this product?

Jordan: It started back when Michael and I were still at the Securities and Exchange Commission. We were working with all these amazing people, building the SEC’s first machine learning infrastructure. And I knew I wanted to start a company in the computer vision space at some point. So I started a research discussion group and invited all those amazing engineers. We read different papers and talked through them once a week, and we settled on this topic about a year in. Making retail frictionless was a fascinating problem, and the technology was not quite there, but close enough to be practical.

Michael: It was also a huge addressable market. That’s a misconception I had before we started out — you hear so much about the growth of e-commerce. But brick-and-mortar retail is actually growing year over year, too, in terms of both number of locations and revenue. And even if you think of it as one pie, physical retail is still almost 90% — it’s a $25 trillion per year industry.

Tell us about the challenges your team is working on.

Jordan: On the technical side, there’s obviously a lot of machine learning work to do. We’re productionizing computer vision in the real world more than anyone else has, so there isn’t a playbook for everything yet. It’s still kind of the wild west — we’re defining best practices for a new industry.

“We’re productionizing computer vision in the real world more than anyone else has, so there isn’t a playbook for everything yet. It’s still kind of the wild west — we’re defining best practices for a new industry.” — Jordan

But at this point, the machine learning piece is actually some of the more straightforward technical work we do. The questions we’re tackling now are how to integrate it into an engineering system, into an account management process, into the entire mindset of an industry. How do you get this into not 10 or 100 stores, but 1,000? How do you design a backend system that solves the unique challenges of this space? The machine learning piece is like the laser in a barcode scanner. When barcode scanners were introduced around 70 years ago, that was cutting-edge physics. But the most interesting work came after that, trying to figure out how to make it work reliably in the chaotic, real-life environment of the front of a busy store.

Above left: The San Francisco office does Halloween 2019. Above right: People Team members show their magical unicorn colors, accompanied by the most magical creature of all — Nala, fur baby of Alex Lebovic (kneeling, VP, People). The SF office is not currently pet-friendly, but Nala got to break the rules for the Halloween costume contest. Shh!
Above left: Data Operations team members showing off new company jackets in the SF office. Above right: Holiday 2019 cheer from the SF fam and their families.
Above left: Tokyo team members enjoying a company picnic, a tradition celebrated by all regions. Above right: Standard Cognition’s newest team members in Milan, where the company recently acquired Checkout Technologies — a startup developing Artificial Intelligence (AI) technology for frictionless retail checkout.

How do you think about the ethics of computer vision?

Michael: A lot of people who hear about Standard Cognition assume we’re capturing biometric data and doing facial recognition, but that’s definitely not the case.

Jordan: Yeah, we take a pretty hard stance on that. The way I see it — if we succeed, we’ll be putting cameras all over the world. And with a system like that, either you design it so it can’t be abused, or it eventually will be. So it’s not “we do facial recognition, but we’re really careful about it.” It’s that our system is fundamentally incapable of doing facial recognition at all.

People also assume that training machines for this work means you’re teaching them to be biased, as if we’re trying to predict what a shoplifter looks like. But it’s the exact opposite — the only thing our system cares about is whether it scans a product or not. It’s actually much more neutral than a human.

“The only thing our system cares about is whether it scans a product or not. It’s actually much more neutral than a human.” — Jordan

Amazon recently licensed its Go technology. How will Standard Cognition compete?

Jordan: The first big difference is Amazon’s technology is very expensive. Standard Cognition is essentially a retrofit, so it has to be cheap and flexible enough to easily deploy in an existing store. With Amazon, everything is custom, down to the shelves. That costs millions, and the end result is turning your store into an Amazon Go store in everything but name.

Even if you get past the price tag, though, I think the biggest difference is that for a brick-and-mortar retailer, Amazon is their biggest competitor, and using their technology means handing over incredibly valuable data. Toys R Us is a great example — they partnered with Amazon, Amazon started to carry everything they had in their physical stores for a lower price, and the stores went bankrupt. So I do think there’s a lot of room in the market for solutions that don’t require you to work with your competitor. We’re actually grateful for Amazon’s presence in this space, because we can show how we’re a foil for their corporate tactics.

What are you excited about in the years ahead?

Michael: On the product side, it’s exciting from multiple angles. We’re fundamentally redefining how people shop, and every part of the company will have a say.

But I think it’s bigger than that, too. Right now, every other industry is watching what we do, because they know computer vision and AI are ultimately going to have an impact that goes far beyond retail. It’s autonomous driving. It’s manufacturing. It’s anywhere where eyes and brains are useful. We’re contacted every week by camera companies, packaging companies, payment processors, cloud providers — and they’re all trying to figure out how to service this industry. I see this as a revolution in the same way the internet was. Computer vision is going to change the way we interact with the physical world, in retail and beyond, and we get to help lead the way.

Interested in joining the team at Standard Cognition?

Get in touch or check out open roles.

Your moment of Zen: The 2019 San Francisco family picnic. Remember picnics?

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