Michael Gronager once didn’t know what KYC meant. Now his blockchain analytics company is helping the financial world apply it to crypto.
Chainalysis CEO Michael Gronager spoke with Protocol about trailblazing blockchain analytics.
Michael Gronager found himself on the back foot at a conference in London a decade ago. Then an executive at Kraken, he was chatting up a Mastercard executive who kept mentioning terms like KYC and AML.
“I did not know what they meant,” he told Protocol. “I knew nothing about finance.” Now CEO at Chainalysis, a top blockchain analytics company, he’s solving customer verification problems for a broad range of financial players. In other words, KYC and AML are driving business his way.
Gronager called the incident “kind of funny and a little bit embarrassing,” but it definitely illustrates the kind of dilemma faced by the technologists who were pioneering crypto then.
It was an odd moment for Gronager, who had co-founded Kraken with Jesse Powell after concluding that bitcoin and crypto was “a big paradigm shift in computing.” But that conversation helped shape his path forward: In just a few years, he pivoted to another segment of the crypto industry focused squarely on the finance jargon that befuddled him in London. It was also an area where he could play to his strengths as a veteran big data technologist.
“I could see that there was a need for a scalable process to do origin of funds and transaction monitoring of crypto,” he told Protocol. “There was an opportunity to build a blockchain analytics company. Back then, that didn’t exist. No one really understood what that was.”
In an interview with Protocol, Gronager talked about how Chainalysis blazed the trail in on-chain analysis. He also shared his regrets about how blockchain analytics could have softened the blow of the crypto market crash and his hope that the technology will eventually play an important role in derisking the controversial industry.
This conversation was lightly edited for clarity and brevity.
Can you talk about your decision to leave Kraken, where you were a co-founder, to launch Chainalysis?
That’s a great question. It’s always fun to tell the story again because every time you remember something new and there’s another angle.
My entire career has been around big data. I did my Ph.D. in quantum mechanics. I was doing computational physics on different distributed computer systems. I dived into virtual reality. There was big data in terms of 3D models visualized. Then I moved to doing computational physics at CERN, the particle accelerator there.
I stumbled upon bitcoin in 2011. When I saw bitcoin for the first time, I was like, “This is a paradigm shift in computing. This could be something on the size of the internet, if not bigger. And it’s something I need to spend time on.” I left my career in the public sector. I dived deep into bitcoin. I was basically trying to figure out: How do you run a business here?
Of course, there were crypto exchanges. But to be honest, I knew nothing about finance. I can tell you a story that is kind of a bit funny and a little bit embarrassing. I was at a conference in London, probably back in 2012. I’m talking to one of the top people of Mastercard in the coffee break before I go on stage. And he’s talking about words like KYC and AML. And honestly, I did not know what they meant. So I’m basically trying to Google it before I go on stage. Suddenly I realized, “Ah, oh, yeah, I actually know what that is. I know what they’re talking about.”
I’m not from the finance industry. I’m from big data. I joined Kraken because I was probably one of the few people interested in the industry who had a real career, who had a background working at big organizations, building an operational framework, who understood how to work with governments because I’d done that in my research. When I joined the founding team of Kraken, I’d been very, very deep in the source code of bitcoin. I’ve been contributing to the core protocol, and had built wallet systems that were way ahead of the industry.
Did Jesse Powell invite you to join, and how did that conversation go?
I met Jesse at the first crypto event I attended in New York in 2011. We were both early in the industry. We started talking and basically connected. We had the same views on the industry around a need for running things in a more professional manner. We were looking at the Mt. Gox exchange [hack] and deeply concerned about that. We were discussing [the idea] that someone needs to do something better than that. We stayed in contact from there on. In 2012, I realized that he wanted to build an exchange. I became part of that team and we started building Kraken.
In 2013, FinCEN issued its first guidance around cryptocurrencies. One of the things I keep reminding regulators today when they look back at the industry is everyone in the industry in 2011, 2012, 2013 — they were techies. They knew nothing about finance. There was no idea of this being finance. This was cool. You could buy a pizza with it. Maybe you get rich. That changed in 2013 with the guidance from FinCEN. The banks would not let you use the platform because they were afraid of being part of a money-laundering scheme. They couldn’t understand what we were doing.
I realized that with all of the anti-money laundering policies of different countries, everyone talks about transaction monitoring. You could not assess the origin of funds in an online exchange without adding a ton of paperwork and a ton of verification of that paperwork. So I could see that there was a need for a scalable process to do origin of funds and transaction monitoring of crypto. That was the summer of 2014 when we really started to look into those things.
I made presentations for our own banks around what could be done in crypto: It’s way more transparent than you think. I had conversations with regulators around the transparency of crypto. I kept saying how transparent crypto is in principle. And they didn’t understand.
One of the things I keep reminding regulators today when they look back at the industry is everyone in the industry in 2011, 2012, 2013, they were techies. They knew nothing about finance. There was no idea of this being finance. This was cool. You could buy a pizza with it. Maybe you get rich.
I basically realized that this is an opportunity. There’s an opportunity to build a blockchain analytics company. Back then, that didn’t exist. There was no blockchain analytics. No one really understood what that was. That was exactly the company that I wanted to build. I just didn’t realize that before that point. I wanted to build something cool in crypto, and it turned out to be blockchain analytics.
I had to leave Kraken. I discussed that with Jesse. He could see it was a good idea. Initially, I was thinking it could be part of Kraken, but it didn’t make sense because it was so different.
There were a lot of people who didn’t believe this was even a thing back then. So it was impossible to get funding. There was a belief that crypto was meant to be anonymous, and I was going to break that and that was not right. So there was pushback initially from investors and others.
Can you give an example of a conversation that sticks out for you, maybe an investor or someone saying, “Are you crazy?”
I will not put his name on it, but I talked to an investor who invests in basically everything in the industry and also invested in Chainalysis in the end. I remember sitting in their office.
By mid-2015, I had sold to the FBI and to other government agencies. It was kind of clear that what we are building is useful. But the investor was like, “Yeah, you can sell for like $30,000 to the FBI. But how many other FBIs are there? This is going to be niche.” No one really saw that the size of this market would be counted in billions at some point.
That’s a good segue to my next question: How do you make money?
One of the very, very early decisions was basically thinking the most valuable companies on the internet today are selling things online, B2B, and charging money for it. I wanted to build a company where you get recurring revenue, where people subscribe to a service, a good way to grow the revenue over time. The most valuable companies are typically SaaS companies that can build recurring revenue. They have good multiples because there’s a lot of stickiness in that revenue. So we did that initially. We are still doing that.
The change that happened in 2015 was the realization that our data and software is actually so powerful, and we don’t want it in the hands of the wrong people. So we had to create a vetting process in the sales process where we don’t want the FSB from Russia to buy it or others to get access to it. That would today be called enterprise SaaS. It typically moves the deal sizes from thousands of dollars to hundreds of thousands of dollars. So that’s where we are today.
We could have predicted that something was about to fall apart.
Our average deal size is more than $100,000. And we see huge growth in our customers because we talk to them a lot. The account sizes are growing 50% year-over-year basically, so there’s a lot of growth in the accounts that we are selling to. In the early days, the main customer was government. It still is. So we have 200 public-sector institutions in some 50 countries in the world, roughly, that are our customers. Sixty percent of our revenue today is from the public sector.
They’re not touching crypto in terms of buying and selling cryptocurrencies. But they want to be able to trace it. So if a hack happens, if they think it’s being used for selling drugs or other things online, they want to trace the funds. They want to build a court case. The product enables them to be smart about crypto and do these investigations. That we ended up becoming a very big business.
Then we have the other side of the business, which is the private sector. In the private sector, the typical customer would be a crypto business. It could be a crypto exchange. It could be a gaming platform. It could be a DeFi platform. It could be others in the crypto space that need compliance and also want to have business intelligence information about their customers.
A lot has changed in the last decade in crypto and blockchain. What has been the most difficult change for the business?
When we see times like the last couple of years, when the entire world was [into] crypto — and we saw that back in 2017, as well — it’s actually hard to run a business because, first of all, everyone thinks they’re going to be rich tomorrow. Everyone gets weird. You suddenly realize there’s a few people in the company who might be key people that suddenly got rich on crypto and don’t need to work anymore. I’ve seen that in Kraken back in the day.
You’re basically operating in an ecosystem that’s growing so fast, it’s really hard to make the right decisions and do the right things. We have seen some extremely fast bull runs where the market just explodes, capital keeps flowing in, new protocols are being launched, new projects are being launched, and you basically are being pulled in all directions all the time.
I can see the opportunities growing 10x a day, which is amazing. But at the same time, I need to make decisions at a millisecond level in terms of where I should deploy resources. Where should we grow? What should we do? If I make the wrong choice, I might lose out on the biggest opportunity. What we saw last year was hard.
Can you give an example of a decision that was hard, and maybe a mistake that you made?
A good question. One is from the last bull run in 2017. We saw the ICOs. Everyone in crypto did an ICO. They all launched funds that way. Everyone else wanted to do an ICO and everyone was like, “Why are we not doing an ICO?”
My gut feeling told me not to do it. But I wanted to play it out to the team. So I remember an event where we were discussing it and I just pretended to the team that I wanted to do it just to see their reaction. And everyone got a little bit concerned because I was basically telling them we’re going to launch an ICO. We’re going to raise money this way.
And people are like, “Yeah, but is it legal? We’re selling to the SEC as one of our customers. They might not like that we are doing an ICO.” We basically ended up not doing it because of the premise that it’s actually not well understood from a regulatory point of view, whether it was legal or not.
Then a few months or half a year later, the SEC actually cracked down pretty hard on ICOs. They felt that this was selling unregulated securities and it was wrong. So I’m happy we didn’t do it. But it was also one of these things that had we done it right, it might have been an opportunity. It’s hard to say. And I would say this today: I would say I feel that there [could] have been a core piece of regulatory innovation that I could have created to enable the ICOs to be a success.
What do you mean?
What happened in the crypto space in the early days was really interesting. We saw that you couldn’t trace cryptocurrencies. It was more and more dangerous and all of that. Because of what we innovated at Chainalysis, it was suddenly not a risk for society anymore. There was no need to go hard on it from a regulatory point of view.
So I always think about every time we see challenges from a regulatory point of view, it’s easy to create technology where you can move funds super fast and make investment schemes like we saw with Three Arrows and terra-luna. That’s the easy part. The hard part is to create the regulatory technology that enables these technologies to work with low risk or less risk. That’s kind of the foundation of Chainalysis.
Every time I see a challenge in the industry, I’m like, “This is an opportunity for us. If we make the right innovation now, we can change the industry.” Otherwise regulators will come in and it’s done. I’m always like, “Can we do this fast in that situation?”
I still don’t know what we should have done. But I’m always thinking that there might have been a way where we could have enabled regulators to get the right oversight and feel they did the right thing for consumer protection and other things through technology. That would have been an opportunity for the company.
You mentioned Three Arrows and Celsius. What are some of the things that you think could have been done better with blockchain analytics given what happened?
The challenge in the industry today is there’s a cross section between traditional finance and crypto. What happens today is that many of the crypto exchanges operate also like traditional finance. Someone is a well-known customer and they will operate on credit. So they will call the exchange and say, “I’m going to buy $10 million of bitcoin tomorrow.” And they say, “OK, you just do it. You can hand in the money later.”
Of course, that happens in traditional finance: Big private equity companies getting loans from very big established banks to buy more private equity that’s highly, highly leveraged investments. In the crypto space, we saw the same. We saw it with Three Arrows. We saw it with Celsius and others. Suddenly that’s not something I can see on the blockchain. I don’t know. I can’t see that. So the challenge here becomes: how do we include that information? There were deals happening in terra-luna that were not visible on-chain.
If decentralized means that I’m my own bank, and everything is out of reach of governments, they’re wrong.
But I would still say — if I should point fingers at myself and blockchain analytics — I think that when our industry and what we’re building at Chainalysis matures even more, there will be a situation where a lot of these schemes and all of these layered investments will actually be more clear. You can build products that can showcase them.
Both on Celsius and terra-luna, we were trying to assess: Could we have predicted this with our data? And the answer was, sadly, yes. We could actually have seen that stuff was going on. We could have predicted that something was about to fall apart. And now, we are, of course, focused on enabling that [kind of prediction].
If we can do these things, it means that that’s a very valuable product. It derisks your investment. Suddenly, if you can get early warning that this is falling apart, you can leave in time, and that makes the investment less risky. I think that that product could really help regulate the industry. So I think that there’s stuff that can be done in blockchain analytics. But there will be parts where, as I said, if it happens on a phone call, I cannot know about it.
I’m assuming you’re using AI to figure these out.
We are. Not on the phone-call side. Not even AI could do that.
Crypto is now 13 years old. What do you say to those who argue that it is no longer as decentralized as it was in the beginning?
If decentralized means that I’m my own bank, and everything is out of reach of governments, they’re wrong. But if decentralized means that, like the internet, we build a platform where anyone in the entire world can create a company based on that protocol and participate in that and be a partner in that without any approvals from anyone, then it is decentralized.
Today you can start a business operating on bitcoin in any corner of the globe. You can do that on Ethereum. You can write a smart contract in Bangladesh. You can write a smart contract in Australia. You can write it anywhere on the globe. You can deploy it to the blockchain and you can build a great big business and it’s very decentralized and very ubiquitous. Then it’s a huge success. And at the same time, you can own it yourself. You don’t need a provider. Everything is available everywhere.
But if you then look at the concentration of funds and other things, that will follow another pattern. We will see a concentration of cryptocurrencies. We’ll see a concentration of other resources. I think it’s a success in that sense. In the sense of the concentration that happens with wealth, that’s a law of nature. That’s not something we should try to break. It’s just how it is. It’s fine. It’s OK.
But you just described earlier a problem about some transactions that you will not see on the blockchain where people will be able to concentrate their resources and their power to do things that may not be beneficial to everyone.
As the crypto industry grows and it becomes a bigger and bigger part of finance, I think people will see that hiding becomes hard. It’s actually hard to hide. Even for North Korea, we’ve seen they stole a lot of funds over the last year. We have prevented them from cashing out. We have also helped in seizing the funds when they try to cash out. So we have seen that even for a nation-state actor, it’s not a free game. You actually meet resistance here, and that’s only going to be more in the future. That will be a healthy balance, hopefully.
Benjamin Pimentel ( @benpimentel) covers crypto and fintech from San Francisco. He has reported on many of the biggest tech stories over the past 20 years for the San Francisco Chronicle, Dow Jones MarketWatch and Business Insider, from the dot-com crash, the rise of cloud computing, social networking and AI to the impact of the Great Recession and the COVID crisis on Silicon Valley and beyond. He can be reached at bpimentel@protocol.com or via Google Voice at (925) 307-9342.
Here’s how one startup is helping big payments players get ready: Fireblocks is powering crypto spending tools for Checkout.com and FIS’ Worldpay.
Fireblocks’ new product enables payment service providers to settle a variety of different types of crypto transactions.
Tomio Geron ( @tomiogeron) is a San Francisco-based reporter covering fintech. He was previously a reporter and editor at The Wall Street Journal, covering venture capital and startups. He was also as a staff writer at Forbes covering social media and venture capital, and edited the Midas List of top tech investors. He can be reached at tgeron@protocol.com or tgeron@protonmail.com.
Crypto payments are a long-promised feature of the technology, dating back to the original bitcoin white paper. But many obstacles have left crypto payments mostly limited to geographies with runaway inflation or tied up in the operations of crypto businesses like miners.
But more companies are building the necessary parts of a system for mainstream crypto payments and expect adoption to happen, even if it may take some time. Mastercard, PayPal, and Stripe have recently made moves to accommodate crypto in consumer payments.
Fireblocks, the crypto infrastructure startup with 1,500 clients including Revolut and Prime Trust, is the latest to do so. The company is releasing a product Monday that enables payment service providers to settle a variety of different types of crypto transactions.
Fireblocks’ new Payments Engine has been used by Checkout.com in a pilot phase and done $1 billion in crypto transactions this year. Now FIS has signed on to do merchant settlement with Fireblocks. FIS’ Worldpay unit already handles card-to-crypto transactions for four large U.S. crypto exchanges, offers USDC settlement, and is planning further moves into crypto.
By providing technology for large institutions to manage and transfer crypto securely, FIreblocks is providing a key piece of the puzzle that these financial firms need to enable crypto payments. While all the other elements needed may not be in place yet, Fireblocks’ offering is laying the groundwork for a future in which spending with crypto is commonplace.
Fireblocks does not handle fiat-to-crypto conversions and doesn’t intend to get into this aspect of payments directly. Instead, it provides technology to handle settlement and other services related to handling crypto.
For example, if a consumer buys crypto on an exchange with fiat currency using a Worldpay-based credit card, the exchange handles sending the crypto to the consumer. Worldpay can then use Fireblocks to settle securely with the exchange via stablecoins in minutes, using a wallet transfer instead of sending fiat, which could take two to three days to settle. Transactions can also be sent 24 hours a day instead of between 9 and 5 on weekdays.
Fireblocks also provides the compliance and reporting that large financial institutions need to do these types of transactions, said Ran Goldi, vice president and head of payments.
Besides helping merchants take payment in crypto, the startup’s new tools could be used for other payment scenarios, including cross-border transactions, creator payouts, and subscriptions. That’s potentially helpful for marketplaces and other companies that currently deal with a wide range of fiat currencies.
For some merchants, the ability to settle almost instantly in stablecoins may be attractive even if they aren’t crypto companies, Goldi said, for the cash flow benefits. Still, he acknowledged, crypto payments have a ways to go. Barriers include regulatory questions, a lack of infrastructure for required identity checks, and the paucity of banks willing to hold stablecoins for customers.
Some banks like Silvergate and Signature are offering digital assets custody services for merchants. If more banks offer support for stablecoins, more merchants will use them, Goldi said. While now there may be “tens” of banks worldwide that support crypto, he expects that number to increase.
Tomio Geron ( @tomiogeron) is a San Francisco-based reporter covering fintech. He was previously a reporter and editor at The Wall Street Journal, covering venture capital and startups. He was also as a staff writer at Forbes covering social media and venture capital, and edited the Midas List of top tech investors. He can be reached at tgeron@protocol.com or tgeron@protonmail.com.
Today, companies across the world are facing unprecedented uncertainty. Consequences of the global pandemic, ongoing trade concerns and political conflicts have disrupted business operations, which has, in turn, exacerbated existing workforce issues, created supply shortages, and made demand forecasting and customer engagements more complex. How are businesses expected to thrive in this world order? According to a new report, the answer lies in the power of automation to stabilize workforces, drive economic growth, and build business resilience. Introducing the Automation Economy.
The Automation Economy—the focus this week at Imagine, and in response to Automation Anywhere’s third edition of the Automation Now & Next report—will accelerate how businesses scale automation and sustain performance. Of the 1,000 global organizations surveyed in the report, more than a third indicated automation will lead them out of global crises.
“Today’s business leaders must look beyond their current business processes and imagine how automation can enable them, and others, to make bolder moves and reimagine work,” says Mihir Shukla, CEO and co-founder of Automation Anywhere. “The reality is we just don’t have enough knowledge workers to do the work, and there’s much more work to be done. It doesn’t matter what you produce, but more importantly, how you are going to get the work completed and deliver the product to your customers?”
A fireside chat with Automation Anywhere youtu.be
For certain sectors, intelligent automation is a must-have, not just a nice-to-have. In financial services, automated processes can include loan payment management, car loan applications, bank account management and much more. In a case study published by Automation Anywhere, one data firm needed data to be converted from one system to another. The projected time for a vendor to finish this process was two years, but the migration was completed in just 12 weeks with automation and bots running 24/7.
In healthcare, automation can improve patient outcomes by supporting medical advancements, managing patient intake, scheduling, claims and billing, freeing staff to ensure patients get the care they need. In retail, automation services can make ERP and supply chain processes more-efficient, and can include creating and disseminating reports, clearing invoices, and checking payment status against service-level agreements (SLAs).
The C-suite views automation as a vital tool in the business toolbox that can revitalize their workforce and improve employee retention. After all, if workers don’t have to focus on routine manual tasks, they can be more engaged with other aspects of their job. In the Automation Anywhere report, around 40% of survey respondents believed that more than half of all employees could benefit from even just a single bot to help them in their daily work routine.
Also, a whopping 94% of respondents said moving employees to higher-value work is a top priority for the coming year.
For nearly twenty years, according to Shukla, he has been on a mission to unleash human potential by helping every company in every sector across the globe build a digital workforce and succeed with automation.
Teaming up with a digital coworker is par for the course for businesses seeking to address key challenges, but it is also useful as a strategy to interest employees with a new kind of colleague. At Automation Anywhere, they are using hundreds of digital coworkers internally in multiple departments. “Our employees aren’t just more productive with bots — they are happier,” says Shukla. “Employees and customers have quickly come to not only rely on their digital workers but to engage with them, giving them friendly nicknames and wanting to communicate with them in a more personal way.”
Shukla goes on to say that Automation Anywhere is delivering on that promise for customers. “When we empower human workers to offload manual tasks to automation, we unleash their potential to pivot to the next big idea, build deeper customer relationships and drive business growth.”
That is a future many business leaders are embracing to attain a competitive advantage.. A quarter of respondents in the Automation Anywhere report said they are escalating automation funding by at least 25% to help speed up automation deployments. Sitting on their hands simply isn’t an option any longer, especially as more companies focus diligently on building a resilient workforce buttressed by both human and digital workers.
Digital transformation continues to accelerate at a rapid pace across enterprise businesses, and it can be overwhelming to adapt to an ever-evolving culture of technological change. But to drive growth, embracing the Automation Economy can be a harbinger of positive outcomes ahead. Business leaders can continue to help run current operations with the status quo model, or they can choose the bold and rewarding path of making calculated bets and exploring new technologies and solutions to scale automation across the company.
Form Energy CEO Mateo Jaramillo explains the promise of iron-air batteries and why the grid needs multiple types of storage to be truly decarbonized and resilient.
Form Energy’s technology sounds deceptively simple.
Lisa Martine Jenkins is a senior reporter at Protocol covering climate. Lisa previously wrote for Morning Consult, Chemical Watch and the Associated Press. Lisa is currently based in Brooklyn, and is originally from the Bay Area. Find her on Twitter ( @l_m_j_) or reach out via email (ljenkins@protocol.com).
Battery storage has emerged as a key technology to reach net zero.
So far, lithium-ion batteries have largely been used by utilities to store renewable energy when the sun sets or the wind stops blowing. However, existing utility-scale storage can only discharge energy for up to four hours at a time, meaning that systems can falter when the grid needs to provide widespread power for a long period of time, such as during a heat wave or major storm. To free the grid from fossil fuels that currently provide that baseload, we need long-duration batteries that provide power for at least several days at a time.
Form Energy is developing batteries that use an iron-air technology and could be poised to fill that gap. Investors certainly seem to think so. The 5-year-old company raised a whopping $450 million in its series E funding round, bringing its total investment to around $800 million. It counts high-profile VCs like Bill Gates’ Breakthrough Energy Ventures and Energy Impact Partners among its investors, as well as the steel company ArcelorMittal. The latter is also among the industrial firms that Form Energy has partnered with to acquire iron for its batteries and deploy them to provide power for notoriously hard-to-decarbonize sectors. (The head of ArcelorMittal’s investment fund said its investment leaves it “well-placed to directly benefit as the technology matures to industrial scale.”)
Form Energy signed a partnership with Georgia Power, its first with an investor-owned utility, earlier this year. The duo will work to deploy up to 15 megawatts of storage capacity. In 2020, it announced a much smaller 1 megawatt pilot project with the Minnesota cooperative Great River Energy. CEO and co-founder Mateo Jaramillo told Protocol that Form Energy will announce more contracts in the near future, and that the company is targeting late 2024 for commercial production of its batteries.
The technology sounds deceptively simple. Form Energy submerges a porous piece of iron (the anode, reminiscent of a flat and thin brick) in an electrolyte solution, and then harnesses the metal’s natural rusting process to charge and discharge energy over the course of several days. Every battery has both a cathode and an anode, which pull electrons from a circuit and push them out, respectively. But in Form Energy’s case, Jaramillo said, “the cathode is a bit of a false term.”
“The active material is not inside the battery,” he said. “It’s the oxygen in the air.”
The oxygen is highly controlled, entering the washer-and-dryer-sized batteries through a specialized membrane that keeps it from going out again. Once it makes contact with the electrolyte solution, a series of chemical reactions causes the iron to rust.
“Before we zeroed in on iron-air batteries, we considered what is fundamentally able to scale and what is fundamentally safe, and what is fundamentally available to us to work with,” Jaramillo said. “Iron ticks all of those boxes.”
This technology has been around for decades and was the subject of a 1970s Department of Energy study in the wake of the oil embargo and accompanying energy crisis. But in Jaramillo’s view, it is only now being commercialized because the technology is particularly well-suited to the demands of today’s grid. He spoke with Protocol about how the iron-air technology works and the importance of long-duration storage.
This interview has been lightly edited for brevity and clarity.
Can you explain exactly how an iron-air battery charges and discharges energy?
We can drive the chemical reaction that causes rusting in both directions. When you return the iron to its metallic state, you’re essentially charging it and preparing it to be discharged, because iron wants to rust. But we know how to keep that from happening automatically by controlling its conditions. In its charged state, a metallic iron anode doesn’t have oxygen working on it. And then in the discharged state, we’re adding the oxygen to it, and in that process, it gives up the electrons.
How do iron-air batteries fit with the energy storage system?
Today, the lowest marginal cost source of electricity is renewable. There is very low-cost wind and solar, but those resources only show up when the weather permits. And when we have a weather-driven power-generation system, we need to be able to solve for the intermittency. The easy pattern to solve for is the daily cycle — the sun going down and coming back up every morning — but we also have patterns around storms and seasonality. To solve that problem, you want really low-cost batteries so you can provide storage for days at a time, and there are trade-offs to get there.
Lithium-ion batteries are very good at cycling many thousands of times. If I charge my phone a few times a day, I’m getting maybe 1,000 cycles per year out of my battery. But let’s say we have a battery that discharges for a week and then charges for a week. That means that the theoretical maximum number of cycles I could get out of my battery is 26 per year. So if I want it to have a 20-year life, we’re talking about roughly 500 cycles. If I want to keep the battery low-cost, I don’t need to prioritize thousands of cycles like I would for a lithium-ion battery.
The trick is to make the right trade-offs in pursuit of the attributes that you really care about. On the grid today, we have great daily cycling batteries like lithium-ion, but what we don’t have are these very low-cost batteries that allow you to smooth out multiple days of intermittency associated with the power generation driven by weather. And that’s what Form Energy is.
Do you have any supply chain challenges?
We certainly didn’t anticipate the supply chain problems for battery materials caused by the pandemic, but we did anticipate the scale of what we’re trying to do. And if you are competing with the automotive industry for the same materials, it’s just going to be very difficult.
How have recent policy developments, such as the bipartisan infrastructure law or the Inflation Reduction Act, informed your work?
There are benefits in both of those pieces of legislation. There are specific programs in the bipartisan infrastructure act for long-duration storage, including for demonstrations. And in the IRA, the benefit to Form is direct and indirect. The biggest benefit is probably indirect, in that it is setting up a path for the energy transition broadly. If you use renewable power, you’re going to want this kind of solution. But there are also direct benefits for storage in there, in particular the investment tax credit. That’s the same vehicle that’s been used for solar for a very long time and has helped bring down costs, but it is calling out storage for the first time as a qualifying technology. The owner of the asset qualifies for the ITC, which would make it cheaper for both companies to develop storage technology.
What other kinds of policies would ease Form Energy’s path?
Probably most important for us at this point is that the market designs are updated to reflect where we really are today and where we want to go. Grid operators and markets were designed with an entirely different and largely combustion-driven grid in mind. There’s a big push in general to acknowledge that and figure out what the right market designs are to get the system to value things like reliability and decarbonization.
For example, last year MISO came out with a report about what they called the “reliability imperative,” in which they started to articulate how the market design needs to incorporate reliability as an explicit thing that gets compensated. That is something that will have to get defined in how wholesale markets are designed so that the value that we bring as an asset is properly compensated.
Lisa Martine Jenkins is a senior reporter at Protocol covering climate. Lisa previously wrote for Morning Consult, Chemical Watch and the Associated Press. Lisa is currently based in Brooklyn, and is originally from the Bay Area. Find her on Twitter ( @l_m_j_) or reach out via email (ljenkins@protocol.com).
It’s likely McLachlan’s code is running on your computer right now.
Alan McLachlan — a celebrated Microsoft and Adobe engineer — learned on a Commodore like the above.
Lizzy Lawrence ( @LizzyLaw_) is a reporter at Protocol, covering tools and productivity in the workplace. She’s a recent graduate of the University of Michigan, where she studied sociology and international studies. She served as editor in chief of The Michigan Daily, her school’s independent newspaper. She’s based in D.C., and can be reached at llawrence@protocol.com.
Alan W. McLachlan, an engineer who helped create the PDF, died at home in San Francisco on Oct. 6. He was 58.
His husband Paul McLachlan, who works as senior engineering manager at Rivian, described him as incredibly humble, talented, and loving. His co-workers described him as vastly knowledgeable and technically gifted. Throughout his career he focused on firmware, essential software that allows a device’s specific hardware to function. It’s not “the sexy part of tech, because everybody wants to write the app,” Paul said. Yet Alan’s code, Paul said, is likely running on the computer of everyone who reads this article.
“His legacy is to celebrate the people who want to help, who are working in the background on the stuff that you don’t see but you use everyday,” Paul said.
Alan was born in Auckland, New Zealand. In 1979, he immigrated to the United States, where he enrolled in Orange County’s Westminster High School. Paul said one of Alan’s early experiences with computers took place in high school, when a teacher sat him down in front of Commodore 64 and made him learn it.
After high school, he attended California State University, Long Beach where he studied radio, film, and television. He graduated in 1985. He was a part of the film crew for the sitcom “Family Ties” during his studies, Paul said, and “he has a bunch of photographs with people like Michael J. Fox and others.”
Alan taught himself to code; he never studied computer science or engineering formally. He pivoted from film to technology soon after graduation, according to his LinkedIn. One of his early jobs was as a senior programmer with the Conographic Corporation. In 1993, he started working at Adobe as a systems programmer. He was a member of the core team that invented the PDF, and built the printer drivers (software that converts data into a printable format) that enabled languages like Arabic, Farsi, and Urdu.
“He was really fortunate to join tech before it was a capital T,” Paul said. “It was a weird industry full of weird people who were not working like other people.”
Alan later worked at Microsoft on the Xbox engineering team. The majority of his career, though, was spent at BigFix, which was acquired by IBM in 2013 and subsequently HCL Technologies in 2019. Brian Shorey, his manager at BigFix, said Alan was known as a company encyclopedia. He knew the product inside-out, and was adept at handling complicated customer problems.
“Everyone knew they could just ping Alan and he could answer their questions,” Shorey said. “It was quicker than doing a Google search or looking it up internally.”
Shorey said Alan was one of the smartest people he’d ever met, describing him as a “super guy.” Fellow BigFix architect Rosario Gangemi echoed Shorey’s descriptions, also noting Alan’s care and thoughtfulness. “He’s somebody that speaks only with reason and when he has something to say,” Gangemi said. BigFix promoted Alan’s position to fellow posthumously. He’s the first fellow within HCL Software.
Paul and Alan met on match.com in 2009. In a lucky coincidence, Paul’s VPN accidentally set his location to San Francisco instead of New York, where he was living at the time. Paul recalled being stuck on his BlackBerry in those early times, texting with Alan even on a Christmas vacation sailing in the Caribbean. After a harrowing, near-death experience when his sailboat flipped over, Paul texted Alan, who booked him a helicopter flight off the island. Paul flew to meet him in San Francisco, and never left.
“He was so gentle, and so handsome,” Paul said. “He was so fascinating, too.”
Outside of work, Alan and Paul cared for rescue dogs together. In fact, the couple planned to open a shelter for older and disabled dogs. One of their adopted dogs is an epileptic and diabetic dog named Ayr. Every morning and evening at 7:30 exactly, Alan would measure out Ayr’s food and take his blood pressure, logging the data points in a journal. He was part Maori, the group indigenous to New Zealand, and would walk the dog past the native pōhutukawa tree to retain the New Zealand connection.
More than work, Alan cared about people. Paul said he was never the type to discuss accolades or technical achievements.
“I don’t think he had a grand narrative like, ‘Wow, look at all of these accomplishments,’” Paul said. “It was always about the people.”
Lizzy Lawrence ( @LizzyLaw_) is a reporter at Protocol, covering tools and productivity in the workplace. She’s a recent graduate of the University of Michigan, where she studied sociology and international studies. She served as editor in chief of The Michigan Daily, her school’s independent newspaper. She’s based in D.C., and can be reached at llawrence@protocol.com.
She’s bullish on generative AI given the “superpowers” it gives humans who work with it.
Sonya Huang, a partner at Sequoia, shared her thoughts about generative AI’s future.
Biz Carson ( @bizcarson) is a San Francisco-based reporter at Protocol, covering Silicon Valley with a focus on startups and venture capital. Previously, she reported for Forbes and was co-editor of Forbes Next Billion-Dollar Startups list. Before that, she worked for Business Insider, Gigaom, and Wired and started her career as a newspaper designer for Gannett.
Generative AI can create more than just text and images — it’s clearly generated a hype cycle around AI companies and rabid investor interest in the space.
In a bright spot for an otherwise lackluster funding environment, two “gen tech” companies became unicorns this week after Stability AI, the company behind the wildly popular image generator Stable Diffusion, and Jasper, which makes an AI-powered system that writes marketing copy, both announced funding rounds. The launch party for Stability AI drew people like Sergey Brin, Naval Ravikant, and Ron Conway into San Francisco for “a coming-out bash for the entire field of generative A.I.,” as The New York Times called it.
The buzz spilled over onto Twitter when a market map of companies in the space went viral after Sequoia partner Sonya Huang laid out the companies (including Stability AI and Jasper) that are building in generative AI, solidifying the space as a sector and not just a handful of companies making fanciful images.
A firm believer in the “superpowers” humans can gain by working with machines — she’s used the language model GPT-3 to help write a blog post on the future of generative AI — Huang talked with Protocol about what sectors founders are building in, the looming ethical concerns, and whether the hype in AI startups is overblown or justified.
This conversation was lightly edited for length and clarity.
I don’t think I’ve ever seen a market map go quite so viral on Twitter. Why do you think it generated — forgive the pun — so much attention when you posted it?
It’s speculative, but I think a few things. One, I would say I think the world is in dark times right now. People are looking for something to latch on to that is hope, and generative AI appears to be that. So I think part of it is just the emotional [impact] where we see so many terrible things happening in the world and [think], “Wow, what an exciting time to be in technology if you look at what’s now possible.”
Then the second thing is there’s been a lot of really exciting progress that’s been shared publicly in terms of models getting bigger, better, and amazing images that are flying around Twitter. But it was probably new to think about this as a model versus application layer. People were thinking, “OK, these models are not only going to be super interesting things that we can play with to make a fun image, but they’re actually going to drive the future of how we work and the next big application companies.” That was probably a new framing that people hadn’t really thought about in that way. Those are probably a couple of the reasons it took off, but it’s speculative. I don’t know what makes things go viral on Twitter. I’m not good at Twitter. [Laughs]
For me, it was interesting because I wrote a few weeks ago about how VCs were exploring whether this was a toy or the next big thing, and then there’s been this huge shift to VCs saying it’s definitely going to be the next big thing. Why do you think there has been a shift? Was it just companies announcing fundraises this week?
I think it’s market maturity. We’ve been following pretty closely these large models for the last several years, and if you look at what’s possible, it is pretty mind-blowing just the rate of progress. There is some benchmark, which is human-level performance, and now that these models are just in the last couple of years starting to exceed that, only then can you have AI that really, really augments how we work. Because if it’s not as good, the technology’s not ready. So the first thing I’d say is, the technology is finally getting ready.
Then the second thing is just that access to these models is now available. Obviously Stability has made an incredible amount of progress and developer interest because they’ve just made their models completely open. And OpenAI has also made their models more publicly available as well. I think GPT-3 was in closed beta until last year, if I’m remembering correctly. So these models are finally available for people to play with, which they weren’t before. Once technology becomes available for people to play with, it is very natural for step one to be very cool demos of what’s possible. I almost compare it to when the iPhone came out: It was a bunch of really gimmicky stuff that came out at first, but then you’ve got people who are really thinking about the business applications in deep ways, and we’re starting to see that.
This is obviously still a pretty nascent area, but where are you seeing most concentration of activity so far?
Image generation is a big one. Images speak to us so viscerally, and so they’re a lot more fun to share on Twitter than whatever GPT-3 could spit out for me. By nature, images are a lot more viral, so we’re seeing a lot there. People are moving on beyond one-shot image generation to a few different branches, whether it’s “Let’s make this really good for the process of interior design or product design” or “Let’s make it a really, really good image generator that you can continue innovating with the machine on” or “We want to take all these images that people are doing and the community we’ve built, and build the next big social media platform.” People are going different directions from image generation, but I would say that’s been an area of just incredible interest from both founders and from users because you need user interest for these things to work.
Then the other big category where there has been a lot has been in the text space. And in the text space, who needs to write all the time? Marketers. So there’s a lot of these marketing Gen AI companies, and some of them are really working. We’re seeing it evolve, as well, where people started from shorter-form generations and now we’re getting really, really long form. We’re getting creative writing, we’re getting scripts and novels. It’s pretty good.
And then code. Code is one that OpenAI has cultivated for a while, and I think GitHub Copilot is incredible. The stat — [that] they’re responsible for 40% of their users’ code — is just mind-blowing to me. I’ve seen the demos from Replit — it’s pretty extraordinary. And so code is the other effort where we’re seeing a lot of both exciting founder development and then also user interest.
The other categories — the boxes on our landscape that are relatively sparse now — I don’t think they’re gonna be sparse for long. When I first put out our blog post about how the tech and how the different pieces of technology are becoming ready, I thought 3D, video, bio, they were going to take longer based on some conversations. Basically everyone wrote in to me like, “You’re wrong, this stuff is happening way faster than you think it is.” And they were right. I think similar to what you saw with text and image happen where the models were a couple years back, I think you’ll start to see the application space start to flourish for these other modalities as well.
Are there any areas on the map that you left off that you’re excited to see happen someday? Any other to-be-discovered areas?
We organized the map by modality, which I thought was most relevant just because it’s the enabling technology that is creating the application within each box. I do think that a lot of the most interesting companies will own the end user, but they will be multimodality. I couldn’t fit that in a neat space on my map, but that would be one.
Another would be this concept of an AI companion or AI copilot. It doesn’t really fit neatly in the map anymore, but you have something intelligent — browse the web, stitch together all your different tools to do things for you — versus currently the map is very much focused on tools that you work with for a very specific test task.
What do you think about the hype cycle around AI right now?
Well, I would be alarmed if the hype was really high and the results weren’t there. The hype is high, and I think part of that is, again, people emotionally want to attach onto something that gives them hope and optimism, but the results are there as well. You see what these models are capable of doing. You see the fundamental technology. You see the applications that people are starting to build. I’ll go back to “writing 40% of people’s code” example — that is phenomenal both technological progress as well as economic value delivery. So absolutely the hype is high. I think it’s absolutely justified given the results that we’re seeing. My hope is actually that by putting out this landscape, we plant that seed and a lot of future founders that have been trying to figure out what to build next, I think it’s wonderful to draw them to this. If I was a founder in [Y Combinator] right now, I would 100% be pointing my guns at one of these models and seeing what I can do.
What about some of the ethical concerns? I spoke with Khosla’s Kanu Gulati about this a few weeks ago and there are some real concerns around copyright and other shortcomings in the space. What do you think the role of investors should be in addressing some of these?
Absolutely. I agree with the ethical concerns. The copyright concerns are a problem that’s really important and hasn’t been solved yet. There isn’t a legal framework for this stuff. Ideally, this is a constructive dialogue between all folks on all sides of the table because until there is that clarity, I think it’s very hard to make progress. I think our role would be helping ensure that whatever rules are crafted are clear so that once you have that clarity, everybody can innovate on all sides of the spectrum, and hopefully everybody feels good.
If I was a founder in [Y Combinator] right now, I would 100% be pointing my guns at one of these models and seeing what I can do.
One of my favorite responses to your map was if it was truly generative AI, it’d be able to generate a market map itself. Are we gonna get to that point anytime soon?
[Laughs] Actually, I’ll tell you how I created the map in the first place: I went into GPT-3.
Before even the map, we put out this blog post of what was going to happen. It wasn’t clear in my head even how to define generative AI. There was some stuff on the internet that wasn’t that good, and so I literally put it in OpenAI, “the difference between classical AI and generative AI,” and it started spitting out amazing stuff. So that became a lot of the base for our article. It wasn’t just a joke that the article was co-written with GPT-3; it actually was. And then, I’m not the most creative person, and I was having trouble brainstorming what the applications will be, so I typed into GPT-3, “the potential applications will be …” and then it started spitting out things, and I was like, “and then 10 more of them will be …” and it just kept on going, which is amazing. And then I’d be like, “Specifically for image generation, you can think of it as ….” That human-machine iteration loop I hadn’t experienced before, and it was very much how we created both the blog post and landscape.
It’s cool to see how the point of generative AI is that it can generate things that you don’t think about. It’s a new frontier for a lot of tech companies.
What I would have loved is if we have eight companies in a bucket on the map somewhere, I would have loved to have a natural way for having a machine that would browse the internet and find companies that sound similar and suggest them for my map. There isn’t a great product encapsulation for that yet, but as we dream about how this might play out, I would guess it’s probably not that far out.
I’m very curious if I can train a model on my newsletter and have it write my newsletter and then submit it to my editor to see if my editor can tell the difference of who wrote it. Although maybe I shouldn’t do that because I’d be out of a job one day.
I’ve had it write some investment memos for me and I swear it was as good as what I can write. [Laughs] To your point about being out of a job, I realize it was said in jest, but there’s the knowledge and the craft of being able to work with the machine and I think that is a new skill that we need to learn. But I think once you master it, you’re better than before, right? You’re more productive, you’re more creative, whatever it is, if you can really really embrace the machine. I don’t think there’s a world where the machine fully replaces us. We have to train how we work with the machines, but I think the result really is we are superpower humans as a result of being able to work with these machines.
Biz Carson ( @bizcarson) is a San Francisco-based reporter at Protocol, covering Silicon Valley with a focus on startups and venture capital. Previously, she reported for Forbes and was co-editor of Forbes Next Billion-Dollar Startups list. Before that, she worked for Business Insider, Gigaom, and Wired and started her career as a newspaper designer for Gannett.
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