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EV charging stations, biofuels, the hydrogen transition and chemicals are pillars of Shell’s climate plan

Published February 11, 2021

Royal Dutch Shell Group, one of the largest publicly traded oil producers in the world, just laid out its plan for how the company will survive in a zero-emission, climate conscious world.

It’s a plan that rests on five main pillars that include the massive rollout of electric vehicle charging stations; a greater emphasis on lubricants, chemicals and biofuels; the development of a significantly larger renewable energy generation portfolio and carbon offset plan; the continued development of hydrogen and natural gas assets while slashing oil production by 1% to 2% per year; and investing heavily in carbon capture and storage.

These categories cut across the company’s business operations and represent one of the most comprehensive (if high level) plans from a major oil company on how to keep their industry from becoming the next victim of the transition to low emission (and eventually) zero emission energy and power sources (I’m looking at you, coal industry).

“Our accelerated strategy will drive down carbon emissions and will deliver value for our shareholders, our customers and wider society,” said Royal Dutch Shell Chief Executive Officer Ben van Beurden in a statement.

To keep those shareholders from abandoning ship, the company also committed to slashing costs and boosting its dividend per share by around 4% per year. That means giving money back to investors that might have been spent on expensive oil and gas exploration operations. The company also committed to pay down its debt and make its payouts to shareholders 20% to 30% of its cash flow from operations. That’s… very generous.

Image Credits: Bryce Durbin

The Plan

Shell is a massive business with more than 1 million commercial and industrial customers and about 30 million customers coming to its 46,000 retail service stations daily, according to the company’s own estimates. The company organized its thinking around what it sees as growth opportunities, energy transition opportunities and then the gradual obsolescence of its upstream drilling and petroleum production operations.

In what it sees as areas for growth, Shell intends to invest around $5 billion to $6 billion to its initiatives, including the development of 500,000 electric vehicle charging locations by 2025 (up from 60,000 today) and an attendant boost in retail and service locations to facilitate charging.

The company also said it would be investing heavily in the expansion of biofuels and renewable energy generation and carbon offsets. The company wants to generate 560 terawatt hours a year by 2030, which is double the amount of electricity it generates today. Expect to see Shell operate as an independent power producer that will provide renewable energy generation as a service to an expected 15 million retail and commercial customers.

Finally the company sees the hydrogen economy as another area where it can grow.

In places where Shell already has assets that can be transitioned to the low carbon economy, the company’s going to be doubling down on its bets. That means zero emission natural gas production and a trebling down on chemicals manufacturing (watch out Dow and BASF). That means more recycling as well, as the company intends to process 1 million tons of plastic waste to produce circular chemicals.

Upstream, which was the heart of the oil and gas business for years, the company said it would “focus on value over volume” in a statement. What that means in practice is looking for easier, low-cost wells to drill (something that points to the continued importance of the Middle East in the oil economy for the foreseeable future). The company expects to reduce its oil production by around 1% to 2% per year. And the company’s going to be investing in carbon capture and storage to the tune of 25 million tons per year through projects like the Quest CCS development in Canada, Norway’s Northern Lights project and the Porthos project n the Netherlands.

“We must give our customers the products and services they want and need – products that have the lowest environmental impact,” van Beurden said in a statement. “At the same time, we will use our established strengths to build on our competitive portfolio as we make the transition to be a net-zero emissions business in step with society.”

Money or finance green pattern with dollar banknotes. Banking, cashback, payment, e-commerce. Vector background. Image Credits: Svetlana Borovkova / Getty Images

Money talk

For the company to survive in a world where revenues from its main business are cut, it’s also going to be keeping operating expenses down and will be looking to sell off big chunks of the business that no longer make sense.

That means expenses of no more than $35 billion per year and sales of around $4 billion per year to keep those dividends and cash to investors flowing.

“Over time the balance of capital spending will shift towards the businesses in the Growth pillar, attracting around half of the additional capital spend,” the company said. “Cash flow will follow the same trend and in the long term will become less exposed to oil and gas prices, with a stronger link to broader economic growth.”

Shell set targets for reducing its carbon intensity as part of the pay that’s going to all of the company’s staff and those targets are… eye opening. It’s looking at reductions in carbon intensity of 6-8% by 2023, 20% by 2030, 45% by 2035 and 100% by 2050, using a baseline of 2016 as its benchmark.

The company said that its own carbon emissions peaked in 2018 at 1.7 giga-tons per year and its oil production peaked in 2019.

The context

Shell’s not taking these steps because it wants to, necessarily. The writing is on the wall that unless something dramatic is done to stop fossil fuel pollution and climate change, the world faces serious consequences.

A study released earlier this week indicated that air pollution from fossil fuels killed 18% of the world’s population. That means burning fossil fuels is almost as deadly as cancer, according to the study from researchers led by Harvard University.

Beyond the human toll directly tied to fossil fuels, there’s the huge cost of climate change, which the U.S. estimated could cost $500 billion per year by 2090 unless steps are taken to reverse course.

New US report says that climate change could cost nearly $500B per year by 2090

Metalenz reimagines the camera in 2D and raises $10M to ship it

Published February 4, 2021

As impressive as the cameras in our smartphones are, they’re fundamentally limited by the physical necessities of lenses and sensors. Metalenz skips over that part with a camera made of a single “metasurface” that could save precious space and battery life in phones and other devices… and they’re about to ship it.

The concept is similar to, but not descended from, the “metamaterials” that gave rise to flat beam-forming radar and lidar of Lumotive and Echodyne. The idea is to take a complex 3D structure and accomplish what it does using a precisely engineered “2D” surface — not actually two-dimensional, of course, but usually a plane with features measured in microns.

In the case of a camera, the main components are of course a lens (these days it’s usually several stacked), which corrals the light, and an image sensor, which senses and measures that light. The problem faced by cameras now, particularly in smartphones, is that the lenses can’t be made much smaller without seriously affecting the clarity of the image. Likewise sensors are nearly at the limit of how much light they can work with. Consequently, most of the photography advancements of the last few years have been done on the computational side.

The future of photography is code

Using an engineered surface that does away with the need for complex optics and other camera systems has been a goal for years. Back in 2016 I wrote about a NASA project that took inspiration from moth eyes to create a 2D camera of sorts. It’s harder than it sounds, though — usable imagery has been generated in labs, but it’s not the kind of thing that you take to Apple or Samsung.

Metalenz aims to change that. The company’s tech is built on the work of Harvard’s Federico Capasso, who has been publishing on the science behind metasurfaces for years. He and Rob Devlin, who did his doctorate work in Capasso’s lab, co-founded the company to commercialize their efforts.

“Early demos were extremely inefficient,” said Devlin of the field’s first entrants. “You had light scattering all over the place, the materials and processes were non-standard, the designs weren’t able to handle the demands that a real world throws at you. Making one that works and publishing a paper on it is one thing, making 10 million and making sure they all do the same thing is another.”

Under a millimeter wide and powered by light, these tiny cameras could hide almost anywhere

Their breakthrough — if years of hard work and research can be called that — is the ability not just to make a metasurface camera that produces decent images, but to do it without exotic components or manufacturing processes.

“We’re really using all standard semiconductor processes and materials here, the exact same equipment — but with lenses instead of electronics,” said Devlin. “We can already make a million lenses a day with our foundry partners.”

Diagram comparing the multi-lens barrel of a conventional phone camera, and their simpler "meta-optic"

The thing at the bottom is the chip where the image processor and logic would be, but the meta-optic could also integrate with that. The top is a pinhole. Image Credits: Metalenz

The first challenge is more or less contained in the fact that incoming light, without lenses to bend and direct it, hits the metasurface in a much more chaotic way. Devlin’s own PhD work was concerned with taming this chaos.

“Light on a macro [i.e. conventional scale, not close-focusing] lens is controlled on the macro scale, you’re relying on the curvature to bend the light. There’s only so much you can do with it,” he explained. “But here you have features a thousand times smaller than a human hair, which gives us very fine control over the light that hits the lens.”

Those features, as you can see in this extreme close-up of the metasurface, are precisely tuned cylinders, “almost like little nano-scale Coke cans,” Devlin suggested. Like other metamaterials, these structures, far smaller than a visible or near-infrared light ray’s wavelength, manipulate the radiation by means that take a few years of study to understand.

Diagram showing chips being manufactured, then an extreme close up showing nano-scale features.

Image Credits: Metalenz

The result is a camera with extremely small proportions and vastly less complexity than the compact camera stacks found in consumer and industrial devices. To be clear, Metalenz isn’t looking to replace the main camera on your iPhone — for conventional photography purposes the conventional lens and sensor are still the way to go. But there are other applications that play to the chip-style lens’s strengths.

Something like the FaceID assembly, for instance, presents an opportunity. “That module is a very complex one for the cell phone world — it’s almost like a Rube Goldberg machine,” said Devlin. Likewise the miniature lidar sensor.

At this scale, the priorities are different, and by subtracting the lens from the equation the amount of light that reaches the sensor is significantly increased. That means it can potentially be smaller in every dimension while performing better and drawing less power.

Image (of a very small test board) from a traditional camera, left, and metasurface camera, right. Beyond the vignetting it’s not really easy to tell what’s different, which is kind of the point. Image Credits: Metalenz

Lest you think this is still a lab-bound “wouldn’t it be nice if” type device, Metalenz is well on its way to commercial availability. The $10 million Series A they just raised was led by 3M Ventures, Applied Ventures LLC, Intel Capital, M Ventures and TDK Ventures, along with Tsingyuan Ventures and Braemar Energy Ventures — a lot of suppliers in there.

Unlike many other hardware startups, Metalenz isn’t starting with a short run of boutique demo devices but going big out of the gate.

“Because we’re using traditional fabrication techniques, it allows us to scale really quickly. We’re not building factories or foundries, we don’t have to raise hundreds of mils; we can use what’s already there,” said Devlin. “But it means we have to look at applications that are high volume. We need the units to be in that tens of millions range for our foundry partners to see it making sense.”

Although Devlin declined to get specific, he did say that their first partner is “active in 3D sensing” and that a consumer device, though not a phone, would be shipping with Metalenz cameras in early 2022 — and later in 2022 will see a phone-based solution shipping as well.

In other words, while Metalenz is indeed a startup just coming out of stealth and raising its A round… it already has shipments planned on the order of tens of millions. The $10 million isn’t a bridge to commercial viability but short-term cash to hire and cover upfront costs associated with such a serious endeavor. It’s doubtful anyone on that list of investors harbors any serious doubts on ROI.

The 3D sensing thing is Metalenz’s first major application, but the company is already working on others. The potential to reduce complex lab equipment to handheld electronics that can be fielded easily is one, and improving the benchtop versions of tools with more light-gathering ability or quicker operation is another.

Though a device you use may in a few years have a Metalenz component in it, it’s likely you won’t know — the phone manufacturer will probably take all the credit for the improved performance or slimmer form factor. Nevertheless, it may show up in teardowns and bills of material, at which point you’ll know this particular university spin-out has made it to the big leagues.

OpenCV AI Kit aims to do for computer vision what Raspberry Pi did for hobbyist hardware

How ‘ghost work’ in Silicon Valley pressures the workforce, with Mary Gray

Published August 16, 2019

The phrase “pull yourself up by your own bootstraps” was originally meant sarcastically.

It’s not actually physically possible to do — especially while wearing Allbirds and having just fallen off a Bird scooter in downtown San Francisco, but I should get to my point.

This week, Ken Cuccinelli, the acting Director of the United States Citizenship and Immigrant Services Office, repeatedly referred to the notion of bootstraps in announcing shifts in immigration policy, even going so far as to change the words to Emma Lazarus’s famous poem “The New Colossus:” no longer “give me your tired, your poor, your huddled masses yearning to breathe free,” but “give me your tired and your poor who can stand on their own two feet, and who will not become a public charge.”

We’ve come to expect “alternative facts” from this administration, but who could have foreseen alternative poems?

Still, the concept of ‘bootstrapping’ is far from limited to the rhetorical territory of the welfare state and social safety net. It’s also a favorite term of art in Silicon Valley tech and venture capital circles: see for example this excellent (and scary) recent piece by my editor Danny Crichton, in which young VC firms attempt to overcome a lack of the startup capital that is essential to their business model by creating, as perhaps an even more essential feature of their model, impossible working conditions for most everyone involved. Often with predictably disastrous results.

It is in this context of unrealistic expectations about people’s labor, that I want to introduce my most recent interviewee in this series of in-depth conversations about ethics and technology.

Mary L. Gray is a Fellow at Harvard University’s Berkman Klein Center for Internet and Society and a Senior Researcher at Microsoft Research. One of the world’s leading experts in the emerging field of ethics in AI, Mary is also an anthropologist who maintains a faculty position at Indiana University. With her co-author Siddharth Suri (a computer scientist), Gray coined the term “ghost work,” as in the title of their extraordinarily important 2019 book, Ghost Work: How to Stop Silicon Valley from Building a New Global Underclass.

Image via Mary L. Gray / Ghostwork / Adrianne Mathiowetz Photography

Ghost Work is a name for a rising new category of employment that involves people scheduling, managing, shipping, billing, etc. “through some combination of an application programming interface, APIs, the internet and maybe a sprinkle of artificial intelligence,” Gray told me earlier this summer. But what really distinguishes ghost work (and makes Mary’s scholarship around it so important) is the way it is presented and sold to the end consumer as artificial intelligence and the magic of computation.

In other words, just as we have long enjoyed telling ourselves that it’s possible to hoist ourselves up in life without help from anyone else (I like to think anyone who talks seriously about “bootstrapping” should be legally required to rephrase as “raising oneself from infancy”), we now attempt to convince ourselves and others that it’s possible, at scale, to get computers and robots to do work that only humans can actually do.

Ghost Work’s purpose, as I understand it, is to elevate the value of what the computers are doing (a minority of the work) and make us forget, as much as possible, about the actual messy human beings contributing to the services we use. Well, except for the founders, and maybe the occasional COO.

Facebook now has far more employees than Harvard has students, but many of us still talk about it as if it were little more than Mark Zuckerberg, Cheryl Sandberg, and a bunch of circuit boards.

But if working people are supposed to be ghosts, then when they speak up or otherwise make themselves visible, they are “haunting” us. And maybe it can be haunting to be reminded that you didn’t “bootstrap” yourself to billions or even to hundreds of thousands of dollars of net worth.

Sure, you worked hard. Sure, your circumstances may well have stunk. Most people’s do.

But none of us rise without help, without cooperation, without goodwill, both from those who look and think like us and those who do not. Not to mention dumb luck, even if only our incredible good fortune of being born with a relatively healthy mind and body, in a position to learn and grow, here on this planet, fourteen billion years or so after the Big Bang.

I’ll now turn to the conversation I recently had with Gray, which turned out to be surprisingly more hopeful than perhaps this introduction has made it seem.

Greg Epstein: One of the most central and least understood features of ghost work is the way it revolves around people constantly making themselves available to do it.

Mary Gray: Yes, [What Siddarth Suri and I call ghost work] values having a supply of people available, literally on demand. Their contributions are collective contributions.

It’s not one person you’re hiring to take you to the airport every day, or to confirm the identity of the driver, or to clean that data set. Unless we’re valuing that availability of a person, to participate in the moment of need, it can quickly slip into ghost work conditions.

The rise of the new crypto “mafias”

Published June 27, 2019

Ash Egan
Contributor

Ash Egan leads crypto investing at Accomplice. He formerly was a VC at ConsenSys Ventures and Converge.

In the early 2000s, journalists popularized the term “PayPal mafia” to describe the PayPal founders and employees who left to start their own wildly successful tech companies, including Peter Thiel, Reid Hoffman, and Elon Musk. Drawing from that idea, this article seeks to cover the formation and flow of talent within the crypto landscape today.

I’m fascinated by the concept of tech mafias, popularized by Paypal in the early 00s.

Early signs of crypto mafias:

Coinbase @0xProject @dydxprotocol
Ethereum/ConsenSys @Cardano @polkadotnetwork @metamask_io
MIT @EnigmaMPC @Algorand Unit-e
IC3 Avalanche

Others?

— Ash Egan (@AshAEgan) April 3, 2019

The crypto world is in a constant state of flux, with new startups entrants joining the industry every single day. These new startups have the potential either to be superstars within a portfolio company or to start the next Coinbase. Additionally, there are already impressive spin-outs from some of the more established crypto companies.

For ease of framing, I’ve separated these early-forming mafias into four categories: Crypto, Tech, Wall Street, and Academia. Since 2009, there have been 186 spinout companies originating from those four categories (33% from Academia, 28% from Crypto, 24% from Tech, and 15% from Wall Street).

Obvious but important disclaimer: this article does not intend to promote organized crime within crypto.

Criteria

DNA Script picks up $38.5 million to make DNA production faster and simpler

Published May 17, 2019

DNA Script has raised $38.5 million in new financing to commercialize a process that it claims is the first big leap forward in manufacturing genetic material.

The revolution in synthetic biology that’s reshaping industries from medicine to agriculture rests on three, equally important pillars.

They include: analytics — the ability to map the genome and understand the function of different genes; synthesis — the ability to manufacture DNA to achieve certain functions; and gene editing — the CRISPR-based technologies that allow for the addition or subtraction of genetic code.

New technologies have already been introduced to transform the analytics and editing of genomes, but little progress has been made over the past 50 years in the ways in which genetic material is manufactured. That’s exactly the problem that DNA Script is trying to solve.

Traditionally, making DNA involved the use of chemical compounds to synthesize (or write) DNA in chains that were limited to around 200 nucleotide bases. Those synthetic pieces of genetic code are then assembled to make a gene.

DNA Script’s technology holds the promise of making longer chains of nucleotides by mirroring the enzymatic process through which DNA is assembled within cells — with fewer errors and no chemical waste material. The enzymatic process can accelerate commercial applications in healthcare, chemical manufacturing and agriculture.

“Any technology that can make that faster is going to be very valuable,” says Christopher Voigt, a synthetic biologist at the Massachusetts Institute of Technology in Cambridge, told the journal Nature.

DNA Script isn’t the only company in the market that’s looking to make the leap forward in enzymatic DNA production. Nuclear, a startup working with Harvard University’s famed geneticist, George Church, and Ansa Bio, a startup affiliated with Jay Keasling’s Berkeley lab at the University of California, are also moving forward with the technology.

But the Paris-based company has achieved some milestones that would make its technology potentially the first to come to market with a commercially viable approach.

At least, that’s what new investors LSP and Bpifrance, through its Large Venture fund, are hoping. They’re joined by previous investors Illumina Ventures, M. Ventures, Sofinnova Partners, Kurma Partners and Idinvest Partners in backing the company’s latest funding.

The company said the money would be used to accelerate the development of its first products and establish a presence in the United States.

“As we announced earlier this year at the AGBT General Meeting, DNA Script was the first company to enzymatically synthesize a 200mer oligo de novo with an average coupling efficiency that rivals the best organic chemical processes in use today,” said Thomas Ybert, chief executive and co-founder of DNA Script. “Our technology is now reliable enough for its first commercial applications, which we believe will deliver the promise of same-day results to researchers everywhere, with DNA synthesis that can be completed in just a few hours.”

Beyond costs, what else can we do to make housing affordable?

Published May 14, 2019

Daniel Wu
Contributor

Dan Wu is a privacy counsel and legal engineer at Immuta. He holds a JD from Harvard University, and is a PhD candidate for Social Policy and Sociology at The Harvard Kennedy School.

Social impact innovations

These innovations address:

The right way to do AI in security

Published April 10, 2019

Artificial intelligence applied to information security can engender images of a benevolent Skynet, sagely analyzing more data than imaginable and making decisions at lightspeed, saving organizations from devastating attacks. In such a world, humans are barely needed to run security programs, their jobs largely automated out of existence, relegating them to a role as the button-pusher on particularly critical changes proposed by the otherwise omnipotent AI.

Such a vision is still in the realm of science fiction. AI in information security is more like an eager, callow puppy attempting to learn new tricks – minus the disappointment written on their faces when they consistently fail. No one’s job is in danger of being replaced by security AI; if anything, a larger staff is required to ensure security AI stays firmly leashed.

Arguably, AI’s highest use case currently is to add futuristic sheen to traditional security tools, rebranding timeworn approaches as trailblazing sorcery that will revolutionize enterprise cybersecurity as we know it. The current hype cycle for AI appears to be the roaring, ferocious crest at the end of a decade that began with bubbly excitement around the promise of “big data” in information security.

But what lies beneath the marketing gloss and quixotic lust for an AI revolution in security? How did AL ascend to supplant the lustrous zest around machine learning (“ML”) that dominated headlines in recent years? Where is there true potential to enrich information security strategy for the better – and where is it simply an entrancing distraction from more useful goals? And, naturally, how will attackers plot to circumvent security AI to continue their nefarious schemes?

How did AI grow out of this stony rubbish?

The year AI debuted as the “It Girl” in information security was 2017. The year prior, MIT completed their study showing “human-in-the-loop” AI out-performed AI and humans individually in attack detection. Likewise, DARPA conducted the Cyber Grand Challenge, a battle testing AI systems’ offensive and defensive capabilities. Until this point, security AI was imprisoned in the contrived halls of academia and government. Yet, the history of two vendors exhibits how enthusiasm surrounding security AI was driven more by growth marketing than user needs.

Meet the startups in the latest Alchemist class

Published September 20, 2018

Alchemist is the Valley’s premiere enterprise accelerator and every season they feature a group of promising startups. They are also trying something new this year: they’re putting a reserve button next to each company, allowing angels to express their interest in investing immediately. It’s a clever addition to the demo day model.

You can watch the live stream at 3pm PST here.

Videoflow – Videoflow allows broadcasters to personalize live TV. The founding team is a duo of brothers — one from the creative side of TV as a designer, the other a computer scientist. Their SaaS product delivers personalized and targeted content on top of live video streams to viewers. Completely bootstrapped to date, they’ve landed NBC, ABC, and CBS Sports as paying customers and appear to be growing fast, having booked over $300k in revenue this year.

Redbird Health Tech – Redbird is a lab-in-a-box for convenient health monitoring in emerging market pharmacies, starting with Africa. Africa has the fastest growing middle class in the world — but also the fastest growing rate of diabetes (double North America’s). Redbird supplies local pharmacies with software and rapid tests to transform them into health monitoring points – for anything from blood sugar to malaria to cholesterol. The founding team includes a Princeton Chemical Engineer, 2 Peace Corps alums, and a Pharmacist from Ghana’s top engineering school. They have 20 customers, and are growing 36% week over week.

Shuttle – Shuttle is getting a head start on the future of space travel by building a commercial spaceflight booking platform. Space tourism may be coming sooner than you think. Shuttle wants to democratize access to the heavens above. Founded by a Stanford Computer Science alum active in Stanford’s Student Space Society, Shuttle has partnerships with the leading spaceflight operators, including Virgin Galactic, Space Adventures, and Zero-G. Tickets to space today will set you back a cool $250K, but Shuttle believes that prices will drop exponentially as reusable rockets and landing pads become pervasive. They have $1.6m in reservations and growing.

Birdnest – Threading the needle between communal and private, Birdnest is the Goldilocks of office space for startups. Communal coworking spaces are accessible but have too many distractions. Traditional office spaces are private but inflexible on their terms. Birdnest brings the best of each without the drawbacks: finding, leasing, and operating a network of underutilized spaces inside of private offices. The cofounders, a duo of Duke and Kellogg MBA grads, are at $300K ARR with a fast-growing 50+ client waitlist.

Tag.bio – Tag.bio wants to make data science actionable in healthtech. The founding team is comprised of a former Ayasdi bioinformatician and a former Honda Racing engineer with a Stanford MBA. They’ve developed a next-generation data science platform that makes it easy and fast to build data apps for end users, or as they say, “WordPress for data science.” The result they claim is lightning-fast analysis apps that can be run by end users, dramatically accelerating insight discovery. They count the UCSF Medical Center and a “large Swiss pharma company” as early customers.

nCorium – They’ve built a new server architecture to handle the onslaught of AI to come with what they claim is the world’s first AI accelerator on memory to deliver 30x greater performance than the status quo. The quad founding team is intimidatingly technical — including a UCSD Professor, and former engineers from Qualcomm and Intel with 40 patents among them. They have $300K in pilots.

Spiio – Software eats landscaping with Spiio, which combines cloud-driven AI with physical sensors to monitor watering and landscaping for big companies. Their smart system knows when to water and when not to. This reduces water consumption by 50%, which means their system pays for itself in less than 30 days for big companies. They want to connect every plant to the internet, and look like they are off to a good start — $100K in orders from brand name Valley tech firms, and they are doubling monthly.

Element42 – Fraud is a major problem — For example, if you buy a Rolex on eBay, you run the risk of winding up with a counterfeit. Started by ex-VPs from Citibank, the founders are using risk models and technologies that banks use to help brands combat fraud and counterfeiting. Designed with token economics, they also incentivize customers to buy genuine products by serving exclusive content and promotions only to genuine product holders. Built on blockchain at the core, they claim to be the world’s first peer-to-peer authentication platform for physical assets. They have 45 customers across two industry verticals, 800K in ARR and are a member of World Economic Forum’s global initiatives against corruption.

My90 – Distrust between the public and the police has rarely been more strained than it is today. My90 wants to solve that by collecting data about interactions between the police and the public—think traffic stops, service calls, etc.—and turn these into actionable intelligence via an online analytics dashboard. Users text My90 anonymously about their interactions, and My90’s dashboard analyzes the results using natural language processing. Customers include major city police departments like the San Jose Police Department and the world’s largest community policing program. They have booked $150K in pilots and are expanding aggressively across the US.

Nunetz – A Stanford Computer Science grad and UCSF Neurosurgeon have come together to try to build a single unifying interface to replace the deluge of monitors and data sources in today’s clinical health environment. The goal is to prepare a daily “battle map” for physicians, nurses, and other providers, with an initial focus on the Intensive Care Unit (ICU). They have closed 3 paid pilots with hospitals through grants.

When Labs – If you hate managing people, When Labs wants to unburden you. Using an AI-powered assistant that texts with employees to negotiate assignments for hourly work, WhenLabs is trying to free customers like Hilton from spending money on managers who would normally do this manually. As the system gets smarter, they claim employees will prefer interfacing with their AI bot more than a human. AI and HR is a crowded space, but this might be the team to separate from the pack: the founding team’s previous company had a 9 figure exit to IBM.

FirstCut – FirstCut helps businesses put video content out at scale. Video dominates social media — it creates 10x more comments than text — and is emerging as a necessity for B2B media. But putting video out if you are a B2B marketer normally requires using agencies that charge hefty fees. FirstCut wants to disrupt the agencies with software and marketplaces. They use software automation and an on-demand talent marketplace to offer a fixed price product for video content. They are at $180k revenue, and most of it is moving to recurring subscriptions.

LynxCare – LynxCare claims that 90% of healthcare data goes untapped when doctors make critical decisions about your life. Further, they claim the average person’s life could be extended by 4 years if that data can be converted into insights. Their team of clinicians and data scientists aims to do just that — building a data platform that aggregates disparate data sets and drive insight for better clinical outcomes. And it looks like their platform has fans: they are active in 9 hospitals, count Pharma companies like Pfizer as Partners, and grew 4x over the past year and now are at $800K ARR.

ADIAN – Adian is a B2B SaaS product that digitizes the complex agrochemical supply chain in order to improve the sales process between manufacturers and distributors. The company claims manufacturers reduce costs by 20% and increase sales by 4% by using their online framework. $1.5 Billion and 70,000 orders have gone through the platform to date.

Hardin Scientific – Hardin is building IoT-enabled, Smart Lab Equipment. The hardware becomes a gateway to become the hub for monitoring, controlling, and sharing scientific data across teams. They’ve closed over $1.5m in revenue, and raised $15m in equity and debt financing. One of their smart devices is being used to 3D print bio-tissues and human organs in space.

ZaiNar – This team of 5 Stanford grads — 3 PhD’s and 2 MBAs — joined up with the Co-Founder of BlueKai to build the world’s best time synchronization technology. ZaiNar claims their ability to wirelessly synchronize and distribute time between networked devices is a thousand times better than existing technologies. This enables them to locate RF-emitting devices (i.e. phones, cars, drones, & RFID) at long distances with sub-meter accuracy. Beyond location, this technology has applications across data transmission, 5G communications, and energy grids. ZaiNar has raised a $1.7 million seed from AME Cloud and Softbank, and has built an extensive patent portfolio.

SMART Brain Aging – This startup claims to reduce the onset of dementia by 2.25 years with software. They are the only company approved by Medicare to get reimbursed on a preventative basis for the treatment of dementia. In conjunction with Harvard University, they have developed 20,000 exercises that are clinically proven to reduce the onset of dementia and, they claim, help build neurotransmitters. The company works with 300 patients per week ($2.2 million annual revenue) and is building to a goal of helping 22,000 people in 24 months.

Phoneic – Phoneic believes the data trapped in voice calls from cellphones is a gold mine waiting to be unleashed. Their app records and transcribes cell phones conversations, and the company has built an integration layer to enterprise AI and CRM systems that traditionally didn’t have access to voice data. The team is led by the co-founder of 3jam, one of the first group SMS and virtual number companies, which was acquired by Skype in 2011. He is keenly aware of the power of virality — and like Skype, the use of Phoneic spreads its adoption. The company has already raised $800,000 in seed funding.

Arkose Labs – Whether or not you think Russia interfered with the 2016 election, it’s no secret that bots are having significant impact on society. Arkose Labs wants to fight fraud, without adding friction to legit users. Most fraud prevention platforms today focus on gathering info from the user and providing a probability score that the traffic is good or bad. This leaves companies with a difficult decision where they may be blocking revenue generating users. Arkose has a different approach, and uses a bilateral approach that doesn’t force this tradeoff. They claim to be the only solution to offer a 100% SLA on fraud prevention. Big companies like Singapore Airlines and Electronic Arts are customers. USVP led a $6 million investment into the company.