The fact that COVID-19 accelerated the need for digital transformation across virtually all sectors is old news. What companies are doing to propel success under the circumstances has been under the spotlight. However, how they do it has managed to find a place in the shadows.
Simply put, the explosive increase in innovation and adoption of digital solutions shouldn’t be allowed to take place at the expense of ethical considerations.
This is about morals — but it’s also about the bottom line. Stakeholders, both internal and external, are increasingly intolerant of companies that blur (or ignore) ethical lines. These realities add up to a need for leaders to embrace an all-new learning curve: How to engage in digital transformation that includes ethics by design.
Simply put, the explosive increase in innovation and adoption of digital solutions shouldn’t be allowed to take place at the expense of ethical considerations.
It’s easy to rail against the evils of the executive lifestyle or golden parachuting, but more often than not, a pattern of ethics violations arises from companywide culture, not leadership alone. Ideally, employees act ethically because it aligns with their personal values. However, at a minimum, they should understand the risk that an ethical breach represents to the organization.
In my experience, those conversations are not being held. Call it poor communication or lack of vision, but most companies rarely model potential ethical risks — at least not openly. If those discussions take place, they’re typically between members of upper management, behind closed doors.
Why don’t ethical concerns get more of a “town hall” treatment? The answer may come down to an unwillingness to let go of traditional thinking about business hierarchies. It could also be related to the strong (and ironically, toxic) cultural message that positivity rules. Case in point: I’ve listened to leaders say they want to create a culture of disruptive thinking — only to promptly tell an employee who speaks up that they “lack a growth mindset.”
What’s the answer, then? There are three solutions I’ve found to be effective:
These simple solutions are a great starting point to solve ethics issues regarding digital transformation and beyond. They cause leaders to look into the heart of the company and make decisions that will impact the organization for years to come.
Making digital shifts is, by nature, a technical operation. It requires personnel with advanced and varied expertise in areas such as AI and data operations. Leaders in the digital transformation space are expected to possess enough cross-domain competency to tackle tough problems.
That’s a big ask — bringing a host of technically minded people together can easily lead to a culture of expertise arrogance that leaves people who don’t know the lingo intimidated and reluctant to ask questions.
Digital transformation isn’t simply about infrastructure or tools. It is, at its heart, about change management, and a multifunctional approach is needed to ensure a healthy transition. The biggest mistake companies can make is assuming that only technical experts should be at the table. The silos that are built as a result inevitably turn into echo chambers — the last place you want to hold a conversation about ethics.
In the rush to go digital, regardless of how technical the problem, the solution will still be a fundamentally human-centric one.
Not all ethical imperatives related to digital transformation are as debatable as the suggestion that it should be people-first; some are much more black and white, like the fact that you have to start somewhere to get anywhere.
Luckily, “somewhere” doesn’t have to be from scratch. Government, risk and compliance (GRC) standards can be used to create a highly structured framework that’s mostly closed to interpretation and provides a solid foundation for building out and adopting digital solutions.
The utility of GRC models applies equally to startup multinationals and offers more than just a playbook; thoughtful application of GRC standards can also help with leadership evaluation, progress reports and risk analysis. Think of it like using bowling bumpers — they won’t guarantee you roll a strike, but they’ll definitely keep the ball out of the gutter.
Of course, a given company might not know how to create a GRC-based framework (just like most of us would be at a loss if tasked with building a set of bowling bumpers). This is why many turn to providers like IBM OpenPages, COBIT and ITIL for prefab foundations. These “starter kits” all share a single goal: Identify policies and controls that are relevant to your industry or organization and draw lines from those to pivotal compliance points.
Although getting started with the GRC process is typically cloud-based and at least partially automated, it requires organizationwide input and transparency. It can’t be effectively run by specific departments, or in a strictly top-down fashion. In fact, the single most important thing to understand about implementing GRC standards is that it will almost certainly fail unless both an organization’s leadership and broader culture fully support the direction in which it points.
Today’s leaders — executives, entrepreneurs, influencers and more — can’t be solely concerned with “winning” the digital race. Arguably, transformation is more of a marathon than a sprint, but either way, technique matters. In pursuing the end goal of competitive advantage, the how and why matter just as much as the what.
This is true for all arms of an organization. Internal stakeholders such as owners and employees risk their careers and reputations by tolerating a peripheral approach to ethics. External stakeholders like customers, investors and suppliers have just as much to lose. Their mutual understanding of this fact is what’s behind the collective, cross-industry push for transparency.
We’ve all seen the massive blowback against individuals and brands in the public eye who allow ethical lapses on their watch. It’s impossible to fully eliminate the risk of experiencing something similar, but it is a risk that can be managed. The danger is in letting the “tech blinders” of digital transformation interfere with your view of the big picture.
Companies that want to mitigate that risk and rise to the challenges of the digital era in a truly ethical way need to start by simply having conversations about what ethics, transparency and inclusivity mean — both in and around the organization. They need to follow up those conversations with action where necessary, and with open-mindedness across the board.
It’s smart to be worried about innovation lag in a time when enterprise is moving and shifting faster than ever, but there is time to make all the proper ethical considerations. Failing to do so will only derail you down the line.
Over the past several years I’ve covered my fair share of upstart avatar companies that were all chasing the same dream — building out a customizable platform for a digital persona that gained wide adoption across games and digital spaces. Few of those startups I’ve covered in the past are still around. But by netting a string of successful partnerships with celebrity musicians, LA-based Genies has come closer than any startup before it to realizing the full vision of a wide-reaching avatar platform.
The company announced today that they’ve closed a $65 million Series B led by Mary Meeker’s firm Bond. NEA, Breyer Capital, Tull Investment Group, NetEase, Dapper Labs and Coinbase Ventures also participated in the deal. Mary Meeker will be joining the Genies board. The company didn’t disclose the Genies’ most recent valuation.
This funding comes at an inflection point for the eight-year-old company, evidenced by the investments from NBA Top Shot-maker Dapper Labs and crypto giant Coinbase. As announced last week, the company is rolling out an NFT platform on Dapper Labs’ Flow blockchain, partnering closely with the startup, which will be building out the backend for a Genies avatar accessories storefront. Like Dapper Labs has leveraged its exclusive deals with sports leagues to ship NFTs with official backing, Genies is planning to capitalize on its partnerships with celebrities in its roster, including Justin Bieber, Shawn Mendes, Cardi B and others to create a platform for buying and trading avatar accessories en masse.
In October, the company announced a brand partnership with Gucci, opening the startup to another big market opportunity.
Genies’ business has largely focused on leveraging high-profile partnerships to give its entertainer clients a digital presence that can spice up what they’re sharing on social media and beyond. As they’ve rolled out avatar creation to all users through beta mobile apps, Genies has been focusing on one of the more explicit dreams of the avatar companies before it; building out a broad network of avatar users and a broad network of compatible platforms through its SDK.
“An avatar is a vehicle to be able to showcase more of your authentic self,” Genies CEO Akash Nigam tells TechCrunch. “It’s not limited by real-world constraints, it’s an alter-ego personality.”
Trends in the NFT world have provided new realms of exploration for Genies, but so have broader pandemic-era trends that have pushed more users to wholly digital spaces where they socialize and connect. “The pandemic accelerated everything,” Nigam says.
Nigam emphasizes that despite the major opportunity its upcoming NFT platform will present, Genies is still an avatar company first-and-foremost, not an NFT startup, though he does say he is believes crypto-backed digital goods are going to be around for a long time. He has few doubts that the current environment around digital goods helped juice Genies’ funding round, which he says was “6-8X oversubscribed” and was an opportunistic play for the startup, which “could have gone years without having to raise.”
The company says their crypto marketplace will launch in the coming months, as early as this summer.
With an increasing number of enterprise systems, growing teams, a rising proliferation of the web and multiple digital initiatives, companies of all sizes are creating loads of data every day. This data contains excellent business insights and immense opportunities, but it has become impossible for companies to derive actionable insights from this data consistently due to its sheer volume.
According to Verified Market Research, the analytics-as-a-service (AaaS) market is expected to grow to $101.29 billion by 2026. Organizations that have not started on their analytics journey or are spending scarce data engineer resources to resolve issues with analytics implementations are not identifying actionable data insights. Through AaaS, managed services providers (MSPs) can help organizations get started on their analytics journey immediately without extravagant capital investment.
MSPs can take ownership of the company’s immediate data analytics needs, resolve ongoing challenges and integrate new data sources to manage dashboard visualizations, reporting and predictive modeling — enabling companies to make data-driven decisions every day.
AaaS could come bundled with multiple business-intelligence-related services. Primarily, the service includes (1) services for data warehouses; (2) services for visualizations and reports; and (3) services for predictive analytics, artificial intelligence (AI) and machine learning (ML). When a company partners with an MSP for analytics as a service, organizations are able to tap into business intelligence easily, instantly and at a lower cost of ownership than doing it in-house. This empowers the enterprise to focus on delivering better customer experiences, be unencumbered with decision-making and build data-driven strategies.
Organizations that have not started on their analytics journey or are spending scarce data engineer resources to resolve issues with analytics implementations are not identifying actionable data insights.
In today’s world, where customers value experiences over transactions, AaaS helps businesses dig deeper into their psyche and tap insights to build long-term winning strategies. It also enables enterprises to forecast and predict business trends by looking at their data and allows employees at every level to make informed decisions.
Platforms like Shopify, Stripe and WordPress have done a lot to make essential business-building tools, like running storefronts, accepting payments, and building websites accessible to businesses with even the most modest budgets. But some very key aspects of setting up a company remain expensive, time-consuming affairs that can be cost-prohibitive for small businesses — but that, if ignored, can result in the failure of a business before it even really gets started.
Trademark registration is one such concern, and Toronto-based startup Heirlume just raised $1.7 million CAD (~$1.38 million) to address the problem with a machine-powered trademark registration platform that turns the process into a self-serve affair that won’t break the budget. Its AI-based trademark search will flag if terms might run afoul of existing trademarks in the U.S. and Canada, even when official government trademark search tools, and even top-tier legal firms might not.
Heirlume’s core focus is on levelling the playing field for small business owners, who have typically been significantly out-matched when it comes to any trademark conflicts.
“I’m a senior level IP lawyer focused in trademarks, and had practiced in a traditional model, boutique firm of my own for over a decade serving big clients, and small clients,” explained Heirlume co-founder Julie MacDonnell in an interview. “So providing big multinationals with a lot of brand strategy, and in-house legal, and then mainly serving small business clients when they were dealing with a cease-and-desist, or an infringement issue. It’s really those clients that have my heart: It’s incredibly difficult to have a small business owner literally crying tears on the phone with you, because they just lost their brand or their business overnight. And there was nothing I could do to help because the law just simply wasn’t on their side, because they had neglected to register their trademarks to own them.”
In part, there’s a lack of awareness around what it takes to actually register and own a trademark, MacDonnell says. Many entrepreneurs just starting out seek out a domain name as a first step, for instance, and some will fork over significant sums to register these domains. What they don’t realize, however, is that this is essentially a rental, and if you don’t have the trademark to protect that domain, the actual trademark owner can potentially take it away down the road. But even if business owners do realize that a trademark should be their first stop, the barriers to actually securing one are steep.
“There was an an enormous, insurmountable barrier, when it came to brand protection for those business owners,” she said. “And it just isn’t fair. Every other business service, generally a small business owner can access. Incorporating a company or even insurance, for example, owning and buying insurance for your business is somewhat affordable and accessible. But brand ownership is not.”
Heirlume brings the cost of trademark registration down from many thousands of dollars, to just under $600 for the first, and only $200 for each additional after that. The startup is also offering a very small business-friendly ‘buy now, pay later’ option supported by Clearbanc, which means that even businesses starting on a shoestring can take step of protecting their brand at the outset.
In its early days, Heirlume is also offering its core trademark search feature for free. That provides a trademark search engine that works across both U.S. and Canadian government databases, which can not only tell you if your desired trademark is available or already held, but also reveal whether it’s likely to be able to be successfully obtained, given other conflicts that might arise that are totally ignored by native trademark database search portals.
Heirlume uses machine learning to identify these potential conflicts, which not only helps users searching for their trademarks, but also greatly decreases the workload behind the scenes, helping them lower costs and pass on the benefits of those improved margins to its clients. That’s how it can achieve better results than even hand-tailored applications from traditional firms, while doing so at scale and at reduced costs.
Another advantage of using machine-powered data processing and filing is that on the government trademark office side, the systems are looking for highly organized, curated data sets that are difficult for even trained people to get consistently right. Human error in just data entry can cause massive backlogs, MacDonnell notes, even resulting in entire applications having to be tossed and started over from scratch.
“There are all sorts of datasets for those [trademark requirement] parameters,” she said. “Essentially, we synthesize all of that, and the goal through machine learning is to make sure that applications are utterly compliant with government rules. We actually have a senior level trademark examiner that that came to work for us, very excited that we were solving the problems causing backlogs within the government. She said that if Heirlume can get to a point where the applications submitted are perfect, there will be no backlog with the government.”
Improving efficiency within the trademark registration bodies means one less point of friction for small business owners when they set out to establish their company, which means more economic activity and upside overall. MacDonnell ultimately hopes that Heirlume can help reduce friction to the point where trademark ownership is at the forefront of the business process, even before domain registration. Heirlume has a partnership with Google Domains to that end, which will eventually see indication of whether a domain name is likely to be trademarkable included in Google Domain search results.
This initial seed funding includes participation from Backbone Angels, as well as the Future Capital collective, Angels of Many and MaRS IAF, along with angel investors including Daniel Debow, Sid Lee’s Bertrand Cesvet and more. MacDonnell notes that just as their goal was to bring more access and equity to small business owners when it comes to trademark protection, the startup was also very intentional in building its team and its cap table. MacDonnell, along with co-founders CTO Sarah Guest and Dave McDonnell, aim to build the largest tech company with a majority female-identifying technology team. Its investor make-up includes 65% female-identifying or underrepresented investors, and MacDonnell says that was a very intentional choice that extended the time of the raise, and even led to turning down interest from some leading Silicon Valley firms.
“We want underrepresented founders to be to be funded, and the best way to ensure that change is to empower underrepresented investors,” she said. “I think that we all have a responsibility to actually do do something. We’re all using hashtags right now, and hashtags are not enough […] Our CTO is female, and she’s often been the only female person in the room. We’ve committed to ensuring that women in tech are no longer the only person in the room.”
Machine learning is capable of doing all sorts of things as long as you have the data to teach it how. That’s not always easy, and researchers are always looking for a way to add a bit of “common sense” to AI so you don’t have to show it 500 pictures of a cat before it gets it. Facebook’s newest research takes a big step toward reducing the data bottleneck.
The company’s formidable AI research division has been working for years now on how to advance and scale things like advanced computer vision algorithms, and has made steady progress, generally shared with the rest of the research community. One interesting development Facebook has pursued in particular is what’s called “semi-supervised learning.”
Generally when you think of training an AI, you think of something like the aforementioned 500 pictures of cats — images that have been selected and labeled (which can mean outlining the cat, putting a box around the cat or just saying there’s a cat in there somewhere) so that the machine learning system can put together an algorithm to automate the process of cat recognition. Naturally if you want to do dogs or horses, you need 500 dog pictures, 500 horse pictures, etc. — it scales linearly, which is a word you never want to see in tech.
Semi-supervised learning, related to “unsupervised” learning, involves figuring out important parts of a data set without any labeled data at all. It doesn’t just go wild, there’s still structure; for instance, imagine you give the system a thousand sentences to study, then showed it 10 more that have several of the words missing. The system could probably do a decent job filling in the blanks just based on what it’s seen in the previous thousand. But that’s not so easy to do with images and video — they aren’t as straightforward or predictable.
But Facebook researchers have shown that while it may not be easy, it’s possible and in fact very effective. The DINO system (which stands rather unconvincingly for “DIstillation of knowledge with NO labels”) is capable of learning to find objects of interest in videos of people, animals and objects quite well without any labeled data whatsoever.
It does this by considering the video not as a sequence of images to be analyzed one by one in order, but as a complex, interrelated set, like the difference between “a series of words” and “a sentence.” By attending to the middle and the end of the video as well as the beginning, the agent can get a sense of things like “an object with this general shape goes from left to right.” That information feeds into other knowledge, like when an object on the right overlaps with the first one, the system knows they’re not the same thing, just touching in those frames. And that knowledge in turn can be applied to other situations. In other words, it develops a basic sense of visual meaning, and does so with remarkably little training on new objects.
This results in a computer vision system that’s not only effective — it performs well compared with traditionally trained systems — but more relatable and explainable. For instance, while an AI that has been trained with 500 dog pictures and 500 cat pictures will recognize both, it won’t really have any idea that they’re similar in any way. But DINO — although it couldn’t be specific — gets that they’re similar visually to one another, more so anyway than they are to cars, and that metadata and context is visible in its memory. Dogs and cats are “closer” in its sort of digital cognitive space than dogs and mountains. You can see those concepts as little blobs here — see how those of a type stick together:
This has its own benefits, of a technical sort we won’t get into here. If you’re curious, there’s more detail in the papers linked in Facebook’s blog post.
There’s also an adjacent research project, a training method called PAWS, which further reduces the need for labeled data. PAWS combines some of the ideas of semi-supervised learning with the more traditional supervised method, essentially giving the training a boost by letting it learn from both the labeled and unlabeled data.
Facebook of course needs good and fast image analysis for its many user-facing (and secret) image-related products, but these general advances to the computer vision world will no doubt be welcomed by the developer community for other purposes.
In the early 2000s, Jeff Bezos gave a seminal TED Talk titled “The Electricity Metaphor for the Web’s Future.” In it, he argued that the internet will enable innovation on the same scale that electricity did.
We are at a similar inflection point in healthcare, with the recent movement toward data transparency birthing a new generation of innovation and startups.
Those who follow the space closely may have noticed that there are twin struggles taking place: a push for more transparency on provider and payer data, including anonymous patient data, and another for strict privacy protection for personal patient data. What’s the main difference?
This sector is still somewhat nascent — we are in the first wave of innovation, with much more to come.
Anonymized data is much more freely available, while personal data is being locked even tighter (as it should be) due to regulations like GDPR, CCPA and their equivalents around the world.
The former trend is enabling a host of new vendors and services that will ultimately make healthcare better and more transparent for all of us.
These new companies could not have existed five years ago. The Affordable Care Act was the first step toward making anonymized data more available. It required healthcare institutions (such as hospitals and healthcare systems) to publish data on costs and outcomes. This included the release of detailed data on providers.
Later legislation required biotech and pharma companies to disclose monies paid to research partners. And every physician in the U.S. is now required to be in the National Practitioner Identifier (NPI), a comprehensive public database of providers.
All of this allowed the creation of new types of companies that give both patients and providers more control over their data. Here are some key examples of how.
This is a key capability of patients’ newly found access to health data. Think of how often, as a patient, providers aren’t aware of treatment or a test you’ve had elsewhere. Often you end up repeating a test because a provider doesn’t have a record of a test conducted elsewhere.
Cybersecurity nightmares like the SolarWinds hack highlight how malicious hackers continue to exploit vulnerabilities in software and apps to do their dirty work. Today a startup that’s built a platform to help organizations protect themselves from this by running threat detection and response at the network level is announcing a big round of funding to continue its growth.
Vectra AI, which provides a cloud-based service that uses artificial intelligence technology to monitor both on-premise and cloud-based networks for intrusions, has closed a round of $130 million at a post-money valuation of $1.2 billion.
The challenge that Vectra is looking to address is that applications — and the people who use them — will continue to be weak links in a company’s security set-up, not least because malicious hackers are continually finding new ways to piece together small movements within them to build, lay and finally use their traps. While there will continue to be an interesting, and mostly effective, game of cat-and-mouse around those applications, a service that works at the network layer is essential as an alternative line of defense, one that can find those traps before they are used.
“Think about where the cloud is. We are in the wild west,” Hitesh Sheth, Vectra’s CEO, said in an interview. “The attack surface is so broad and attacks happen at such a rapid rate that the security concerns have never been higher at the enterprise. That is driving a lot of what we are doing.”
Sheth said that the funding will be used in two areas. First, to continue expanding its technology to meet the demands of an ever-growing threat landscape — it also has a team of researchers who work across the business to detect new activity and build algorithms to respond to it. And second, for acquisitions to bring in new technology and potentially more customers.
(Indeed, there has been a proliferation of AI-based cybersecurity startups in recent years, in areas like digital forensics, application security and specific sectors like SMBs, all of which complement the platform that Vectra has built, so you could imagine a number of interesting targets.)
The funding is being led by funds managed by Blackstone Growth, with unnamed existing investors participating (past backers include Accel, Khosla and TCV, among other financial and strategic investors). Vectra today largely focuses on enterprises, highly demanding ones with lots at stake to lose. Blackstone was initially a customer of Vectra’s, using the company’s flagship Cognito platform, Viral Patel — the senior MD who led the investment for the firm — pointed out to me.
The company has built some specific products that have been very prescient in anticipating vulnerabilities in specific applications and services. While it said that sales of its Cognito platform grew 100% last year, Cognito Detect for Microsoft Office 365 (a separate product) sales grew over 700%. Coincidentally, Microsoft’s cloud apps have faced a wave of malicious threats. Sheth said that implementing Cognito (or indeed other network security protection) “could have prevented the SolarWinds hack” for those using it.
“Through our experience as a client of Vectra, we’ve been highly impressed by their world-class technology and exceptional team,” John Stecher, CTO at Blackstone, said in a statement. “They have exactly the types of tools that technology leaders need to separate the signal from the noise in defending their organizations from increasingly sophisticated cyber threats. We’re excited to back Vectra and Hitesh as a strategic partner in the years ahead supporting their continued growth.”
Looking ahead, Sheth said that endpoint security will not be a focus for the moment because “in cloud there is so much open territory”. Instead it partners with the likes of CrowdStrike, SentinelOne, Carbon Black and others.
In terms of what is emerging as a stronger entry point, social media is increasingly coming to the fore, he said. “Social media tends to be an effective vector to get in and will remain to be for some time,” he said, with people impersonating others and suggesting conversations over encrypted services like WhatsApp. “The moment you move to encryption and exchange any documents, it’s game over.”
Growing up, did you ever wonder how many chairs you’d have to stack to reach the sky?
No? I guess that’s just me then.
As a child, I always asked a lot of “how many/much” questions. Some were legitimate (“How much is 1 USD in VND?”); some were absurd (“How tall is the sky and can it be measured in chairs?”). So far, I’ve managed to maintain my obnoxious statistical probing habit without making any mortal enemies in my 20s. As it turns out, that habit comes with its perks when working in product.
Growing up, did you ever wonder how many chairs you’d have to stack to reach the sky?
My first job as a product designer was at a small but energetic fintech startup whose engineers also dabbled in pulling data. I constantly bothered them with questions like, “How many exports did we have from that last feature launched?” and “How many admins created at least one rule on this page?” I was curious about quantitative analysis but did not know where to start.
I knew I wasn’t the only one. Even then, there was a growing need for basic data literacy in the tech industry, and it’s only getting more taxing by the year. Words like “data-driven,” “data-informed” and “data-powered” increasingly litter every tech organization’s product briefs. But where does this data come from? Who has access to it? How might I start digging into it myself? How might I leverage this data in my day-to-day design once I get my hands on it?
“Curiosity is our compass” is one of Kickstarter’s guiding principles. Powered by a desire for knowledge and information, curiosity is the enemy of many larger, older and more structured organizations — whether they admit it or not — because it hinders the production flow. Curiosity makes you pause and take time to explore and validate the “ask.” Asking as many what’s, how’s, why’s, who’s and how many’s as possible is important to help you learn if the work is worth your time.
The last year of pandemic living has been real-world, and sometimes harrowing, proof of how important it can be to have efficient and well-equipped emergency response services in place. They can help people remotely if need be, and when they cannot, they make sure that in-person help can be dispatched quickly in medical and other situations. Today, a company that’s building cloud-based tools to help with this process is announcing a round of funding as it continues to grow.
RapidDeploy, which provides computer-aided dispatch technology as a cloud-based service for 911 centers, has closed a round of $29 million, a Series B round of funding that will be used both to grow its business, and to continue expanding the SaaS tools that it provides to its customers. In the startup’s point of view, the cloud is essential to running emergency response in the most efficient manner.
“911 response would have been called out on a walkie talkie in the early days,” said Steve Raucher, the co-founder and CEO of RapidDeploy, in an interview. “Now the cloud has become the nexus of signals.”
Washington, DC-based RapidDeploy provides data and analytics to 911 centers — the critical link between people calling for help and connecting those calls with the nearest medical, police or fire assistance — and today it has about 700 customers using its RadiusPlus, Eclipse Analytics and Nimbus CAD products.
That works out to about 10% of all 911 centers in the US (7,000 in total), and covering 35% of the population (there are more centers in cities and other dense areas). Its footprint includes state coverage in Arizona, California, and Kansas. It also has operations in South Africa, where it was originally founded.
The funding is coming from an interesting mix of financial and strategic investors. Led by Morpheus Ventures, the round also had participation from GreatPoint Ventures, Ericsson Ventures, Samsung Next Ventures, Tao Capital Partners, Tau Ventures, among others. It looks like the company had raised about $30 million before this latest round, according to PitchBook data. Valuation is not being disclosed.
Ericsson and Samsung, as major players in the communication industry, have a big stake in seeing through what will be the next generation of communications technology and how it is used for critical services. (And indeed, one of the big leaders in legacy and current 911 communications is Motorola, a would-be competitor of both.) AT&T is also a strategic go-to-market (distribution and sales) partner of RapidDeploy’s, and it also has integrations with Apple, Google, Microsoft, and OnStar to feed data into its system.
The business of emergency response technology is a fragmented market. Raucher describes them as “mom-and-pop” businesses, with some 80% of them occupying four seats or less (a testament to the fact that a lot of the US is actually significantly less urban than its outsized cities might have you think it is), and in many cases a lot of these are operating on legacy equipment.
However, in the US in the last several years — buffered by innovations like the Jedi project and FirstNet, a next-generation public safety network — things have been shifting. RapidDeploy’s technology sits alongside (and in some areas competes with) companies like Carbyne and RapidSOS, which have been tapping into the innovations of cell phone technology both to help pinpoint people and improve how to help them.
RapidDeploy’s tech is based around its RadiusPlus mapping platform, which uses data from smart phones, vehicles, home security systems and other connected devices and channels it to its data stream, which can help a center determine not just location but potentially other aspects of the condition of the caller. Its Eclipse Analytics services, meanwhile, are meant to act as a kind of assistant to those centers to help triage situations and provide insights into how to respond. The Nimbus CAD then helps figure out who to call out and routing for response.
Longer term, the plan will be to leverage cloud architecture to bring in new data sources and ways of communicating between callers, centers and emergency care providers.
“It’s about being more of a triage service rather than a message switch,” Raucher said. “As we see it, the platform will evolve with customers’ needs. Tactical mapping ultimately is not big enough to cover this. We’re thinking about unified communications.” Indeed, that is the direction that many of these services seem to be going, which can only be a good thing for us consumers.
“The future of emergency services is in data, which creates a faster, more responsive 9-1-1 center,” said Mark Dyne, Founding Partner at Morpheus Ventures, in a statement. “We believe that the platform RapidDeploy has built provides the necessary breadth of capabilities that make the dream of Next-Gen 9-1-1 service a reality for rural and metropolitan communities across the nation and are excited to be investing in this future with Steve and his team.” Dyne has joined the RapidDeploy board with this round.
TikTok will open a center in Europe where outside experts will be shown information on how it approaches content moderation and recommendation, as well as platform security and user privacy, it announced today.
The European Transparency and Accountability Centre (TAC) follows the opening of a U.S. center last year — and is similarly being billed as part of its “commitment to transparency”.
Soon after announcing its U.S. TAC, TikTok also created a content advisory council in the market — and went on to replicate the advisory body structure in Europe this March, with a different mix of experts.
It’s now fully replicating the U.S. approach with a dedicated European TAC.
To-date, TikTok said more than 70 experts and policymakers have taken part in a virtual U.S. tour, where they’ve been able to learn operational details and pose questions about its safety and security practices.
The short-form video social media site has faced growing scrutiny over its content policies and ownership structure in recent years, as its popularity has surged.
Concerns in the U.S. have largely centered on the risk of censorship and the security of user data, given the platform is owned by a Chinese tech giant and subject to Internet data laws defined by the Chinese Communist Party.
While, in Europe, lawmakers, regulators and civil society have been raising a broader mix of concerns — including around issues of child safety and data privacy.
In one notable development earlier this year, the Italian data protection regulator made an emergency intervention after the death of a local girl who had reportedly been taking part in a content challenge on the platform. TikTok agreed to recheck the age of all users on its platform in Italy as a result.
TikTok said the European TAC will start operating virtually, owing to the ongoing COVID-19 pandemic. But the plan is to open a physical center in Ireland — where it bases its regional HQ — in 2022.
EU lawmakers have recently proposed a swathe of updates to digital legislation that look set to dial up emphasis on the accountability of AI systems — including content recommendation engines.
A draft AI regulation presented by the Commission last week also proposes an outright ban on subliminal uses of AI technology to manipulate people’s behavior in a way that could be harmful to them or others. So content recommender engines that, for example, nudge users into harming themselves by suggestively promoting pro-suicide content or risky challenges may fall under the prohibition. (The draft law suggests fines of up to 6% of global annual turnover for breaching prohibitions.)
It’s certainly interesting to note TikTok also specifies that its European TAC will offer detailed insight into its recommendation technology.
“The Centre will provide an opportunity for experts, academics and policymakers to see first-hand the work TikTok teams put into making the platform a positive and secure experience for the TikTok community,” the company writes in a press release, adding that visiting experts will also get insights into how it uses technology “to keep TikTok’s community safe”; how trained content review teams make decisions about content based on its Community Guidelines; and “the way human reviewers supplement moderation efforts using technology to help catch potential violations of our policies”.
Another component of the EU’s draft AI regulation sets a requirement for human oversight of high risk applications of artificial intelligence. Although it’s not clear whether a social media platform would fall under that specific obligation, given the current set of categories in the draft regulation.
However the AI regulation is just one piece of the Commission’s platform-focused rule-making.
Late last year it also proposed broader updates to rules for digital services, under the DSA and DMA, which will place due diligence obligations on platforms — and also require larger platforms to explain any algorithmic rankings and hierarchies they generate. And TikTok is very likely to fall under that requirement.
The UK — which is now outside the bloc, post-Brexit — is also working on its own Online Safety regulation, due to present this year. So in the coming years there will be multiple content-focused regulatory regimes for platforms like TikTok to comply with in Europe. And opening your algorithms to outside experts may be hard requirement, not soft PR.
Commenting on the launch of its European TAC in a statement, Cormac Keenan, TikTok’s head of trust and safety, said: “With more than 100 million users across Europe, we recognise our responsibility to gain the trust of our community and the broader public. Our Transparency and Accountability Centre is the next step in our journey to help people better understand the teams, processes, and technology we have to help keep TikTok a place for joy, creativity, and fun. We know there’s lots more to do and we’re excited about proactively addressing the challenges that lie ahead. I’m looking forward to welcoming experts from around Europe and hearing their candid feedback on ways we can further improve our systems.”
Swedish digital health startup Kry, which offers a telehealth service (and software tools) to connect clinicians with patients for remote consultations, last raised just before the pandemic hit in Western Europe, netting a €140M Series C in January 2020.
Today it’s announcing an oversubscribed sequel: The Series D raise clocks in at $312M (€262M) and will be used to keep stepping on the growth gas in the region.
Investors in this latest round for the 2015-founded startup are a mix of old and new backers: The Series D is led by CPP Investments (aka, the Canadian Pension Plan Investment Board) and Fidelity Management & Research LLC, with participation from existing investors including The Ontario Teachers’ Pension Plan, as well as European-based VC firms Index Ventures, Accel, Creandum and Project A.
The need for people to socially distance during the coronavirus pandemic has given obvious uplift to the telehealth category, accelerating the rate of adoption of digital health tools that enable remote consultations by both patients and clinicians. Kry quickly stepped in to offer a free service for doctors to conduct web-based consultations last year, saying at the time that it felt a huge responsibility to help.
That agility in a time of public health crisis has clearly paid off. Kry’s year-over-year growth in 2020 was 100% — meaning that the ~1.6M digital doctors appointments it had served up a year ago now exceed 3M. Some 6,000 clinicians are also now using its telehealth platform and software tools. (It doesn’t break out registered patient numbers).
Yet co-founder and CEO, Johannes Schildt, says that, in some ways, it’s been a rather quiet 12 months for healthcare demand.
Sure the pandemic has driven specific demand, related to COVID-19 — including around testing for the disease (a service Kry offers in some of its markets) — but he says national lockdowns and coronavirus concerns have also dampened some of the usual demand for healthcare. So he’s confident that the 100% growth rate Kry has seen amid the COVID-19 public health crisis is just a taster of what’s to come — as healthcare provision shifts toward more digital delivery.
“Obviously we have been on the right side of a global pandemic. And if you look back the mega trend was obviously there long before the pandemic but the pandemic has accelerated the trend and it has served us and the industry well in terms of anchoring what we do. It’s now very well anchored across the globe — that telemedicine and digital healthcare is a crucial part of the healthcare systems moving forward,” Schildt tells TechCrunch.
“Demand has been increasing during the year, most obviously, but if you look at the broader picture of healthcare delivery — in most European markets — you actually have healthcare usage at an all time low. Because a lot of people are not as sick anymore given that you have tight restrictions. So it’s this rather strange dynamic. If you look at healthcare usage in general it’s actually at an all time low. But telemedicine is on an upward trend and we are operating on higher volumes… than we did before. And that is great, and we have been hiring a lot of great clinicians and been shipping a lot of great tools for clinicians to make the shift to digital.”
The free version of Kry’s tools for clinicians generated “big uplift” for the business, per Schildt, but he’s more excited about the wider service delivery shifts that are happening as the pandemic has accelerated uptake of digital health tools.
“For me the biggest thing has been that [telemedicine is] now very well established, it’s well anchored… There is still a different level of maturity between different European markets. Even [at the time of Kry’s Series C round last year] telemedicine was maybe not something that was a given — for us it’s always been of course; for me it’s always been crystal clear that this is the way of the future; it’s a necessity, you need to shift a lot of the healthcare delivery to digital. We just need to get there.”
The shift to digital is a necessary one, Schildt argues, in order to widen access to (inevitably) limited healthcare resources vs ever growing demand (current pandemic lockdown dampeners excepted). This is why Kry’s focus has always been on solving inefficiencies in healthcare delivery.
It seeks to do that in a variety of ways — including by offering support tools for clinicians working in public healthcare systems (for example, more than 60% of all the GPs in the UK market, where most healthcare is delivered via the taxpayer-funded NHS, is using Kry’s tools, per Schildt); as well as (in a few markets) running a full healthcare service itself where it combines telemedicine with a network of physical clinics where users can go when they need to be examined in person by a clinician. It also has partnerships with private healthcare providers in Europe.
In short, Kry is agnostic about how it helps deliver healthcare. That philosophy extends to the tech side — meaning video consultations are just one component of its telemedicine business which offers remote consultations for a range of medical issues, including infections, skin conditions, stomach problems and psychological disorders. (Obviously not every issue can be treated remotely but at the primary care level there are plenty of doctor-patient visits that don’t need to take place in person.)
Kry’s product roadmap — which is getting an investment boost with this new funding — involves expanding its patient-facing app to offer more digitally delivered treatments, such as Internet Cognitive Based Therapy (ICBT) and mental health self-assessment tools. It also plans to invest in digital healthcare tools to support chronic healthcare conditions — whether by developing more digital treatments itself (either by digitizing existing, proven treatments or coming up with novel approaches), and/or expanding its capabilities via acquisitions and strategic partnerships, according to Schildt.
Over the past five+ years, a growing number of startups have been digitizing proven treatment programs, such as for disorders like insomnia and anxiety, or musculoskeletal and chronic conditions that might otherwise require accessing a physiotherapist in person. Options for partners for Kry to work with on expanding its platform are certainly plentiful — although it’s developed the ICBT programs in house so isn’t afraid to tackle the digital treatment side itself.
“Given that we are in the fourth round of this massive change and transition in healthcare it makes a lot of sense for us to continue to invest in great tools for clinicians to deliver high quality care at great efficiency and deepening the experience from the patient side so we can continue to help even more people,” says Schildt.
“A lot of what we do we do is through video and text but that’s just one part of it. Now we’re investing a lot in our mental health plans and doing ICBT treatment plans. We’re going deeper into chronic treatments. We have great tools for clinicians to deliver high quality care at scale. Both digitally and physically because our platform supports both of it. And we have put a lot of effort during this year to link together our digital healthcare delivery with our physical healthcare delivery that we sometimes run ourselves and we sometimes do in partnerships. So the video itself is just one piece of the puzzle. And for us it’s always been about making sure we saw this from the end consumer’s perspective, from the patient’s perspective.”
“I’m a patient myself and still a lot of what we do is driven by my own frustration on how inefficient the system is structured in some areas,” he adds. “You do have a lot of great clinicians out there but there’s truly a lack of patient focus and in a lot of European markets there’s a clear access problem. And that has always been our starting point — how can we make sure that we solve this in a better way for the patients? And then obviously that involves us both building strong tools and front ends for patients so they can easily access care and manage their health, be pro-active about their health. It also involves us building great tools for clinicians that they can operate and work within — and there we’re putting way more effort as well.
“A lot of clinicians are using our tools to deliver digital care — not only clinicians that we run ourselves but ones we’re partnering with. So we do a lot of it in partnerships. And then also, given that we are a European provider, it involves us partnering with both public and private payers to make sure that the end consumer can actually access care.”
Another batch of startups in the digital healthcare delivery space talk a big game about ‘democratizing’ access to healthcare with the help of AI-fuelled triage or even diagnosis chatbots — with the idea that these tools can replace at least some of the work done by human doctors. The loudest on that front is probably Babylon Health.
Kry, by contrast, has avoided flashy AI hype, even though its tools do frequently incorporate machine learning technology, per Schildt. It also doesn’t offer a diagnosis chatbot. The reason for its different emphasis comes back to the choice of problem to focus on: Inefficiencies in healthcare delivery — with Schildt arguing that decision-making by doctors isn’t anywhere near the top of the list of service pain-points in the sector.
“We’re obviously using what would be considered AI or machine learning tools in all products that we’re building. I think sometimes personally I’m a bit annoyed at companies screaming and shouting about the technology itself and less about what problem you are solving with it,” he tells us. “On the decision-support [front], we don’t have the same sort of chatbot system that some other companies do, no. It’s obviously something that we could build really effortlessly. But I think — for me — it’s always about asking yourself what is the problem that you’re solving for? For the patient. And to be honest I don’t find it very useful.
“In many cases, especially in primary care, you have two categories. You have patients that already know why they need help, because you have a urinary tract infection; you had it before. You have an eye infection. You have a rash — you know that it’s a rash, you need to see someone, you need to get help. Or you’re worried about your symptoms and you’re not really sure what it is — and you need comfort. And I think we’re not there yet where a chatbot would give you that sort of comfort, if this is something severe or not. You still want to talk to a human being. So I think it’s of limited use.
“Then on the decision side of it — sort of making sure that clinicians are making better decisions — we are obviously doing decision support for our clinicians. But if it’s one thing clinicians are really good at it’s actually making decisions. And if you look into the inefficiencies in healthcare the decision-making process is not the inefficiency. The matching side is an inefficiency side.”
He gives the example of how much the Swedish healthcare system spends on translators (circa €200M) as a “huge inefficiency” that could be reduced simply — by smarter matching of multilingual clinicians to patients.
“Most of our doctors are bilingual but they’re not there at the same time as the patient. So on the matching side you have a lot of inefficiency — and that’s where we have spent time on, for example. How can we sort that, how can we make sure that a patient that is seeking help with us ends up with the right level of care? If that is someone that speaks your native language so you can actually understand each other. Is this something that could be fully treated by a nurse? Or should it be directly to a psychologist?”
“With all technology it’s always about how do we use technology to solve a real problem, it’s less about the technology itself,” he adds.
Another ‘inefficiency’ that can affect healthcare provision in Europe relates to a problematic incentive to try to shrink costs (and, if it’s private healthcare, maximize an insurer’s profits) by making it harder for patients to access primary medical care — whether through complicated claims processes or by offering a bare minimum of information and support to access services (or indeed limiting appointment availability), making patients do the legwork of tracking down a relevant professional for their particular complaint and obtaining a coveted slot to see them.
It’s a maddening dynamic in a sector that should be focused on making as many people as healthy as they possibly can be in order that they avoid as much disease as possible — obviously as that outcome is better for the patients themselves. But also given the costs involved in treating really sick people (medical and societal). A wide range of chronic conditions, from type 2 diabetes to lower back pain, can be particularly costly to treat and yet may be entirely preventable with the right interventions.
Schildt sees a key role for digital healthcare tools to drive a much needed shift toward the kind of preventative healthcare that would be better all round, for both patients and for healthcare costs.
“That annoys me a lot,” he says. “That’s sometimes how healthcare systems are structured because it’s just costly for them to deliver healthcare so they try to make it as hard as possible for people to access healthcare — which is an absurdity and also one of the reasons why you now have increasing costs in healthcare systems in general, it’s exactly that. Because you have a lack of access in the first point of contact, with primary care. And what happens is you do have a spillover effect to secondary care.
“We see that in the data in all European markets. You have people ending up in emergency rooms that should have been treated in primary care but they can’t access primary care because there’s no access — you don’t know how to get in there, it’s long waiting times, it’s just triaged to different levels without getting any help and you have people with urinary tract infections ending up in emergency rooms. It’s super costly… when you have healthcare systems trying to fend people off. That’s not the right way doing it. You have to — and I think we will be able to play a crucial role in that in the coming ten years — push the whole system into being more preventative and proactive and access is a key part of that.
“We want to make it very, very simple for the patients — that they should be able to reach out to us and we will direct you to the right level of care.”
With so much still to do tackling the challenges of healthcare delivery in Europe, Kry isn’t in a hurry to expand its services geographically. Its main markets are Sweden, Norway, France, Germany and the UK, where it operates a healthcare service itself (not necessarily nationwide), though it notes that it offers a video consultation service to 30 regional markets.
“Right now we are very European focused,” says Schildt, when asked whether it has any plans for a U.S. launch. “I would never say that we would never go outside of Europe but for here and now we are extremely focused on Europe, we know those markets very, very well. We know how to manoeuvre in the European systems.
“It’s a very different payer infrastructure in Europe vs the US and then it’s also so that focus is always king and Europe is the mega market. Healthcare is 10% of the GDP in all European markets, we don’t have to go outside of Europe to build a very big business. But for the time being I think it makes a lot of sense for us to stay focused.”
Sign language is used by millions of people around the world, but unlike Spanish, Mandarin or even Latin, there’s no automatic translation available for those who can’t use it. SLAIT claims the first such tool available for general use, which can translate around 200 words and simple sentences to start — using nothing but an ordinary computer and webcam.
People with hearing impairments, or other conditions that make vocal speech difficult, number in the hundreds of millions, rely on the same common tech tools as the hearing population. But while emails and text chat are useful and of course very common now, they aren’t a replacement for face-to-face communication, and unfortunately there’s no easy way for signing to be turned into written or spoken words, so this remains a significant barrier.
We’ve seen attempts at automatic sign language (usually American/ASL) translation for years and years. In 2012 Microsoft awarded its Imagine Cup to a student team that tracked hand movements with gloves; in 2018 I wrote about SignAll, which has been working on a sign language translation booth using multiple cameras to give 3D positioning; and in 2019 I noted that a new hand-tracking algorithm called MediaPipe, from Google’s AI labs, could lead to advances in sign detection. Turns out that’s more or less exactly what happened.
SLAIT is a startup built out of research done at the Aachen University of Applied Sciences in Germany, where co-founder Antonio Domènech built a small ASL recognition engine using MediaPipe and custom neural networks. Having proved the basic notion, Domènech was joined by co-founders Evgeny Fomin and William Vicars to start the company; they then moved on to building a system that could recognize first 100, and now 200 individual ASL gestures and some simple sentences. The translation occurs offline, and in near real time on any relatively recent phone or computer.
They plan to make it available for educational and development work, expanding their dataset so they can improve the model before attempting any more significant consumer applications.
Of course, the development of the current model was not at all simple, though it was achieved in remarkably little time by a small team. MediaPipe offered an effective, open-source method for tracking hand and finger positions, sure, but the crucial component for any strong machine learning model is data, in this case video data (since it would be interpreting video) of ASL in use — and there simply isn’t a lot of that available.
As they recently explained in a presentation for the DeafIT conference, the first team evaluated using an older Microsoft database, but found that a newer Australian academic database had more and better quality data, allowing for the creation of a model that is 92 percent accurate at identifying any of 200 signs in real time. They have augmented this with sign language videos from social media (with permission, of course) and government speeches that have sign language interpreters — but they still need more.
A GIF showing one of the prototypes in action — the consumer product won’t have a wireframe, obviously. Image Credits: SLAIT
Their intention is to make the platform available to the deaf and ASL learner communities, who hopefully won’t mind their use of the system being turned to its improvement.
And naturally it could prove an invaluable tool in its present state, since the company’s translation model, even as a work in progress, is still potentially transformative for many people. With the amount of video calls going on these days and likely for the rest of eternity, accessibility is being left behind — only some platforms offer automatic captioning, transcription, summaries, and certainly none recognize sign language. But with SLAIT’s tool people could sign normally and participate in a video call naturally rather than using the neglected chat function.
“In the short term, we’ve proven that 200 word models are accessible and our results are getting better every day,” said SLAIT’s Evgeny Fomin. “In the medium term, we plan to release a consumer facing app to track sign language. However, there is a lot of work to do to reach a comprehensive library of all sign language gestures. We are committed to making this future state a reality. Our mission is to radically improve accessibility for the Deaf and hard of hearing communities.”
He cautioned that it will not be totally complete — just as translation and transcription in or to any language is only an approximation, the point is to provide practical results for millions of people, and a few hundred words goes a long way toward doing so. As data pours in, new words can be added to the vocabulary, and new multigesture phrases as well, and performance for the core set will improve.
Right now the company is seeking initial funding to get its prototype out and grow the team beyond the founding crew. Fomin said they have received some interest but want to make sure they connect with an investor who really understands the plan and vision.
When the engine itself has been built up to be more reliable by the addition of more data and the refining of the machine learning models, the team will look into further development and integration of the app with other products and services. For now the product is more of a proof of concept, but what a proof it is — with a bit more work SLAIT will have leapfrogged the industry and provided something that deaf and hearing people both have been wanting for decades.
The two founders of Crusoe Energy think they may have a solution to two of the largest problems facing the planet today — the increasing energy footprint of the tech industry and the greenhouse gas emissions associated with the natural gas industry.
Crusoe, which uses excess natural gas from energy operations to power data centers and cryptocurrency mining operations, has just raised $128 million in new financing from some of the top names in the venture capital industry to build out its operations — and the timing couldn’t be better.
Methane emissions are emerging as a new area of focus for researchers and policymakers focused on reducing greenhouse gas emissions and keeping global warming within the 1.5 degree targets set under the Paris Agreement. And those emissions are just what Crusoe Energy is capturing to power its data centers and bitcoin mining operations.
The reason why addressing methane emissions is so critical in the short term is because these greenhouse gases trap more heat than their carbon dioxide counterparts and also dissipate more quickly. So dramatic reductions in methane emissions can do more in the short term to alleviate the global warming pressures that human industry is putting on the environment.
And the biggest source of methane emissions is the oil and gas industry. In the U.S. alone roughly 1.4 billion cubic feet of natural gas is flared daily, said Chase Lochmiller, a co-founder of Crusoe Energy. About two thirds of that is flared in Texas with another 500 million cubic feet flared in North Dakota, where Crusoe has focused its operations to date.
For Lochmiller, a former quant trader at some of the top American financial services institutions, and Cully Cavmess, a third generation oil and gas scion, the ability to capture natural gas and harness it for computing operations is a natural combination of the two men’s interests in financial engineering and environmental preservation.
NEW TOWN, ND – AUGUST 13: View of three oil wells and flaring of natural gas on The Fort Berthold Indian Reservation near New Town, ND on August 13, 2014. About 100 million dollars worth of natural gas burns off per month because a pipeline system isn’t in place yet to capture and safely transport it . The Three Affiliated Tribes on Fort Berthold represent Mandan, Hidatsa and Arikara Nations. It’s also at the epicenter of the fracking and oil boom that has brought oil royalties to a large number of native americans living there. (Photo by Linda Davidson / The Washington Post via Getty Images)
The two Denver natives met in prep-school and remained friends. When Lochmiller left for MIT and Cavness headed off to Middlebury they didn’t know that they’d eventually be launching a business together. But through Lochmiller’s exposure to large scale computing and the financial services industry, and Cavness assumption of the family business they came to the conclusion that there had to be a better way to address the massive waste associated with natural gas.
Conversation around Crusoe Energy began in 2018 when Lochmiller and Cavness went climbing in the Rockies to talk about Lochmiller’s trip to Mt. Everest.
When the two men started building their business, the initial focus was on finding an environmentally friendly way to deal with the energy footprint of bitcoin mining operations. It was this pitch that brought the company to the attention of investors at Polychain, the investment firm started by Olaf Carlson-Wee (and Lochmiller’s former employer), and investors like Bain Capital Ventures and new investor Valor Equity Partners.
(This was also the pitch that Lochmiller made to me to cover the company’s seed round. At the time I was skeptical of the company’s premise and was worried that the business would just be another way to prolong the use of hydrocarbons while propping up a cryptocurrency that had limited actual utility beyond a speculative hedge against governmental collapse. I was wrong on at least one of those assessments.)
“Regarding questions about sustainability, Crusoe has a clear standard of only pursuing projects that are net reducers of emissions. Generally the wells that Crusoe works with are already flaring and would continue to do so in the absence of Crusoe’s solution. The company has turned down numerous projects where they would be a buyer of low cost gas from a traditional pipeline because they explicitly do not want to be net adders of demand and emissions,” wrote a spokesman for Valor Equity in an email. “In addition, mining is increasingly moving to renewables and Crusoe’s approach to stranded energy can enable better economics for stranded or marginalized renewables, ultimately bringing more renewables into the mix. Mining can provide an interruptible base load demand that can be cut back when grid demand increases, so overall the effect to incentivize the addition of more renewable energy sources to the grid.”
Other investors have since piled on including: Lowercarbon Capital, DRW Ventures, Founders Fund, Coinbase Ventures, KCK Group, Upper90, Winklevoss Capital, Zigg Capital and Tesla co-founder JB Straubel.
The company now operate 40 modular data centers powered by otherwise wasted and flared natural gas throughout North Dakota, Montana, Wyoming and Colorado. Next year that number should expand to 100 units as Crusoe enters new markets such as Texas and New Mexico. Since launching in 2018, Crusoe has emerged as a scalable solution to reduce flaring through energy intensive computing such as bitcoin mining, graphical rendering, artificial intelligence model training and even protein folding simulations for COVID-19 therapeutic research.
Crusoe boasts 99.9% combustion efficiency for its methane, and is also bringing additional benefits in the form of new networking buildout at its data center and mining sites. Eventually, this networking capacity could lead to increased connectivity for rural communities surrounding the Crusoe sites.
Currently, 80% of the company’s operations are being used for bitcoin mining, but there’s increasing demand for use in data center operations and some universities, including Lochmiller’s alma mater of MIT are looking at the company’s offerings for their own computing needs.
“That’s very much in an incubated phase right now,” said Lochmiller. “A private alpha where we have a few test customers… we’ll make that available for public use later this year.”
Crusoe Energy Systems should have the lowest data center operating costs in the world, according to Lochmiller and while the company will spend money to support the infrastructure buildout necessary to get the data to customers, those costs are negligible when compared to energy consumption, Lochmiller said.
The same holds true for bitcoin mining, where the company can offer an alternative to coal powered mining operations in China and the construction of new renewable capacity that wouldn’t be used to service the grid. As cryptocurrencies look for a way to blunt criticism about the energy usage involved in their creation and distribution, Crusoe becomes an elegant solution.
Institutional and regulatory tailwinds are also propelling the company forward. Recently New Mexico passed new laws limiting flaring and venting to no more than 2 percent of an operator’s production by April of next year and North Dakota is pushing for incentives to support on-site flare capture systems while Wyoming signed a law creating incentives for flare gas reduction applied to bitcoin mining. The world’s largest financial services firms are also taking a stand against flare gas with BlackRock calling for an end to routine flaring by 2025.
“Where we view our power consumption, we draw a very clear line in our project evaluation stage where we’re reducing emissions for an oil and gas projects,” Lochmiller said.
Faculty, a VC-backed artificial intelligence startup, has won a tender to work with the NHS to make better predictions about its future requirements for patients, based on data drawn from how it handled the COVID-19 pandemic.
In December 2019, Faculty raised a $10.5M Series A funding round from UK-based VCs Local Globe, GMG Ventures, and, Jaan Tallinn, one of Skype’s founding engineers, giving it a valuation of around $100 million.
Faculty will work with NHS England and NHS Improvement to build upon the Early Warning System (EWS) it developed for the service, during the pandemic. Based on Bayesian hierarchical modeling, Faculty says the EWS uses aggregate data (for example, COVID-19 positive case numbers, 111 calls, and mobility data) to warn hospitals about potential spikes in cases so they can divert staff, beds, and equipment needed. This learning will now be applied across the whole of the service, for issues other than the pure pandemic response, such as improving service delivery and patient care and predicting A&E demand and winter pressures.
Faculty also worked with NHSX as a partner for the NHS AI Lab, which developed the National COVID-19 Chest Imaging Database (NCCID).
Faculty has also reportedly worked with the UK Home Office to apply AI to its database of terrorists, as well as the BBC and easyJet.
I asked Richard Sargeant, COO of Faculty, if he thought Faculty was the ‘Palantir for the UK’ (Palantir has also worked with the NHS during the pandemic: “We are, I believe, a really effective and scalable AI company, not just for the UK but we’re working in the US and in Europe, Asia. I think we will continue to scale. We’re growing, and we’re going to grow because I believe that AI can make things better for the citizens, for customers. Palantir doesn’t really do AI, they do data engineering in a big way. And we’ve seen them be effective in the NHS. I think Faculty kind of stands on its own.”
He said that Faculty has a different role to Palantir: “Palantir has helped with the data pipelines, and they’re using their software to pull a lot of data together, but really they’re not a machine learning organization, their specialism is in gathering data together. Data across the NHS is rather an archipelago. It’s in hundreds of different places, and being able to gather together makes it much easier to do machine learning, both centrally and at a local level. One of the things that sets the early warning system apart is not just the use of machine learning, but the use of explainability to give clinicians and managers, some understanding of why the models are forecasting the results that they are, which is relatively cutting edge stuff, and that’s the stuff that Faculty specializes in that Palantir doesn’t.”
I asked him why Faculty had attracted VC when, typically, VCs invest in startups that have scalable products: “It’s a good question and it’s something that we often get asked. I see Faculty as a little bit different from your classic software as a service business, and from a consultancy. AI isn’t a ‘once and done’ product, and neither is it something that people create from scratch every time. But there are core components of what we do, that we can use again and again, but also the models themselves are always bespoke… it’s a combination of the bespoke, and the common, or generic together, that makeup Faculty, and that’s a bit different.”
Faculty is not a stranger to controversy over its government contracts. Last year it was revealed that a a U.K. cabinet minister owned £90,000 of shares in Faculty, when it was awarded a £2.3 million contract from NHSX to help run the NHS COVID-19 Data Store.
Earlier this year we reported on how Snap had acquired Berlin-based Fit Analytics, an AI-based fitting technology startup, as part of a wider push into e-commerce services, specifically to gain technology that can help prospective online shoppers a better sense of how a particular item or size would fit them. A 10-Q filing from Snap today has now put a pricetag on that deal.
Snap paid a total of $124.4 million, covering technology, IP, customer relationships and payouts to the team. The filing also noted that Snap spent a total of $204.5 million on acquisitions in 2020, but did not break them out.
The news comes ahead of Snap — whose flagship app Snapchat now has 280 million daily active users — preparing for its Snap Partner Conference in May. Sources say the company plans to announce, among other news, deeper commerce features for Snapchat — specifically tools to make it easier for Snapchat users to interact with and buy items that appear in the app, either in ads or more organically in content shared by other users.
While the exact details of those commerce tools, and the timing of when they might come online, are not yet known, Snap has hardly kept its interest in commerce a secret.
Snap has been hiring for roles to support its commerce efforts. Currently it’s advertising for a variety of engineering, marketing and product roles in commerce, to, in the words of one of the listings, for a Product Manager, “develop and launch shopping experiences and services that make shopping fun for Snapchatters and drive results for brands.” The listings also include a role specifically to work on Snapchat-based e-commerce efforts for direct-to-consumer (D2C) businesses.
And it has been making other recent acquisitions in addition to Fit Analytics that also line up with that.
They have included Screenshop, an app that describes itself as “the first AI-back style lens,” which can identify shoppable items in photos and then build a custom catalog of similar products that you can buy (akin to “shop the look” features that you will have come across in fashion media). And it’s also acquired Ariel AI, which has built technology to quickly render people in 3D, technology that can be used in a diverse set of applications, from games to virtual try-ons of clothing, makeup or accessories.
Snap confirmed the Ariel acquisition to CNBC in January. And while Screenshop deal was first reported earlier this month by The Information, Snap has declined to comment on it, although we have found people who worked at the startup now working at Snap.
Both acquisitions closed in 2020, according to reports, meaning that they came out of that year’s $204.5 million acquisition run. (Snap also noted a smaller acquisition, for $7.6 million, in the most recent quarter, but it did not disclose any further details.)
Even before all this, Snap had been making smaller efforts and tests in commerce going back years, although none of them have tipped into mainstream efforts.
Among them, in 2018 it launched a Snap Store — but that so far has not progressed beyond selling merchandise based on Bitmoji characters. And work on a Gucci shoe campaign last year, where Snapchat users could try shoes on in AR and then buy them, was seen by some as its big step into commerce — “we’ve moved from pure entertainment and expanded the use-case. And so with brands, it’s a really exciting time, especially in fashion and beauty. The Snapchat camera is connecting brands to their audiences in new ways,” a Snapchat AR executive said at the time — but that also didn’t develop into much beyond a one-off effort.
But with the pandemic leading to a surge of shopping online, and technology continuing to improve, the iron may finally be hot here.
As we said around the Fit Analytics acquisition, the idea of diversifying Snapchat’s revenue streams by building in more commerce experiences makes a lot of sense.
It gives the company another revenue stream at a time when Apple is introducing changes that might well affect how advertising can run and be monetized in the future. (The company most recently posted average revenues per user of $2.74, a figure Wall Street will be hoping will grow, not shrink.) It also plays into the demographics that Snapchat targets, where younger consumers are using social media apps to discover, share and shop for goods.
And specifically in the case of fashion, building experiences to shop for items on Snapchat leans into the augmented reality, image-altering, hyper-visual technology that has become a well-known and much-used hallmark of Snapchat and its owner, self-titled “camera company” Snap.
A biotech company, that has spent 11 years researching supplements to increase human longevity, plans to launch its supplements later this year. Longevica says it has attracted a total of $13 million from investors including, Alexander Chikunov, a longevity investor, who is also president of the company.
Longevica says it created a biotechnology platform for longevity after researching the life-span of laboratory mice. It now aims to produce medicines, dietary supplements, and food products.
The longevity space is a growing sector for tech startups. Google backed the launch of Calico in the space. Late last year Humanity Inc. raised $2.5 million in a round led by Boston fund One Way Ventures for its longevity company that will leverage AI to maximize people’s healthspan.
Longevica’s CEO Aynar Abdrakhmanov, backing up his company’s aim to tap the desire for people to live longer, said: “According to the WHO, by 2050, 2 billion people will be 60+ years old. By 2026, the sales of services and products for this audience will be around $27 trillion… By comparison, it was only $17 trillion in 2019.”
According to CB Insights, life-extension startups raised a record total of $800 million in 2018 alone. And there are some high-profile investors in the space.
PayPal co-founder Peter Thiel invested in Unity Biotechnology, which is developing drugs to treat diseases that accompany aging, has also raised significant funding. And Ethereum founder Vitalik Buterin invested $2.4 million worth of Ether into the nonprofit SENS Research foundation, where famed longevity research Aubrey de Grey is chief science officer, to develop rejuvenation biotechnologies.
Longevica is basing its platform on the work of scientist Alexey Ryazanov, who holds 10 US patents in the space, and a long-time researcher into the regulation of protein biosynthesis cells.
Chikunov said: “I gathered scientists known in this field to discuss their approaches to the problem. Then Alexey Ryazanov proposed the innovative idea of large-scale screening of all known pharmacological substances on long-lived mice in order to find those that prolong life.”
Under the leadership of Ryazanov, Longevica says it used 20,000 long-lived female mice and 1,033 drugs representing compounds from 62 pharmacological classes, to find five substances that statistically significantly increased longevity by 16-22%: Inulin, Pentetic Acid, Clofibrate, Proscillaridin A, D-Valine.
From this work, they formed a view about the elimination of certain heavy metals from the body and improve the body’s ability to remove toxins.