Google has threatened to close its search engine in Australia — as it dials up its lobbying against draft legislation that is intended to force it to pay news publishers for reuse of their content.
Facebook would also be subject to the law. And has previously said it would ban news from being shared on its products owing if the law was brought in, as well as claiming it’s reduced its investment in the country as a result of the legislative threat.
“The principle of unrestricted linking between websites is fundamental to Search. Coupled with the unmanageable financial and operational risk if this version of the Code were to become law it would give us no real choice but to stop making Google Search available in Australia,” Google warned today.
Last August the tech giant took another pot-shop at the proposal, warning that the quality of its products in the country could suffer and might stop being free if the government proceeded with a push to make the tech giants share ad revenue with media businesses.
Since last summer Google appears to have changed lobbying tack — apparently giving up its attempt to derail the law entirely in favor of trying to reshape it to minimize the financial impact.
Its latest bit of lobbying is focused on trying to eject the most harmful elements (as it sees it) of the draft legislation — while also pushing its News Showcase program, which it hastily spun up last year, as an alternative model for payments to publishers that it would prefer becomes the vehicle for remittances under the Code.
The draft legislation for Australia’s digital news Code which is currently before the parliament includes a controversial requirement that tech giants, Google and Facebook, pay publishers for linking to their content — not merely for displaying snippets of text.
Yet Google has warned Australia that making it pay for “links and snippets” would break how the Internet works.
In a statement to the Senate Economics Committee today, its VP for Australia and New Zealand, Mel Silva, said: “This provision in the Code would set an untenable precedent for our business, and the digital economy. It’s not compatible with how search engines work, or how the internet works, and this is not just Google’s view — it has been cited in many of the submissions received by this Inquiry.
“The principle of unrestricted linking between websites is fundamental to Search. Coupled with the unmanageable financial and operational risk if this version of the Code were to become law it would give us no real choice but to stop making Google Search available in Australia.”
Google is certainly not alone in crying foul over a proposal to require payments for links.
Sir Tim Berners-Lee, inventor of the world wide web, has warned that the draft legislation “risks breaching a fundamental principle of the web by requiring payment for linking between certain content online”, among other alarmed submissions to the committee.
In written testimony he goes on:
“Before search engines were effective on the web, following links from one page to another was the only way of finding material. Search engines make that process far more effective, but they can only do so by using the link structure of the web as their principal input. So links are fundamental to the web.
“As I understand it, the proposed code seeks to require selected digital platforms to have to negotiate and possibly pay to make links to news content from a particular group of news providers.
“Requiring a charge for a link on the web blocks an important aspect of the value of web content. To my knowledge, there is no current example of legally requiring payments for links to other content. The ability to link freely — meaning without limitations regarding the content of the linked site and without monetary fees — is fundamental to how the web operates, how it has flourished till present, and how it will continue to grow in decades to come.”
However it’s notable that Berners-Lee’s submission does not mention snippets. Not once. It’s all about links.
Meanwhile Google has just reached an agreement with publishers in France — which they say covers payment for snippets of content.
In the EU, the tech giant is subject to an already reformed copyright directive that extended a neighbouring right for news content to cover reuse of snippets of text. Although the directive does not cover links or “very short extracts”.
In France, Google says it’s only paying for content “beyond links and very short extracts”. But it hasn’t said anything about snippets in that context.
French publishers argue the EU law clearly does cover the not-so-short text snippets that Google typically shows in its News aggregator — pointing out that the directive states the exception should not be interpreted in a way that impacts the effectiveness of neighboring rights. So Google looks like it would have a big French fight on its hands if it tried to deny payments for snippets.
But there’s still everything to play for in Australia. Hence, down under, Google is trying to conflate what are really two separate and distinct issues (payment for links vs payment for snippets) — in the hopes of reducing the financial impact vs what’s already baked into EU law. (Although it’s only been actively enforced in France so far, which is ahead of other EU countries in transposing the directive into national law).
In Australia, Google is also heavily pushing for the Code to “designate News Showcase” (aka the program it launched once the legal writing was on the wall about paying publishers) — lobbying for that to be the vehicle whereby it can reach “commercial agreements to pay Australian news publishers for value”.
Of course a commercial negotiation process is preferable (and familiar) to the tech giant vs being bound by the Code’s proposed “final offer arbitration model” — which Google attacks as having “biased criteria”, and claims subjects it to “unmanageable financial and operational risk”.
“If this is replaced with standard commercial arbitration based on comparable deals, this would incentivise good faith negotiations and ensure we’re held accountable by robust dispute resolution,” Silva also argues.
A third provision the tech giant is really keen gets removed from the current draft requires it to give publishers notification ahead of changes to its algorithms which could affect how their content is discovered.
“The algorithm notification provision could be adjusted to require only reasonable notice about significant actionable changes to Google’s algorithm, to make sure publishers are able to respond to changes that affect them,” it suggests on that.
It’s certainly interesting to consider how, over a few years, Google’s position has moved from ‘we’ll never pay for news’ — pre- any relevant legislation — to ‘please let us pay for licensing news through our proprietary licensing program’ once the EU had passed a directive now being very actively enforced in France (with the help of competition law) and also with Australia moving toward inking a similar law.
Turns out legislation can be a real tech giant mind-changer.
Of course the idea of making anyone pay to link to content online is obviously a terrible idea — and should be dropped.
But if that bit of the draft is a negotiating tactic by Australians lawmakers to get Google to accept that it will have to pay publishers something then it appears to be winning one.
And while Google’s threat to close down its search engine might sound ‘full on’, as Silva suggests, when you consider how many alternative search engines exist it’s hardly the threat it once was.
When the two year-old Indian company Jetsons Robotics began searching for a partner to help design charging stations for their autonomous rooftop solar installation cleaning robots, the Israeli company Powermat was an obvious choice.
While the company had made its name as the designer for wireless charging technologies for consumer electronics, over the past two years the company was shifting its focus to more industrial applications. So it made sense to work with the Indian company on new form factors and applications for its charging technologies.
Indeed, the consumer market that Powermat had hoped to capture had been, by that point, broadly commoditized, so the tech developer needed a new direction.
Cleaning rooftop solar installations can be a costly endeavor, running companies anywhere from $100,000 to $500,000 per year, according to Jetsons Robotics chief executive, Jatin Sharma. The use of robots to replace human labor can save money, but the autonomous solution that the company wanted to build necessitated some kind of wireless charging dock, he said.
Contact-based charging meant too many variables in the outdoor environment, but an inductive charger would be too costly. Until the company worked with Powermat on a solution, Sharma said.
Backed by 100x.vc, Sharma’s robots are already cleaning roughly 1.7 megawatts of solar installations on a daily basis.
For Powermat, the solar cleaning robots are a good test of the company’s new industrial focus, according to chief technology officer Itay Sherman.
“You can look at it like maturation of the market,” Sherman said. “Powermat had been a pioneer in driving wireless technology. This market is maturing and we are moving on to markets where the technology and innovation is important. We have decided to shift our efforts to these emerging markets. Robotics is one, medical devices, IOT, and the automotive market are others.”
Volta, the developer of a network of electric vehicle charging stations that monetize using advertising, has raised $125 million in new funding in a process managed by Goldman Sachs.
Volta builds and operates a network of electric vehicle charging stations that are sited in parking lots around grocery stores, pharmacy chains, banks and hospitals.
The company has placed its charging stations, with their 55-inch digital displays in locations at 200 cities across 23 states, according to a statement.
The charge is free for vehicle owners and is supported by the retailers and consumer goods companies that want to reach the EV audience.
With the new financing, Volta has now raised over $200 million in funding and intends to use its cash to begin expanding internationally.
Companies who have placed Volta’s chargers on their sites include Albertsons Companies, Giant Food, Regency Centers, Wegmans and TopGolf. Brands advertising on the company’s screens include GM, Hulu, Nestlé, Polestar, Porsche and Unilever.
“Since our initial investment in Volta in 2018, excitement and interest in electrification — and specifically solving for public charging solutions — has continued to gain momentum,” said John Tough, Managing Partner at Energize Ventures, a major and existing investor in this round. “Our conviction in this team has similarly grown, and we believe Volta is poised to lead this market as the most capital-efficient and highly utilized EV charging network in the country.”
Stacklet, a startup that is commercializing the Cloud Custodian open-source cloud governance project, today announced that it has raised an $18 million Series A funding round. The round was led by Addition, with participation from Foundation Capital and new individual investor Liam Randall, who is joining the company as VP of business development. Addition and Foundation Capital also invested in Stacklet’s seed round, which the company announced last August. This new round brings the company’s total funding to $22 million.
Stacklet helps enterprises manage their data governance stance across different clouds, accounts, policies and regions, with a focus on security, cost optimization and regulatory compliance. The service offers its users a set of pre-defined policy packs that encode best practices for access to cloud resources, though users can obviously also specify their own rules. In addition, Stacklet offers a number of analytics functions around policy health and resource auditing, as well as a real-time inventory and change management logs for a company’s cloud assets.
The company was co-founded by Travis Stanfield (CEO) and Kapil Thangavelu (CTO). Both bring a lot of industry expertise to the table. Stanfield spent time as an engineer at Microsoft and leading DealerTrack Technologies, while Thangavelu worked at Canonical and most recently in Amazon’s AWSOpen team. Thangavelu is also one of the co-creators of the Cloud Custodian project, which was first incubated at Capital One, where the two co-founders met during their time there, and is now a sandbox project under the Cloud Native Computing Foundation’s umbrella.
“When I joined Capital One, they had made the executive decision to go all-in on cloud and close their data centers,” Thangavelu told me. “I got to join on the ground floor of that movement and Custodian was born as a side project, looking at some of the governance and security needs that large regulated enterprises have as they move into the cloud.”
As companies have sped up their move to the cloud during the pandemic, the need for products like Stacklets has also increased. The company isn’t naming most of its customers, but one of them is FICO, among a number of other larger enterprises. Stacklet isn’t purely focused on the enterprise, though. “Once the cloud infrastructure becomes — for a particular organization — large enough that it’s not knowable in a single person’s head, we can deliver value for you at that time and certainly, whether it’s through the open source or through Stacklet, we will have a story there.” The Cloud Custodian open-source project is already seeing serious use among large enterprises, though, and Stacklet obviously benefits from that as well.
“In just 8 months, Travis and Kapil have gone from an idea to a functioning team with 15 employees, signed early Fortune 2000 design partners and are well on their way to building the Stacklet commercial platform,” Foundation Capital’s Sid Trivedi said. “They’ve done all this while sheltered in place at home during a once-in-a-lifetime global pandemic. This is the type of velocity that investors look for from an early-stage company.”
Looking ahead, the team plans to use the new funding to continue to developed the product, which should be generally available later this year, expand both its engineering and its go-to-market teams and continue to grow the open-source community around Cloud Custodian.
Archer, a company that’s looking to develop an airline of electric vertical take-off and landing (eVTOL) aircraft for sue in urban transport, will work with automaker Fiat Chrysler Automobiles (FCA) in a new partnership to benefit from the latter’s expertise in engineering, design, supply chain and materials science. Archer aims to start production of its eVTOLs at scale beginning in 2023, with an initial unveiling to occur early this year.
The new team-up will see FCA provide input that contributes to the design of Archer’s eVTOL cockpit, as well, another area where the automaker has ample expertise, since it has designed spaces for drivers for many decades in its automotive business. Archer’s aircraft will be powered by an electric motor, and will be able to fly for up to 60 miles at top speeds of 150 mph. The Archer eVTOL is designed to be quiet and efficient, with efforts from the FCA collaboration going towards lowering the cost of its manufacturing to make high-volume manufacturing achievable and sustainable.
Ultimately, Archer is looking to FCA to help it realize efficiencies in its process that can make bringing its eVTOL to market a sound business that can also be accessed affordably by end users. Palo Alto-based Archer is looking to ultimately scale production to the point where it can produce “thousands” of its eVTOL aircraft per year, for use in future air taxi services serving cities globally.
Based in Palo Alto and led by co-founders Brett Adcock and Adam Goldstein, and including industry executives like Chief Engineer Goeff Bower, who previously served int hat role at Airbus’ Vahana eVTOL initiative, Archer launched out of stealth earlier this year with backing from Marc Lore, current President and CEO of Walmart’s ecommerce business (he was co-founder and CEO of Jet when it was acquired by the retailer).
Launched in South Korea five years ago, content discovery platform Dable now serves a total of six markets in Asia. Now it plans to speed up the pace of its expansion, with six new markets in the region planned for this year, before entering European countries and the United States. Dable announced today that it has raised a $12 million Series C at a valuation of $90 million, led by South Korean venture capital firm SV Investment. Other participants included KB Investment and K2 Investment, as well as returning investor Kakao Ventures, a subsidiary of Kakao Corporation, one of South Korea’s largest internet firms.
Dable (the name is a combination of “data” and “able”) currently serves more than 2,500 media outlets in South Korea, Japan, Taiwan, Indonesia, Vietnam and Malaysia. It has subsidiaries in Taiwan, which accounts for 70% of its overseas sales, and Indonesia.
The Series C brings Dable’s total funding so far to $20.5 million. So far, the company has taken a gradual approach to international expansion, co-founder and chief executive officer Chaehyun Lee told TechCrunch, first entering one or two markets and then waiting for business there to stabilize. In 2021, however, it plans to use its Series C to speed up the pace of its expansion, launching in Hong Kong, Singapore, Thailand, mainland China, Australia and Turkey before entering markets in Europe and the United States, too.
The company’s goal is to become the “most utilized personalized recommendation platform in at last 30 countries by 2024.” Lee said it also has plans to transform into a media tech company by launching a content management system (CMS) next year.
Dable currently claims an average annual sales growth rate since founding of more than 50% and says it reached $27.5 million in sales in 2020, up from 63% the previous year. Each month, it has a total of 540 million unique users and recommends five billion pieces of content, resulting in more than 100 million clicks. Dable also says its average annual sales growth rate since founding is more than 50%, and in that 2020, it reached $27.5 million in sales, up 63% from the previous year.
Before launching Dable, Lee and three other members of its founding team worked at RecoPick, a recommendation engine developer operated by SK Telecom subsidiary SK Planet. For media outlets, Dable offers two big data and machine learning-based products: Dable News to make personalized recommendations of content, including articles, to visitors, and Dable Native Ad, which draws on ad networks including Google, MSN and Kakao.
A third product, called karamel.ai, is an ad targeting solution for e-commerce platforms that also makes personalized product recommendations.
Dable’s main rivals include Taboola and Outbrain, both of which are headquartered in New York (and recently called off a merger), but also do business in Asian markets, and Tokyo-based Popin, which also serves clients in Japan and Taiwan.
Lee said Dable proves the competitiveness of its products by running A/B tests to compare the performance of competitors against Dable’s recommendations and see which one results in the most clickthroughs. It also does A/B testing to compare the performance of articles picked by editors against ones that were recommended by Dable’s algorithms.
Dable also provides algorithms that allow clients more flexibility in what kind of personalized content they display, which is a selling point as media companies try to recover from the massive drop in ad spending precipitated by COVID-19 pandemic. For example, Dable’s Related Articles algorithm is based on content that visitors have already viewed, while its Perused Article algorithm gauges how interested visitors are in certain articles based on metrics like how much time they spent reading them. It also has another algorithm that displays the most viewed articles based on gender and age groups.
Epic today announced the acquisition of Rad Game Tools, maker of game development tools for many years. They’ve stayed largely behind the scenes, but many gamers will recognize the colorful Bink Video logo, which has appeared in the openings of many a title over the years.
“Our work with Epic goes back decades, and joining forces is a natural next step given our alignment on products, mission, and culture,” said Rad Game Tools founder and CEO Jeff Roberts said in the announcement. And it has seemingly only intensified recently.
Close integration with engines and platforms makes for good standards, and good standards get embraced by developers. That’s why Epic has been cozying up to Sony as well as snapping up components to fit into its Unreal engine, positioning it as an all-encompassing development platform for next-generation games.
Rad (styled RAD) has been in games for a long time, as its decidedly old-school website attests. Bink is a video codec for games that focuses on high compression and speedy rendering, both important in the gaming world. Oodle, Telemetry, Granny 3D, and Miles Sound System are all development tools beyond what the lay person would understand, but no doubt have many fans.
Epic may be known now as the creator of money printing machine Fortnite, but the company has been around for decades and probably knows the Rad team well. That may help explain the friendly terms under which the acquisition will take place.
“RAD will continue supporting their game industry, film, and television partners, with their sales and business development team maintaining and selling licenses for their products to companies across industries – including those that do not utilize Unreal Engine,” Epic said in its announcement.
So while Bink and the rest will continue to be available for anyone to use outside Epic’s domain, they will almost certainly be better integrated with the Unreal ecosystem. As game development cost and complexity rises, means of simplification are often taken advantage of. Epic is working hard to make Unreal not just the most graphically powerful engine for development, but also the most unified.
A request for comment and further details on the deal sent to Rad Game Tools was intercepted by Epic and declined.
The end of the year is looming and with it one of your most important tasks as a manager. Summarizing the performance of 10, 20 or 50 developers over the past 12 months, offering personalized advice and having the facts to back it up — is no small task.
We believe that the only unbiased, accurate and insightful way to understand how your developers are working, progressing and — last but definitely not least — how they’re feeling, is with data. Data can provide more objective insights into employee activity than could ever be gathered by a human.
It’s still very hard for many managers to fully understand that all employees work at different paces and levels.
Consider this: Over two-thirds of employees say they would put more effort into their work if they felt more appreciated, and 90% want a manager who’s fair to all employees.
Let’s be honest. It’s hard to judge all of your employees fairly if you’re (1) unable to work physically side-by-side with them, meaning you’ll inevitably have more contact with the some over others (e.g., those you’re more friendly with); and (2) you’re relying on manual trackers to keep on top of everyone’s work, which can get lost and take a lot of effort to process and analyze; (3) you expect engineers to self-report their progress, which is far from objective.
It’s also unlikely, especially with the quieter ones, that on top of all that you’ll have identified areas for them to expand their talents by upskilling or reskilling. But it’s that kind of personal attention that will make employees feel appreciated and able to progress professionally with you. Absent that, they’re likely to take the next best job opportunity that shows up.
So here’s a run down of why you need data to set up a fair annual review process; if not this year, then you can kick-start it for 2021.
The best way to track your developers’ progress automatically is by using Git Analytics tools, which track the performance of individuals by aggregating historical Git data and then feeding that information back to managers in minute detail.
This data will clearly show you if one of your engineers is over capacity or underworked and the types of projects they excel in. If you’re assessing an engineering manager and the team members they’re responsible for have been taking longer to push their code to the shared repository, causing a backlog of tasks, it may mean that they’re not delegating tasks properly. An appropriate goal here would be to track and divide their team’s responsibilities more efficiently, which can be tracked using the same metrics, or cross-training members of other teams to assist with their tasks.
Another example is that of an engineer who is dipping their toe into multiple projects. Indicators of where they’ve performed best include churn (we’ll get to that later), coworkers repeatedly asking that same employee to assist them in new tasks and of course positive feedback for senior staff, which can easily be integrated into Git analytics tools. These are clear signs that next year, your engineer could be maximizing their talents in these alternative areas, and you could diversify their tasks accordingly.
Once you know what targets to set, you can use analytics tools to create automatic targets for each engineer. That means that after you’ve set it up, it will be updated regularly on the engineer’s progress using indicators directly from the code repository. It won’t need time-consuming input from either you or your employee, allowing you both to focus on more important tasks. As a manager you’ll receive full reports once the deadline of the task is reached and get notified whenever metrics start dropping or the goal has been met.
This is important — you’ll be able to keep on top of those goals yourself, without having to delegate that responsibility or depend on self-reporting by the engineer. It will keep employee monitoring honest and transparent.
The easiest way for managers to “conclude” how an engineer has performed is by looking at superficial output: the number of completed pull requests submitted per week, the number of commits per day, etc. Especially for nontechnical managers, this is a grave but common error. When something is done, it doesn’t mean it’s been done well or that it is even productive or usable.
Instead, look at these data points to determine the actual quality of your engineer’s work:
From a young age, Will Bruey, the co-founder and chief executive of Varda Space Industries, was fascinated with space and running his own business.
So when the former SpaceX engineer was tapped by Delian Asparouhov and Trae Stephens of Founders Fund to work on Varda he didn’t think twice.
Bruey spent six years at SpaceX. First working on the Falcon and Dragon video systems and then the bulk of the systems actuators and controllers used in the avionics for the crewed Dragon capsule (which recently docked at the International Space Station). `
According to Asparouhov, that background, and the time that Bruey spent running his own angel syndicate and working at Bank of America getting a grounding in finance and startups, made him an ideal candidate to run the next startup to be spun out of Founders Fund .
Like other Founders Fund companies, Palantir and Anduril, Varda takes its name from the novels of J.R.R. Tolkien. Named for the Elf queen who created constellations, the company has set itself no less lofty a task than bringing manufacturing to space.
While companies like Space Tango and Made In Space already are attempting to make a viable business out of space manufacturing, they focus on small scale pilots and experimental projects. Varda separates itself by its loftier ambition — to manufacture commercially viable products at scale in space.
To be economically viable, these products have to be very very high value, and according to the IEEE there are already some goods that fit the bill. Things like carbon nanotubes and fiber optic cables, organs, and novel materials are all potential targets for a space manufacturing company, because they can conceivably justify the high cost of material transportation.
Image Credit: Getty Images/AbelCreativeStudio
“Manufacturing is the next step for commercialization in space,” said Bruey. “The primary driver that makes us economical is success in the launch business.”
With now-established companies like SpaceX, Rocket Lab and Blue Origin, and upstarts like Relativity Space, Spinlaunch, and the newly launched Aevum Space all driving down the cost of launching objects into space, the next wave of commercialization is coming.
Varda’s backers, led by Founders Fund and Lux Capital, with additional participation from Fifty Years, Also Capital, Raymond Tonsing, Justin Mateen, and Naval Ravikant are all placing a bet that the biggest returns could be in manufacturing. As a result of their investments, Founders Fund partner Trae Stephens and Lux Capital co-founder Josh Wolfe are both taking seats on the company’s board.
“The first things we will manufacture are things with high dollar per-unit-mass value,” said Bruey. “As we establish our manufacturing platform that will ramp into the longer term vision of offloading manufacturing for all space operations.”
There are two categories of space manufacturing in the industry to come, according to Bruey and Asparouhov and those are additive manufacturing for making products to be used in space, and manufacturing in space for terrestrial applications. It’s the second of these that Varda focuses on. “Nothing we will be doing will be 3D printing,” said Asparouhov. “We will be focused on making things in space that we can bring back to earth.
The company may not be working on 3D printing, but its manufacturing facilities won’t look like anything on Earth. Initially, they’ll be unmanned, according to a blog post published by Fifty Years. Then they’ll manufacture things in space that benefit from low gravity. Finally, the company intends to build the first inrastructure that can harvest source materials for new products in-space via asteroid mining.
“Varda can make manufacturing sustainable by eliminating the need to destructively extract earth’s resources, help cure chronic diseases, deepen our understanding of biology, help connect more people to the Internet, and usher in higher-throughput and lower energy methods of computation,” Fifty Years co-founder Seth Bannon wrote in a direct message. “Bringing human industry into the stars — this is entrepreneurship at its boldest! Varda is the sort of big swing ambition venture capital was invented for.”
Richard Socher, former chief scientist at Salesforce, who helped build the Einstein artificial intelligence platform, is taking on a new challenge — and it’s a doozy. Socher wants to fix consumer search and today he announced you.com, a new search engine to take on the mighty Google.
“We are building you.com. You can already go to it today. And it’s a trusted search engine. We want to work on having more click trust and less clickbait on the internet,” he said. He added that in addition to trust, he wants it to be built on kindness and facts, three worthy but difficult goals to achieve.
He said that there were several major issues that led him and his co-founders to build a new search tool. For starters, he says that there is too much information and nobody can possibly process it all. What’s more, as you find this information, it’s impossible to know what you can trust as accurate, and he believes that issue is having a major impact on society at large. Finally, as we navigate the internet in 2020, the privacy question looms large as is how you balance the convenience-privacy trade-off.
He believes his background in AI can help in a consumer-focused search tool. For starters the search engine, while general in nature, will concentrate on complex consumer purchases where you have to open several tabs to compare information.
“The biggest impact thing we can do in our lives right now is to build a trusted search engine with AI and natural language processing superpowers to help everyone with the various complex decisions of their lives, starting with complex product purchases, but also being general from the get go as well,” he said.
While Socher was light on details, preferring to wait until GA in a couple of months to share some more, he said he wants to differentiate from Google by not relying on advertising and what you know about the user. He said he learned from working with Marc Benioff at Salesforce that you can make money and still build trust with the people buying your product.
He certainly recognizes that it’s tough to take on an entrenched incumbent, but he and his team believe that by building something they believe is fundamentally different, they can undermine the incumbent with a classic “Innovator’s Dilemma” kind of play where they’re doing something that is hard for Google to reproduce without undermining their primary revenue model.
He also sees Google running into antitrust issues moving forward and that could help create an opening for a startup like this. “I think, a lot of stuff that Google [has been doing], I think with the looming antitrust will be somewhat harder for them to get away with on a continued basis,” he said.
He acknowledges that trust and accuracy elements could get tricky as social networks have found out. Socher hinted at some social sharing elements they plan to build into the search tool including allowing you to have your own custom you.com URL with your name to facilitate that sharing.
Socher said he has funding and a team together working actively on the product, but wouldn’t share how much or how many employees at this point. He did say that Benioff and venture capitalist Jim Breyer are primary backers and he would have more information to share in the coming months.
For now, if you’re interested, you can go to the website and sign up for early access.
It’s GitHub Universe week and unsurprisingly, the ubiquitous code management service is announcing a slew of updates. Companies can now become GitHub Sponsors and invest in open-source projects by paying developers directly, there is automatic merging of pull requests (if that’s your thing), discussions for all public repositories and the beta of dependency reviews. GitHub is also making some updates to its continuous delivery features.
That’s all good and well, but let’s face it: you came here to see GitHub’s new dark mode.
Here it is:
“Dark mode may offer respite from the visual overstimulation of a bright screen or simply give you a more consistent development experience across your text editor, IDE, and terminal. Whether you like your screen bright or if you want to feel like Mr. Robot in dark mode, it’s your choice in how you experience GitHub. Enable dark mode from your settings or set it to track your system preferences,” the company says. That sums it up pretty well.
Dozens of medical imaging devices built by General Electric are secured with hardcoded default passwords that can’t be easily changed, but could be exploited to access sensitive patient scans, according to new findings by security firm CyberMDX.
The researchers said that an attacker would only need to be on the same network to exploit a vulnerable device, such as by tricking an employee into opening an email with malware. From there, the attacker could use those unchanged hardcoded passwords to obtain whatever patient data was left on the device or disrupt the device from operating properly.
CyberMDX said X-ray machines, CT and MRI scanners, and ultrasound and mammography devices are among the affected devices.
GE uses hardcoded passwords to remotely maintain the devices. But Elad Luz, head of research at CyberMDX, said some customers were not aware that their devices had vulnerable devices. Luz described the passwords as “hardcoded,” because although they can be changed, customers have to rely on a GE engineer to change the passwords on-site.
The vulnerability has also prompted an alert by Homeland Security’s cybersecurity advisory unit, CISA. Customers of affected devices should contact GE to change the passwords.
Hannah Huntly, a spokesperson for GE Healthcare, said in a statement: “We are not aware of any incident where this potential vulnerability has been exploited in a clinical situation. We have conducted a full risk assessment and concluded that there is no patient safety concern. Maintaining the safety, quality, and security of our devices is our highest priority.”
It’s the latest find by the New York-based healthcare cybersecurity startup. Last year the startup also reported vulnerabilities in other GE equipment, which the company later admitted could have led to patient injury after initially clearing the device for use.
CyberMDX, which works primarily to secure medical devices and improve hospital network security through its cyber intelligence platform while conducting security research on the side, raised $20 million earlier this year, just a month into the COVID-19 pandemic.
As TC readers know, the tricky trade-off of the modern web is privacy for convenience. Online tracking is how this ‘great intimacy robbery’ is pulled off. Mass surveillance of what Internet users are looking at underpins Google’s dominant search engine and Facebook’s social empire, to name two of the highest profile ad-funded business models.
TechCrunch’s own corporate overlord, Verizon, also gathers data from a variety of end points — mobile devices, media properties like this one — to power its own ad targeting business.
Countless others rely on obtaining user data to extract some perceived value. Few if any of these businesses are wholly transparent about how much and what sort of private intelligence they’re amassing — or, indeed, exactly what they’re doing with it. But what if the web didn’t have to be like that?
Berlin-based Xayn wants to change this dynamic — starting with personalized but privacy-safe web search on smartphones.
Today it’s launching a search engine app (on Android and iOS) that offers the convenience of personalized results but without the ‘usual’ shoulder surfing. This is possible because the app runs on-device AI models that learn locally. The promise is no data is ever uploaded (though trained AI models themselves can be).
The team behind the app, which is comprised of 30% PhDs, has been working on the core privacy vs convenience problem for some six years (though the company was only founded in 2017); initially as an academic research project — going on to offer an open source framework for masked federated learning, called XayNet. The Xayn app is based on that framework.
They’ve raised some €9.5 million in early stage funding to date — with investment coming from European VC firm Earlybird; Dominik Schiener (Iota co-founder); and the Swedish authentication and payment services company, Thales AB.
Now they’re moving to commercialize their XayNet technology by applying it within a user-facing search app — aiming for what CEO and co-founder, Dr Leif-Nissen Lundbæk bills as a “Zoom”-style business model, in reference to the ubiquitous videoconferencing tool which has both free and paid users.
This means Xayn’s search is not ad-supported. That’s right; you get zero ads in search results.
Instead, the idea is for the consumer app to act as a showcase for a b2b product powered by the same core AI tech. The pitch to business/public sector customers is speedier corporate/internal search without compromising commercial data privacy.
Lundbæk argues businesses are sorely in need of better search tools to (safely) apply to their own data, saying studies have shown that search in general costs around 18% of working time globally. He also cites a study by one city authority that found staff spent 37% of their time at work searching for documents or other digital content.
“It’s a business model that Google has tried but failed to succeed,” he argues, adding: “We are solving not only a problem that normal people have but also that companies have… For them privacy is not a nice to have; it needs to be there otherwise there is no chance of using anything.”
On the consumer side there will also be some premium add-ons headed for the app — so the plan is for it to be a freemium download.
One key thing to note is Xayn’s newly launched web search app gives users a say in whether the content they’re seeing is useful to them (or not).
It does this via a Tinder-style swipe right (or left) mechanic that lets users nudge its personalization algorithm in the right direction — starting with a home screen populated with news content (localized by country) but also extending to the search result pages.
The news-focused homescreen is another notable feature. And it sounds like different types of homescreen feeds may be on the premium cards in future.
Another key feature of the app is the ability to toggle personalized search results on or off entirely — just tap the brain icon at the top right to switch the AI off (or back on). Results without the AI running can’t be swiped, except for bookmarking/sharing.
Elsewhere, the app includes a history page which lists searches from the past seven days (by default). The other options offered are: Today, 30 days, or all history (and a bin button to purge searches).
There’s also a ‘Collections’ feature that lets you create and access folders for bookmarks.
As you scroll through search results you can add an item to a Collection by swiping right and selecting the bookmark icon — which then opens a prompt to choose which one to add it to.
The swipe-y interface feels familiar and intuitive, if slightly laggy to load content in the TestFlight beta version TechCrunch checked out ahead of launch.
Swiping left on a piece of content opens a bright pink color-block stamped with a warning ‘x’. Keep going and you’ll send the item vanishing into the ether, presumably seeing fewer like it in future.
Whereas a swipe right affirms a piece of content is useful. This means it stays in the feed, outlined in Xayn green. (Swiping right also reveals the bookmark option and a share button.)
While there are pro-privacy/non-tracking search engines on the market already — such as US-based DuckDuckGo or France’s Qwant — Xayn argues the user experience of such rivals tends to fall short of what you get with a tracking search engine like Google, i.e. in terms of the relevance of search results and thus time spent searching.
Simply put: You probably have to spend more time ‘DDGing’ or ‘Qwanting’ to get the specific answers you need vs Googling — hence the ‘convenience cost’ associated with safeguarding your privacy when web searching.
Xayn’s contention is there’s a third, smarter way of getting to keep your ‘virtual clothes’ on when searching online. This involves implementing AI models that learn on-device and can be combined in a privacy-safe way so that results can be personalized without putting people’s data at risk.
“Privacy is the very fundament… It means that quite like other privacy solutions we track nothing. Nothing is sent to our servers; we don’t store anything of course; we don’t track anything at all. And of course we make sure that any connection that is there is basically secured and doesn’t allow for any tracking at all,” says Lundbæk, explaining the team’s AI-fuelled, decentralized/edge-computing approach.
Xayn is drawing on a number of search index sources, including (but not solely) Microsoft’s Bing, per Lundbæk, who described this bit of what it’s doing as “relatively similar” to DuckDuckGo (which has its own web crawling bots).
The big difference is that it’s also applying its own reranking algorithms in order generate privacy-safe personalized search results (whereas DDG uses a contextual ads-based business model — looking at simple signals like location and keyword search to target ads without needing to profile users).
The downside to this sort of approach, according to Lundbæk, is users can get flooded with ads — as a consequence of the simpler targeting meaning the business serves more ads to try to increase chances of a click. And loads of ads in search results obviously doesn’t make for a great search experience.
“We get a lot of results on device level and we do some ad hoc indexing — so we build on the device level and on index — and with this ad hoc index we apply our search algorithms in order to filter them, and only present you what is more relevant and filter out everything else,” says Lundbæk, sketching how Xayn works. “Or basically downgrade it a bit… but we also try to keep it fresh and explore and also bump up things where they might not be super relevant for you but it gives you some guarantees that you won’t end up in some kind of bubble.”
Some of what Xayn’s doing is in the arena of federated learning (FL) — a technology Google has been dabbling in in recent years, including pushing a ‘privacy-safe’ proposal for replacing third party tracking cookies. But Xayn argues the tech giant’s interests, as a data business, simply aren’t aligned with cutting off its own access to the user data pipe (even if it were to switch to applying FL to search).
Whereas its interests — as a small, pro-privacy German startup — are markedly different. Ergo, the privacy-preserving technology it’s spent years building has a credible interest in safeguarding people’s data, is the claim.
“At Google there’s actually [fewer] people working on federate learning than in our team,” notes Lundbæk, adding: “We’ve been criticizing TFF [Google-designed TensorFlow Federated] at lot. It is federated learning but it’s not actually doing any encryption at all — and Google has a lot of backdoors in there.
“You have to understand what does Google actually want to do with that? Google wants to replace [tracking] cookies — but especially they want to replace this kind of bumpy thing of asking for user consent. But of course they still want your data. They don’t want to give you any more privacy here; they want to actually — at the end — get your data even easier. And with purely federated learning you actually don’t have a privacy solution.
“You have to do a lot in order to make it privacy preserving. And pure TFF is certainly not that privacy-preserving. So therefore they will use this kind of tech for all the things that are basically in the way of user experience — which is, for example, cookies but I would be extremely surprised if they used it for search directly. And even if they would do that there is a lot of backdoors in their system so it’s pretty easy to actually acquire the data using TFF. So I would say it’s just a nice workaround for them.”
“Data is basically the fundamental business model of Google,” he adds. “So I’m sure that whatever they do is of course a nice step in the right direction… but I think Google is playing a clever role here of kind of moving a bit but not too much.”
So how, then, does Xayn’s reranking algorithm work?
The app runs four AI models per device, combining encrypted AI models of respective devices asynchronously — with homomorphic encryption — into a collective model. A second step entails this collective model being fed back to individual devices to personalize served content, it says.
The four AI models running on the device are one for natural language processing; one for grouping interests; one for analyzing domain preferences; and one for computing context.
“The knowledge is kept but the data is basically always staying on your device level,” is how Lundbæk puts it.
“We can simply train a lot of different AI models on your phone and decide whether we, for example, combine some of this knowledge or whether it also stays on your device.”
“We have developed a quite complex solution of four different AI models that work in composition with each other,” he goes on, noting that they work to build up “centers of interest and centers of dislikes” per user — again, based on those swipes — which he says “have to be extremely efficient — they have to be moving, basically, also over time and with your interests”.
The more the user interacts with Xayn, the more precise its personalization engine gets as a result of on-device learning — plus the added layer of users being able to get actively involved by swiping to give like/dislike feedback.
The level of personalization is very individually focused — Lundbæk calls it “hyper personalization” — more so than a tracking search engine like Google, which he notes also compares cross-user patterns to determine which results to serve — something he says Xayn absolutely does not do.
“We have to focus entirely on one user so we have a ‘small data’ problem, rather than a big data problem,” says Lundbæk. “So we have to learn extremely fast — only from eight to 20 interactions we have to already understand a lot from you. And the crucial thing is of course if you do such a rapid learning then you have to take even more care about filter bubbles — or what is called filter bubbles. We have to prevent the engine going into some kind of biased direction.”
To avoid this echo chamber/filter bubble type effect, the Xayn team has designed the engine to function in two distinct phases which it switches between: Called ‘exploration’ and (more unfortunately) ‘exploitation’ (i.e. just in the sense that it already knows something about the user so can be pretty certain what it serves will be relevant).
“We have to keep fresh and we have to keep exploring things,” he notes — saying that’s why it developed one of the four AIs (a dynamic contextual multi-armed bandit reinforcement learning algorithm for computing context).
Aside from this app infrastructure being designed natively to protect user privacy, Xayn argues there are a bunch of other advantages — such as being able to derive potentially very clear interests signs from individuals; and avoiding the chilling effect that can result from tracking services creeping users out (to the point people they avoid making certain searches in order to prevent them from influencing future results).
“You as the user can decide whether you want the algorithm to learn — whether you want it to show more of this or less of this — by just simply swiping. So it’s extremely easy, so you can train your system very easily,” he argues.
There is potentially a slight downside to this approach, too, though — assuming the algorithm (when on) does some learning by default (i.e in the absence of any life/dislike signals from the user).
This is because it puts the burden on the user to interact (by swiping their feedback) in order to get the best search results out of Xayn. So that’s an active requirement on users, rather than the typical passive background data mining and profiling web users are used to from tech giants like Google (which is, however, horrible for their privacy).
It means there’s an ‘ongoing’ interaction cost to using the app — or at least getting the most relevant results out of it. You might not, for instance, be advised to let a bunch of organic results just scroll past if they’re really not useful but rather actively signal disinterest on each.
For the app to be the most useful it may ultimately pay to carefully weight each item and provide the AI with a utility verdict. (And in a competitive battle for online convenience every little bit of digital friction isn’t going to help.)
Asked about this specifically, Lundbæk told us: “Without swiping the AI only learns from very weak likes but not from dislikes. So the learning takes place (if you turn the AI on) but it’s very slight and does not have a big effect. These conditions are quite dynamic, so from the experience of liking something after having visited a website, patterns are learned. Also, only 1 of the 4 AI models (the domain learning one) learns from pure clicks; the others don’t.”
Xayn does seem alive to the risk of the swiping mechanic resulting in the app feeling arduous. Lundbæk says the team is looking to add “some kind of gamification aspect” in the future — to flip the mechanism from pure friction to “something fun to do”. Though it remains to be seen what they come up with on that front.
There is also inevitably a bit of lag involved in using Xayn vs Google — by merit of the former having to run on-device AI training (whereas Google merely hoovers your data into its cloud where it’s able to process it at super-speeds using dedicated compute hardware, including bespoke chipsets).
“We have been working for over a year on this and the core focus point was bringing it on the street, showing that it works — and of course it is slower than Google,” Lundbæk concedes.
“Google doesn’t need to do any of these [on-device] processes and Google has developed even its own hardware; they developed TPUs exactly for processing this kind of model,” he goes on. “If you compare this kind of hardware it’s pretty impressive that we were even able to bring [Xayn’s on-device AI processing] even on the phone. However of course it’s slower than Google.”
Lundbæk says the team is working on increasing the speed of Xayn. And anticipates further gains as it focuses more on that type of optimization — trailing a version that’s 40x faster than the current iteration.
“It won’t at the end be 40x faster because we will use this also to analyze even more content — to give you can even broader view — but it will be faster over time,” he adds.
On the accuracy of search results vs Google, he argues the latter’s ‘network effect’ competitive advantage — whereby its search reranking benefits from Google having more users — is not unassailable because of what edge AI can achieve working smartly atop ‘small data’.
Though, again, for now Google remains the search standard to beat.
“Right now we compare ourselves, mostly against Bing and DuckDuckGo and so on. Obviously there we get much better results [than compared to Google] but of course Google is the market leader and is using quite some heavy personalization,” he says, when we ask about benchmarking results vs other search engines.
“But the interesting thing is so far Google is not only using personalization but they also use kind of a network effect. PageRank is very much a network effect where the most users they have the better the results get, because they track how often people click on something and bump this also up.
“The interesting effect there is that right now, through AI technology — like for example what we use — the network effect becomes less and less important. So actually I would say that there isn’t really any network effect anymore if you really want to compete with pure AI technology. So therefore we can get almost as relevant results as Google right now and we surely can also, over time, get even better results or competing results. But we are different.”
In our (brief) tests of the beta app Xayn’s search results didn’t obviously disappoint for simple searches (and would presumably improve with use). Though, again, the slight load lag adds a modicum of friction which was instantly obvious compared to the usual search competition.
Not a deal breaker — just a reminder that performance expectations in search are no cake walk (even if you can promise a cookie-free experience).
“So far Google has so far had the advantage of a network effect — but this network effect gets less and less dominant and you see already more and more alternatives to Google popping up,” Lundbæk argues, suggesting privacy concerns are creating an opportunity for increased competition in the search space.
“It’s not anymore like Facebook or so where there’s one network where everyone has to be. And I think this is actually a nice situation because competition is always good for technical innovations and for also satisfying different customer needs.”
Of course the biggest challenge for any would-be competitor to Google search — which carves itself a marketshare in Europe in excess of 90% — is how to poach (some of) its users.
Lundbæk says the startup has no plans to splash millions on marketing at this point. Indeed, he says they want to grow usage sustainably, with the aim of evolving the product “step by step” with a “tight community” of early adopters — relying on cross-promotion from others in the pro-privacy tech space, as well as reaching out to relevant influencers.
He also reckons there’s enough mainstream media interest in the privacy topic to generate some uplift.
“I think we have such a relevant topic — especially now,” he says. “Because we want to show also not only for ourselves that you can do this for search but we think we show a real nice example that you can do this for any kind of case.
“You don’t always need the so-called ‘best’ big players from the US which are of course getting all of your data, building up profiles. And then you have these small, cute privacy-preserving solutions which don’t use any of this but then offer a bad user experience. So we want to show that this shouldn’t be the status quo anymore — and you should start to build alternatives that are really build on European values.”
And it’s certainly true EU lawmakers are big on tech sovereignty talk these days, even though European consumers mostly continue to embrace big (US) tech.
Perhaps more pertinently, regional data protection requirements are making it increasing challenging to rely on US-based services for processing data. Compliance with the GDPR data protection framework is another factor businesses need to consider. All of which is driving attention onto ‘privacy-preserving’ technologies.
Xayn’s team is hoping to be able spread its privacy-preserving gospel to general users by growing the b2b side of the business, according to Lundbæk — so it’s hoping some home use will follow once employees get used to convenient private search via their workplaces, in a small-scale reverse of the business consumerization trend that was powered by modern smartphones (and people bringing their own device to work).
“We these kind of strategies I think we can step by step build up in our communities and spread the word — so we think we don’t even need to really spend millions of euros in marketing campaigns to get more and more users,” he adds.
While Xayn’s initial go-to-market push has been focused on getting the mobile apps out, a desktop version is also planned for Q1 next year.
The challenge there is getting the app to work as a browser extension as the team obviously doesn’t want to build its own browser to house Xayn. tl;dr: Competing with Google search is mountain enough to climb, without trying to go after Chrome (and Firefox, and so on).
“We developed our entire AI in Rust which is a safe language. We are very much driven by security here and safety. The nice thing is it can work everywhere — from embedded systems towards mobile systems, and we can compile into web assembly so it runs also as a browser extension in any kind of browser,” he adds. “Except for Internet Explorer of course.”
Engineers at Cloudflare and Apple say they’ve developed a new internet protocol that will shore up one of the biggest holes in internet privacy that many don’t know even exists. Dubbed Oblivious DNS-over-HTTPS, or ODoH for short, the new protocol makes it far more difficult for internet providers to know which websites you visit.
But first, a little bit about how the internet works.
Every time you go to visit a website, your browser uses a DNS resolver to convert web addresses to machine-readable IP addresses to locate where a web page is located on the internet. But this process is not encrypted, meaning that every time you load a website the DNS query is sent in the clear. That means the DNS resolver — which might be your internet provider unless you’ve changed it — knows which websites you visit. That’s not great for your privacy, especially since your internet provider can also sell your browsing history to advertisers.
Recent developments like DNS-over-HTTPS (or DoH) have added encryption to DNS queries, making it harder for attackers to hijack DNS queries and point victims to malicious websites instead of the real website you wanted to visit. But that still doesn’t stop the DNS resolvers from seeing which website you’re trying to visit.
Enter ODoH, which decouples DNS queries from the internet user, preventing the DNS resolver from knowing which sites you visit.
Here’s how it works: ODoH wraps a layer of encryption around the DNS query and passes it through a proxy server, which acts as a go-between the internet user and the website they want to visit. Because the DNS query is encrypted, the proxy can’t see what’s inside, but acts as a shield to prevent the DNS resolver from seeing who sent the query to begin with.
“What ODoH is meant to do is separate the information about who is making the query and what the query is,” said Nick Sullivan, Cloudflare’s head of research.
In other words, ODoH ensures that only the proxy knows the identity of the internet user and that the DNS resolver only knows the website being requested. Sullivan said that page loading times on ODoH are “practically indistinguishable” from DoH and shouldn’t cause any significant changes to browsing speed.
A key component of ODoH working properly is ensuring that the proxy and the DNS resolver never “collude,” in that the two are never controlled by the same entity, otherwise the “separation of knowledge is broken,” Sullivan said. That means having to rely on companies offering to run proxies.
Sullivan said a few partner organizations are already running proxies, allowing for early adopters to begin using the technology through Cloudflare’s existing 220.127.116.11 DNS resolver. But most will have to wait until ODoH is baked into browsers and operating systems before it can be used. That could take months or years, depending on how long it takes for ODoH to be certified as a standard by the Internet Engineering Task Force.
Cybersecurity firm Dragos has raised $110 million in its Series C, almost triple the amount that it raised two years ago in its last round.
Dragos was founded in 2016 to detect and respond to threats facing industrial control systems (ICS), the devices critical to the continued operations of power plants, water and energy supplies, and other critical infrastructure. The company’s threat detection platform — its moneymaker — helps companies with industrial control systems defend against hackers trying to get into important operational systems. Its platform kicks out hackers that could shut down manufacturing lines or control energy supply systems, while its research arm keeps tabs on the hackers that can break into these highly complex and segmented industrial networks in the first place.
The startup’s latest round was led by National Grid Partners and Koch Disruptive Technologies, with both firms adding a member each to Dragos’ board. The round also saw participation from Saudi Aramco Energy Ventures and Hewlett Packard Enterprise, as well as return investors Allegis Cyber, Canaan Partners, DataTribe, Energy Impact Partners and Schweitzer Engineering Labs.
This latest round of funding will help the company with its go-to-market efforts, as well as growing its customer support team with 30 staff and building up its sales and marketing team. Lee said the company’s priority had been to work on its threat platform, and less selling it.
About one-third of the company’s employees work in software engineering to build its threat platform.
Dragos founder and chief executive Robert Lee said the pandemic, which forced vast swathes of the world to work remotely from home under lockdown restrictions, served as a wake-up call for companies with critical infrastructure.
“When you’re talking about critical infrastructure sites and people’s utilities, you need to put your best foot forward on the tech first,” he said.
Many companies were already trying to adapt with the digital age, but Lee said many companies realized they had underinvested in ICS security.
A team photo of Dragos employees. Image Credits: Dragos
Based just outside Washington D.C., Dragos now has over 220 employees and will be adding more, close to doubling its headcount since last year, and adding new offices in Melbourne, Dubai and in the United Kingdom.
Lee said the U.K.’s transition out of the European Union would all but ensure that the new U.K. office could not serve as an EU hub for the company, but that it was necessary to “to go where the problems are.”
Another one of those places is Saudi Arabia, one of the world’s largest oil and gas producers, where Dragos has an office and now draws an investment. Saudi oil and gas manufacturing plants have been the target of several cyberattacks, including the Trisis malware in 2017 that shut down one of the kingdom’s biggest petrochemical plants. But the country has faced extensive criticism for its human rights record by international rights groups. Lee said the company works to protect infrastructure that serves civilians and has actively rejected military contracts that would fall afoul of those values. “I don’t want to put asterisks on that mission,” he said.
Lee told TechCrunch that the company has grown at a rapid pace since it was founded four years ago.
“Our goal was never to get acquired,” he said. Echoing remarks he made last year, Lee said that the company’s plan was to continue growing and investing in the problems that Dragos sees — with an eventual goal to take the company public. “But we’re not rushed,” he said.
“The hallmark of Dragos being successful won’t be a successful IPO,” said Lee. “The hallmark will be having validated and built the market large enough that there can be other companies that come behind us serving the other more niche aspects of the ICS market and building out the community, and making sure our infrastructure is safer.”
When one of AWS’s east coast data centers went down at the end of last month, it had an impact on countless companies relying on its services including Roku, Adobe and Shipt. When the incident was resolved, the company had to analyze what happened. For most companies, that involves manually pulling together information from various internal tools, not a focused incident platform.
Jeli.io wants to change that by providing one central place for incident analysis, and today the company announced a $4 million seed round led by Boldstart Ventures with participation by Harrison Metal and Heavybit.
Jeli CEO and founder Nora Jones knows a thing or two about incident analysis. She helped build the chaos engineering tools at Netflix, and later headed chaos engineering at Slack. While chaos engineering helps simulate possible incidents by stress testing systems, incidents still happen, of course. She knew that there was a lot to learn from them, but there wasn’t a way to pull together all of the data around an incident automatically. She created Jeli to do that.
“While I was at Netflix pre pandemic, I discovered the secret that looking at incidents when they happen — like when Netflix goes down, when Slack goes down or when any other organization goes down — that’s actually a catalyst for understanding the delta between how you think your org works and how your org actually works,” Jones told me.
She began to see that there would be great value in trying to figure out the decision-making processes, the people and tools involved, and what companies could learn from how they reacted in these highly stressful situations, how they resolved them and what they could do to prevent similar outages from happening again in the future. With no products to help, Jones began building tooling herself at her previous jobs, but she believed that there needed to be a broader solution.
“We started Jeli and began building tooling to help engineers by [serving] the insights to help them know where to look after incidents,” she said. They do this by pulling together all of the data from emails, Slack channels, PagerDuty, Zoom recordings, logs and so forth that captured information about the incident, surfacing insights to help understand what happened without having to manually pull all of this information together.
The startup currently has 8 employees with plans to add people across the board in 2021. As she does this, she is cognizant of the importance of building a diverse workforce. “I am extremely committed to diversity and inclusion. It is something that’s been important and a requirement for me from day one. I’ve been in situations in organizations before where I was the only one represented, and I know how that feels. I want to make sure I’m including that from day one because ultimately it leads to a better product,” she said.
The product is currently in private beta, and the company is working with early customers to refine the platform. The plan is to continue to invite companies in the coming months, then open that up more widely some time next year.
Eliot Durbin, general partner at Boldstart Ventures says that he began talking to Jones a couple of years ago when she was at Netflix just to learn about this space, and when she was ready to start a company, his firm jumped at the chance to write an early check, even while the startup was pre-revenue.
“When we met Nora we realized that she’s on a lifelong mission to make things much more resilient […]. And we had the benefit of getting to know her for years before she started the company, so it was really a natural continuation to a conversation that we were already in,” Durbin explained.
Amid the pandemic, workplace cultures have been turned on their heads, meanwhile investment and growth haven’t slowed for many tech companies, requiring them to still onboard new engineering managers even while best practices for remote management are far from codified.
Because of remote work habit shifts, plenty of new tools have popped up to help engineers be more productive, or quickly help managers interface with direct-reports more often. Okay is taking a more observatory route, aiming to give managers dashboards that quantify the performance of their teams so that they can get a picture of where they have room to improve.
The startup, which launched out of Y Combinator earlier this year, tells TechCrunch they’ve raised $2.2 million in funding led by Sequoia and are launching the open beta of their service.
Co-founders Antoine Boulanger and Tomas Barreto met while working at Box — Boulanger as a senior director of engineering and Barreto as a VP of engineering. They told TechCrunch that in the process of building out a suite of in-house tools designed to help managers at Box understand their teams better, they realized the opportunity for a subscription toolset that could help managers across companies. For the most part, Boulanger says that today Okay is largely replacing tools built in-house as well.
Getting a picture of an engineering team’s productivity means plugging into these toolsets and gathering data into a digestible feed. Okay can be integrated with a number of toolsets, including software like GitHub, PagerDuty, CircleCI and Google Calendar.
“Part of the problem for managers is that there are so many tools, so how do you get signal from the noise?” Barreto tells TechCrunch.
A large part of Okay’s sell seems to be ensuring that managers can keep an active eye on the common pitfalls of rapid scaling and keep them in check so that can keep direct-reports satisfied. On the individual basis, managers can quickly see stats related to how much of an individual manager’s time is being spent in meetings compared to un-interrupted “maker time” where they actually have the ability to get work done.
People don’t like to be micro-managed and the idea that everything you do is feeding into a pie chart that judges whether you’re a good employee or not isn’t the most savory sell for engineers. Okay’s founders hope they can strike a balance and give managers data that they’re not tempted to over-rely on, instead defaulting to team-level insights when they can so that managers are dialed into general trends like how long projects are taking on average or how long it takes for pull requests to be reviewed.
Investors have been bankrolling remote work tools at a heightened pace for the last several months and things have been especially fortunate for young companies that were ahead of the trend. Barreto, for his part, has served as a scout at Sequoia since 2018 according to his LinkedIn.
The team says their product, as it stands today, is best fit for companies with 50-200 engineers that are high-growth and perhaps going through some of those growing pains. The company’s early customers include teams at Brex, Plaid and Split.
A mere two weeks remain until we kick off TC Sessions: Space (December 16 & 17), our first conference focused on the technology designed to push galactic boundaries and the people making it happen. Building successful space programs, whether private, public or hybrid combination, requires a well-trained workforce — today and for generations to come. That’s why we can’t wait for Building the Workforce of the Future, a breakout panel discussion featuring Steve Isakowitz.
Isakowitz is the president and CEO of The Aerospace Corporation, a national nonprofit corporation that operates a federally funded research and development center. It addresses complex problems across the space enterprise focused on agility, innovation and objective technical leadership.
In his 30+ year career, Isakowitz has held prominent roles across the government, private, space and technology sectors, including at NASA, U.S. Department of Energy and the White House Office of Management and Budget. Prior to joining Aerospace, he was president of Virgin Galactic, where his responsibilities included the development of privately funded launch systems, advanced technologies and other new space applications.
Building the Workforce of the Future focuses on what’s required to advance the United States’ leading role in space, namely developing a workforce that’s up to the challenge. Panelists also include Dava Newman, MIT’s Apollo Program Professor of Astronautics, and Yannis C. Yortsos, Dean, USC Viterbi School of Engineering and former Zohrab Kaprielian Chair in Engineering, University of Southern California.
The COVID-19 pandemic has created opportunities to imagine new models for how and where to train the next generation of scientists and engineers. This session will explore how universities and industry can work together to integrate professional experience into the curriculum and how universities and industry can work together to build robust talent pipelines that create digitally fluent, agile workers for the future.
The panelists will weigh in on strategies to build diverse workforces — with different perspectives and experiences that drive innovation — as well as new approaches that promote continuous learning for workers throughout their careers.
The space industry requires a deep bench and a long pipeline of engineers and scientists. Tune in to Building the Workforce of the Future for the latest thinking on this vital topic. It’s one session you don’t want to miss.
Late registration tickets are still available, as are discounts for groups, students, active military/government employees and for early-stage space startup founders who want to give their startup extra visibility.
Is your company interested in sponsoring TC Sessions: Space 2020? Click here to talk with us about available opportunities.
Microsoft announced a few updates to its Edge browser today that are all about shopping. In addition to expanding the price comparison feature the team announced last month, Edge can now also automatically find coupons for you. In addition, the company is launching a new shopping hub in its Bing search engine. The timing here is undoubtedly driven by the holiday shopping season — though this year, it feels like Black Friday-style deals already started weeks ago.
The potential usefulness of the price comparison tools is pretty obvious. I’ve found this always worked reasonably well in Edge Collections — though at times it could also be a frustrating experience because it just wouldn’t pull any data for items you saved from some sites. Now, with this price comparison running in the background all the time, you’ll see a new badge pop up in the URL bar that lets you open the price comparison. And when you already found the best price, it’ll tell you that right away, too.
At least in the Edge Canary, where this has been available for a little bit already, this was also hit and miss. It seems to work just fine when you shop on Amazon, for example, as long as there’s only one SKU of an item. If there are different colors, sizes or other options available, it doesn’t really seem to kick in, which is a bit frustrating.
The coupons feature, too, is a bit of a disappointment. It works more consistently and seems to pull data from most of the standard coupon sites (think RetailMeNot and Slickdeals), but all it does is show sitewide coupons. Since most coupons only apply to a limited set of items, clicking on the coupon badge quickly feels like a waste of time. To be fair, the team implemented a nifty feature where at checkout, Bing will try to apply all of the coupons it found. That could be a potential time and money-saver. Given the close cooperation with the Bing team in other areas, this feels like an area of improvement, though. I turned it off.
Microsoft is also using today’s announcement to launch a new URL shortener in Edge. “Now, when you paste a link that you copied from the address bar, it will automatically convert from a long, nonsensical URL address to a short hyperlink with the website title. If you prefer the full URL, you can convert to plain text using the context menu,” Microsoft explains. I guess that makes sense in some scenarios. Most of the time, though, I just want the link (and no third-party in-between), so I hope this can easily be turned off, too.
We’ve initiated the final countdown, and we’re just hours away from the deadline for early-bird savings to TC Sessions: Space 2020 (December 16-17). It’s your last chance to grab the first of many opportunities this two-day conference provides.
Purchase your early-bird ticket today before the offer expires tonight at 11:59 p.m. (PT).
Let’s talk about the opportunities at TC Sessions: Space. You’ll learn from and engage with the top leaders and officials across private, public and military sectors. These are the people currently driving and funding the future of space technology — founders, CEOs, generals, NASA officials, scientists and investors. Peruse the event agenda for all the presentations, fireside chats interviews, breakout sessions and interactive Q&As.
Fresh from the “Thank you, Captain Obvious” file, building a space startup ain’t cheap. Don’t miss your opportunity to meet some of the leading space funding programs and learn how you can access grant money to fuel your startup for the long haul. Representatives from each program will present and explain its grant process for 30 minutes. Then you can schedule individual appointments — using CrunchMatch — to discuss the specifics of your proposal.
We’ll add even more programs in the coming days, but here are four of the programs available (read more about them here):
You’ll go further with a strong network, and you won’t find a better opportunity to expand yours. Connect with people who share your business goals and can help you achieve startup success. CrunchMatch, our free, AI-powered platform, makes it much easier to find and connect with people across a virtual environment. Schedule 1:1 video calls, find partners, potential customers, investors or the perfect engineer to advance your business.
Explore the early-stage startups exhibiting in the expo area and see what your peers are working on. All exhibitors will get five minutes to pitch live to global attendees. If you want in on that action, grab an Early-Stage Startup Exhibitor Package ($360 gets you three tickets, digital exhibition space and the ability to generate leads).
TC Sessions: Space 2020 offers almost infinite opportunity, but your first opportunity — to save $100 — disappears tonight at 11:59 p.m. (PT). Take flight with the early bird and buy your ticket right now.
Is your company interested in sponsoring TC Sessions: Space 2020? Click here to talk with us about available opportunities.