The former CEO of Cambridge Analytica, the disgraced data company that worked for the 2016 Trump campaign and shut down in 2018 over a voter manipulation scandal involving masses of Facebook data — has been banned from running limited companies for seven years.
“Within the undertaking, Alexander Nix did not dispute that he caused or permitted SCL Elections Ltd or associated companies to market themselves as offering potentially unethical services to prospective clients; demonstrating a lack of commercial probity,” the U.K. insolvency service wrote in a press release.
Nix was suspended as CEO of Cambridge Analytica at the peak of the Facebook data scandal after footage emerged of him, filmed by undercover reporters, boasting of spreading disinformation and entrapping politicians to meet clients’ needs.
Cambridge Analytica was a subsidiary of the SCL Group, which included the division SCL Elections, while Nix was one of the key people in the group — being a director for SCL Group Ltd, SCL Social Ltd, SCL Analytics Ltd, SCL Commercial Ltd, SCL Elections and Cambridge Analytica (UK) Ltd. All six companies entered into administration in May 2018, going into compulsory liquidation in April 2019.
The “potentially unethical” activities that Nix does not dispute the companies offered, per the undertaking, are:
Last year the FTC also settled with Nix over the data misuse scandal — with the former Cambridge Analytica boss agreeing to an administrative order restricting how he conducts business in the future. The order also required the deletion/destruction of any personal information collected via the business.
Back in 2018 Nix was also grilled by the U.K. parliament’s DCMS committee — and in a second hearing he claimed Cambridge Analytica had licensed “millions of data points on American individuals from very large reputable data aggregators and data vendors such as Acxiom, Experian, Infogroup”, arguing the Facebook data had not been its “foundational data-set”.
It’s fair to say there are still many unanswered questions attached to the data misuse scandal. Last month, for example, the U.K.’s data watchdog — which raided Cambridge Analytica’s U.K. offices in 2018, seizing evidence, before going on to fine and then settle with Facebook (which did not admit any liability) over the scandal — said it would no longer be publishing a final report on its data analytics investigation.
Asked about the fate of the final report on Cambridge Analytica, an ICO spokesperson told us: “As part of the conclusion to our data analytics investigation we will be writing to the DCMS select committee to answer the outstanding questions from April 2019. We have committed to updating the select committee on our final findings but this will not be in the form of a further report.”
It’s not clear whether the DCMS committee — which has reformed with a different chair versus the one who in 2018 led the charge to dig into the Cambridge Analytica scandal as part of an enquiry into the impact of online disinformation — will publish the ICO’s written answers. Last year its final report called for Facebook’s business to be investigated over data protection and competition concerns.
You can read a TechCrunch interview with Nix here, from 2017 before the Facebook data scandal broke, in which he discusses how his company helped the Trump campaign.
Despite the surprise release of iOS 14 that left app developers unprepared, an ambitious few have managed to push their way through — or even pull an all-nighter — in order to make their apps available with iOS 14 support on launch day. For the first time in years, the new version of iOS offers a new way for consumers to organize their home screens. Now, your less frequently used apps can be shuffled away to the App Library on the iPhone’s back screen, while those apps offering information and updates can feature their content through new home screen widgets.
In time, widget support will be a standard feature for a large number of apps. But due to the way Apple chose to release iOS 14 this year, there may not be as many app widgets offered on day one.
Below are some of the first apps launching today alongside iOS 14 that include interesting iOS 14 widgets. These apps and their widgets should be available today shortly after the iOS 14 release.
Twitter client Aviary released widgets that allow you to view either 1, 2 or 4 of the latest tweets (depending on which widget size you select) from your Twitter timeline. The widgets will update periodically by themselves, as well. The app will be available today after iOS 14 rolls out.
Image Credits: Aviary (widget shown in top right)
Unbiased news app Brief is keeping to its promises to avoid clickbait with its minimalist, monochromatic widget designed to stop attention hijacking. The “Front Page” widget’s content will be carefully curated by its news team, so only the most important stories of the day will show up on your home screen.
A second “Election Snapshot” widget will let you keep track of the current presidential, house and senate races at a glance. Users can customize this widget to track their own most-watched races, like those in their home state, for example.
Image Credits: Brief
Soor, a premium music player app for iPhone users, has released three widgets in various sizes. The “Now Playing” widget shows the current song and what’s up next, and updates in near real time. There’s also a “Magic Mixes” widget for your mixes and a “Music Collection” widget that can be configured to show eight types of curated content.
Image Credits: Soor
Readdle: Spark Mail, Calendar 5, Documents
Readdle has released widgets for its Calendar iOS app that show your appointments and the month.
Image Credits: Readdle/Calendar 5
Its Spark Mail app offers widgets for email and calendar, too.
Image Credits: Readdle/Spark Mail
And Documents by Readdle is adding widgets for quick access for file actions like VPN, music, player, browser, etc.
Image Credits: Readdle
Cheep’s app lets you know about mistake fares or other ridiculously discounted flight deals. Its new iOS 14 widgets can be customized to feature deals from your airports and can be stacked together to make it easy to see the deals without opening the app.
Image Credits: Cheep
Dice, from PCalc, is a physics-based simulation of polyhedral dice for use in tabletop role-playing games. The app’s new widgets bring its dice to your home screen allowing you to open the app with just a tap.
Image Credits: PCalc
Forecasting app Weather Line already offers a lot of visual data related to weather and forecasts. Now it’s bringing its insights and graphs right to the iOS 14 home screen. The app’s all-in-one weather widget delivers current conditions, forecasts and other content like high/low, sunrise/sunset, incoming rain, extreme weather warnings and more.
Image Credits: Weather Line
Nighthawk’s Twitter client will release its first widget today. “Vanity” lets you keep an eye on your Twitter profile metrics, like how many followers you have and how many you’re following.
The first Nighthawk widget for iOS 14, “Vanity,” is coming today, along with big enhancements to Smart Filter made possible by new iOS features! We have so much more on the horizon, but things are still up in the air a bit.
Get it? Air? Birds? Aw f pic.twitter.com/MzzlJoQ8O8
— Team Nighthawk (@NighthawkApp) September 16, 2020
Apollo for Reddit
Popular Reddit client app Apollo is offering a collection of widgets, including a Post widget that shows a post from a Reddit feed of your choosing, a Multiple Posts widgets that will show several posts from your favorite feed, a Post Feed Grid that presents posts in a more visual, grid-style layout, a Wallpaper widget that will rotate through photos from image-heavy subreddits you like, as well as Showerthoughts and Jokes widgets that put a little humor on your home screen.
Image Credits: Apollo for Reddit
The iOS 14 release of Carrot’s humorous weather app brings a forecast widget, hourly and daily widgets, a weather maps widget and — in true carrot fashion — a snark widget that delivers your weather with the app’s classic snarky comments.
Habit and mood tracking app Tangerine will offer a variety of widgets to remind you about your progress on your day’s goals, like your commitments to run, exercise, drink water or whatever else you may be tracking.
Image Credits: Tangerine
Nudget’s mobile budgeting app will introduce widgets for keeping up with your household budget, including things like those categories where you’ve spent too much or have dropped your spending, and how much money you have left this week.
Image Credits: Nudget
Organized photo notes app Birch includes a Featured Photo widget that lets you put a photo on your home screen — a neat trick, since there’s not a way to do so with the iOS Photos app. (Submitting today)
Image Credits: Birch
The above apps should be live today after iOS 14 releases, barring some unforeseen rejection.
Once known for its affordable smartphones, Xiaomi has in recent years been transforming itself into an online mall for consumer electronics by cutting checks and building relationships with hundreds of hardware and lifestyle startups. And some of its allies are now going after the Western market with their high-end, China-made products.
Beijing-based Dreame, which produces premium hairdryers and vacuums in the style of Dyson but at lower prices, is one of Xiaomi’s latest bets. The startup announced this week the completion of a Series B+ round led by IDG Capital. The financing of nearly 100 million yuan ($14.6 million) also saw the participation of existing investors Xiaomi and Xiaomi founder Lei Jun’s Shunwei Capital, as well as Peak Valley Capital and Edge Ventures.
Dreame makes Xiaomi-branded vacuums and operates its own label, a common setup between Xiaomi and its suppliers, which get to enjoy the security of Xiaomi distribution and build their names at the same time.
The startup has emerged as a more affordable vacuum brand than the area’s pioneer Dyson, whose inventor James Dyson topped the U.K.’s rich list this year. Dreame’s latest handheld cordless broom V11, for example, costs €350 ($413) whereas Dyson’s new model asks for $600.
“If we compare Dyson to Apple, then there must be a Huawei in the [home cleaning] area, and we believe this company will come from China,” co-founder and vice president of marketing and sales Roc Woo told TechCrunch. Domestic businesses are poised to tap China’s rich manufacturing resources, cheaper labor and longer work hours compared to Western counterparts, he asserted.
“There are more and more success stories of Chinese brands going global, from small players like us through to behemoths like Huawei, Xiaomi, Oppo and Vivo.”
The fresh proceeds will fuel Dreame’s marketing and sales efforts in Europe and North America and allow it to spend more on research and development, which tackles the likes of high-speed motors, fluid mechanics, robot dynamics and visual simultaneous localization and mapping (VSLAM), all essential technologies for Dreame’s family of home cleaners and personal care electronics.
The five-year-old startup likes to talk up its robust engineering background. The founding team consists of friends from Tsinghua University, and chief executive Yu Hao made a dent on campus by launching Skyworks, now the prestigious university’s largest hackerspace with sponsorship from industry giants like Boeing and Megvii. A number of its key staff were involved in China’s national spaceship program Shenzhou.
In addition, the startup boasts spending 12% of its annual sales revenue on R&D and operating a 20,000-sqm factory in eastern China’s Suzhou city, where it works to improve its proprietary designs, a growing trend among Chinese startups as Beijing calls for more tech self-reliance.
Xiaomi doesn’t put all its eggs in one basket when it comes to picking suppliers. In the realm of home cleaning, it’s also backed robot cleaner Roborock, which raised about 4.4 billion yuan ($640 million) from an initial public listing on China’s new tech board in February. Xiaomi first bankrolled Roborock back in 2014, four years before its first investment in Dreame.
Woo believed Dreame and Roborock can co-exist, for his company targets a wider product spectrum while Roborock is more focused and akin to iRobot. The startup doesn’t consider Tyson, of which Woo spoke highly, a direct competitor either, for it’s venturing beyond cleaning into areas like smart mobility.
When asked whether Xiaomi picks winners, Woo said “Xiaomi is more of a platform and doesn’t allocate resources.” While it tended to work closely with startups in its early years, Xiaomi’s empire of consumer products runs on the basis of market competition these days.
“Our collaboration with Xiaomi is no different from the way we work with Amazon or eBay. The investment means not much more than having a capital tie-up and a foundation for trust,” he said. Being in the Xiaomi family does provide a practical perk: it’s a guarantee for sales and offers a bargaining chip for Dreame in its negotiation with production partners.
What Xiaomi gets in return is millions of global consumers signed onto its Mi Home app, a central platform for managing Xiaomi-branded Internet of Things. In Europe, its biggest market, Dreame said it strictly follows the GDPR’s rules on data protection.
Boosted with new capital, Dreame is ready to foray into the U.S. by the end of this year. It already derives 70-80% of its sales outside of China, with a concentration in Europe where it saw a spike in orders since the COVID-19 outbreak for its products were sold mainly online.
For the current year, it aims to generate 3 billion yuan ($440 million) in sales, which doesn’t seem far off given it had shopped over 1 million vacuums by May since the category’s debut two years ago.
Microsoft’s venture capital fund, M12 Ventures, has led a slew of strategic corporate investors backing a new chip developer out of Southern California called Syntiant, which makes semiconductors for voice recognition and speech-based applications.
“We started out to build a new type of processor for machine learning, and voice is our first application,” says Syntiant chief executive Kurt Busch. “We decided to build a chip for always-on battery-powered devices.”
Those chips need a different kind of processor than traditional chipsets, says Busch. Traditional compute is about logic, and deep learning is about memory access; traditional microchip designs also don’t perform as well when it comes to parallel processing of information.
Syntiant claims that its chips are two orders of magnitude more efficient, thanks to its data flow architecture that was built for deep learning, according to Busch.
It’s that efficiency that attracted investors, including M12, Microsoft Corp.’s venture fund; the Amazon Alexa Fund; Applied Ventures, the investment arm of Applied Materials; Intel Capital; Motorola Solutions Venture Capital; and Robert Bosch Venture Capital.
These investment firms represent some of the technology industry’s top chip makers and software developers, and they’re pooling their resources to support Syntiant’s Irvine, California-based operations.
Image Credits: Bryce Durbin / TechCrunch
“Syntiant aligns perfectly with our mission to support companies that fuel voice technology innovation,” said Paul Bernard, director of the Alexa Fund at Amazon. “Its technology has enormous potential to drive continued adoption of voice services like Alexa, especially in mobile scenarios that require devices to balance low power with continuous, high-accuracy voice recognition. We look forward to working with Syntiant to extend its speech technology to new devices and environments.”
Syntiant’s first device measures 1.4 by 1.8 millimeters and draws 140 microwatts of power. In some applications, Syntiant’s chips can run for a year on a single coin cell.
“Syntiant’s neural network technology and its memory-centric architecture fits well with Applied Materials’ core expertise in materials engineering as we enable radical leaps in device performance and novel materials-enabled memory technologies,” said Michael Stewart, principal at Applied Ventures, the venture capital arm of Applied Materials, Inc. “Syntiant’s ultra-low-power neural decision processors have the potential to create growth in the chip marketplace and provide an effective solution for today’s demanding voice and video applications.”
So far, 80 customers are working with Syntiant to integrate the company’s chips into their products. There are a few dozen companies in the design stage and the company has already notched design wins for products ranging from cell phones and smart speakers to remote controls, hearing aids, laptops and monitors. Already the company has shipped its first million units.
“We expect to scale that by 10x by the end of this year,” says Busch.
Syntiant’s chipsets are designed specifically to handle wakes and commands, which means that users can add voice recognition features and commands unique to their particular voice, Busch says.
Initially backed by venture firms including Atlantic Bridge, Miramar and Alpha Edison, Syntiant raised its first round of funding in October 2017. The company has raised a total of $65 million to date, according to Busch.
“Syntiant’s architecture is well-suited for the computational patterns and inherent parallelism of deep neural networks,” said Samir Kumar, an investor with M12 and new director on the Syntiant board. “We see great potential in its ability to enable breakthroughs in power performance for AI processing in IoT [Internet of things].”
The coronavirus caused some disagreement amongst Boston’s venture capital community. Looking back at our mid-2020 survey of its VCs, some saw the city’s strength in biotech and healthcare as a competitive advantage, while others saw Boston’s diverse startup ecosystem as key to its survival.
And some were worried that activity was about to clamp down. Jeff Bussgang, Flybridge Ventures, put it most frankly: “Q2 financing for Boston is going to fall off a cliff. The biotech industry may see some bright spots […] but the financing market has frozen up as solid as the Charles River in February.”
With fresh data in hand, it appears that the more bullish were more right than the bears and that, in a good turn of affairs for Boston startups, Bussgang was wrong.
The city, much like the country, did not see the sharply negative quarter that many anticipated. Boston posted record venture capital investment in the period, its highest total since at least Q3 2018 according to CB Insights data.
The same dataset also says that Boston-area companies raised $3.7 billion across 126 deals. Indeed, the good news from Boston’s Q1 bested better-than-anticipated-results from both the global venture capital community, and the domestic VC world in Q2.
Bussgang sent an updated metaphor to the TechCrunch team in response to this data: “It was a tundra in March and April but, as happens in Boston, April showers and May flowers kicked in and the financing markets started to gush again in the late spring/early summer, just in time to save Q2 .”
While the data isn’t historically definitive due to reporting lags, it can be used as a directional sign that Boston’s rebound isn’t ahead of us, it’s upon us.
The solid numbers are a sign that COVID-19 and economic turmoil have put many startups in greater demand than before, which means that they need to amass money to meet growth needs.
The Colombian trucking and logistics services startup Liftit has raised $22.5 million in a new round of funding to capitalize on its newfound traction in markets across Latin America as responses to the COVID-19 epidemic bring changes to the industry across the region.
“We’re focusing on the five countries that we’re already in,” says Liftit chief executive Brian York.
The company recently hired a head of operations for Mexico and a head of operations for Brazil as it looks to double down on its success in both regions.
Funding for the round was led by Cambridge Capital and included investments from the new Latin American focused firm H20 Capital along with AC Ventures, the venture arm of the 2nd largest coca-cola bottler in Latam; 10x Capital, Banyan Tree Ventures, Alpha4 Ventures, the lingerie brand Leonisa; and Mexico’s largest long haul trucking company, Grupo Transportes Monterrey. Individual investor, Jason Radisson the former chief operating officer of the on-demand ride hailing startup 99, also invested.
The new capital comes on top of Liftit’s $14.3 million Series A from some of the region’s top local investors. Firms like Monashees, Jaguar Ventures and NXTP Ventures all joined the International Finance Corp. in financing the company previously and all returned to back the company again with its new funding.
Investors likely responded to the company’s strong performance in its core markets. Already profitable in Chile and Colombia, Liftit expects to reach profitability across all of its operations before the end of the year. That’s despite the global pandemic.
Of the 220 contracts the company had with shippers half of them went to zero and the other half spiked significantly, York said. While Liftit’s major Colombian customer stumbled, new business, like Walmart, saw huge spikes in deliveries and usage.
“Managing truck drivers is incredibly difficult, and trucking, in our opinion, is not on demand,” said York. “At the end of the day the trucking market in all of Latin America is a majority of independent owners. They’re not looking for on-demand work… they’re looking for full time work.”
Less than one percent of the company’s deliveries come from on-demand orders, instead, it’s a service comprised of scheduled shipments with optimized routes and efficiencies that are bringing customers to Liftit’s virtual door.
“We do scheduled trucking delivery so we integrate with existing systems that shippers have and start planning how many trucks they’re going to need and the routes they’re going to take and … tee it up exactly what is going to happen regardless what the traffic conditions are so we have been able to reduce the delivery times for the trucks,” said York.
Teal, a platform that looks to help people land jobs that they love, has closed a $5 million seed round, which was led by Flybridge Capital, with participation from Lerer Hippeau, Corigin Ventures, Aleph, Oceans Ventures, Hight Output, AVG Basecamp, and Kairos Angels.
Teal launched in November of 2019 with a system that did all of the heavy lifting for people seeking jobs, including resume consultations, searching listings, and sending application information to the right people. Essentially, Teal handled everything but the interview.
Since launch, the company has made a slight pivot to a product that’s more scalable, called Career Assist.
Fano explained that, with the original product (called Career Agent), there was a group of people who were very clear on what they wanted and saw great success on the platform. But there was also a group of people who were unsure about their career path that Teal was spending a tremendous amount of time and energy on, and they still weren’t seeing success.
“There was something kind of flawed in this model in that the people that want us the most and will pay us for the longest are going to be the least satisfied,” said Fano, adding that Career Agent was built more for job-hopping than helping people who were unemployed find a job. “So we decided to take all the learnings we’ve gotten through Career Agent and understand where things repeat and where there are inefficiencies that don’t get identified on an individual basis. When you do that for many people, you can start to identify those patterns.”
Career Assist is a curriculum that allows cohorts (of 20-30 people) to learn the best possible process for finding and landing a job they want. It includes a four-week workshop (eight classes in total) guided by experts who lead live sessions around everything from writing a resume to how to send in that resume (to the right person) to interview skills.
According to cofounder and CEO Dave Fano, applying for a job through a website is one of the worst things you can do. Instead, applicants should find the head of recruiting or HR and send them a direct email. There are also plenty of tactics, gleaned from the sales playbook, that increase an applicant’s chances of hearing back on an email.
Teal looks not only to give job-seekers a better, more interactive playbook for landing a job, but also pairs its members with other members who are going through the same thing, to offer emotional support and empathy during a time where people desperately need it.
Career Assist was originally launched for free, but has since moved to a paid model, costing users $149 for full access to the four-week program. Since April, more than 200 people have landed new jobs after going through the course.
Fano, a serial entrepreneur who sold his first company, CASE, to WeWork, has a much broader vision for Teal than getting a job. There are many situations over the course of a person’s career where they can benefit from guidance and expertise, such as negotiating contracts, asking for a promotion or a raise, or resigning.
Teal wants to stay with workers throughout the entirety of their career to help them navigate these more challenging situations.
Teal plans on using the funding to continue growing the team, which is currently at 12 people, with a 50/50 split between men and women.
Fano says that one of the greatest challenges for the company is also one of its biggest opportunities. He explained that most people think they need an individual, bespoke career coach because of the general complexity of individual careers.
Fano believes that by combining resources that exist with data from its existing user base, Teal can cover a broader set of situations and circumstances for people than an individual coach may be able to while still being able to give specific advice from this collective data set.
“Building up that data set is one of the bigger challenges, and that’s why these things don’t exist,” said Fano. “But that’s also why we’re taking the approach that we are, focusing on things that don’t scale, and so far we’ve seen that people are very willing to interact with us because we’ve shown we’ve got their best interest at heart.”
He added that the company has no interest in becoming a B2B tool that sells into the HR department, but rather wants to focus on the end-consumer.
Since widespread protests over racial inequality began, IBM announced it would cancel its facial recognition programs to advance racial equity in law enforcement. Amazon suspended police use of its Rekognition software for one year to “put in place stronger regulations to govern the ethical use of facial recognition technology.”
But we need more than regulatory change; the entire field of artificial intelligence (AI) must mature out of the computer science lab and accept the embrace of the entire community.
We can develop amazing AI that works in the world in largely unbiased ways. But to accomplish this, AI can’t be just a subfield of computer science (CS) and computer engineering (CE), like it is right now. We must create an academic discipline of AI that takes the complexity of human behavior into account. We need to move from computer science-owned AI to computer science-enabled AI. The problems with AI don’t occur in the lab; they occur when scientists move the tech into the real world of people. Training data in the CS lab often lacks the context and complexity of the world you and I inhabit. This flaw perpetuates biases.
AI-powered algorithms have been found to display bias against people of color and against women. In 2014, for example, Amazon found that an AI algorithm it developed to automate headhunting taught itself to bias against female candidates. MIT researchers reported in January 2019 that facial recognition software is less accurate in identifying humans with darker pigmentation. Most recently, in a study late last year by the National Institute of Standards and Technology (NIST), researchers found evidence of racial bias in nearly 200 facial recognition algorithms.
In spite of the countless examples of AI errors, the zeal continues. This is why the IBM and Amazon announcements generated so much positive news coverage. Global use of artificial intelligence grew by 270% from 2015 to 2019, with the market expected to generate revenue of $118.6 billion by 2025. According to Gallup, nearly 90% Americans are already using AI products in their everyday lives – often without even realizing it.
Beyond a 12-month hiatus, we must acknowledge that while building AI is a technology challenge, using AI requires non-software development heavy disciplines such as social science, law and politics. But despite our increasingly ubiquitous use of AI, AI as a field of study is still lumped into the fields of CS and CE. At North Carolina State University, for example, algorithms and AI are taught in the CS program. MIT houses the study of AI under both CS and CE. AI must make it into humanities programs, race and gender studies curricula, and business schools. Let’s develop an AI track in political science departments. In my own program at Georgetown University, we teach AI and Machine Learning concepts to Security Studies students. This needs to become common practice.
Without a broader approach to the professionalization of AI, we will almost certainly perpetuate biases and discriminatory practices in existence today. We just may discriminate at a lower cost — not a noble goal for technology. We require the intentional establishment of a field of AI whose purpose is to understand the development of neural networks and the social contexts into which the technology will be deployed.
In computer engineering, a student studies programming and computer fundamentals. In computer science, they study computational and programmatic theory, including the basis of algorithmic learning. These are solid foundations for the study of AI – but they should only be considered components. These foundations are necessary for understanding the field of AI but not sufficient on their own.
For the population to gain comfort with broad deployment of AI so that tech companies like Amazon and IBM, and countless others, can deploy these innovations, the entire discipline needs to move beyond the CS lab. Those who work in disciplines like psychology, sociology, anthropology and neuroscience are needed. Understanding human behavior patterns, biases in data generation processes are needed. I could not have created the software I developed to identify human trafficking, money laundering and other illicit behaviors without my background in behavioral science.
Responsibly managing machine learning processes is no longer just a desirable component of progress but a necessary one. We have to recognize the pitfalls of human bias and the errors of replicating these biases in the machines of tomorrow, and the social sciences and humanities provide the keys. We can only accomplish this if a new field of AI, encompassing all of these disciplines, is created.