Prosthetic limbs are getting better every year, but the strength and precision they gain doesn’t always translate to easier or more effective use, since amputees have only a basic level of control over them. One promising avenue being investigated by Swiss researchers is having an AI take over where manual control leaves off.
To visualize the problem, imagine a person with their arm amputated above the elbow controlling a smart prosthetic limb. With sensors placed on their remaining muscles and other signals, they may fairly easily be able to lift their arm and direct it to a position where they can grab an object on a table.
But what happens next? The many muscles and tendons that would have controlled the fingers are gone, and with them the ability to sense exactly how the user wants to flex or extend their artificial digits. If all the user can do is signal a generic “grip” or “release,” that loses a huge amount of what a hand is actually good for.
Here’s where researchers from École Polytechnique Fédérale de Lausanne (EPFL) take over. Being limited to telling the hand to grip or release isn’t a problem if the hand knows what to do next — sort of like how our natural hands “automatically” find the best grip for an object without our needing to think about it. Robotics researchers have been working on automatic detection of grip methods for a long time, and it’s a perfect match for this situation.
Prosthesis users train a machine learning model by having it observe their muscle signals while attempting various motions and grips as best they can without the actual hand to do it with. With that basic information the robotic hand knows what type of grasp it should be attempting, and by monitoring and maximizing the area of contact with the target object, the hand improvises the best grip for it in real time. It also provides drop resistance, being able to adjust its grip in less than half a second should it start to slip.
The result is that the object is grasped strongly but gently for as long as the user continues gripping it with, essentially, their will. When they’re done with the object, having taken a sip of coffee or moved a piece of fruit from a bowl to a plate, they “release” the object and the system senses this change in their muscles’ signals and does the same.
It’s reminiscent of another approach, by students in Microsoft’s Imagine Cup, in which the arm is equipped with a camera in the palm that gives it feedback on the object and how it ought to grip it.
It’s all still very experimental, and done with a third-party robotic arm and not particularly optimized software. But this “shared control” technique is promising and could very well be foundational to the next generation of smart prostheses. The team’s paper is published in the journal Nature Machine Intelligence.
In November 2020, America will go to the polls to vote in perhaps the most consequential election in a generation. The winner will lead the country amid great social, economic and ecological unrest. The 2020 election will be a referendum on both the current White House and the direction of the country at large.
Nearly 20 years into the young century, technology has become a pervasive element in all of our lives, and will continue to only grow more important. Whoever takes the oath of office in January 2021 will have to answer some difficult questions, raging from an impending climate disaster to concerns about job loss at the hands of robotics and automation.
Many of these questions are overlooked in day to day coverage of candidates and during debates. In order to better address the issues, TechCrunch staff has compiled a 10-part questionnaire across a wide range of tech-centric topics. The questions have been sent to national candidates, regardless of party. We will be publishing the answers as we receive them. Candidates are not required to answer all 10 in order for us to publish, but we will be noting which answers have been left blank.
First up is former Congressman John Delaney. Prior to being elected to Maryland’s 6th Congressional District, Delaney co-founded and led healthcare loan service Health Care Financial Partners (HCFP) and commercial lender CapitalSource. He was elected to Congress in 2013, beating out a 10-term Republican incumbent. Rumored to be running against Maryland governor Larry Hogan for a 2018 bid, Delaney instead announced plans to run for president in 2020.
1. Which initiatives will you prioritize to limit humankind’s impact on climate and avoid potential climate catastrophe?
My $4 trillion Climate Plan will enable us to reach the goal of net zero emissions by 2050, which the IPCC says is the necessary target to avoid the worst effects of climate change. The centerpiece of my plan is a carbon-fee-and-dividend that will put a price on carbon emissions and return the money to the American people through a dividend. My plan also includes increased federal funding for renewable energy research, advanced nuclear technologies, direct air capture, a new Climate Corps program, and the construction of the Carbon Throughway, which would transport captured carbon from all over the country to the Permian Basin for reuse and permanent sequestration.
2. What is your plan to increase black and Latinx startup founders’ access to funding?
As a former entrepreneur who started two companies that went on to be publicly traded, I am a firm believer in the importance of entrepreneurship. To ensure people from all backgrounds have the support they need to start a new business, I will create nonprofit banks to serve economically distressed communities, launch a new SBIC program to help provide access to capital to minority entrepreneurs, and create a grant program to fund business incubators and accelerators at HBCUs. Additionally, I pledge to appoint an Entrepreneurship Czar who will be responsible for promoting entrepreneurship-friendly policies at all levels of government and encouraging entrepreneurship in rural and urban communities that have been left behind by venture capital investment.
3. Why do you think low-income students are underrepresented in STEM fields and how do you think the government can help fix that problem?
I think a major part of the problem is that schools serving low-income communities don’t have the resources they need to provide a quality STEM education to every student. To fix that, I have an education plan that will increase investment in STEM education and use Title I funding to eliminate the $23 billion annual funding gap between predominantly white and predominantly black school districts. To encourage students to continue their education after they graduate from high school and ensure every student learns the skills they need, my plan also provides two years of free in-state tuition and fees at a public university, community college, or technical school to everyone who completes one year of my mandatory national service program.
4. Do you plan on backing and rolling out paper-only ballots or paper-verified election machines? With many stakeholders in the private sector and the government, how do you aim to coordinate and achieve that?
Making sure that our elections are secure is vital, and I think using voting machines that create a voter-verified paper record could improve security and increase voters’ confidence in the integrity of our elections. To address other facets of the election security issue, I have proposed creating a Department of Cybersecurity to help protect our election systems, and while in Congress I introduced election security legislation to ensure that election vendors are solely owned and controlled by American citizens.
5. What, if any, federal regulation should be enacted for autonomous vehicles?
I was proud to be the founder of the Congressional Artificial Intelligence Caucus, a bipartisan group of lawmakers dedicated to understanding the impacts of advances in AI technology and educating other legislators so they have the knowledge they need to enact policies that ensure these innovations benefit Americans. We need to use the legislative process to have a real conversation involving experts and other stakeholders in order to develop a comprehensive set of regulations regarding autonomous vehicles, which should include standards that address data collection practices and other privacy issues as well as more fundamental questions about public safety.
6. How do you plan to achieve and maintain U.S. superiority in space, both in government programs and private industry?
Space exploration is tremendously important to me as a former Congressman from Maryland, the home of NASA’s Goddard Space Flight Center, major space research centers at the University of Maryland, and many companies that develop crucial aerospace technologies. As president, I will support the NASA budget and will continue to encourage innovation in the private sector.
7. Increased capital in startups founded by American entrepreneurs is a net positive, but should the U.S. allow its businesses to be part-owned by foreign governments, particularly the government of Saudi Arabia?
I am concerned that joint ventures between U.S. businesses and foreign governments, including state-owned enterprises, could facilitate the theft of intellectual property, potentially allowing foreign governments to benefit from taxpayer-funded research. We need to put in place greater protections that defend American innovation from theft.
8. Will U.S.-China technology decoupling harm or benefit U.S. innovation and why?
In general, I am in favor of international technology cooperation but in the case of China, it engages in predatory economic behavior and disregards international rules. Intellectual property theft has become a big problem for American businesses as China allows its companies to steal IP through joint ventures. In theory, U.S.-China collaboration could advance technology and innovation but without proper IP and economic protections, U.S.-China joint ventures and partnerships can be detrimental to the U.S.
9. How large a threat does automation represent to American jobs? Do you have a plan to help train low-skilled workers and otherwise offset job loss?
Automation could lead to the disruption of up to 54 million American jobs if we aren’t prepared and we don’t have the right policies. To help American workers transition to the high-tech, high-skill future economy, I am calling for a national AI strategy that will support public/private AI partnerships, develop a social contract with the communities that are negatively impacted by technology and globalization, and create updated education and job training programs that will help students and those currently in the workforce learn the skills they need.
To help provide jobs to displaced workers and drive economic growth in communities that suffer negative effects from automation, I have proposed a $2 trillion infrastructure plan that would create an infrastructure bank to facilitate state and local government investment, increase the Highway Trust Fund, create a Climate Infrastructure Fund, and create five new matching funds to support water infrastructure, school infrastructure, deferred maintenance projects, rural broadband, and infrastructure projects in disadvantaged communities in urban and rural areas. In addition, my proposed national service program will create new opportunities that allow young adults to learn new skills and gain valuable work experience. For example, my proposal includes a new national infrastructure apprenticeship program that will award a professional certificate proving mastery of particular skill sets for those who complete the program.
10. What steps will you take to restore net neutrality and assure internet users that their traffic and data are safe from manipulation by broadband providers?
I support the Save Net Neutrality Act to restore net neutrality, and I will appoint FCC commissioners who are committed to maintaining a fair and open internet. Additionally, I would work with Congress to update our digital privacy laws and regulations to protect consumers, especially children, from their data being collected without consent.
While tech giants like Google and Amazon build and invest in a multitude of artificial intelligence applications to grow their businesses, a startup has raised a big round of funding to help those that are not technology businesses by nature also jump into the AI fray.
Element AI, the very well-funded, well-connected Canadian startup that has built an AI systems integrator of sorts to help other companies develop and implement artificial intelligence solutions — an “Accenture” for machine learning, neural network-based solutions, computer vision applications and so on — is today announcing a further 200 million Canadian dollars ($151.3 million) in funding, money that it plans to use to commercialise more of its products, as well as to continue working on R&D, specifically working on new AI solutions.
“Operationalising AI is currently the industry’s toughest challenge, and few companies have been successful at taking proofs-of-concept out of the lab, imbedding them strategically in their operations, and delivering actual business impact,” said Element AI CEO Jean-François (JF) Gagné in a statement. “We are proud to be working with our new partners, who understand this challenge well, and to leverage each other’s expertise in taking AI solutions to market.”
The company did not disclose its valuation in the short statement announcing the funding, nor has it ever talked about it publicly, but PitchBook notes that as of its previous funding round of $102 million back in 2017, it had a post-money valuation of $300 million, a figure a source close to the company confirmed to me. From what I understand, the valuation now is between $600 million and $700 million, a mark of how Element AI has grown, which is especially interesting, considering how quiet is has been.
The funding is being led by Caisse de dépôt et placement du Québec (CDPQ), along with participation from McKinsey & Company and its advanced analytics company QuantumBlack; and the Québec government. Previous investors DCVC (Data Collective), Hanwha Asset Management, BDC (Business Development Bank of Canada), Real Ventures and others also participated, with the total raised to date now at C$340 million ($257 million). Other strategic investors in the company have included Microsoft, Nvidia and Intel.
Element AI was started under an interesting premise that goes something like this: AI is the next major transformational shift — not just in computing, but in how businesses operate. But not every business is a technology business by DNA, and that creates a digital divide of sorts between the companies that can identify a problem that can be fixed by AI and build/invest in the technology to do that and those that cannot.
Element AI opened for business from the start as a kind of “AI shop” for the latter kinds of enterprises, to help them identify areas where they could build AI solutions to work better, and then build and implement those solutions. Today it offers products in insurance, financial services, manufacturing, logistics and retail — a list that is likely to get longer and deeper with this latest funding.
One catch about Element AI is that the company has not been very forthcoming about its customer list up to now — those that have been named as partners include Bank of Canada and Gore Mutual, but there is a very notable absence of case studies or reference customers on its site.
However, from what we understand, this is more a by-product of the companies (both Element AI and its customers) wishing to keep involvement quiet for competitive and other reasons; and in fact there are apparently a number of large enterprises that are building and deploying long-term products working with the startup. We have also been told big investors in this latest round (specifically McKinsey) are bringing in customers of their own by way of this deal, expanding that list. Total bookings are a “significant double digit million number” at the moment.
“With this transaction, we are investing capital and expertise alongside partners who are ideally suited to transform Element AI into a company with a commercial focus that anticipates and creates AI products to address clients’ needs,” said Charles Émond, EVP and head of Québec Investments and Global Strategic Planning at la Caisse, in a statement. CDPQ launched an AI Fund this year and this is coming out of that fund to help export more of the AI tech and IP that has been incubated and developed in the region. “Through this fund, la Caisse wants to actively contribute to build and strengthen Québec’s global presence in artificial intelligence.”
Management consultancies like McKinsey would be obvious competitors to Element AI, but in fact, they are turning out to be customer pipelines, as traditional system integrators also often lack the deeper expertise needed in newer areas of computing. (And that’s even considering that McKinsey itself has been investing in building its own capabilities, for example through its acquisition of the analytics firm QuantumBlack.
“For McKinsey, this investment is all about helping our clients to further unlock the potential of AI and Machine Learning to improve business performance,” said Patrick Lahaie, senior partner and Montreal managing partner for McKinsey & Company, in a statement. “We look forward to collaborating closely with the talented team at Element AI in Canada and globally in our shared objective to turn cutting-edge thinking and technology into AI assets which will transform a wide range of industries and sectors. This investment fits into McKinsey’s long-term AI strategy, including the 2015 acquisition of QuantumBlack, which has grown substantially since then and will spearhead the collaboration with Element AI on behalf of our Firm.”
Anti-fraud startup Shape Security has tipped over the $1 billion valuation mark following its latest Series F round of $51 million.
The Mountain View, Calif.-based company announced the fundraise Thursday, bringing the total amount of outside investment to $173 million since the company debuted in 2011.
C5 Capital led the round along with several other new and returning investors, including Kleiner Perkins, HPE Growth, and Norwest Ventures Partners.
Shape Security protects companies against automated and imitation attacks, which often employ bots to break into networks using stolen or reused credentials. Shape uses artificial intelligence to discern bots from ordinary users by comparing known information such as a user’s location, and collected data like mouse movements to shut down attempted automated logins in real-time.
The company said it now protects against two billion fraudulent logins daily.
C5 managing partner André Pienaar said he believes Shape will become the “definitive” anti-fraud platform for the world’s largest companies.
“While we while we expect a strong financial return, we also believe that we can bring Shape’s platform into many of the leading companies in Europe who look to us for strategic ideas that benefit the entire value-chain where B2C applications are used,” Pienaar told TechCrunch.
Shape’s chief executive Derek Smith said the $51 million injection will go towards the company’s international expansion and product development — particularly the capabilities of its AI system.
He added that Shape was preparing for an IPO.
Homeownership has long been touted as the American dream. But rising rates of mortgage debt, student loan debt, or otherwise are making the pursuit of homeownership a nightmare. Debt burdened individuals or those with inconsistent or tight cash flow can not only struggle to get credit loan approval when buying a home but also struggle to satisfy monthly mortgage payments even after purchase.
Patch Homes is hoping to keep the proverbial American dream alive. Patch looks to provide homeowners with cash flow and liquidity by allowing them to monetize their homes without taking on debt, interest or burdensome monthly payments.
Today, Patch took another big step in making its vision a far-reaching reality. The company has announced it’s raised a $5 million Series A round led by Union Square Ventures (USV) with participation by from Tribe Capital and previous investors Techstars Ventures, Breega Capital, and Greg Schroy.
Patch Home looks to partner with homeowners by investing up to $250,000 (with an average investment of ~$100,000) for an equity stake in the home’s value, generally in the 5% to 20% range. Homeowners aren’t subject to any interest or recurring payments and have ten years to pay back Patch’s investment. Upon doing so, the only incremental money Patch receives is its portion of the change in the home’s value over the course of the ten year period. If the value of the home goes down in value, Patch willingly takes a loss on its investment.
According to Patch Homes CEO and cofounder Sahil Gupta, one of the major motivations behind the company’s model is to align Patch’s incentives with the homeowners, allowing both parties to think of each other as trusted partners even after financing. After Patch’s investment, the company provides a number of ancillary services to homeowners such as credit score monitoring, as well as home value and property tax tracking.
In one instance recounted by Gupta in an interview with TechCrunch, Patch even covered three months of an owner’s mortgage during a liquidity crunch for his small business, allowing him to maintain his home and credit score. Patch is incentivized to provide all services that can help ensure an increase in home value, benefitting both Patch and the homeowner, with the homeowner earning the majority of the asset’s appreciated value.
Additionally, since Patch’s model isn’t focused on a homeowner’s ability to pay back a loan, interest or periodic payments, Patch is able to provide financing to more people. Patch is able to help those with more variable qualifications that struggle to get traditional loans — such as a 1099 contracted worker — monetize their illiquid assets with less harsh or restrictive terms and without increasing their debt burden. Gupta described this as solving the core problem of providing liquidity to asset-rich but cash-flow sensitive people.
Patch is not only looking to provide easier liquidity to more homeowners, but they’re trying to do so faster than traditional lenders. Interested customers can first receive a free estimate of whether Patch will invest in their home or not, how much its willing to invest and what percentage equity it will take — primarily based on Patch’s machine learning models that focus on asset, market, and location level attributes.
After the initial estimate, a Patch home advisor will educate the customer on the product and start a formal application process, which includes your standard income and credit score verification and otherwise, that takes 5-10 days. All-in, homeowners have the ability to get money in as little as 14 days, a significantly shorter timeline than your standard home credit process. Once the investment is made, owners have full freedom with how they use the money.
According to Patch, while its customers come from a diverse set of backgrounds, many either accumulated debt have to pay down the net or may struggle making monthly payments. The average Patch homeowner uses 40% of the investment to eliminate debt, adds 40% to their savings account or passive income, and invests 20% into home improvements.
To date, Patch has raised a total of $6 million and believes the latest round of funding will help scale its operations as they team up with advisors like USV that have experience scaling fintech companies (such as a Lending Club or Carta). The funds will be used to invest in product and Patch’s clearing technology in order to further speed up Patch’s lending process.
Patch also hopes to use the investment to help them gradually expand their footprint, with the goal of eventually having a presence all 50 states. (Patch is currently available in 11 regional markets within California and Washington and expects to be in 18 regional markets by the end of the year including those in Utah, Colorado and Oregon.)
What makes homeownership so galvanizing for the Patch team? Patch CEO Sahil Gupta spent years putting his Carnegie Mellon financial engineering degree to work in banking and finance, as well as in financial products and strategy positions at fintech startups backed by heavy hitters such as YC to Goldman Sachs.
After realizing the majority of the US population were homeowners, but were struggling to make monthly payments or save for the future, Sahil wanted to figure out how we could take an illiquid asset like a home and make it easily accessible.
Around the same time, Sahil’s cofounder Sundeep Ambat was working as a contractor on a new business venture of his and was struggling to get a home equity loan. While these circumstances ultimately led Sahil and Sundeep to found Patch Homes in 2016 out of the TechStars New York accelerator program, the deeper motivation behind Patch can be traced back nearly 30 years when Sahil’s father made an equity sharing agreement with his brother as they were building his family’s home in India.
With a growing family and a pregnant wife, Sunil’s father was adamant about living debt-free and so his brother provided an investment in exchange for an equity stake in the house. According to Sahil, the home is still in the family and has appreciated substantially in value to the benefit of both Sahil’s father and his brother. Longer-term, Patch wants to be the preferred partner for homeownership, helping reduce cash tight owners’ financial anxiety without the debilitating weight of debt.
“Some companies want to help people buy or sell homes, but homeownership really begins after that point. Patch is built to be inside the home with you and everything that comes thereafter,” Gupta told TechCrunch.
“Patch was created to partner with homeowners to help them unlock their home equity so they can achieve their financial goals along every step of their homeownership journey.
In December, Amazon launched a crowdsourced Q&A platform into beta with the goal of improving Alexa’s ability to answer questions. That feature, Alexa Answers, is now live to all. Amazon says the feature was well-received by the early community of invite-only participants, who have since contributed hundreds of thousands of answers that have been shared with Alexa customers millions of times.
To differentiate these answers from other Alexa responses, they’re attributed to “an Amazon customer.”
As the company explained at launch, there are thousands of answers that had previously stumped Alexa, like “Where was Barbara Bush buried?,” “Who wrote the score for Lord of the Rings?,” “What’s cork made out of?,” and “Where do bats go in the winter?”
Though Alexa should have the ability to answer some of these sorts of questions thanks to its integrations with Bing, it falls short in many areas.
The ability to answer common questions like the above is currently one of Google Assistant’s stronger features, thanks to the years Google spend building up a Knowledge Graph that’s based on a web’s worth of data.
Meanwhile, Amazon’s decision to quickly ramp up its own database of answers by way of crowdsourcing opens itself up to many potential challenges, including most notably, abuse and inaccuracy.
As anyone who uses crowdsourced Q&A platforms like Yahoo Answers or Quora could tell you, the most upvoted answers aren’t always the best or most accurate. In some cases, they’re also profane. In addition, when users are incentivized to answer questions by way of some sort of rewards system, some will attempt to answer as many as possible in order to be designated as a “top contributor.” But they may not always be the best person to answer the questions they’re plowing through.
Amazon is attempting to address these problems with a platform that uses automatic filtering to catch the inappropriate and offensive content and language, along with a community platform where answered are rated and the best are then shared by Alexa, earning the person who answered the question some points.
Before, this community was limited to a smaller number of invitees.
Today, any Amazon account holder can sign in and begin contributing. You can then see a list of questions available and choose to filter them based on things like “most frequently asked,” or “newest” or by other topic areas. After you submit an answer, you earn points towards monthly and weekly leaderboards and badges based on how many questions you’ve answered, how many times it’s been shared with Alexa users, and more.
“This new feature is just one example of the many ways we’re continuously working to grow Alexa’s knowledge,” an Amazon spokesperson said. “As always, we’ll continue to evolve the experience based on customer feedback.”
There haven’t been any reports of abuse of this feature so far, but it hadn’t been so broadly available. It’s unclear, however, if Amazon has in place strong enough protections against those who like to disrupt online communities just for the sake of watching them burn.
While crowdsourcing isn’t necessarily a bad idea — Wikipedia turned out well, for example — it’s an area that requires a lot of oversight. In Wikipedia’s case, that comes down to an elite group of editors who handle much of the site’s content. Alexa Answers may not be able to create the same sort of self-policed system, given it pits community members against one another with its leaderboards. Gamification like this doesn’t always lead to collaboration and support.
A better model may have been that of Reddit’s with virtual currency and tiered rewards, and moderation by topical area from strong community leads. But growing a community organically takes time and effort. And today’s voice assistants are engaged in sprints, not marathons, when it comes to one-upping one another by feature set.
The Alexa Answers feature is open for everyone at alexaanswers.amazon.com/about.
Veo, a Copenhagen, Denmark-based startup that offers an “AI camera” to make it easier for amateur soccer clubs to video and stream matches, has raised $6 million in Series A funding.
Backing the round is U.S.-based CourtsideVC, France’s Ventech Capital and Danish firm VC Seed Capital. Veo says the new capital will be used to launch in the U.S.
Founded in 2015 by Henrik Teisbæk, Jesper Taxbøl and Keld Reinicke, Veo has set out to “democratise” the filming of soccers matches and training by negating the need for multiple camera operators and/or a vision mixer.
It does this by employing a 4K lens camera that records the entire pitch (it’s designed to be mounted on a 23 foot tripod for optimal view), coupled with its AI video technology that processes the resulting video. This sees Veo follow the action via virtual panning and zooming, to create a TV-like viewing experience.
As we’ve noted before, that does mean a portion of the image will often be cropped out, resulting in a loss of resolution overall. However, the idea is that by starting with 4K the video quality is more than sufficient for playback on smaller screens, such as smartphones and tablets.
“Our immediate goal is to establish a foothold for Veo on the U.S. market, and a lot of the investment will go towards achieving that,” Veo CEO Henrik Teisbæk tells TechCrunch with regards to the new funding round. “In the long term, we want to use our U.S. market presence as a stepping stone towards becoming a central player on the global football market, and to hopefully break into other sports”.
Teisbæk says the U.S. was chosen because one of the “biggest and most exciting” soccer markets, and North American soccer players, coaches, clubs and associations are very data driven and open to new technology. “That represents a huge potential for us,” he adds.
Meanwhile, Veo says that in the last year it has seen 25,000 games recorded by 1,000 clubs in 50 countries. The company now employs 35 people in its Copenhagen HQ, where it develops the Veo software and hardware.
Concept vehicles are a staple of the auto show circuit. And while most will never end up as a production vehicle, they can provide insight into an automaker and clues to where it’s headed.
Over at Audi, designers and engineers might have had a distant planet in mind. Or at least an expanse of wilderness.
The German automaker unveiled Tuesday at the Frankfurt Motor Show the Audi AI: TRAIL quattro, a concept electric vehicle designed for the “future of off roading.” The “Trail” off roader is one of four concept vehicles that Audi has presented at various auto shows since 2017. Other concepts included a sports car, luxury vehicle and one designed for megacities.
Audi argues that these concepts aren’t efforts of futility. Instead, the company says it these four vehicles show how Audi vehicles in the future will be designed for specific use cases.
“In the future, customers will be able to order any of these specialist Audi models from an Audi on-demand vehicle pool to suit their personal preferences and requirements and to lease them for a limited period,” the company said in its announcement.
Audi takes this idea of the on-demand subscription further by noting that vehicles will be configured to suit individual preferences of customers who use this still non-existent and totally conceptual on-demand product. All the essential customer information would be stored in the myAudi system and accompanying app, the company said.
In the video below, Audi’s head of design Marc Lichte explains the thinking behind these concepts.
In the case of the Audi AI: TRAIL, designers put an emphasis on exploration and seeing the surrounding environment. It even comes with five drones, which aside from replacing the headlights, can provide other tasks such as lighting up your camping area or picnic spot.
The all-electric concept, which has a range of up to 310 miles, is about 13.5 feet long and 7 feet wide and is outfitted with beefy 22-inch wheels. And because it’s a vehicle meant to off road, designers gave it ground clearance of 13.4 inches. This concept, if it really existed beyond the showroom floor, can ford through water more than half a meter deep. The range of the vehicle does drop on rough roads to about 155 miles, which would theoretically (if this vehicle actually existed) make wilderness travel more difficult.
The battery unit is integrated into the floor providing a spacious interior that sits four people. Glass surrounds the cabin to provide unrivaled views of the environment, whether it’s an earthly vista or the binary sunset over the fictional Tatooine desert.
The remaining exterior body is made of a mixture of high-tech steel, aluminum and carbon fiber, giving it a total weight of 3,858 pounds.
The concept vehicle is equipped with four electric motors, systems for assisted and automated driving and all-wheel drive. What you won’t find are any screens for streaming video. This concept was designed for viewing the outside world.
The interior, which uses recycled materials, is scant. There are pedals, a yoke for a steering wheel, a few buttons, and a smartphone attached to the steering column as a display and control center for vehicle functions and navigation.
The second row features seats that are designed to function like hammocks — and can be removed and used as mobile outdoor chairs.
Perhaps the most interesting feature is the inclusion of five rotorless electrically operated drones, which serve a variety of purposes. The drones, which have matrix LED lighting, can dock on the roof to get more power with the inductive charging elements.
Audi calls these drones Audi Light Pathfinders because of their ability to fly and illuminate the path ahead. These drones, Audi says replace headlights altogether. When the vehicle is parked, the drones can be used ti light up the surrounding area.
Occupants control the drones through their smartphones in this theoretical use case. The on-board cameras can generate a video image that can be transmitted to the display in front of the driver via Wi-Fi, turning the Pathfinders into “eyes in the sky,” Audi says.
Policing hate speech is something nearly every online communication platform struggles with. Because to police it, you must detect it; and to detect it, you must understand it. Hatebase is a company that has made understanding hate speech its primary mission, and it provides that understanding as a service — an increasingly valuable one.
Essentially Hatebase analyzes language use on the web, structures and contextualizes the resulting data, and sells (or provides) the resulting database to companies and researchers that don’t have the expertise to do this themselves.
The Canadian company, a small but growing operation, emerged out of research at the Sentinel Project into predicting and preventing atrocities based on analyzing the language used in a conflict-ridden region.
“What Sentinel discovered was that hate speech tends to precede escalation of these conflicts,” explained Timothy Quinn, founder and CEO of Hatebase. “I partnered with them to build Hatebase as a pilot project — basically a lexicon of multilingual hate speech. What surprised us was that a lot of other NGOs [non-governmental organizations] started using our data for the same purpose. Then we started getting a lot of commercial entities using our data. So last year we decided to spin it out as a startup.”
You might be thinking, “what’s so hard about detecting a handful ethnic slurs and hateful phrases?” And sure, anyone can tell you (perhaps reluctantly) the most common slurs and offensive things to say — in their language… that they know of. There’s much more to hate speech than just a couple ugly words. It’s an entire genre of slang, and the slang of a single language would fill a dictionary. What about the slang of all languages?
As Victor Hugo pointed out in Les Miserables, slang (or “argot” in French) is the most mutable part of any language. These words can be “solitary, barbarous, sometimes hideous words… Argot, being the idiom of corruption, is easily corrupted. Moreover, as it always seeks disguise so soon as it perceives it is understood, it transforms itself.”
Not only is slang and hate speech voluminous, but it is ever-shifting. So the task of cataloguing it is a continuous one.
Hatebase uses a combination of human and automated processes to scrape the public web for uses of hate-related terms. “We go out to a bunch of sources — the biggest, as you might imagine, is Twitter — and we pull it all in and turn it over to Hatebrain. It’s a natural language program that goes through the post and returns true, false, or unknown.”
True means it’s pretty sure it’s hate speech — as you can imagine, there are plenty of examples of this. False means no, of course. And unknown means it can’t be sure; perhaps it’s sarcasm, or academic chatter about a phrase, or someone using a word who belongs to the group and is attempting to reclaim it or rebuke others who use it. Those are the values that go out via the API, and users can choose to look up more information or context in the larger database, including location, frequency, level of offensiveness, and so on. With that kind of data you can understand global trends, correlate activity with other events, or simply keep abreast of the fast-moving world of ethnic slurs.
Hate speech being flagged all around the world — these were a handful detected today, along with the latitude and longitude of the IP they came from.
Quinn doesn’t pretend the process is magical or perfect, though. “There are very few 100 percents coming out of Hatebrain,” he explained. “It varies a little from the machine learning approach others use. ML is great when you have an unambiguous training set, but with human speech, and hate speech, which can be so nuanced, that’s when you get bias floating in. We just don’t have a massive corpus of hate speech, because no one can agree on what hate speech is.”
That’s part of the problem faced by companies like Google, Twitter, and Facebook — you can’t automate what can’t be automatically understood.
Fortunately Hatebrain also employs human intelligence, in the form of a corps of volunteers and partners who authenticate, adjudicate, and aggregate the more ambiguous data points.
“We have a bunch of NGOs that partner with us in linguistically diverse regions around the world, and we just launched our ‘citizen linguists’ program, which is a volunteer arm of our company, and they’re constantly updating and approving and cleaning up definitions,” Quinn said. “We place a high degree of authenticity on the data they provide us.”
That local perspective can be crucial for understanding the context of a word. He gave the example of a word in Nigeria, which when used between members of one group means friend, but when used by that group to refer to someone else means uneducated. It’s unlikely anyone but a Nigerian would be able to tell you that. Currently Hatebase covers 95 languages in 200 countries, and they’re adding to that all the time.
Furthermore there are “intensifiers,” words or phrases that are not offensive on their own but serve to indicate whether someone is emphasizing the slur or phrase. Other factors enter into it too, some of which a natural language engine may not be able to recognize because it has so little data concerning them. So in addition to keeping definitions up to date, the team is also constantly working on improving the parameters used to categorize speech Hatebrain encounters.
The system just ingested its millionth hate speech sighting (out of perhaps tens times that many phrases evaluated), which sounds simultaneously like a lot and a little. It’s a little because the volume of speech on the internet is so vast that one rather expects even the tiny proportion of it constituting hate speech to add up to millions and millions.
But it’s a lot because no one else has put together a database of this size and quality. A vetted, million-data-point set of words and phrases classified as hate speech or not hate speech is a valuable commodity all on its own. That’s why Hatebase provides it for free to researchers and institutions using it for humanitarian or scientific purposes.
But companies and larger organizations looking to outsource hate speech detection for moderation purposes pay a license fee, which keeps the lights on and allows the free tier to exist.
“We’ve got, I think, four of the world’s ten largest social networks pulling our data. We’ve got the UN pulling data, NGOs, the hyper local ones working in conflict areas. We’ve been pulling data for the LAPD for the last couple years. And we’re increasingly talking to government departments,” Quinn said.
They have a number of commercial clients, many of which are under NDA, Quinn noted, but the most recent to join up did so publicly, and that’s TikTok. As you can imagine, a popular platform like that has a great need for quick, accurate moderation.
In fact it’s something of a crisis, since there are laws coming into play that penalize companies enormous amounts if they don’t promptly remove offending content. That kind of threat really loosens the purse strings; If a fine could be in the tens of millions of dollars, paying a significant fraction of that for a service like Hatebase’s is a good investment.
“These big online ecosystems need to get this stuff off their platforms, and they need to automate a certain percentage of their content moderation,” Quinn said. “We don’t ever think we’ll be able to get rid of human moderation, that’s a ridiculous and unachievable goal; What we want to do is help automation that’s already in place. It’s increasingly unrealistic that every online community under the sun is going to build up their own massive database of multilingual hate speech, their own AI. The same way companies don’t have their own mail server any more, they use Gmail, or they don’t have server rooms, they use AWS — that’s our model, we call ourselves hate speech as a service. About half of us love that term, half don’t, but that really is our model.”
Hatebase’s commercial clients have made the company profitable from day one, but they’re “not rolling in cash by any means.”
“We were nonprofit until we spun out, and we’re not walking away from that, but we wanted to be self-funding,” Quinn said. Relying on the kindness of rich strangers is no way to stay in business, after all. The company is hiring and investing in its infrastructure, but Quinn indicated that they’re not looking to juice growth or anything — just make sure the jobs that need doing have someone to do them.
In the meantime it seems clear to Quinn and everyone else that this kind of information has real value, though it’s rarely simple.
“It’s a really, it’s a really complicated problem. We always grapple with it, you know, in terms of, well, what role does hate speech play? What role does misinformation play? What role do socioeconomics play?” he said. “There’s a great paper that came out of the University of Warwick, they studied the correlation between hate speech and violence against immigrants in Germany over, I want to say, 2015 to 2017. They graph it out. And its peak for peak, you know, valid for Valley. It’s amazing. We don’t do a hell of a lot of analysis — we’re a data provider.”
“But now have like, almost 300 universities pulling the data, and they do those kinds of those kinds of analyses. So that’s very validating for us.”
Caper wants to deliver a major update to the self checkout aisle without keeping its dreaded catchphrases, i.e. “Unknown item in the bagging area,” “Please place the item in the bag.”
The New York startup is tapping some of Silicon Valley’s more recognizable VC firms to fund their dreams for a shopping cart of the future that uses computer vision and other sensors to let shoppers quickly scan items as they drop them into their carts.
The company is announcing that they’ve closed a $10 million Series A led by Lux Capital. The round also saw participation from First Round Capital, Y Combinator, Hardware Club, FundersClub, Sidekick Fund and Red Apple Group.
Caper closed its $2.15 million seed round led by First Round earlier this year. The startup has now raised $13 million to date. The startup’s leadership plans to use the capital to bring their smart grocery carts to more locations.
The startup says its tech could help grocery store chains bring more seamless checkout processes to customers as the groups aim to keep pace with Amazon which has doubled down on physical retail automation with its Amazon Go convenience stores.
While Amazon’s small stores rely on a complex web of cameras and sensors tracking your purchase habits, Caper’s solution is more insular focusing only on what’s happening inside a shopper’s cart.
“Instead of monitoring an entire store, we’re monitoring this very small cart. Our computation is faster, our cameras are a lot closer and we’re able to scale much faster because we don’t need to implement any infrastructure inside the store,” Yang tells TechCrunch.
The company declined to detail exactly how pricey these carts were for a store. When asked whether rollouts would costs “thousands, tens of thousands or hundreds of thousands of dollars,” Yang told TechCrunch that a full rollout at a grocery store would “probably be within the hundreds of thousands range though it could be less.”
Alternatively, Bloomberg reported that the Seattle’s first Amazon Go store required $1 million worth of hardware.
Caper isn’t expecting physical retailers to go all-in and toss out their old-school grocery carts when they become customers. Part of Caper’s advantage is that it doesn’t alienate customers who don’t want to bring AI into their process, those people can just grab an old cart and check out the regular way if the don’t feel like pushing around a computer.
The credit card reader, barcode scanner and image recognition cameras are just a slice of the sell for investors backing Caper. It’s less about streamlining checkout than it is finding a new way to bring AI-driven online retail conventions into physical stores. Personalized recommendations, shopping lists and recipes could eventually find their way onto the built-in touchscreen, Yang says.
“Our vision is ultimately to build a platform layer on retail that never existed before.”
As the antitrust investigations stack up on US tech giants’ home turf there’s no sign of pressure letting up across the pond.
European Commission president-elect Ursula von der Leyen today unveiled her picks for the next team of commissioners who will take up their mandates on November 1 — giving an expanded role to competition commissioner Margrethe Vestager. The pick suggests the next Commission is preparing to dial up its scrutiny of big tech’s data monopolies.
Under the draft list of commissioners-designate, which still needs to be approved in full by the European Parliament, Vestager has been named executive VP overseeing a new portfolio called ‘Europe fit for the digital age’.
But, crucially, she will also retain the competition portfolio — which implies attention on growing Europe’s digital economy will go hand in glove with scrutiny of fairness in ecommerce and ensuring a level playing field vs US platform giants.
“Executive vice-president Margrethe Vestager will lead our work on a Europe fit for the digital age,” said von der Leyen at a press conference to announce her picks. “Digitalization has a huge impact on the way we live, we work, we communicate. In some fields Europe has to catch up — for example in the field of business to consumer but in other fields we’re excellent. Europe is the frontrunner, for example in business to business, when we talk about digital twins of products and procedures.
“We have to make more out of the field of artificial intelligence. We have to make our single market a digital single market. We have to use way more the big data that is out there but we don’t make enough out of it. What innovation and startups are concerned. It’s not only need to know but it’s need to share big data. We have to improve on cyber security. We have to work hard on our technological sovereignty just to name a few issues in these broad topics.
“Margrethe Vestager will co-ordinate the whole agenda. And be the commissioner for competition. She will work together with the commissioner for internal market, innovation and youth, transport, energy, jobs, health and justice.”
If tech giants were hoping for Europe’s next Commission to pay a little less attention to question marks hanging over the fairness of their practices they’re likely to be disappointed as Vestager is set to gain expanded powers and a broader canvas to paint on. The new role clearly positions her to act on the review of competition policy she instigated towards the end of her current mandate — which focused on the challenges posed by digital markets.
Since taking over as Europe’s competition chief back in 2014, Vestager has made a name for herself by blowing the dust off the brief and driving forward on a series of regulatory interventions targeting tech giants including Amazon, Apple and Google . In the latter case this has included opening a series of fresh probes as well as nailing the very long running Google Shopping saga inherited from her predecessor.
The activity of the department under her mandate has clearly catalyzed complainants — creating a pipeline of cases for her to tackle.
Just last month Reuters reported she had been preparing an “intensive” handover of work looking into complaints against Google’s job search product to her successor — a handover that won’t now be necessary, assuming the EU parliament gives its backing to von der Leyen’s team.
While the competition commissioner has thus far generated the biggest headlines for the size of antitrust fines she’s handed down — including a record-breaking $5BN fine for Google last year for illegal restrictions attached to Android — her attention on big data holdings as a competition risk is most likely to worry tech giants going forward.
See, for example, the formal investigation of Amazon’s use of merchant data announced this summer for a sign of the direction of travel.
Vestager has also talked publicly about regulating data flows as being a more savvy route to control big tech versus swinging a break up hammer. And while — on the surface — regulating data might sound less radical a remedy than breaking giants like Google and Facebook up, placing hard limits on how data can be used has the potential to effect structural separation via a sort of regulatory keyhole surgery that’s likely to be quicker and implies a precision that may also make it more politically palatable.
That’s important given the ongoing EU-US trade friction kicked up by the Trump administration which is never shy of lashing out, especially at European interventions that seek to address some of the inequalities generated by tech giants — most recently Trump gave France’s digital tax plans a tongue-lashing.
von der Leyen was asked during the press conference whether Vestager might not been seen as a controversial choice given Trump’s views of her activity to date (Europe’s “tax lady” is one of the nicer things he’s said about Vestager). The EU president-elect dismissed the point saying the only thing that matters in assigning Commission portfolios is “quality and excellence”, adding that competition and digital is the perfect combination to make the most of Vestager’s talents.
“Vestager has done an outstanding job as a commissioner for competition,” she went on. “At competition and the issues she’s tackling there are closely linked to the digital sector too. So having her as an executive vice-president for the digital in Europe is absolutely a perfect combination.
“She’ll have this topic as a cross-cutting topic. She’ll have to work on the Digital Single Market. She will work on the fact that we want to use in a better way big data that is out there, that we collect every day — non-personalized data. That we should use way better, in the need for example to share with others for innovation, for startups, for new ideas.
“She will work on the whole topic of cyber security. Which is the more we’re digitalized, the more we’re vulnerable. So there’s a huge field in front of her. And as she’s shown excellence in the Commission portfolio she’ll keep that — the executive vice-presidents have with the DGs muscles to deal with their vast portfolios’ subject they have to deal with.”
In other choices announced today, the current commissioner for Digital Economy and Society, Mariya Gabriel, will be taking up a new portfolio called ‘Innovation and Youth’. And Sylvie Goulard was named as ‘Internal Market’ commissioner, leading on industrial policy and promoting the Digital Single Market, as well as getting responsibility for Defence Industry and Space.
Another executive VP choice, Valdis Dombrovskis, looks likely to be tackling thorny digital taxation issues — with responsibility for co-ordinating the Commission’s work on what’s been dubbed an “Economy that Works for People”, as well as also being commissioner for financial services.
In prepared remarks on that role, von der Leyen said: “We have a unique social market economy. It is the source of our prosperity and social fairness. This is all the more important when we face a twin transition: climate and digital. Valdis Dombrovskis will lead our work to bring together the social and the market in our economy.”
Frans Timmermans, who was previously in the running as a possible candidate for Commission president but lost out to von der Leyen, is another exec VP pick. He be focused on delivering a European Green Deal and managing climate action policy.
Another familiar face — current justice, consumer and gender affairs commissioner Věra Jourová — has also been named as an exec VP, gaining responsibility for “Values and Transparency” which suggests she’ll continue to be involved in EU efforts to combat online disinformation on platforms.
The rest of the Commission portfolio appointments can be found here.
There are 26 picks in all — 27 counting von der Leyen who has already been confirmed as president; one per EU country, with the UK having no representation in the next Commission given it is due to leave the bloc on October 31, the day before the new Commission takes up its mandate.
von der Leyen touted the team she presented today as balanced and diverse, including on gender lines as well as geographically to take account of the full span of European Union members.
“It draws on all the strength and talents, men and women, experienced and young, east and west, south and north, a team that is well balanced, a team that brings together diversity of experience and competence,” she said. “I want a Commission that is led with determination, that is clearly focused on the issues at hand — and that provides answers.”
“There’s one fundamental that connects this team: We want to bring new impetus to Europe’s democracy,” she added. “This is our joint responsibility. And democracy is more than voting in elections in every five years; it is about having your voice heard. It’s about having been able to participate in the way our society’s built. We gave to address some of the deeper issues in our society that have led to a loss of faith in democracy.”
In a signal of her intention that the new Commission should “walk the talk” on making Europe fit for the digital age she announced that college meetings will be paperless and digital.
On lawmaking, she added that there will be a one-in, one-out policy — with any new laws and regulation supplanting an existing rule in a bid to cut red tape.
Fifty attorneys general are pushing forward with an antitrust investigation against Google, led by the Texas state attorney general, Ken Paxton.
In an announcement on the steps of the U.S. Supreme Court building, Paxton and a gathering of attorneys general said that the focus of the investigation would be on Google’s advertising practices, but that other points of inquiry could be included in the investigation.
The investigation into Google comes as big technology companies find themselves increasingly under the regulatory microscope for everything from anticompetitive business practices to violations of users’ privacy and security to accusations of political bias.
Last week, the New York state attorney general launched an investigation into Facebook.
“Google’s control over nearly every aspect of our lives has placed the company at the center of our digital economy. But it doesn’t take a search engine to understand that unchecked corporate power shouldn’t eclipse consumers’ rights,” said New York Attorney General Letitia James, in a statement. “That is why New York has joined this bipartisan investigation of Google to determine whether the company has achieved or maintained its dominance through anticompetitive conduct. As with the Facebook investigation we are leading, we will use every investigative tool at our disposal in the Google investigation to ensure the truth is exposed.”
For those trying to keep score on antitrust:
The FTC is investigating Facebook.
The Department of Justice is investigating Apple, Google and Amazon.
The DoJ is also investigating ALL of Big Tech.
State attorneys general set to announce inquiry expected to focus on Google
— Jeremy C. Owens (@jowens510) September 9, 2019
Ad platforms create equal opportunities for businesses but not equal outcomes.
They’re mostly marketed as self-service and easy to use, however, there are new features added regularly and open-ended ways to set, structure and target. Meaning, countless ways to spend—creating winners and losers in advertising.
This is where machines and digital advertisers are needed, to provide a profitable outcome.
Enter AI, ML and experts as freelancers, via agencies or housed in some of the world’s biggest companies, equipped with ample data, tech and educational resources to match people with companies via ads on search, social, and elsewhere on the web.
But, are the machines still in infancy or too heavily relied upon and do the experts always get it right?
Well, how often are you seeing ads that are irrelevant to what you wanted or where you were or who you are?
An irrelevant ad is an ad paid for by the company advertising but can return zero value as it’s of no use to the person receiving the ad.
As a digital advertiser via my company Adboy.com, I’m always curious as to why I was served an ad and if the company paying makes or loses money from it.
Something I’ve noticed is that in easily avoidable errors, ads can be served to existing customers, people with irrelevant needs and people that can’t be or are far less likely to become customers.
With this article, I’m going to give you the lenses of a fastidious digital advertiser. You’ll spot errors like these for yourself and know how they could occur, what the negative impact could be and how they can be avoided.