Twitter finally shuts down its abandoned prototype app twttr

Twitter is shutting down its experimental app twttr, which the company had used publicly prototype new features back in 2019. The app was first introduced at the Consumer Electronics Show in January 2019, then launched to testers that March. Its primary focus had been on trying out new designs for threaded conversations, including things like how to branch replies, apply labels and color-code responses, among other things. Some of those tests eventually turned into Twitter features and the twttr app was no longer being used.

The idea to design in public was an interesting experiment by Twitter.

Most companies roll out internal beta tests, followed by smaller-scale A/B tests to a percentage of their public user base to get feedback about new ideas. But with twttr, the company actually invited its users to be a part of the much earlier stage development process.

The concept for twttr had been spearheaded by Twitter’s then Director of Product Management, Sara Beykpour (then Sara Haider — she and Twitter Product Lead Kayvon Beykpour have since married). But Sara announced last year she would be stepping into a new role at the company and Twitter’s new product director in charge of conversations would be Suzanne Xie, who had joined by way of Twitter’s acquisition of Lightwell.

Work on twttr appeared to stop around the time Xie stepped in, as no other significant updates were released to twttr’s TestFlight user base. And Xie left Twitter this fall for Stripe.

Now, it seems that maintaining the largely unused app no longer makes sense for the company.

We appreciate the feedback you gave us through this run of our prototype app twttr. For now we’re turning it off so we can work on new tests to improve the conversation experience on Twitter.

If you’re using twttr, switch to the main Twitter app to keep up with what’s happening. https://t.co/xq4emx9HeH

— Twitter Support (@TwitterSupport) December 3, 2020

Twitter announced its plans to formally shut down twttr today, saying it was turning off the app in order to work on new tests related to the conversation taking place on Twitter itself. The shutdown appears to be immediate. Though the app may still function for those who have it installed, when the TestFlight build expires in 26 days, that may no longer be the case.

It’s not likely that twttr had many dedicated users at this point, especially as the app lacked Twitter’s newer features like Topics and Fleets, for example, and was no longer offering new experiments to test.

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Boost ROI with intent data and personalized multichannel marketing campaigns

Coronavirus is causing large and small businesses to drastically cut marketing budgets. In Forrester’s self-described “most optimistic scenario,” the analysts project a 28% drop in U.S. marketing spend by the end of 2021. Even Google is cutting its marketing budget in half. As marketers move forward, Forrester predicts marketing automation platforms will grow despite an overall decline in marketing technology investment.

Automation platforms help marketers scale their communications. However, scaling communications is not a substitute for intimacy, which all humans crave. Because of the pandemic, it is harder than ever to get attention, let alone make a connection. More mass email blasts from your marketing automation platform are not going to get you the connections with prospects you crave. So how should marketers proceed? Direct mail captures 100% of your audience’s attention. It provides a sensory experience for your prospects and customers, and that helps establish an emotional connection.

Winning marketers are strategically merging automation and digital data with the more intimate channel of direct mail. We call this tactile marketing automation (TMA).

TMA is the integration of direct mail or personalized swag with a marketing automation platform. With TMA, a marketer doesn’t have to think about creating direct mail campaigns outside of digital campaigns. Rather, direct mail experiences are already fully integrated into the pre-built customer journey.

TMA uses intent data to inform content, messaging and the timing of direct mail touchpoints that maximize relevancy and scalability. Multichannel campaigns including direct mail report an ROI 18 percentage points higher than those without direct mail. Plus, 84% of marketers state direct mail improves multichannel campaign performance.

Read on to see how you can merge digital communications and direct mail to deliver remarkable experiences that spark a connection.

Incorporate intent data

Personalization is a key ingredient of a remarkable experience. Many marketers automate processes by introducing marketing software and then call it personalization. But, oftentimes it’s just quicker batching and blasting. Brands can’t just change the first name on a piece of content and call it “personalized.” Real personalization is necessary and vital for real results. Our consumers expect more. The best way to introduce real personalization within a marketing mix is to use intent data and trigger-driven campaigns.

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Space startup Aevum debuts world’s first fully autonomous orbital rocket launching drone

Launching things to space doesn’t have to mean firing a large rocket vertically using massive amounts of rocket-fuel powered thrust – startup Aevum breaks the mould in multiple ways, with an innovative launch vehicle design that combines uncrewed aircraft with horizontal take-off and landing capabilities, with a secondary stage that deploys at high altitude and can take small payloads the rest of the way to space.

Aevum’s model actually isn’t breaking much new ground in terms of its foundational technology, according to founder and CEO Jay Skylus, who I spoke to prior to today’s official unveiling of the startup’s Ravn X launch vehicle. Skylus, who previously worked for a range of space industry household names and startups including NASA, Boeing, Moon Express and Firefly, told me that the startup has focused primarily on making the most of existing available technologies to create a mostly reusable, fully automated small payload orbital delivery system.

To his point, Ravn X doesn’t look too dissimilar from existing jet aircraft, and bears obvious resemblance to the Predator line of UAVs already in use for terrestrial uncrewed flight. The vehicle is 80 feet long, and has a 60-foot wingspan, with a total max weight of 55,000 lbs including payload. 70% of the system is fully reusable today, and Skylus says that the goal is to iterate on that to the point where 95% of the launch system will be reusable in the relatively near future.

Image Credits: Aevum

Ravn X’s delivery system is design for rapid response delivery, and is able to get small satellites to orbit in as little as 180 minutes – with the capability of having it ready to fly and deliver another again fairly shortly after that. It uses traditional jet fuel, the same kind used on commercial airliners, and it can take off and land in “virtually any weather,” according to Skylus. It also takes off and lands on any 1-mile stretch of traditional aircraft runway, meaning it can theoretically use just about any active airport in the world as a launch and landing site.

One of they key defining differences of Aevum relative to other space launch startups is that what they’re presenting isn’t theoretical, or in development – the Ravn X already has paying customers, including over $1 billion in U.S. government contracts. It’s first mission is with the U.S. Space Force, the ASLON-45 small satellite launch mission (set for late 2021), and it also has a contract for 20 missions spanning 9 years with the U.S. Air Force Space and Missile Systems Center.  Deliveries of Aevum’s production launch vehicles to its customers have already begun, in fact, Skylus says.

The U.S. Department of Defense has been actively pursuing space launch options that provide it with responsive, short turnaround launch capabilities for quite some time now. That’s the same goal that companies like Astra, which was originally looking to win the DARPA challenge for such systems (since expired) with its Rocket small launcher. Aevum’s system has the added advantage of being essentially fully compatible with existing airfield infrastructure – and also of not requiring that human pilots be involved or at risk at all, as they are with the superficially similar launch model espoused by Virgin Orbit.

Astra targets December for next orbital launch attempt

Aevum isn’t just providing the Ravn X launcher, either; its goal is to handle end-to-end logistics for launch services, including payload transportation and integration, which are parts of the process that Skylus says are often overlooked or underserved by existing launch providers, and that many companies creating payloads also don’t realize are costly, complicated and time-consuming parts of actually delivering a working small satellite to orbit. The startup also isn’t “re-inventing the wheel” when it comes to its integration services – Skylus says they’re working with a range of existing partners who all already have proven experience doing this work but who haven’t previously had the motivation or the need to provide these kinds of services to the customers that Skylum sees coming online, both in the public and private sector.

The need isn’t for another SpaceX, Skylus says; rather, thanks to SpaceX, there’s a wealth of aerospace companies who previously worked almost exclusively with large government contracts and the one or two massive legacy rocket companies to put missions together. They’re now open to working with the greatly expanded market for orbital payloads, including small satellites that aim to provide cost-effective solutions in communications, environmental monitor, shipping and defense.

Aevum’s solution definitely sounds like it addresses a clear and present need, in a way that offers benefits in terms of risk profile, reusability, cost and flexibility. The company’s first active missions will obviously be watched closely, by potential customers and competitors alike.

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ANYbotics, Swiss company behind quadrupedal ANYmal robot, announces $20M A round

ANYbotics, the creators of ANYmal, a four-legged autonomous robot platform intended for a variety of industrial uses, has raised a $22.3 million Swiss Franc (~$20 million) round A to continue developing and scaling the business. With similar robots just beginning to break into the mainstream, the market seems ready to take off.

The company spun out of ETH Zurich in 2016, at which point the robot was already well into development. ANYmal is superficially similar to Spot, the familiar quadrupedal robot from Boston Dynamics, but the comparison mustn’t be taken too far. A four-legged robot is a natural form for navigating and interacting with environments built for humans.

ANYbotics is on the third generation of the robot, which has progressively integrated computing units and sensors of increasing sophistication.

“Our current ANYmal C model features three built-in high-end Intel i7 computers that power the robot and customer-applications such as automated inspection tasks,” explained co-founder and CEO Péter Fankhauser in an email to TechCrunch. “The availability of smaller and more performant sensors, propelled by AR/VR and autonomous driving applications, has enabled us to equip the latest ANYmal model with 360-degree situational awareness and long-range scanning capabilities. Where commercially available components are not satisfactory, we invest in our proprietary technologies, which have resulted in core components such as custom motors, docking stations, and inspection payload units.”

Watch the ANYmal quadrupedal robot go for an adventure in the sewers of Zurich

The most obvious application for robots like ANYmal is inspection of facilities that would normally involve a human. If a robot can traverse the same paths, climb stairs, open doors and so on, it can do so more frequently and regularly than its human counterparts, who tire and take breaks. It also can monitor and relay its surroundings in detail, using lidar and RGB cameras, among other tools. Humans can then perform the more difficult (and human) work of integrating that information and making decisions based on it. An ANYmal at a factory, power plant, or data center could save costs and shoe leather.

Of course, that’s no use if the bot is fragile; fortunately, that’s not the case.

“In terms of mobility, we have focused on what matters most to our industrial customers: Operational reliability and robustness to harsh environmental conditions,” Fankhauser said. “For example, we design and test ANYmal for day and night usage in indoor and outdoor locations, including offshore platforms with salty air and large temperature ranges. It’s less about agility in these environments but more about reliably and safely performing the tasks multiple times a day over many months without human intervention.”

Swisscom Ventures leads the round, and partner Alexander Schläpfer said that good roots (ETHZ is of course highly respected) and good results from early commercial partnerships more than justified their investment.

“Over 10 years ago, some of our co-founders developed their first walking robots during their studies at ETH Zurich,” said Fankhauser. “Today, the industries are ready to adopt this technology, and we are deploying our robots to our early customers.”

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Find out how startups like Skyroot and Bluefield are building new industries at TC Sessions: Space 2020

At our fast-approaching first TC Sessions: Space event, which is happening December 16-17, we’re going to be highlighting some of the most exciting startups and founders tackling big problems with innovative and groundbreaking solutions.

Some of those companies are focused on building tomorrow’s spacecraft, and others are working on in-space technologies that could become the next big anchor upon which countless other businesses are built.

Two of the companies joining us at TC Sessions: Space are Skyroot and Bluefield. Skyroot is India’s first private space launch startup, founded in 2018 with the goal of developing a low-cost and reliable launch vehicle to help democratize access of space.

More panels from TC Sessions: Space

• Lockheed Martin VP Lisa Callahan
• Rocket Lab’s Peter Beck
• US Space Force Lt. General John F. Thompson
• Will Roper, Assistant Secretary, Air Force
• NASA’s head of human spaceflight, Kathryn Lueders
• Read the agenda

Founder, CEO and CTO Pawan Kumar Chandana will join us to talk about building his new business, his prior experience developing rockets for the Indian Space Research Organization (ISRO) and how Skyroot’s Vikram-series launch vehicles plan to achieve the company’s ambitious goals.

Bluefield Technologies is focused on an entirely different, but potentially just as impactful opportunity: Observation, monitoring and analysis of methane emissions data on Earth. Their satellite-based methane observation technology offer a new high bar of precision and detail.

Bluefield founder and CEO Yotam Ariel will join us to talk about what becomes possible across a range of industries once you offer them the ability to track up to 90% of the Earth’s methane emissions with pinpoint accuracy, at costs that are up to 100 percent cheaper than existing solutions on up to a daily basis.

We’ll have conversations with Chandana, Ariel and others as part of our ‘Founders in Focus’ series, just one small part of the all-star agenda at TC Sessions: Space. Tickets are still available at the Late Registration price with discounts for students, government/military employees and groups, so grab yours below to attend this fully virtual event.

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VCs who want better outcomes should use data to reduce founder team risk

Janneke Niessen Contributor

Janneke Niessen is a partner at CapitalT, a serial entrepreneur and a tech diversity advocate.

VCs expect the companies they invest in to use data to improve their decision-making. So why aren’t they doing that when evaluating startup teams?

Sure, venture capital is a people business, and the power of gut feeling is real. But using an objective, data-backed process to evaluate teams — the same way we do when evaluating financial KPIs, product, timing and market opportunities — will help us make better investment decisions, avoid costly mistakes and discover opportunities we might have otherwise overlooked.

An objective assessment process will also help investors break free from patterns and back someone other than a white male for a change. Is looking at how we have always done things the best way to build for the future?

Sixty percent of startups fail because of problems with the team. Instinct matters, but a team is too big a risk to leave to intuition. I will use myself as an example. I have founded two companies. I know what it takes to build a company and to achieve a successful exit. I like to think I can sense when someone has that special something and when a team has chemistry. But I am human. I am limited by bias and thought patterns; data is not.

You can (and should) take a scientific approach to evaluating a startup team. A “strong” team isn’t a vague concept — extensive research confirms what it takes to execute a vision. Despite what people expect, soft skills can be measured. VCVolt is a computerized selection model that analyzes the performance of companies and founding teams developed by Eva de Mol, Ph.D., my partner at CapitalT.

We use it to inform every investment decision we make and to demystify a common hurdle to entrepreneurial success. (The technology also evaluates the company, market opportunity, timing and other factors, but since most investors aren’t taking a structured, data-backed approach to analyzing teams, let’s focus on that.)

VCVolt allows us to reduce team risk early on in the selection and due diligence process, thereby reducing confirmation bias and fail rates, discovering more winning teams and driving higher returns.

I will keep this story brief for privacy reasons, but you will get the point. While testing the model, we advised another VC firm not to move forward with an investment based on the model’s findings. The firm moved forward anyway because they were in love with the deal, and everything the model predicted transpired. It was a big loss for the investors, and a reminder that hunch and gut feeling can be wrong — or at least blind you to some serious risk factors.

The platform uses a validated model that is based on more than five years of scientific research, data from more than 1,000 companies and input from world-class experts and scientists. Its predictive validity is noted in top-tier scientific journals and other publications, including Harvard Business Review. By asking the right questions — science-based questions validated by more than 80,000 datapoints — the platform analyzes the likelihood that a team will succeed. It considers:

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Taking on the business scenario-planning giants, Pigment raises a $25.9M Series A led by Blossom Capital

Realizing that modern, complex businesses can no longer be adequately managed using spreadsheet-style programs, the founders of Pigment decided there had to be a better solution. Their business forecasting platform has now raised a substantial Series A of $25.9 million, led by Blossom Capital. Also participating was New York-based FirstMark Capital and Frst, as well as angel investors including Paul Melchiorre, former CEO of business planning giant Anaplan, and David Clarke, the ex-CTO of Workday, another business planning incumbent.

Those last two investors are significant because Paris-based Pigment competes with both Anaplan and Workday. Also of note is the fact that another planning product, Adaptive Insights, was sold to Workday for $1.6bn.

Pigment has so far secured large-scale enterprise and pre-IPO start-up clients for its beta product, including a major European bank – although it declines to name any of its clients so far.

Pigment says it aims to overhaul the painful experience of using error-prone spreadsheets and inflexible software to do business forecast forecasting, instead presenting a dashboard-like approach in real-time through charts, simulations and continuous modeling.

Eléonore Crespo, co-founder and co-CEO of Pigment said in a statement: “We’re a bit like Minecraft for business strategy – with that kind of creative, organic potential for the user. Standard planning solutions are basically mechanical, treating a business like a machine with levers that you just push and pull.”

Ophelia Brown, partner at Blossom Capital, said: ‘Existing planning software was built around 20th-century models of how to do business. Pigment is a 21-st century platform that reflects the way successful companies need to work today – socially and environmentally conscious, proactively scanning the horizon for risks and opportunities, and capable of unlocking new opportunities in an increasingly complex and uncertain world.”

Pigment was founded in 2019 by Crespo, a former data analyst at Google and investor at Index Ventures, and Romain Niccoli, the former CTO and co-founder of Criteo – the ad-tech company which IPO’d on NASDAQ in 2013.

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Portugal’s Bizay — a customized products marketplace for SMBs — just raised a $38.6M C round

Bizay, a marketplace for small-to-medium-sized businesses allowing them to create highly customized products (such as merchandise), has raised a $38.6 million (€32 million) funding round. The Series C financing round was co-led by investors Indico Capital and the European Investment Bank, with “strong support” from Iberis Capital and existing investors including LeadX Capital Partners, Omnes Capital and Pathena.

This means Bizay has now raised a total of more than €54 million. The company previously raised a Series B financing round of €22 million. This new round will accelerate the development of further product expansion targeted at SMBs and reinforce Bizay´s operation supplying more than one million SMBs in 21 countries across Europe and America.

Bizay’s idea is to become the “Amazon” for SMBs in terms of merchandising, packaging, consumables, business essentials, decorations and uniforms, with good quality, at a fraction of the normal costs associated with these items.

Bizay’s Chief of Growth Officer José Salgado, said: “The current health crisis accelerated the shift to online ordering of customizable products at reduced prices. Our platform will be a key facilitator for businesses to recover at a faster pace. We are totally confident in achieving the goals that will allow us to enter a new level of global ambition”.

Speaking to TechCrunch Salgado added: “We are a software company, and our technology enables us to connect to industrial manufacturers that would usually work only for large corporations. We have no stock, we have no machines, no production. Using AI we aggregate multiple orders, and supply those orders using the network of industrial producers that we have in our marketplace. So we are able to offer these SMBs competitive prices for small individual orders. These industrial manufacturers would never normally supply SMBs because they are just too small.”

Stephan Morais, managing general partner at Indico Capital Partners, said: “Bizay is entering a new growth phase and this round will consolidate their presence across Europe and enable them to capture the opportunity that stems from the shift towards online ordering of personalized products for SMBs.”

Portugal’s Faber reaches $24.3M for its second fund aimed at data-driven startups from Iberia

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Android’s winter update adds new features to Gboard, Maps, Books, Nearby Share and more

{rss:content:encoded} Android’s winter update adds new features to Gboard, Maps, Books, Nearby Share and more https://ift.tt/2Jnppof https://ift.tt/37ALWFU December 03, 2020 at 06:00PM

Google announced this morning Android phones will receive an update this winter that will bring some half-dozen new features to devices, including improvements to apps like Gboard, Google Play Books, Voice Access, Google Maps, Android Auto, and Nearby Share. The release is the latest in a series of update bundles that now allow Android devices to receive new features outside of the usual annual update cycle.

The bundles may not deliver Android’s latest flagship features, but they offer steady improvements on a more frequent basis.

One of the more fun bits in the winter update will include a change to “Emoji Kitchen,” the feature in the Gboard keyboard app that lets users combine their favorite emoji to create new ones that can be shared as customized stickers. To date, users have remixed emoji over 3 billion times since the feature launched earlier this year, Google says. Now, the option is being expanded. Instead of offering hundreds of design combinations, it will offer over 14,000. You’ll also be able to tap two emoji to see suggested combinations or double tap on one emoji to see other suggestions.

Image Credits: Google

This updated feature had been live in the Gboard beta app, but will now roll out to Android 6.0 and above devices in the weeks ahead.

Another update will expand audiobook availability on Google Play Books. Now, Google will auto-generate narrations for books that don’t offer an audio version. The company says it worked with publishers in the U.S. and U.K. to add these auto-narrated books to Google Play Books. The feature is in beta but will roll out to all publishers in early 2021.

An accessibility feature that lets people use and navigate their phone with voice commands, Voice Access, will also be improved. The feature will soon leverage machine learning to understand interface labels on devices. This will allow users to refer to things like the “back” and “more” buttons, and many others by name when they are speaking.

The new version of Voice Access, now in beta, will be available to all devices worldwide running Android 6.0 or higher.

An update for Google Maps will add a new feature to one of people’s most-used apps.

In a new (perhaps Waze-inspired) “Go Tab,” users will be able to more quickly navigate to frequently visited places — like a school or grocery store, for example — with a tap. The app will allow users to see directions, live traffic trends, disruptions on the route, and gives an accurate ETA, without having to type in the actual address. Favorite places — or in the case of public transit users, specific routes — can be pinned in the Go Tab for easy access. Transit users will be able to see things like accurate departure and arrival times, alerts from the local transit agency, and an up-to-date ETA.

Image Credits: Google

One potentially helpful use case for this new feature would be to pin both a transit route and driving route to the same destination, then compare their respective ETAs to pick the faster option.

This feature is coming to both Google Maps on Android as well as iOS in the weeks ahead.

Android Auto will expand to more countries over the next few months. Google initially said it would reach 36 countries, but then updated the announcement language as the timing of the rollout was pushed back. The company now isn’t saying how many countries will gain access in the months to follow or which ones, so you’ll need stay tuned for news on that front.

Image Credits: Google

The final change is to Nearby Share, the proximity-based sharing feature that lets users share things like links, files, photos and and more even when they don’t have a cellular or Wi-Fi connection available. The feature, which is largely designed with emerging markets in mind, will now allow users to share apps from Google Play with people around them, too.

To do so, you’ll access a new “Share Apps” menu in “Manage Apps & Games” in the Google Play app. This feature will roll out in the weeks ahead.

Some of these features will begin rolling out today, so you may receive them earlier than a timeframe of several “weeks,” but the progress of each update will vary.

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Food robotics startup Karakuri unveils automated canteen, plus $8.4M investment led by firstminute

Last week I witnessed for myself how a new kind of robot really could — as sci-fi has been telling us for many years — create and serve us food. Today, Karakuri, a food robotics startup, unveils its first automated canteen to make meals: the “DK-One” robot. It’s also revealing an $8.4 million (£6.3 million) investment, led by firstminute capital, which includes funding from Hoxton Ventures, Taylor Brothers, Ocado Group and the U.K.’s government-backed Future Fund. It has now closed a total of £13.5 million in funding.

Karakuri’s robotic system has been initially designed to make breakfast bowls. But the technology will end up being employed in a large array of scenarios, including restaurants, canteens, buffets, hotels and supermarkets. Possibly even tending vertical farms. Its particular strength is in being able to create extremely tailor-made combinations of food, putting “personalized nutrition” within practical reach. Remember those movies where the food is tailored by a robot? That.

The post-COVID world is also highly likely to embrace this technology due to the robot’s inherent cleanliness and efficiency, compared to human-made food. That said, Karakuri is not positioned to replace humans but to augment them, taking on the boring and repetitive tasks which typically see kitchen staff have far more itinerant careers due to the sheer pressure of low-level jobs where a robot would be far more suitable.

The DK-One robot is Karakuri’s first pre-production machine, which uses the latest in robotics, sensing and control technologies. It’s capable of creating high-quality hot and cold meals, which maximize nutritional benefits, restaurant performance and minimize food waste.

Post COVID restrictions, further on-customer-site trials of the DK-One are expected to take place in the first half of 2021.

The DK-One robot zips around a circular enclosure at a rate of knots, each time measuring accurate portion sizes as determined by an app, where the customer can tailor to their tastes. It means anyone ordering something would be able to track the ingredients, nutrients, calories and quantity of literally every meal.

Up to 18 ingredients can be dispensed per installation, with each ingredient temperature controlled. It will dispense of any ingredient type, including wet, dry, soft or hard food onto plates, bowls or a range of meal containers.

Because it’s so accurate it therefore reduces food waste around portions and allows for real-time data on ingredients. The thin margins restaurateurs typically have could be improved by using such a robot in repetitive tasks, and means employees can be tasked with more complex and fruitful and fulfilling work. It’s also easily integrated into existing commercial kitchens.

Barney Wragg, CEO and co-founder of Karakuri, said in a statement: “This will be the first time we can use a pre-production machine to demonstrate the DK-One’s commercial and nutritional benefits in the real world and thus demonstrate our vision for the future of food.”

Karakuri was founded by Simon Watt and Wragg, two longtime friends and colleagues who previously worked together at ARM. In April 2018 the Founders Factory venture studio invested in Karakuri and Brent Hoberman joined the board as chairman (and is also listed as a co-founder).

Robotics startups won’t win without also incorporating AI, as Karakuri’s fundraise shows

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AutoX becomes China’s first to remove safety drivers from robotaxis

Residents of Shenzhen will see truly driverless cars on the road starting Thursday. AutoX, a four-year-old startup backed by Alibaba, MediaTek and Shanghai Motors, is deploying a fleet of 25 unmanned vehicles in downtown Shenzhen, marking the first time any autonomous driving car in China tests on public roads without safety drivers or remote operators.

The cars, meant as robotaxis, are not yet open to the public, an AutoX spokesperson told TechCrunch.

The milestone came just five months after AutoX landed a permit from California to start driverless tests, following in the footsteps of Waymo and Nuro.

It also indicates that China wants to bring its smart driving industry on par with the U.S. Cities from Shenzhen to Shanghai are competing to attract autonomous driving upstarts by clearing regulatory hurdles, touting subsidies and putting up 5G infrastructure.

As a result, each city ends up with its own poster child in the space: AutoX and Deeproute.ai in Shenzhen, Pony.ai and WeRide in Guangzhou, Momenta in Suzhou and Baidu’s Apollo fleet in Beijing, to name a few. The autonomous driving companies, in turn, work closely with traditional carmakers to make their vehicles smarter and more suitable for future transportation.

“We have obtained support from the local government. Shenzhen is making a lot of rapid progress on legislation for self-driving cars,” said the AutoX representative.

The decision to remove drivers from the front and operators from a remote center appears a bold move in one of China’s most populated cities. AutoX equips its vehicles with its proprietary vehicle control unit called XCU, which it claims has faster processing speed and more computational capability to handle the complex road scenarios in China’s cities.

“[The XCU] provides multiple layers of redundancy to handle this kind of situation,” said AutoX when asked how its vehicles will respond should the machines ever go rogue.

The company also stressed the experience it learned from “millions of miles” driven in China’s densest city centers through its 100 robotaxis in the past few years. Its rivals are also aggressively accumulating mileage to train their self-driving algorithms while banking sizable investments to fund R&D and pilot tests. AutoX itself, for instance, has raised more than $160 million to date.

How China’s first autonomous driving unicorn Momenta hunts for data

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iPhones can now automatically recognize and label buttons and UI features for blind users

{rss:content:encoded} iPhones can now automatically recognize and label buttons and UI features for blind users https://ift.tt/3lIOp6w https://ift.tt/2VyfGxI December 03, 2020 at 05:30PM

Apple has always gone out of its way to build features for users with disabilities, and Voiceover on iOS is an invaluable tool for anyone with a vision impairment — assuming every element of the interface has been manually labeled. But the company just unveiled a brand new feature that uses machine learning to identify and label every button, slider, and tab automatically.

Screen Recognition, available now in iOS 14, is a computer vision system that has been trained on thousands of images of apps in use, learning what a button looks like, what icons mean, and so on. Such systems are very flexible — depending on the data you give them, they can become expert at spotting cats, facial expressions, or as in this case the different parts of a user interface.

The result is that in any app now, users can invoke the feature and a fraction of a second later every item on screen will be labeled. And by “every,” they mean every — after all, screen readers need to be aware of every thing that a sighted user would see and be able to interact with, from images (which iOS has been able to create one-sentence summaries of for some time) to common icons (home, back) and context-specific ones like “…” menus that appear just about everywhere.

The idea is not to make manual labeling obsolete — developers know best how to label their own apps, but updates, changing standards, and challenging situations (in-game interfaces, for instance) can lead to things not being as accessible as they could be.

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I chatted with Chris Fleizach from Apple’s iOS accessibility engineering team, and Jeff Bigham from the AI/ML accessibility team, about the origin of this extremely helpful new feature. (It’s described in a paper due to be presented next year.)

“We looked for areas where we can make inroads on accessibility, like image descriptions,” said Fleizach. “In iOS 13 we labeled icons automatically – Screen Recognition takes it another step forward. We can look at the pixels on screen and identify the hierarchy of objects you can interact with, and all of this happens on device within tenths of a second.”

The idea is not a new one, exactly; Bigham mentioned a screen reader, Outspoken, which years ago attempted to use pixel-level data to identify UI elements. But while that system needed precise matches, the fuzzy logic of machine learning systems and the speed of iPhones’ built-in AI accelerators means that Screen Recognition is much more flexible and powerful.

It wouldn’t have been possibly just a couple years ago — the state of machine learning and the lack of a dedicated unit for executing it meant that something like this would have been extremely taxing on the system, taking much longer and probably draining the battery all the while.

But once this kind of system seemed possible, the team got to work prototyping it with the help of their dedicated accessibility staff and testing community.

“VoiceOver has been the standard bearer for vision accessibility for so long. If you look at the steps in development for Screen Recognition, it was grounded in collaboration across teams — Accessibility throughout, our partners in data collection and annotation, AI/ML, and, of course, design. We did this to make sure that our machine learning development continued to push toward an excellent user experience,” said Bigham.

It was done by taking thousands of screenshots of popular apps and games, then manually labeling them as one of several standard UI elements. This labeled data was fed to the machine learning system, which soon became proficient at picking out those same elements on its own.

It’s not as simple as it sounds — as humans, we’ve gotten quite good at understanding the intention of a particular graphic or bit of text, and so often we can navigate even abstract or creatively designed interfaces. It’s not nearly as clear to a machine learning model, and the team had to work with it to create a complex set of rules and hierarchies that ensure the resulting screen reader interpretation makes sense.

The new capability should help make millions of apps more accessible, or just accessible at all, to users with vision impairments. You can turn it on by going to Accessibility settings, then VoiceOver, then VoiceOver Recognition, where you can turn on and off image, screen, and text recognition.

It would not be trivial to bring Screen Recognition over to other platforms, like the Mac, so don’t get your hopes up for that just yet. But the principle is sound, though the model itself is not generalizable to desktop apps, which are very different from mobile ones. Perhaps others will take on that task; the prospect of AI-driven accessibility features is only just beginning to be realized.

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