More than 50% of residential apartments and other real estate properties in Jakarta are currently vacant, according to official estimates. A startup that is attempting to make it easier for tenants to rent these properties…
Last year Adobe, SAP and Microsoft came together and formed the Open Data Initiative. Not to be outdone, this week AWS, Salesforce and Genesys in partnership with The Linux Foundation announced the Cloud Information Model.…
We’re excited to announce a new Extra Crunch community perk from Zendesk. Starting today, annual and two-year Extra Crunch members that are new to Zendesk and located within the U.S. or Canada can receive a…
Freshworks, a company that makes a variety of business software tools from CRM to help desk software, announced a $150 million Series H investment today from Sequoia Capital, CapitalG (formerly Google Capital) and Accel on…
“There is but one truly serious question in philosophy, and that is suicide,” wrote Albert Camus in The Myth of Sisyphus. This is equally true for a human navigating an absurd existence, and an artificial…
Atlassian today announced a set of new templates and workflows for Jira Service Desk that were purpose-built for HR, legal and facilities teams. Service Desk started six years ago as a version of Jira that…
The Daily Crunch is TechCrunch’s roundup of our biggest and most important stories. If you’d like to get this delivered to your inbox every day at around 9am Pacific, you can subscribe here. 1. MacBook…
Google Maps is adding a feature that will make it easier for people traveling in foreign countries where they don’t speak the local language: built-in translation with text-to-speech support. The feature will allow users to…
Volkswagen said Wednesday it will build a battery pack assembly facility as part of an $800 million expansion project that will turn the Chattanooga, Tenn. factory into its North American base for manufacturing electric vehicles.…
More than 50% of residential apartments and other real estate properties in Jakarta are currently vacant, according to official estimates. A startup that is attempting to make it easier for tenants to rent these properties in Jakarta and other places in Indonesia said on Thursday that it has closed a new financing round.
Travelio has raised $18 million in its Series B financing round led by Singapore-based Pavilion Capital and Gobi Partners, the four-year-old startup said. Some existing investors also participated in the round.
The startup works with individual apartment owners and property dealers to allow tenants to find and rent apartments. People can book an apartment for a day to months, Christina Suriadjaja, cofounder and chief strategy officer of Travelio, told TechCrunch in an interview.
Travelio has over 4,000 properties exclusively signed up with the platform, she said. The startup takes between 20% to 35% of the revenue cut from its property owner partners, she explained.
Typically, it would cost a little more than $350 for someone to rent an apartment for a month from Travelio. In Indonesia, currently those looking for an apartment from property dealers and individual owners have to make a down payment of 20% and pay an advanced security deposit for more than a year. Through its pricing structure, Travelio is attempting to address this issue as well.
A number of startups including RedDoorz, Oyo, and Airbnb operate in Indonesia, but because they are focused on providing rooms for a day or two like hotels, this differentiates them from Tavelio. Suriadjaja said Airbnb, which lists properties of Tavelio, is more of a partner than a competitor. “Our competitors are property dealers,” she said.
In addition to offering these fully furnished apartments on rents, Tavelio also takes care of house cleaning and maintenance of these properties.. “In the coming months, we will work on expanding the services we offer,” she said. Some of the services it is exploring include interior design, daily necessities, financing, payments and other logistic-related offerings.
The startup aims to have 20,000 apartments on its platform in one year. “With Indonesia’s rising middle class population, Travelio is well-positioned to serve the growing demand for temporary housing, urbanization and affordable living options,” the startup said.
A recent research report by Google, Temasek and Bain & Co projected that Southeast Asia’s internet economy would top $100 billion this year. Indonesia, home to more than 260 million people, would be the biggest contributor to the internet economy’s growth in the region, the report said.
Last year Adobe, SAP and Microsoft came together and formed the Open Data Initiative. Not to be outdone, this week AWS, Salesforce and Genesys in partnership with The Linux Foundation announced the Cloud Information Model.
The two competing data models have a lot in common. They are both about bringing together data and applying a common open model to it. The idea is to allow for data interoperability across products in the partnership without a lot of heavy lifting, a common problem for users of these big company’s software.
Jim Zemlin, executive director at The Linux Foundation says this project provides a neutral home for the Cloud Information model, where a community can work on the problem. “This allows for anyone across the community to collaborate and provide contributions under a central governance model. It paves the way for full community-wide engagement in data interoperability efforts and standards development, while rapidly increasing adoption rate of the community,” Zemlin explained in a statement.
Each of the companies in the initial partnership is using the model in different ways. AWS will use it conjunction with its AWS Lake Formation tool to help customers move, catalog, store and clean data from a variety of data sources, while Genesys customers can use its cloud and AI products to communicate across a variety of channels.
Patrick Stokes from Salesforce says his company is using the Cloud Information Model as the underlying data model for his company’s Customer 360 platform of products. “We’re super excited to announce that we’ve joined together with a few partners — AWS, Genesys and The Linux Foundation — to actually open source that data model,” Stokes told TechCrunch.
Of course, now we have two competing “open” data models, and it’s going to create some friction until the two competing projects find a way to come together. The fact is that many companies use tools from each of these companies, and if there continues to be these competing approaches, it’s going to defeat the purpose of creating these initiatives in the first place.
As Satya Nadella said in 2015, “It is incumbent upon us, especially those of us who are platform vendors to partner broadly to solve real pain points our customers have.” If that’s the case having competing models is not really achieving that.
We’re excited to announce a new Extra Crunch community perk from Zendesk. Starting today, annual and two-year Extra Crunch members that are new to Zendesk and located within the U.S. or Canada can receive a credit for six months of unlimited licenses for any combination of Zendesk Support, Talk, Chat, Guide and Sell products, for free. Zendesk Talk and Zendesk Sell minutes are not included.
Zendesk is a customer service and engagement platform that creates better experiences for agents, admins and customers. Zendesk’s products are powerful and flexible, and scale to meet the needs of any business. You can learn more about Zendesk here.
In order to qualify for the Zendesk community perk from Extra Crunch, you must meet the following criteria:
Must be an annual or two-year Extra Crunch member. You can sign up here.
Must be located within the U.S. or Canada.
Must be a new customer of Zendesk.
The Zendesk community perk from Extra Crunch is inclusive of subscription fees free for six months, after which you will be responsible for payment. Any downgrades to your Zendesk subscription will result in the forfeiture of the promotion, so please check with Zendesk first regarding any changes (firstname.lastname@example.org). The credit is only available for the Zendesk Support, Talk, Chat, Guide and Sell products.
Extra Crunch is a membership program from TechCrunch that features intelligence on the most disruptive opportunities for startups, how-tos and interviews on company building, an experience on TechCrunch.com that’s free of banner ads, discounts on TechCrunch events and several community perks like the one mentioned in this article. Our goal is to democratize information about startups, and we’d love to have you join our community.
Here’s how the process works. After signing up for an annual or two-year Extra Crunch membership, you’ll receive a welcome email with a link to apply to the Zendesk perk. Apply for the perk via the provided link in the email. Within 48 hours, the Zendesk team will send an email to you with the promo code.
Start a Zendesk Trial, and from inside your Zendesk trial, click the “Buy Now” button. Select your chosen plan and number of product licenses. Don’t forget to use monthly billing.
Enter the promo code that Zendesk provides you, and complete the checkout process.
Zendesk offers a free 15-day trial, and if you are interested in purchasing a plan after the trial you can enter the code to get six months free.
If you are already an annual or two-year Extra Crunch member, you will receive a separate email with the offer at some point in the next 48 hours. If you are currently a monthly Extra Crunch subscriber and want to upgrade to annual in order to claim this deal, head over to the “my account” section on TechCrunch.com and click the “upgrade” button.
If there are other community perks you want to see us add, please let us know by emailing email@example.com. Sign up for an annual Extra Crunch membership today to claim this community perk. You can purchase an annual or two-year Extra Crunch membership here.
Freshworks, a company that makes a variety of business software tools from CRM to help desk software, announced a $150 million Series H investment today from Sequoia Capital, CapitalG (formerly Google Capital) and Accel on a hefty $3.5 billion valuation. The late-stage startup has raised almost $400 million, according to Crunchbase data.
The company has been building an enterprise SaaS platform to give customers a set of integrated business tools, but CEO and co-founder Girish Mathrubootham says they will be investing part of this money in R&D to keep building out the platform.
To that end, the company also announced a new unified data platform today called the “Customer-for-Life Cloud” that runs across all of its it tools. “We are actually investing in really bringing all of this together to create the “Customer-for-Life Cloud,” which is how you take marketing, sales, support and customer success — all of the aspects of a customer across the entire lifecycle journey and bring them to a common data model where a business that is using Freshworks can see the entire lifecycle of the customer,” Mathrubootham explained.
While Mathrubootham was not ready to commit to an IPO, he said that they are in the process of hiring a CFO and are looking ahead to one day becoming a public company. “We don’t have a definite timeline. We want to go public at the right time. We are making sure that as a company that we are ready with the right processes and teams and predictability in the business,” he said.
In addition, he says he will continue to look for good acquisition targets, and having this money in the bank will help the company fill in gaps in the product set should the right opportunity arise. “We don’t generally acquire revenue, but we are looking for good technology teams both in terms of talent, as well as technology that would help give us a jumpstart in terms of go-to-market.” It hasn’t been afraid to target small companies in the past, having acquired 12 already.
Freshworks, which launched in 2010, has almost 2500 employees, a number that’s sure to go up with this new investment. It has 250,00 customers worldwide, including almost 40,000 paying customers. These including Bridgestone Tires, Honda, Hugo Boss, Toshiba and Cisco.
“There is but one truly serious question in philosophy, and that is suicide,” wrote Albert Camus in The Myth of Sisyphus. This is equally true for a human navigating an absurd existence, and an artificial intelligence navigating a morally insoluble situation.
As AI-powered vehicles take the road, questions about their behavior are inevitable — and the escalation to matters of life or death equally so. This curiosity often takes the form of asking whom the car should steer for should it have no choice but to hit one of a variety innocent bystanders. Men? Women? Old people? Young people? Criminals? People with bad credit?
There are a number of reasons this question is a silly one, yet at the same time a deeply important one. But as far as I’m concerned, there is only one real solution that makes sense: when presented with the possibility of taking a life, the car must always first attempt to take its own.
The trolley non-problem
First, let’s get a few things straight about the question we’re attempting to answer.
There is unequivocally an air of contrivance to the situations under discussion. That’s because they’re not plausible real-world situations but mutations of a venerable thought experiment often called the “Trolley Problem.” The most familiar version dates to the ’60s, but versions of it can be found going back to discussions of utilitarianism, and before that in classical philosophy.
The problem goes: A train car is out of control, and it’s going to hit a family of five who are trapped on the tracks. Fortunately, you happen to be standing next to a lever that will divert the car to another track… where there’s only one person. Do you pull the switch? Okay, but what if there are ten people on the first track? What if the person on the second one is your sister? What if they’re terminally ill? If you choose not to act, is that in itself an act, leaving you responsible for those deaths? The possibilities multiply when it’s a car on a street: for example, what if one of the people is crossing against the light — does that make it all their fault? But what if they’re blind?
And so on. It’s a revealing and flexible exercise that makes people (frequently undergrads taking Intro to Philosophy) examine the many questions involved in how we value the lives of others, how we view our own responsibility, and so on.
But it isn’t a good way to create an actionable rule for real-life use.
After all, you don’t see convoluted moral logic on signs at railroad switches instructing operators on an elaborate hierarchy of the values of various lives. This is because the actions and outcomes are a red herring; the point of the exercise is to illustrate the fluidity of our ethical system. There’s no trick to the setup, no secret “correct” answer to calculate. The goal is not even to find an answer, but generate discussion and insight. So while it’s an interesting question, it’s fundamentally a question for humans, and consequently not really one our cars can or should be expected to answer, even with strict rules from its human engineers.
A self-driving car can no more calculate its way out of an ethical conundrum than Sisyphus could have calculated a better path by which to push his boulder up the mountain.
And it must also be acknowledged that these situations are going to be vanishingly rare. Most of the canonical versions of this thought experiment – five people versus one, or a kid and an old person – are so astronomically unlikely to occur that even if we did find a best method that a car should always choose, it’ll only be relevant once every trillion miles driven or so. And who’s to say whether that solution will be the right one in another country, among people with different values, or in ten or twenty years?
No matter how many senses and compute units a car has, it can no more calculate its way out of an ethical conundrum than Sisyphus could have calculated a better path by which to push his boulder up the mountain. The idea is, so to speak, absurd.
We can’t have our cars attempting to solve a moral question that we ourselves can’t. Yet somehow that doesn’t stop us from thinking about it, from wanting an answer. We want to somehow be prepared for the situation even though it may never arise. What’s to be done?
Implicit and explicit trust
The entire self-driving car ecosystem has to be built on trust. That trust will grow over time, but there are two aspects to be considered.
The first is implicit trust. This is the kind of trust we have in the cars we drive today: that despite being one-ton metal missiles propelled by a series of explosions and filled with high octane fuel, they won’t blow up, fail to stop when we hit the brakes, spin out when we turn the wheel, and so on. That we trust the vehicle to do that is the result of years and years of success on the part of car manufacturers. Considering their complexity, cars are among the most reliable machines ever made. That’s been proven in practice and most of the time, we don’t even think of the possibility of the brakes not catching when the pedal is depressed.
You trust your personal missile to work the way you trust a fridge to stay cold. Let’s take a moment to appreciate how amazing that is.
Self-driving cars, however, introduce new factors, unproven ones. Their proponents are correct when they say that autonomous vehicles will revolutionize the road, reduce traffic deaths, shorten commutes, and so on. Computers are going to be much better drivers than us in countless ways. They have superior reflexes, can see in all directions simultaneously (not to mention in the dark, and around or through obstacles), communicate and collaborate instantly with nearby vehicles, immediately sense and potentially fix technical problems… the list goes on.
But until these amazing abilities lose their luster and become just more pieces of the transportation tech infrastructure that we trust, they’ll be suspect. That part we can’t really accelerate except, paradoxically, by taking it slow and making sure no highly visible outlier events (like that fatal Uber crash) arrest the zeitgeist and set back that trust by years. Make haste slowly, as they say. Few people remember anti-lock brakes saving their lives, though it’s probably happened to several people reading this right now — it just quietly reinforced our implicit trust in the vehicle. And no one will remember when their car improved their commute by 5 minutes with a hundred tiny improvements. But they sure do remember that Toyotas killed dozens with bad software that locked the car’s accelerator.
The second part of that trust is explicit: something that has to be communicated, learned, something of which we are consciously aware.
For cars there aren’t many of these. The rules of the road differ widely and are flexible — some places more than others — and on ordinary highways and city streets there we operate our vehicles almost instinctively. When we are in the role of pedestrian, we behave as a self-aware part of an the ecosystem — we walk, we cross, we step in front of moving cars because we assume the driver will see us, avoid us, stop before they hit us. This is because we assume that behind the wheel of every car is an attentive human who will behave according to the rules we have all internalized.
Nevertheless we have signals, even if we don’t realize we’re sending or receiving them; how else can you explain how you know that truck up there is going to change lanes fives seconds before it turns its blinker on? How else can you be so sure a car isn’t going to stop, and hold a friend back from stepping into the crosswalk? Just because we don’t quite understand it doesn’t mean we don’t exert it or assess it all the time. Making eye contact, standing in a place implying the need to cross, waving, making space for a merge, short honks and long honks… It’s a learned skill, and a culture- or even city-specific one at that.
With self-driving cars there is no humanity in which to place our trust. We trust other people because they’re like us; Computers are not like us.
In time autonomous vehicles of all kinds will become as much a part of the accepted ecosystem as automated lights and bridges, metered freeway entrances, parking monitoring systems, and so on. Until that time we will have to learn the rules by which autonomous vehicles operate, both through observation and straightforward instruction.
Some of these habits will be easily understood, for instance maybe autonomous vehicles will never, ever try to make an U-turn by crossing a double yellow line. I try not to myself, but you know how it is. I’d rather do that than go an extra three blocks to do it legally. But an AV will perhaps scrupulously adhere to traffic laws like that. So there’s one possible rule.
Others might not be quite so hard and fast. Merging and lane changes can be messy, but perhaps it will be the established pattern that AVs will always brake and join the line further back rather than try to move up a spot. This requires a little more context and the behavior is more adaptive, but it’s still a relatively simple pattern that you can perceive and react to, or even exploit to get ahead a bit (please don’t).
It’s important to note that, like the trolley problem “solutions,” there’s no huge list of car behaviors that says, always drop back when merging, always give the right of way, never this, this if that, etc. Just as our decision to switch or not switch tracks proceeds from a higher-order process of morality in our minds, these autonomous behaviors will be the natural result of a large set of complicated evaluations and decision-making processes that weigh hundreds of factors like positions of nearby cars, speed, lane width, etc. But I think they’ll be reliable enough in some ways and in some behaviors that there will definitely be a self-driving “style” that doesn’t deviate too much.
Although few if any of these behaviors are likely to be dangerous in and of themselves, it will be helpful to understand them if you are going to be sharing the road with them. Imperfect knowledge is how we get accidents to begin with. Establishing an explicit trust relationship with self-driving vehicles is part of the process accepting them into our everyday lives.
But people naturally want to take things to their logical ends, even if those ends aren’t really logical. And as you consider the many ways AVs will drive and how they will navigate certain situations, the “but what if…” scenarios naturally get more and more dire and specific as variables approach limits, and ultimately you arrive at the AV equivalent of the trolley problem that we started with. What happens when the car has to make a choice between people?
It’s not that anyone even thinks it will happen to them. What they want to know, as a prerequisite to trust, is that the system is not unprepared, and that the prepared response is not one that puts them in danger. People don’t want to be the victim of the self-driving car’s logic, even theoretically — that would be an impassible barrier to trust.
Because whatever the scenario, whoever it “chooses” between, one of those parties is undeniably the victim. The car got on the road and, following its ill logic to the bitter end, homed in on and struck this person rather than that one.
If neither of the people in this AV-trolley problem can by any reasonable measure be determined to be the “correct” one to choose, especially from their perspective (which must after all be considered), what else is there to do? Well, we have to remember that there’s one other “person” involved here: the car itself.
Is it self-destruction if you don’t have a self?
My suggestion is simply that it be made a universal policy that should a self-driving car be put in a situation where it is at serious risk of striking a person, it must take whatever means it can to avoid it — up to and including destroying itself, with no consideration for its own “life.” Essentially, when presented with the possibility of murder, an autonomous vehicle must always prefer suicide.
When presented with the possibility of murder, an autonomous vehicle must always prefer suicide.
It doesn’t have to detonate itself or anything. It just needs to take itself out of the action, and a robust improvisational engine can be produced to that end just as well as for avoiding swerving trucks, changing lanes suddenly, and any other behavior. There are telephone poles, parked cars, trees — take your pick; any of these things will do as long as they stop the car.
The objection, of course, is that there is likely to be a person inside the self-driving car. Yes — but this person has consented to the inherent risk involved, while the people on the street haven’t. While much of the moral calculus of the trolley problem is academic, this bit actually makes a difference.
Consenting to the risks of using a self-driving system means the occupant is acknowledging the possibility that should such a situation arise, however remote the possibility, they would be the person who may be the victim of it. They are the ones who will explicitly consent to trust their lives to the logic of the self-driving system. Furthermore, as a practical consideration, the occupant is so to speak on the soft side of the car.
As we’ve already established, it’s unlikely a car will ever have to do this. But what it does is provide a substantial and easily understood answer when someone asks the perfectly natural question of what an autonomous vehicle will do when it is careening towards a pedestrian. Simple: it will do its level best to destroy itself first.
There are extremely specific and dire situations that there will never be a solution to as long as there are moving cars and moving people, and self-driving vehicles are no exception to that. You’ll never run out of imaginary scenarios for any system, human or automated, to fail. But it is in order to reduce the number of such scenarios and help establish trust, not to render tragedy impossible, that every self-driving car should robustly and provably prefer its own destruction to that of a person outside itself.
We are not aiming for a complete solution, just an intuitive one. Self-driving cars will, say, always brake to merge, never cross a double yellow in normal traffic, and so on and so forth — and will crash themselves rather than hit a pedestrian. Regardless of the specifics and limitations of the model, that’s a behavior anyone can understand, including those who must consent to it.
Although even the most hard-bitten existentialist would be unlikely to support a systematic framework for suicide, it makes a difference when “suicide” is more likely to mean a fender bender and damage to one’s pocket rather than the death or injury of another. To destroy oneself is different when there is no self to destroy, and practically speaking the risk to passengers, equipped with airbags and seat belts, is far less than the risk to pedestrians.
How exactly would this all be accomplished in practice? Well, it could of course be required by transportation authorities, like seat belts and other safety measures. But unlike seat belts, the proprietary and complex inner workings of an autonomous system aren’t easily verifiable by non-experts. There are ways, but we should be wary of putting ourselves in a position where we have to trust not a technology but the company that administrates it. Either can fail us, but only one can betray us.
We should be wary of putting ourselves in a position where we have to trust not a technology but the company that administrates it. Either can fail us, but only one can betray us.
Perhaps there will be no need to rely on regulators, though: No brand of car wants to have its vehicles associated with running down a pedestrian. Today there are probably more accidents in Civics and Camrys than anything else, but no one thinks that makes them dangerous to drive — it just means more people drive them, and people make mistakes like anyone else.
On the other hand, if an automaker’s brand of self-driving vehicle hits someone, it’s obvious (and right) that the company will bear the blame. And consumers will see that — for one thing, it will be widely reported, and for another, there will probably be highly robust tracking of this kind of thing, including footage and logs from these accidents.
If automakers want to avoid pedestrian strikes and fatalities, they will incorporate something like this self-destruction protocol in their cars as a last line of defense, even if it leads to a net increase in autonomous collisions. It would be much preferable to be known as having a cautious AI than a killer one. So I think that, like other safety mechanisms, this or something like it will be included and, I hope, publicized on every car not because it’s required, but because it makes sense.
People deserve to know how things like self-driving cars work, even if few people on the planet can truly understand the complex computations and algorithms that govern them. They should, like regular cars, be able to be understood at a surface level. This case of understanding them at an extreme end of their behavior is not one that will be relevant every day, but it is a crucial one because it is something that matters to us at a gut level: knowing that these cars aren’t evaluating us as targets via mysterious and fundamentally inadequate algorithms.
To repurpose Camus: “These are facts the heart can feel; Yet they call for careful study before they become clear to the intellect.” Start with a simple solution we feel to be just and work backward from there. And soon — because this is no longer a thought experiment.
Atlassian today announced a set of new templates and workflows for Jira Service Desk that were purpose-built for HR, legal and facilities teams. Service Desk started six years ago as a version of Jira that was mostly meant for IT departments. Atlassian, however, found that other teams inside the companies that adopted it started to use it as well, including various teams at Twitter and Airbnb, for example. With today’s update, it’s now making it easier for these teams, at least in legal, HR and facilities, to get started with Jira Service Desk without having to customize the product themselves.
“Over the last six years, one of the observations that we’ve made was that we need to provide really good services — the idea that we can provide great services to employees is really something that is really on the rise,” said Edwin Wong, the head of the company’s IT products. “I think in the past, maybe we were a bit more forgiving in terms of what employees expected from services departments. But today you’re just so used to great experiences in your consumer life and when you come to work, you expect the same.”
But lots of service teams, he argues, didn’t have the tools to provide this experience, yet they were looking for tools to streamline their workflows (think onboarding for HR teams, for example) and to move from manual processes to something more automated and modern. Jira was already flexible enough to allow them to do this, but the new set of templates now codifies these processes for them.
Wong stressed this isn’t just about tracking but also managing work across teams and providing them a more centralized hub for information. “One of the big challenges that we’ve seen from many of the customers that we’ve spoken to is the challenge of just figuring out where to go when you want something,” he said. “When I have a new employee, where do I go to ask for a new laptop? Is that the same process as telling my facilities teams that perhaps there is an issue with a bathroom?”
Atlassian is starting with these three templates because that’s where it saw the most immediate need. Over time, I’m sure we’ll see the company get into other verticals as well.
Apple Music is taking on Spotify with the launch of a new feature, Apple Music Replay, that will allow subscribers to take a look back at their favorite music from 2019. The feature is similar in some ways to Spotify’s popular year-end review, known as Wrapped, but Apple’s version is more than just an annual summary — it’s an ongoing experience.
With Apple Music Replay, subscribers will get a playlist of their top songs from 2019, plus playlists for every year you’ve subscribed to Apple Music, retroactively. These can be added to your Apple Music Library, so you can stream them at any time, even when offline. Like any playlist, your Apple Music Replay can also be shared with others, allowing you to compare top songs with friends, for example, or post to social media.
But while Spotify’s Wrapped is more of an annual retrospective, Apple Music Replay will continue to be updated all year long, evolving as your musical tastes and interests do throughout the year. The playlist and its associated data insights will be updated on Sundays to reflect subscribers’ latest listening activity, says Apple.
That makes the playlist more of a compilation of favorites, which continues to add value throughout the year — not just at the end. And when January rolls around, the 2020 Replay playlist will be a blank slate to fill with your favorites from Apple Music’s catalog of 60 million tracks.
Apple Music Replay is available from the Apple Music app across platforms, including via the web at replay.music.apple.com.
Over the past few years, Apple’s MacBook game had begun to suffer from complacency — as problems with the models started to mount (unreliable keyboards, low RAM ceilings and anemic graphics offerings), the once insurmountable advantage that the MacBook had compared to the rest of the notebook industry started to show signs of dwindling.
So the new 16” MacBook Pro is an attempt to rectify most, if not all, of the major complaints of its most loyal, and vocal, users.
Google is calling the project “Cache,” and it’ll partner with banks and credit unions to offer the checking accounts, with the banks handling all financial and compliance activities related to the accounts.
A federal court has ruled that the government is not allowed to search travelers’ phones or other electronic devices at the U.S. border without first having reasonable suspicion of a crime. The case was brought by 11 travelers — 10 of whom are U.S. citizens — with support from the American Civil Liberties Union and the Electronic Frontier Foundation.
Convoy co-founders Dan Lewis and Grant Goodale set out in 2015 to modernize freight brokerage, a fragmented and oftentimes analog business that matches loads from shippers with truckers. The company has gone from hundreds of loads per week in 2016 to tens of thousands per week across the U.S.
To be forward-looking, brands and retailers are turning to startups in image recognition and machine learning to know, at a very deep level, what each consumer’s current context and personal preferences are and how they evolve. (Extra Crunch membership required.)
Invented by a man named Brock Seiler, and led by former Beats by Dre CEO Susan Paley, DropLabs aims to take audio to a whole new level by syncing music, movies and other audio to shoes that vibrate the soles of your feet.
Musk said Tesla is also going to create an engineering and design center in Berlin because “I think Berlin has some of the best art in the world.”
Google Maps is adding a feature that will make it easier for people traveling in foreign countries where they don’t speak the local language: built-in translation with text-to-speech support. The feature will allow users to tap on a new speaker button next to a place name or address, to have Google Maps say the name out loud — a particularly useful addition for anyone who has needed to communicate about directions when traveling.
Most people who have ventured outside of their home country, at some point, needed to ask for directions or tell a taxi driver their destination. And when you don’t speak the language, that can be difficult to do — even with the aid of translation apps or language dictionaries, as they’re often more focused on everyday vocabulary, not necessarily on the proper names of places.
Now, instead of struggling with pronunciation and having awkward conversations or even handing over your phone to a cab driver, you can tap a button.
In addition, Google Maps will also now link you to the Google Translate app if you need to continue the conversation further.
The new feature works by detecting what language your phone is currently using, then determining when to show you the translate option. For example, an English speaker who was browsing a map of Tokyo may see the speaker icon, but may not see the icon if looking at places in the U.S.
It’s somewhat surprising this sort of text-to-speech functionality wasn’t already included in Google Maps, given its use for travel purposes. But Google has more recently been waking up to the power of integrating Google Translate into other experiences outside the app itself, including in Google Home, Google Assistant, Google Lens, and more. And in the end, this translation support makes Google’s products more powerful and competitive — and for consumers, more useful.
Translate for Google Maps is rolling out this month on iOS and Android with initial support for 50 languages. More languages will arrive in the future, Google says.
Volkswagen said Wednesday it will build a battery pack assembly facility as part of an $800 million expansion project that will turn the Chattanooga, Tenn. factory into its North American base for manufacturing electric vehicles.
The Chattanooga factory expansion, which is includes a 564,000-square-foot addition to the body shop and is expected to create 1,000 new jobs at the plant, has been in the works for some time now. But the battery pack assembly announcement, while logical, came as a surprise.
“This is a big, big moment for this company,” Scott Keogh, president and CEO of Volkswagen Group of America said in a statement. “Expanding local production sets the foundation for our sustainable growth in the U.S. Electric vehicles are the future of mobility and Volkswagen will build them for millions of people.”
The automaker’s Chattanooga expansion is just a piece its broader plan to move away from diesel in the wake of the emissions cheating scandal that erupted in 2015. Globally, VW Group plans to commit almost $50 billion through 2023 toward the development and production of electric vehicles and digital services.
The Tennessee factory (along with the other new facilities) will produce electric vehicles using Volkswagen’s modular electric toolkit chassis, or MEB, introduced by the company in 2016. The MEB is a flexible modular system — really a matrix of common parts — for producing electric vehicles that VW says make it more efficient and cost-effective.
The company also built a European facility in Zwickau, Germany. Earlier this month, VW began production of the ID. 3 electric vehicle began at the Zwickau factory. By 2022, VW’s MEB vehicles will be produced at eight locations on three continents.
EV-production at facilities are expected to come online in Anting and Foshan in China in 2020, and in the German cities of Emden and Hanover by 2022.
Volkswagen currently produces the midsize Atlas SUV and the Passat sedan at the Chattanooga factory. Production of its electric vehicles is set to begin in Chattanooga in 2022. First model will be a SUV of ID. family.