June 25, 2019
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Consumer Reports knocks Tesla’s Navigate on Autopilot feature

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Consumer Reports is calling the automatic lane-change feature on Tesla’s Navigate on Autopilot “far less competent” than a human driver and cautioned it could pose safety risks.

The consumer advocacy organization posted its review Wednesday on the newest version of Tesla’s advanced driver assistance system.

Navigate on Autopilot is an active guidance system that is supposed to navigate a car from a highway on-ramp to off-ramp, including interchanges and making lane changes. Once drivers enter a destination into the navigation system, they can enable “Navigate on Autopilot” for that trip.

Tesla pushed out a software update last month to allow for automatic lane changes. Drivers have to enable this feature, which gives the car permission to make its own lane changes. If not enabled, the system asks the driver to confirm the lane change before moving over. Automatic lane changes can be canceled at any time.

The system has been touted as a way to make driving less stressful and improve safety. In practice, the system had startling behavior, Jake Fisher, senior director of auto testing at Consumer Reports told TechCrunch.

“It doesn’t take very long behind the wheel with this feature on to realize it’s not quite ready for prime time,” Fisher said. CR said one of the more troubling concerns were failures of Tesla’s three rearward-facing cameras to detect fast-approaching objects from the rear better than the average driver.

The CR reviewers found Navigate on Autopilot lagged behind human driving skills and engaged in problematic behavior such as cutting off cars and passing on the right. CR drivers often had to take over to prevent the system from making poor decisions.

As a result, the system increases stress and doesn’t improve safety, Fisher said, before asking “So what is the point of this feature?”

The automatic lane change reviewed by Consumer Reports is not the default setting for Autopilot, Tesla notes. It’s an option that requires drivers to remove the default setting. Tesla also argues that drivers using Navigate on Autopilot properly have successfully driven millions of miles and safely made millions of automated lane changes.

While Fisher acknowledged the default setting, he contends that isn’t the issue. He notes the Tesla has many warnings that the driver must be alert and ready to take over at any time.

“Our concern is that if you’re not alert (or ready to take over) you could be put into a tricky situation,” he said.

The bigger concern for all systems like these is the driver will put too much trust into it, Fisher said. The automatic lane-change feature might not be good enough for drivers to let down their guard yet. If Tesla improves this system, even a little bit, the risk of complacency and too much trust rises.

And that’s problematic because drivers still must be ready to take over. “Just watching automation is a harder human task than driving the car,” he said.

CR asserts that an effective driver monitoring system would mitigate this risk. DMS is typically a camera combined with software designed to track a driver’s attention and pick up on cognitive issues that could cause an accident such as drowsiness.

DMS are found in certain BMW models with an ADAS system called DriverAssist Plus, the new 2020 Subaru Outback and Cadillac’s equipped with its Super Cruise system.

This isn’t the first time CR has raised concerns about Autopilot. Last week, the consumer advocacy organization called on Tesla to restrict the use of Autopilot and install a more effective system to verify driver engagement in response to a preliminary report by National Transportation Safety Board on the fatal March 2019 crash of a Tesla Model 3 with a semi-trailer in Delray Beach, Fla.

Last year, CR gave GM’s Super Cruise the top spot in its first-ever ranking of partially automated driving systems because it is the best at striking a balance between technical capabilities and ensuring drivers are paying attention and operating the vehicle safely. Tesla followed in the ranking not because it was less capable, but because of its approach to safety, Fisher noted.

CR evaluated four systems: Super Cruise on the Cadillac CT6, Autopilot on Tesla Model S, X and 3 models, ProPilot Assist on Infiniti QX50 and Nissan Leaf, and Pilot Assist on Volvo XC40 and XC60 vehicles. The organization said it picked these systems because they’re considered the most capable and well-known in the industry.

Chef goes 100% open source

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Chef, the popular automation service, today announced that it is open sourcing all of its software under the Apache 2 license. Until now, Chef used an open core model with a number of proprietary products that complemented its open-source tools. Most of these proprietary tools focused on enterprise users and their security and deployment needs. Now, all of these tools, which represent somewhere between a third and half of Chef’s total code base, are open source, too.

“We’re moving away from our open core model,” Chef SVP of products and engineering Corey Scobie told me. “We’re now moving to exclusively open source software development.”

He added that this also includes open product development. Going forward, the company plans to share far more details about its roadmap, feature backlogs and other product development details. All of Chef’s commercial offerings will also be built from the same open source code that everybody now has access to.

Scobie noted that there are a number of reasons why the company is doing this. He believes, for example, that the best way to build software is to collaborate in public with those who are actually using it.

“With that philosophy in mind, it was really easy to justify how we’d take the remainder of the software that we product and make it open source,” Scobie said. “We believe that that’s the best way to build software that works for people — real people in the real world.”

Another reason, Scobie said, is that it was becoming increasingly difficult for Chef to explain which parts of the software were open source and which were not. “We wanted to make that conversation easier, to be perfectly honest.”

Chef’s decision comes during a bit of a tumultuous time in the open source world. A number of companies like Redis, MongoDB and Elasic have recently moved to licenses that explicitly disallow the commercial use of their open source products by large cloud vendors like AWS unless they also buy a commercial license.

But here is Chef, open sourcing everything. Chef co-founder and board member Adam Jacob doesn’t think that’s a problem. “In the open core model, you’re saying that the value is in this proprietary sliver. The part you pay me for is this sliver of its value. And I think that’s incorrect,” he said. “I think, in fact, the value was always in the totality of the product.”

Jacob also argues that those companies that are moving to these new, more restrictive licenses, are only hurting themselves. “It turns out that the product was what mattered in the first place,” he said. “They continue to produce great enterprise software for their customers and their customers continue to be happy and continue to buy it, which is what they always would’ve done.” He also noted that he doesn’t think AWS will ever be better at running Elasticsearch than Elastic or, for that matter, at running Chef better than Chef.

It’s worth noting that Chef also today announced the launch of its Enterprise Automation Stack, which brings together all of Chef’s tools (Chef Automate, Infra, InSpec, Habitat and Workstation) under a unified umbrella.

“Chef is fully committed to enabling organizations to eliminate friction across the lifecycle of all of their applications, ensuring that, whether they build their solutions from our open source code or license our commercial distribution, they can benefit from collaboration as code,” said Chef CEO Barry Crist. “Chef Enterprise Automation Stack lets teams establish and maintain a consistent path to production for any application, in order to increase velocity and improve efficiency, so deployment and updates of mission-critical software become easier, move faster and work flawlessly.”

Aurora Solar’s computer-generated installation maps pull in a $20M Series A

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Solar installations are becoming a no-brainer for anyone with a roof in much of the country. But getting an estimate on how much it would cost and how much juice it would generate can be complicated and time consuming. Aurora Solar has made an automated process for doing this, and attracted $20 million in funding as a result.

A big part of the uncertainty anyone has about getting solar installed is the upfront cost and return on investment. An on-site visit may cost hundreds, or thousands for a commercial property, or that cost may be rolled up into the overall charge. But why send someone out when all the data you need can be acquired in bulk from the air?

Aurora uses lidar data for this — but not the kind of lidar where you have to fly a drone with the instrument over the house. That would hardly be less expensive and time-consuming than a normal visit. Instead they use lidar collected by small aircraft making low-altitude passes over the city.

The resulting data (you can see it above) produces detailed 3D models of the terrain and all the buildings on it; the exact size and slope of a roof can be determined with high precision. It’s actually similar in a way to how archaeologists used it to map out an ancient Mayan metropolis.

There are some programs and services out there that do virtual site visits, but many just estimate your roof area and orientation by looking at satellite imagery. That’s good for a basic estimate, but Aurora uses multiple sources of data to create a detailed 3D map of your roof, and its proud of its results.

“From the get go, we have been very ambitious about the way we address the problem, probably since we faced same issues our clients face ourselves,” said co-founder Christopher Hopper in an email to TechCrunch. That would have been in 2012, when he and co-founder Samuel Adeyemo experienced significant friction with a solar install in East Africa. The installation itself was a snap, they found, but the planning and design of the system took months.

“Aurora pioneered the concept of ‘remote site visits,’ which enables solar installers to precisely calculate how many solar panels fit on a property, and how much energy they produce without traveling to the site,” Hopper said. “We have a large dataset of LIDAR data pre-loaded in the application that’s accessible to our users. We estimate that that covers about 2/3 of the US population.”

This and other data lets Aurora create a detailed CAD model of the building in just a few minutes, and generate a basic plan for solar cell placement as well that accounts for slope, exposure, and any shade-producing obstacles like chimneys or trees nearby. (Shade reports are usually done in person, and are necessary to receive certain rebates.)

From there users can go straight into the sales and financing process, even including line diagrams for the electrical system you’ll be building. And theoretically it could all take under an hour, which is probably how much time you’d spend on the phone trying to get a local solar installer to come out.

The A round was led by Energize Ventures, whose managing director Amy Francetic will be joining the board, with S28 and seed investor Pear also contributing.

Once nice thing about companies relying on data and automation: they scale well. So Aurora won’t need to buy a thousand new trucks to get its next few thousand customers — it needs to hire engineers, sales and support people, which is exactly what it plans to do.

“We expect to expand all of the functions in our organization,” said Hopper. “We are particularly excited about all of the things we can do on the product side and in customer success. And finally, this funding means that we are here to stay. For companies [i.e. Aurora’s clients] that rely on a software provider for their day-to-day operations this is important factor.”

Adeyemo notes in the press release announcing the funding that “the solar professional” is the “fastest growing occupation in the U.S.” Hopefully making things easier for the customer will keep it that way for a while.

Disclosure: Former TechCruncher Rahul Nihalani now works for Aurora. Rahul’s great, but this does not affect our coverage.

Nvidia dives into a new business segment with Drive AutoPilot

in Artificial Intelligence/Automation/Automotive/Autopilot/CES 2019/continental/deep neural networks/Delhi/drive/driver/Emerging-Technologies/India/nvidia/Politics/self-driving car/Technology/Tesla/transport/Transportation/Xavier/zf by

Nvidia’s automotive ambitions seemed targeted solely on creating a platform to enable fully autonomous vehicles, notably the robotaxis that so many companies hope to deploy in the coming decade.

It turns out that Nvidia has also been working a more near-term product that opens it up to a different segment in the automotive industry. The company announced Monday at CES 2019 that it has launched Nvidia Drive AutoPilot, a reference platform that automakers can use to bring more sophisticated automated driving features into their production vehicles. This is not a self-driving car product, although it will likely be misinterpreted as such.

The Drive AutoPilot system is meant to make those advanced driver assistance system in today’s cars even better. It enables highway merging, lane changes, lane splits, pedestrian and cyclist detection, parking assist, and personal mapping as well as in-cabin features like driver monitoring, AI copilot capabilities, and advanced in-cabin visualization of the vehicle’s computer vision system. It also allows for over-the-air software updates, a capability that automakers, with the exception of Tesla, have been slow to adopt.

Nvidia already has two customers for Nvidia Drive AutoPilot — a name not to be confused with Tesla’s consumer-facing semi-autonomous system Autopilot. (It should be noted that a Tesla uses a derivative of Nvidia’s Drive platform, although that could change. Tesla has been developing its own chip, otherwise known as “Hardware 3.”

On Monday, Tier 1 suppliers Continental and ZF announced that by 2020 they will have partially automated driving systems ready for production that are based on the Drive AutoPilot platform.

Nvidia argues that there’s a market for this improved automation, noting a recent Insurance Institute for Highway Safety study that found existing Level 2 ADAS systems “offer inconsistent vehicle detections and poor ability to stay within lanes on curvy or hilly roads, resulting in a high occurrence of system disengagements where the driver abruptly had to take control.” Level 2 is a designation from SAE that means the vehicle’s automated system can handle accelerating, braking and steering, but must still be monitored by the driver, who should be prepared to take control at any time.

Nvidia doesn’t make plug-and-play type systems. Instead, Continental, ZF or other suppliers can take this reference platformand use it to deliver any combination of more advanced automation. For example, Continental will use it to produce an automated driving and parking solution that will be available to customers by 2020.

The foundation of the Drive AutoPilot is Nvidia’s Xavier system-on-a-chip processor, which can handle some 30 trillion operations per second. Then it adds Nvidia’s Drive software to process deep neural networks for perception as well as data pouring in from surround camera sensors.

The Drive AutoPilot system is part of Nvidia’s broader Drive platform. It’s also designed to complement the company’s Nvidia Drive AGX Pegasus system that provides Level 5 capabilities for robotaxis.


“A full-featured, Level 2+ system requires significantly more computational horsepower and sophisticated software than what is on the road today,” Rob Csongor, vice president of Autonomous Machines at Nvidia said, adding that the company’s system makes it possible for carmakers to quickly deploy advanced autonomous solutions by 2020 and to scale this solution to higher levels of autonomy faster.

Trello acquires Butler to add power of automation

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Trello, the organizational tool owned by Atlassian, announced an acquisition of its very own this morning when it bought Butler for an undisclosed amount.

What Butler brings to Trello is the power of automation, stringing together a bunch of commands to make something complex happen automatically. As Trello’s Michael Pryor pointed out in a blog post announcing the acquisition, we are used to tools like IFTTT, Zapier and Apple Shortcuts, and this will bring a similar type of functionality directly into Trello.

Screenshot: Trello

“Over the years, teams have discovered that by automating processes on Trello boards with the Butler Power-Up, they could spend more time on important tasks and be more productive. Butler helps teams codify business rules and processes, taking something that might take ten steps to accomplish and automating it into one click.” Pryor wrote.

This means that Trello can be more than a static organizational tool. Instead, it can move into the realm of light-weight business process automation. For example, this could allow you to move an item from your To Do board to your Doing board automatically based on dates, or to share tasks with appropriate teams as a project moves through its lifecycle, saving a bunch of manual steps that tend to add up.

The company indicated that it will be incorporating the Alfred’s capabilities directly into Trello in the coming months. It will make it available to all level of users including the free tier, but they promise more advanced functionality for Business and Enterprise customers when the integration is complete. Pryor also suggested that more automation could be coming to Trello. “Butler is Trello’s first step down this road, enabling every user to automate pieces of their Trello workflow to save time, stay organized and get more done.”

Atlassian bought Trello in 2017 for $425 million, but this acquisition indicates it is functioning quasi-independently as part of the Atlassian family.

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