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DroneSeed is planting trees from the air – TechCrunch

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Wildfires are consuming our forests and grasslands faster than we can replace them. It’s a vicious cycle of destruction and inadequate restoration rooted, so to speak, in decades of neglect of the institutions and technologies needed to keep these environments healthy.

DroneSeed is a Seattle-based startup that aims to combat this growing problem with a modern toolkit that scales: drones, artificial intelligence and biological engineering. And it’s even more complicated than it sounds.

Trees in decline

A bit of background first. The problem of disappearing forests is a complex one, but it boils down to a few major factors: climate change, outdated methods and shrinking budgets (and as you can imagine, all three are related).

Forest fires are a natural occurrence, of course. And they’re necessary, as you’ve likely read, to sort of clear the deck for new growth to take hold. But climate change, monoculture growth, population increases, lack of control burns and other factors have led to these events taking place not just more often, but more extensively and to more permanent effect.

On average, the U.S. is losing 7 million acres a year. That’s not easy to replace to begin with — and as budgets for the likes of national and state forest upkeep have shrunk continually over the last half century, there have been fewer and fewer resources with which to combat this trend.

The most effective and common reforestation technique for a recently burned woodland is human planters carrying sacks of seedlings and manually selecting and placing them across miles of landscapes. This back-breaking work is rarely done by anyone for more than a year or two, so labor is scarce and turnover is intense.

Even if the labor was available on tap, the trees might not be. Seedlings take time to grow in nurseries and a major wildfire might necessitate the purchase and planting of millions of new trees. It’s impossible for nurseries to anticipate this demand, and the risk associated with growing such numbers on speculation is more than many can afford. One missed guess could put the whole operation underwater.

Meanwhile, if nothing gets planted, invasive weeds move in with a vengeance, claiming huge areas that were once old growth forests. Lacking the labor and tree inventory to stem this possibility, forest keepers resort to a stopgap measure: use helicopters to drench the area in herbicides to kill weeds, then saturate it with fast-growing cheatgrass or the like. (The alternative to spraying is, again, the manual approach: machetes.)

At least then, in a year, instead of a weedy wasteland, you have a grassy monoculture — not a forest, but it’ll do until the forest gets here.

One final complication: helicopter spraying is a horrendously dangerous profession. These pilots are flying at sub-100-foot elevations, performing high-speed maneuvers so that their sprays reach the very edge of burn zones but they don’t crash head-on into the trees. This is an extremely dangerous occupation: 80 to 100 crashes occur every year in the U.S. alone.

In short, there are more and worse fires and we have fewer resources — and dated ones at that — with which to restore forests after them.

These are facts anyone in forest ecology and logging are familiar with, but perhaps not as well known among technologists. We do tend to stay in areas with cell coverage. But it turns out that a boost from the cloistered knowledge workers of the tech world — specifically those in the Emerald City — may be exactly what the industry and ecosystem require.

Simple idea, complex solution

So what’s the solution to all this? Automation, right?

Automation, especially via robotics, is proverbially suited for jobs that are “dull, dirty, and dangerous.” Restoring a forest is dirty and dangerous to be sure. But dull isn’t quite right. It turns out that the process requires far more intelligence than anyone was willing, it seems, to apply to the problem — with the exception of those planters. That’s changing.

Earlier this year, DroneSeed was awarded the first multi-craft, over-55-pounds unmanned aerial vehicle license ever issued by the FAA. Its custom UAV platforms, equipped with multispectral camera arrays, high-end lidar, six-gallon tanks of herbicide and proprietary seed dispersal mechanisms have been hired by several major forest management companies, with government entities eyeing the service as well.

These drones scout a burned area, mapping it down to as high as centimeter accuracy, including objects and plant species, fumigate it efficiently and autonomously, identify where trees would grow best, then deploy painstakingly designed seed-nutrient packages to those locations. It’s cheaper than people, less wasteful and dangerous than helicopters and smart enough to scale to national forests currently at risk of permanent damage.

I met with the company’s team at their headquarters near Ballard, where complete and half-finished drones sat on top of their cases and the air was thick with capsaicin (we’ll get to that).

The idea for the company began when founder and CEO Grant Canary burned through a few sustainable startup ideas after his last company was acquired, and was told, in his despondency, that he might have to just go plant trees. Canary took his friend’s suggestion literally.

“I started looking into how it’s done today,” he told me. “It’s incredibly outdated. Even at the most sophisticated companies in the world, planters are superheroes that use bags and a shovel to plant trees. They’re being paid to move material over mountainous terrain and be a simple AI and determine where to plant trees where they will grow — microsites. We are now able to do both these functions with drones. This allows those same workers to address much larger areas faster without the caloric wear and tear.”

It may not surprise you to hear that investors are not especially hot on forest restoration (I joked that it was a “growth industry” but really because of the reasons above it’s in dire straits).

But investors are interested in automation, machine learning, drones and especially government contracts. So the pitch took that form. With the money DroneSeed secured, it has built its modestly sized but highly accomplished team and produced the prototype drones with which is has captured several significant contracts before even announcing that it exists.

“We definitely don’t fit the mold or metrics most startups are judged on. The nice thing about not fitting the mold is people double take and then get curious,” Canary said. “Once they see we can actually execute and have been with 3 of the 5 largest timber companies in the U.S. for years, they get excited and really start advocating hard for us.”

The company went through Techstars, and Social Capital helped them get on their feet, with Spero Ventures joining up after the company got some groundwork done.

If things go as DroneSeed hopes, these drones could be deployed all over the world by trained teams, allowing spraying and planting efforts in nurseries and natural forests to take place exponentially faster and more efficiently than they are today. It’s genuine change-the-world-from-your-garage stuff, which is why this article is so long.

Hunter (weed) killers

The job at hand isn’t simple or even straightforward. Every landscape differs from every other, not just in the shape and size of the area to be treated but the ecology, native species, soil type and acidity, type of fire or logging that cleared it and so on. So the first and most important task is to gather information.

For this, DroneSeed has a special craft equipped with a sophisticated imaging stack. This first pass is done using waypoints set on satellite imagery.

The information collected at this point is really far more detailed than what’s actually needed. The lidar, for instance, collects spatial information at a resolution much beyond what’s needed to understand the shape of the terrain and major obstacles. It produces a 3D map of the vegetation as well as the terrain, allowing the system to identify stumps, roots, bushes, new trees, erosion and other important features.

This works hand in hand with the multispectral camera, which collects imagery not just in the visible bands — useful for identifying things — but also in those outside the human range, which allows for in-depth analysis of the soil and plant life.

The resulting map of the area is not just useful for drone navigation, but for the surgical strikes that are necessary to make this kind of drone-based operation worth doing in the first place. No doubt there are researchers who would love to have this data as well.

Now, spraying and planting are very different tasks. The first tends to be done indiscriminately using helicopters, and the second by laborers who burn out after a couple of years — as mentioned above, it’s incredibly difficult work. The challenge in the first case is to improve efficiency and efficacy, while in the second case is to automate something that requires considerable intelligence.

Spraying is in many ways simpler. Identifying invasive plants isn’t easy, exactly, but it can be done with imagery like that the drones are collecting. Having identified patches of a plant to be eliminated, the drones can calculate a path and expend only as much herbicide is necessary to kill them, instead of dumping hundreds of gallons indiscriminately on the entire area. It’s cheaper and more environmentally friendly. Naturally, the opposite approach could be used for distributing fertilizer or some other agent.

I’m making it sound easy again. This isn’t a plug and play situation — you can’t buy a DJI drone and hit the “weedkiller” option in its control software. A big part of this operation was the creation not only of the drones themselves, but the infrastructure with which to deploy them.

Conservation convoy

The drones themselves are unique, but not alarmingly so. They’re heavy-duty craft, capable of lifting well over the 57 pounds of payload they carry (the FAA limits them to 115 pounds).

“We buy and gut aircraft, then retrofit them,” Canary explained simply. Their head of hardware, would probably like to think there’s a bit more to it than that, but really the problem they’re solving isn’t “make a drone” but “make drones plant trees.” To that end, Canary explained, “the most unique engineering challenge was building a planting module for the drone that functions with the software.” We’ll get to that later.

DroneSeed deploys drones in swarms, which means as many as five drones in the air at once — which in turn means they need two trucks and trailers with their boxes, power supplies, ground stations and so on. The company’s VP of operations comes from a military background where managing multiple aircraft onsite was part of the job, and she’s brought her rigorous command of multi-aircraft environments to the company.

The drones take off and fly autonomously, but always under direct observation by the crew. If anything goes wrong, they’re there to take over, though of course there are plenty of autonomous behaviors for what to do in case of, say, a lost positioning signal or bird strike.

They fly in patterns calculated ahead of time to be the most efficient, spraying at problem areas when they’re over them, and returning to the ground stations to have power supplies swapped out before returning to the pattern. It’s key to get this process down pat, since efficiency is a major selling point. If a helicopter does it in a day, why shouldn’t a drone swarm? It would be sad if they had to truck the craft back to a hangar and recharge them every hour or two. It also increases logistics costs like gas and lodging if it takes more time and driving.

This means the team involves several people, as well as several drones. Qualified pilots and observers are needed, as well as people familiar with the hardware and software that can maintain and troubleshoot on site — usually with no cell signal or other support. Like many other forms of automation, this one brings its own new job opportunities to the table.

AI plays Mother Nature

The actual planting process is deceptively complex.

The idea of loading up a drone with seeds and setting it free on a blasted landscape is easy enough to picture. Hell, it’s been done. There are efforts going back decades to essentially load seeds or seedlings into guns and fire them out into the landscape at speeds high enough to bury them in the dirt: in theory this combines the benefits of manual planting with the scale of carpeting the place with seeds.

But whether it was slapdash placement or the shock of being fired out of a seed gun, this approach never seemed to work.

Forestry researchers have shown the effectiveness of finding the right “microsite” for a seed or seedling; in fact, it’s why manual planting works as well as it does. Trained humans find perfect spots to put seedlings: in the lee of a log; near but not too near the edge of a stream; on the flattest part of a slope, and so on. If you really want a forest to grow, you need optimal placement, perfect conditions and preventative surgical strikes with pesticides.

Although it’s difficult, it’s also the kind of thing that a machine learning model can become good at. Sorting through messy, complex imagery and finding local minima and maxima is a specialty of today’s ML systems, and the aerial imagery from the drones is rich in relevant data.

The company’s CTO led the creation of an ML model that determines the best locations to put trees at a site — though this task can be highly variable depending on the needs of the forest. A logging company might want a tree every couple of feet, even if that means putting them in sub-optimal conditions — but a few inches to the left or right may make all the difference. On the other hand, national forests may want more sparse deployments or specific species in certain locations to curb erosion or establish sustainable firebreaks.

Once the data has been crunched, the map is loaded into the drones’ hive mind and the convoy goes to the location, where the craft are loaded with seeds instead of herbicides.

But not just any old seeds! You see, that’s one more wrinkle. If you just throw a sagebrush seed on the ground, even if it’s in the best spot in the world, it could easily be snatched up by an animal, roll or wash down to a nearby crevasse, or simply fail to find the right nutrients in time despite the planter’s best efforts.

That’s why DroneSeed’s head of Planting and his team have been working on a proprietary seed packet that they were unbelievably reticent to detail.

From what I could gather, they’ve put a ton of work into packaging the seeds into nutrient-packed little pucks held together with a biodegradable fiber. The outside is dusted with capsaicin, the chemical that makes spicy food spicy (and also what makes bear spray do what it does). If they hadn’t told me, I might have guessed, since the workshop area was hazy with it, leading us all to cough and tear up a little. If I were a marmot, I’d learn to avoid these things real fast.

The pucks, or “seed vessels,” can and must be customized for the location and purpose — you have to match the content and acidity of the soil, things like that. DroneSeed will have to make millions of these things, but it doesn’t plan to be the manufacturer.

Finally these pucks are loaded in a special puck-dispenser which, closely coordinating with the drone, spits one out at the exact moment and speed needed to put it within a few centimeters of the microsite.

All these factors should improve the survival rate of seedlings substantially. That means that the company’s methods will not only be more efficient, but more effective. Reforestation is a numbers game played at scale, and even slight improvements — and DroneSeed is promising more than that — are measured in square miles and millions of tons of biomass.

Proof of life

DroneSeed has already signed several big contracts for spraying, and planting is next. Unfortunately, the timing on their side meant they missed this year’s planting season, though by doing a few small sites and showing off the results, they’ll be in pole position for next year.

After demonstrating the effectiveness of the planting technique, the company expects to expand its business substantially. That’s the scaling part — again, not easy, but easier than hiring another couple thousand planters every year.

Ideally the hardware can be assigned to local teams that do the on-site work, producing loci of activity around major forests from which jobs can be deployed at large or small scales. A set of five or six drones does the work of one helicopter, roughly speaking, so depending on the volume requested by a company or forestry organization, you may need dozens on demand.

That’s all yet to be explored, but DroneSeed is confident that the industry will see the writing on the wall when it comes to the old methods, and identify them as a solution that fits the future.

If it sounds like I’m cheerleading for this company, that’s because I am. It’s not often in the world of tech startups that you find a group of people not just attempting to solve a serious problem — it’s common enough to find companies hitting this or that issue — but who have spent the time, gathered the expertise and really done the dirty, boots-on-the-ground work that needs to happen so it goes from great idea to real company.

That’s what I felt was the case with DroneSeed, and here’s hoping their work pays off — for their sake, sure, but mainly for ours.

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Google loses two execs: one for Messaging and Workspace, another for Payments

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Google had a pair of high-ranking executives leave this week. The first was Bill Ready, Google’s “President of Commerce, Payments & Next Billion Users,” who left to become CEO of Pinterest. The second big departure is Javier Soltero, who was vice president and GM of Google Workspace, Google’s paid business app, and was the leader of Google Messaging. Both executives made big changes to Google in their nearly three-year stints at the company. Now that they are leaving, it’s unclear what the future of their respective products holds.

Ready was only at Google for two-and-a-half years, where his highest-profile move was presiding over the disastrous rollout of a significant Google Pay revamp. The new Google Pay app was spearheaded by Ready’s payments team, led by another recently ousted executive, Caesar Sengupta. The Google Pay revamp brought an app originally developed for India to the US, where the requirement for phone number-based identity came with a huge list of downgrades: The Google Pay website had to be stripped of payment functionality, the app no longer supported multiple accounts, and you couldn’t be logged in to multiple devices.

The rollout of the new app was also clumsy. Slowly, over a month or two, users were kicked out of the old Google Pay and had to transition to a new app. The new identity system wasn’t backward compatible with the old Google Pay, though, which meant users still on the old app couldn’t send money to users on the new app.

According to Pulse network (a wing of Discover card) Google Pay has 3 percent of the entire US NFC market. Keep in mind Google entered this market years before Apple.

According to Pulse network (a wing of Discover card) Google Pay has 3 percent of the entire US NFC market. Keep in mind Google entered this market years before Apple.

The new Google Pay was announced one year into Ready’s tenure at Google and launched in March 2021. The app initially came with big plans for expansion, including a wild announcement of Google-branded bank accounts. Sengupta left Google one month after the US launch of the new Google Pay, which triggered an “exodus” of employees, according to Insider. The report said, “Dozens of employees and executives” left the payments team after Sengupta’s departure, with one employee saying there was “frustration” the new Google Pay “wasn’t growing at the rate we wanted it to.”

What happened afterward seems like a complete scrapping of the original “New Google Pay” game plan. Google generally launches a product in the US first and then slowly rolls it out to the rest of the world, but after the initial poor reception, the new Google Pay never saw a wide rollout outside of the US. Google canceled its heavily promoted plans for a Google bank account, even though, according to the Wall Street Journal, the company already had 400,000 curious users sign up for the public waitlist.

Ready appointed a new leader of Payments this January, a move Bloomberg described as a “reset” of Google’s payments strategy. Ready also made headlines at the time by saying, “Crypto is something we pay a lot of attention to,” though no Google product has emerged.

Four months later, at Google I/O 2022, another revamp of Google Pay was announced, re-branding the product to “Google Wallet.” That’s right, after a big revamp of Google’s payment app in 2021, there’s now another new revamp in 2022. Ready is now leaving five months after appointing a new Payments lead and setting these plans in motion, but he won’t be around for the launch of Google Wallet. Between the departure of old Payments lead Sengupta, Sengupta’s boss, Ready, and “dozens” of team members, it sure seems like the payments team ended up cleaning house.

This nightmare of a map has the US with Google Pay and Google Wallet co-existing, while the rest of the world gets a cleaner solution of one payment app: Wallet.

This nightmare of a map has the US with Google Pay and Google Wallet co-existing, while the rest of the world gets a cleaner solution of one payment app: Wallet.

Google

At the heart of Google’s payments turbulence is probably the fact that most estimates put Google Pay at 3-4 percent of the US NFC payments market, which is way behind Apple’s nearly 92 percent market share. It’s an embarrassing loss considering Google was a pioneer in NFC payments and entered the market three years before Apple.

A big part of Google’s payment problems is this kind of instability, with Google’s payment app running through four different brands in 10 years (Google Wallet, then Android Pay, then Google Pay, now Google Wallet again). It still doesn’t seem like the company has arrived at a great solution with the new Google Wallet. The current plan—which could change once Ready’s replacement is hired—is for Google Wallet and Google Pay to co-exist in the US. In the rest of the world, there will be one payment app, Wallet, which sounds like a clean, reasonable offering. In the US and Singapore, though, Google doesn’t want to kill the widely panned new Google Pay app, so Google Wallet and Google Pay will be available. Why? If Wallet is rolling out to the rest of the world, the codebase clearly has the full payment feature set, why not just roll it out everywhere?

Google is still searching for a VP to replace Bill Ready, but the interim Payments president will be longtime Googler Nick Fox. Fox was previously front and center in the Google tech landscape as the head of Google messaging when the company produced Google Allo. Allo was Google’s main messaging app from 2016-2018, lasting about 576 days on the market. Since Allo, Fox has been running Google Search.

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Forget smart glasses, this smart contact lens prototype has a new vision for AR 

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Enlarge / Smart contact lenses don’t work quite this easily yet. (credit: Getty)

Since 2015, a California-based company called Mojo Vision has been developing smart contact lenses. Like smart glasses, the idea is to put helpful AR graphics in front of your eyes to help accomplish daily tasks. Now, a functioning prototype brings us closer to seeing a final product.

In a blog post this week, Drew Perkins, the CEO of Mojo Vision, said he was the first to have an “on-eye demonstration of a feature-complete augmented reality smart contact lens.” In an interview with CNET, he said he’s been wearing only one contact at a time for hour-long durations. Eventually, Mojo Vision would like users to be able to wear two Mojo Lens simultaneously and create 3D visual overlays, the publication said.

According to his blog, the CEO could see a compass through the contact and an on-screen teleprompter with a quote written on it. He also recalled viewing a green, monochromatic image of Albert Einstein to CNET.

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Some Macs are getting fewer updates than they used to. Here’s why it’s a problem

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Aurich Lawson

When macOS Ventura was announced earlier this month, its system requirements were considerably stricter than those for macOS Monterey, which was released just eight months ago as of this writing. Ventura requires a Mac made in 2017 or later, dropping support for a wide range of Monterey-supported Mac models released between 2013 and 2016.

This certainly seems more aggressive than new macOS releases from just a few years ago, where system requirements would tighten roughly every other year or so. But how bad is it, really? Is a Mac purchased in 2016 getting fewer updates than one bought in 2012 or 2008 or 1999? And if so, is there an explanation beyond Apple’s desire for more users to move to shiny new Apple Silicon Macs?

Using data from Apple’s website and EveryMac.com, we pulled together information on more than two decades of Mac releases—almost everything Apple has released between the original iMac in late 1998 and the last Intel Macs in 2020. We recorded when each model was released, when Apple stopped selling each model, the last officially supported macOS release for each system, and the dates when those versions of macOS received their last point updates (i.e. 10.4.11, 11.6) and their last regular security patches. (I’ve made some notes on how I chose to streamline and organize the data, which I’ve put at the end of this article).

The end result is a spreadsheet full of dozens of Macs, with multiple metrics for determining how long each one received official software support from Apple. These methods included measuring the amount of time between when each model was discontinued and when it stopped receiving updates, which is particularly relevant for models like the 2013 Mac Pro, 2014 Mac mini, and 2015 MacBook Air that were sold for multiple years after they were first introduced.

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