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Potentially bad news for those of us who prefer not to be assimilated into the Google hive mind: Mozilla seems to be on the rocks. Citing revenue problems, the maker of Firefox and other popular tools will be trimming 250 employees, about a quarter of its workforce, and shuttering its office in Taipei. CEO Mitchell Baker specifically mentioned that “development tools, internal tooling, and platform feature development” in the Firefox team would see reduced investment. Like a lot of companies do these days, she managed to blame COVID-19 for the company’s woes. That seems a little specious to us, but whatever the reason for the downturn in revenue, here’s hoping that Mozilla can keep Firefox alive.
Speaking of our evil overlords, looks like it another one of those “oopsies” moment for Google when it “accidentally” activated some of its smart speakers to listen into household events without the wake word. In this case, a user reported getting a text about a smoke alarm going off in their home. The alarm was not a surprise, since the user was cooking at the time, but the notification was, since they didn’t opt into that particular service. Google’s response was that an update pushed to the speaker accidentally activated that feature, a situation that they say has since been rectified. To be clear, this is an interesting feature and one of the more compelling use cases we’ve seen for a smart speaker, but it’s something we’d certainly want to sign off on before it’s activated. Yes, accidents happen, but these kinds of accidents seem to happen to Google an awful lot lately.
We’ve probably all had the experience over the last few months of being in public when the urge to cough hits. Masked or not, you struggle to fight back the tickle, lest someone hear you and think you’re infected. But now it’s possible for a computer to cough-shame you, thanks to a deep learning cough locater. The model was trained against recordings of people coughing and is coupled to an acoustic camera, which identifies the cougher with a bounding box and a contour image of the cough which looks for all the world like a virtual cloud of microbes. It’s genuinely interesting technology, sort of the public health version of ShotSpotter, but we doubt it’ll be of much practical use in public; if you want to find someone who has just coughed, someone acting like this will likely already be on the case.
Modern jet fighter technology is advancing rapidly, so much so that the forces they can apply during extreme maneuvers can quickly be lethal to pilots. Given that humans aren’t likely to evolve the ability to resist turning into a puddle of goo under high g-forces anytime soon, fighters of the future will likely incorporate AI of some sort. To prepare for that eventuality, the Defense Advanced Research Projects Agency (DARPA) is running some AI fighter competitions this week that really look interesting. Dubbed Alpha Dogfight Trials, the challenge starts with simulated dogfights between AI systems. The winner of those rounds will go up against a human pilot in the final match, which will be streamed live with commentary and multi-screen coverage. You need to register to get in on the action, and time is limited.
And finally, let these three words roll around in your head for a minute: robotic chameleon tongue. It’s actually nowhere near as disturbing as it sounds, since at its heart the “Snatcher” is actually just a beefed-up tape measure. Designed for remote retrieval tasks, the Snatcher can shoots it steel proboscis out almost a meter in just 600 milliseconds. Its designers envision uses for it on drones, but we can see it potentially being deployed on satellites too. It shouldn’t be too hard to build something like this at home, either.
People sometimes say “when you have a hammer, everything looks like a nail” as if that were a bad thing. Hitting up Wikipedia, they’re calling it the Law of the Instrument or Maslow’s Hammer and calling it a cognitive bias. But I like hammers…
I’m working on a new tool, a four-axis hot-wire foam cutter based roughly on this design, but built out of stuff in my basement so far. I want it primarily to turn out wings for RC airplanes so that I can play around with airfoils and construction methods and so on. But halfway through building this new “hammer”, I’m already getting funny ideas of other projects that could be built with it. Classic nail-seeking behavior.
And some of these thoughts are making me reconsider the design of my hammer. I originally wanted to build it low, because it’s not likely that I’ll ever want to cut wing sections taller than 50 mm or so. But as soon as cutting out giant letters to decorate my son’s room, or maybe parts for a boat hull enter my mind, that means a significantly taller cutter, with ensuing complications.
So here I am suffering simultaneously from Maslow’s Hammer and scope creep, but I’m not sad about either of these “ills”. Playing with a couple manual prototypes for the CNC hot-wire cutter has expanded my design vocabulary; I’ve thought of a couple cool projects that I simply wouldn’t have had the mental map for before. Having tools expands the possible ways you can build, cognitive bias or not.
One person’s scope creep is another’s “fully realizing the potential of a project”. I’m pretty sure that I’ll build a version two of this machine anyway, so maybe it’s not a big deal if the first draft were height-limited, but the process of thinking through the height problem has actually lead me to a better design even for the short cutter. (Tension provided by an external bow instead of born by the vertical CNC towers. I’ll write the project up when I’m done. But that’s not the point.)
Maybe instead of lamenting Maslow’s cognitive bias, we should be celebrating the other side of the same coin: that nails are tremendously useful, and that the simple fact of having a hammer can lead you to fully appreciate them, and in turn expand what you’re capable of. As for scope creep? As long as I get the project done over my vacation next week, all’s well, right?
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You’ve built a brand new project, and it’s a wonderful little thing that’s out and about in the world. The only problem is, you need to know its location to a decent degree of accuracy. Thankfully, GPS is a thing! With an off-the-shelf module, it’s possible to get all the location data you could possibly need. But how do you go about it, and what parts are the right ones for your application? For the answers to these questions, read on! Continue reading “How To Choose The Right GPS Module For Your Project”→
Hackaday editors Elliot Williams and Mike Szczys flip through the index of great hacks. This week we learn of a co-existence attack on WiFi and Bluetooth radios called Spectra. The craftsmanship in a pneumatic drone is so awesome we don’t care that it doesn’t fly. Building a powerful TEA laser is partly a lesson in capacitor design. And join us in geeking out at the prospect of big rigs getting their juice from miles of overhead wires.
Take a look at the links below if you want to follow along, and as always, tell us what you think about this episode in the comments!
Take a look at the links below if you want to follow along, and as always, tell us what you think about this episode in the comments!
The holy grail of every particle physics experiment is the discovery of a new particle. Finding a new constituent of matter may earn you eternal glory within the history of physics. Unfortunately, since the last missing piece of the Standard Model, the Higgs boson, was discovered in 2012, and with still no clue about the nature of dark matter and dark energy, there is not much hope to stumble upon a new fundamental building block of matter any time soon.
In the fast food industry, speed is everything. The concept has never just been about cooking quickly. Players in this competitive space spend huge fortunes every year on optimizing every aspect of the experience, from ordering, to queueing, to cleaning up afterwards. And while fast food restaurants are major employers worldwide, there’s always been a firm eye cast over the gains that automation has to offer.
Flipping Burgers
In the West, fast food most commonly brings burgers to mind. Preparing a quality burger requires attention to the grade of meat, fat content, as well as the preparation steps before it hits the grill. Then it’s all about temperature and time, and getting just the right sear to bring out the natural flavors of the beef. While a boutique burger joint will employ a skilled worker to get things just right, that doesn’t fly for fast food. Every order needs to be preparable by whichever minimum-wage worker got the shift, and be as repeatable as possible across entire countries, or even the world, to meet customer expectations.
Flippy ROAR (Robot On A Rail) at work on the fryers in a White Castle in Chicago.
In their efforts to improve efficiency, White Castle have taken the bold step of installing a robotic burger flipper, imaginitively named Flippy. Built by Miso Robotics, the robot hangs from a ceiling rail to minimise the space taken up in the kitchen area. Based on a Fanuc robot arm, the system uses artificial intelligence to manage kitchen resources, Flippy is capable of managing both the grill and fryers together to ensure fries don’t get cold while the burgers are still cooking, for example. Currently undergoing a trial run in Chicago, White Castle has ambitions to roll the technology out to further stores if successful.
We’ve seen other robotic burger systems before, too. In late 2018, our own [Brian Benchoff] went down to check out Creator, which cooks and assembles its burgers entirely by machine. Despite suspicions about the business model, Creator have persisted until the present day with their unique blend of technology and culinary arts. Particularly impressive were their restaurant modifications in the face of COVID-19. The restaurant received an overhaul, with meals being robotically prepared directly in a take-out box with no human contact. Take-out meals are double-bagged and passed to customers through an airlock, with a positive-pressure system in the restaurant to protect staff from the outside world.
Pizzabots
Pizza is a staple food for many, with high demand and a stronger dependence on delivery than other fast food options. This has led to the industry exploring many avenues for automation, from preparation to order fulfillment.
In terms of outright throughput, Zume were a startup that led the charge. Their system involves multiple robots to knead dough, apply sauce and place the pie in the oven. Due to the variable nature sizes and shapes of various toppings, these are still applied by humans in the loop. Capable of turning out 120 pizzas per hour, a single facility could compete with many traditional human-staffed pizza shops. They also experimented with kitchens-on-wheels that use predictive algorithms to stock out trucks that cook pizzas on the way to the customer’s door. Unfortunately, despite a one-time $4 billion USD valuation, the startup hit a rocky patch and is now focusing on packaging instead.
Picnic aim to make lots of pizza, fast. Their business model involves working directly with existing restaurants, rather than creating their own fast-food brand from scratch.
Picnic have gone further, claiming an output rate of up to 300 twelve-inch pies an hour. The startup aims to work with a variety of existing pizza restaurants, rather than striking out as their own brand. One hurdle to overcome is the delivery of a prepared pizza into the oven. There are many varieties and kinds of pizza oven used in commercial settings, and different loading techniques are required for each. This remains an active area of development for the company. The company has a strong focus on the emerging ghost kitchen model, where restaurants are built solely to fulfill online delivery orders, with no dining area.
Domino’s is one of the largest pizza companies in the world, and thus far have focused their efforts on autonomous delivery. The DRU, or Domino’s Robotic Unit, was launched to much fanfare, promising to deliver pizzas by a small wheeled robotic unit. Equipped with sensors to avoid obstacles and GPS navigation, the project has not entered mainstream service just yet. However, between this and the multitude of companies exploring drone delivery, expect to see this become more of a thing in coming years.
Despite the marketing sizzle, the DOM Pizza Checker does not project holograms.
A more immediate innovation from Domino’s has been the DOM Pizza Checker. With customer complaints about pizza quality plaguing the chain, the pizza checker is an AI-powered visual system. It’s responsible for determining if the correct pizza has been made, with the right toppings and good distribution. An impressive practical use of AI imaging technology, it sounds an alarm if the pizza isn’t up to scratch, prompting it to be remade. However, it has come under scrutiny as a potential method to harass franchisees and workers. Additionally, the limitations of the system mean that Domino’s are still perfectly capable of turning out a bad pizza on occasion.
Other Efforts
One of the most visible examples of fast food automation is the widespread adoption of order kiosks by McDonalds, which kicked off in earnest in 2015. The majority of stores in the US now rely on these to speed up the ordering process, while also enabling more customization for customers with less fuss. Over-the-counter ordering is still possible at most locations, but there’s a heavy emphasis on using the new system.
McDonald’s automated beverage dispenser will be a familiar sight to many. Considered a great help when it works, and a great hindrance when it jams, spills, or simply shuts down.
In general, online ordering and delivery has become the norm, where ten years ago, the idea of getting McDonalds delivered was considered magical and arcane. This writer made seven attempts to take advantage of an early version of the service in China in 2015, succeeding only once, largely due to a lack of understanding of addresses written in non-Latin characters. However, due to the now-ubiquitous nature of services like Ubereats, Postmates, and Menulog, it’s simple for any restaurant to largely automate their ordering and fulfillment process, and reach customers at a distance from their brick-and-mortar locations.
Other efforts are smaller in scope, but contribute to great efficiency gains back-of-house. McDonalds and other chains have widely adopted automated beverage systems. Capable of automatically dispensing cups and the requisite fluids, they take instructions directly from the digital ordering system and take the manual labor out of drink preparation. They’re also great at slightly underfilling the cups, in a way that any human would consider incredibly rude.
Conclusion
Robots in the fast-food kitchen stand to reduce or eliminate tedious, repetitive work. Robots don’t get sick, and less human labour means fewer rostering hassles. It seems to be a foregone conclusion that more automation is on the way, and while some startups may falter, others will surely succeed. Your next meal may just yet be entirely prepared by a robot, even if it’s still delivered by a tired grad student on a moped. Come what may!
