We might think of the moon as a cold, dead chunk of rock, and it mostly is. However, a new analysis from Brown University claims there’s evidence of recent tectonic activity on the moon’s surface. The team didn’t need to launch a new lunar probe or land seismic sensors on the moon — NASA has already done that. Instead, researchers analyzed images from the Lunar Reconnaissance Orbiter (LRO) with an eye toward the prevalence of exposed bedrock.
Most of the surface is covered in lunar regolith, and scientists believe this material builds up quickly (on a geological scale). The LRO’s Diviner instrument measures the surface temperature across the moon, which can determine the surface composition — regolith tends to be colder than areas of exposed bedrock. They found more than 500 patches of exposed bedrock on narrow ridges, most of which were on the edges of lunar maria. Those are the large dark patches of the moon’s surface, and they don’t appear connected to volcanic activity in the moon’s early eons.
In the past, scientists have seen exposed bedrock on the moon as evidence of ancient lava flows. Indeed, NASA’s GRAIL mission in 2014 identified cracks in the moon’s crust where magma once flowed to the surface. Mapping out the exposed bedrock locations, the team found they lined up with the GRAIL cracks. Study co-author Peter Schultz says the correlation is nearly perfect, which suggests there’s some recent geological activity on the moon. The study calls this an Active Nearside Tectonic System, or ANTS.
The warmer spots (upper left) indicate regions with exposed bedrock.
The moon was most likely formed from material blasted off the primordial Earth by a massive impact. Lacking in mass, the moon cooled quickly and never developed the tectonic features seen on Earth. However, our local natural satellite has seen its fair share of impacts as well. The study speculates that the ANTS began billions of years ago following a large impact on the moon’s surface. The energy from that impact may still be driving small changes in the crust, pushing up portions of the bedrock faster than they can be covered with regolith.
These changes are minor, but they stand out on a planetoid with no other naturally occurring surface movement. We might not even notice the effect of long-ago impacts on an object like Earth.
Theaters across the country are closed, but that doesn’t mean you can’t enjoy a new film. Pick up a large 4K TV and you can enjoy movies in stunning detail from the comfort and safety of your own living room.
This inexpensive 4K TV costs just $299.99 from Dell and it comes with a $75 Dell eGift Card, which makes it an incredible deal. Don’t mistake this TV’s low price for a lack of features, however, as it supports HDR and can stream content from numerous sources just like the more expensive competition. Vizio also added built-in voice controls to this TV, which lets you control it without the need for a remote.
Sony designed this high-end 4K TV with one of its X1 Ultimate processors that intelligently upscales content to 4K giving you truly stunning image quality. The TV also supports a 120Hz refresh rate and it has several other built-in smart TV features for streaming content. Right now you can get this TV from Dell marked down from $1,398 to $998, and it also comes with a $250 gift card.
This compact desktop is all business with a relatively small physical footprint that’s in no way indicative of its performance. At the heart of this PC is an Intel Core i7-9700 processor with six CPU cores that can turbo boost up to 4.7GHz, which gives it exceptional performance for running numerous applications at the same time. Currently, you can get this system from Dell marked down from $1,141.43 to just $689.00.
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The web just continues to expand our world. If you can’t find a book you’re looking for on Amazon.com, you might find it on Amazon’s German storefront Amazon.de. If you don’t read German, that’s usually where a helpful resource like Google Translate can step in and convert the foreign text into your native tongue.
But what if you need to understand the spoken words in a podcast? Or figure out the translation of words in a picture? Unless you transcribe it all yourself, then feed it into a translator, you’re pretty much out of luck.
Whether you’re on a computer or a mobile device, LingvaNex is a full-service translation and dictionary app serving travelers, students, foreign language learners, international business associates, or virtually anyone who has the drive to understand.
If you have text, documents, or a website you need to be translated, LingvaNex gets to work, producing clean transcripts in the language of your choice.
But this app’s true power comes from everything else it can do. Voice translation is also simple for LingvaNex, allowing direct voice-to-voice conversation translations in more than 100 languages. If you have audio in a language you don’t understand, just play it for Lingvanex and it’ll tell you what the speaker said.
Its machine learning algorithms can also identify words in an image and translate that. There’s even an augmented reality feature, which offers full translations for all text captured by your mobile device camera. If you’re traveling and can’t tell which bathroom is which, it’s a very handy feature.
LingvaNex Translator also saves a history of your translations or lets you save favorites as bookmarks, offers alternate translations, and lets you share your translated text with friends or with other applications.
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It’s widely agreed that re-opening major portions of our economy relatively safely will require an extensive testing and contact-tracing system. Manual contact tracing — where those who test positive are interviewed about recent travel and person-to-person contacts — is expensive, hard to scale, and error-prone. So it is natural to see if digital technologies can help.
There are almost as many different approaches to how that might work as there are countries. But they fall into a few broad categories in terms of which technologies they use, how much data they store, and how they protect privacy. Here’s a look at some of the current and planned efforts, with a focus on those being piloted for deployment in the US.
All Roads Lead to the Smartphone
While there are some limited efforts using dedicated devices that have proven effective in controlled situations such as nursing homes, for broad deployment among the general public the obvious device of choice is the smartphone. Most people have one, they have a broad array of sensors, and they can be programmed to run custom apps. But “most people” isn’t “all people,” and many older phones don’t have the needed capability to run some of the proposed apps. So even phone-based solutions will need to deal with making their platform ubiquitous.
Stanford, Google, Apple: Protecting Privacy Via BLE
Perhaps the most “private” solution being proposed is one that was first publicized as Covid Watch, led by Stanford researcher Christina White and now embraced by the unlikely alliance of Apple and Google. This solution relies entirely on logging anonymized Bluetooth Low Energy (BLE) contacts between two users. Each phone broadcasts a random ID that changes every 10-20 minutes — meaning it should be impossible to use the IDs to track a specific user or find out more about them. At the same time, nearby phones log all the IDs they receive. So far, no data has left anyone’s phone.
When a user tests positive for infection, they can get a code from a medical professional that allows the app to upload the recent (probably last 14 days worth of) random IDs that their phone has broadcast. At least once a day, phones running the app download a full set of “infected” IDs, and compare them with the list they have logged. If there is a match, then the user gets the day, duration, and signal strength of the contact, so they know that they may have come in contact with someone who was infected.
Limits to Bluetooth-Based Tracking
Unfortunately, Bluetooth is limited when it comes to assessing the nature of a contact, in at least three important ways. First is that by itself, it doesn’t provide much help in ascertaining the nature of the contact. Was I simply walking behind someone on the sidewalk while practicing safe distancing and wearing a mask, or was I near them in a crowded store? The Stanford prototype only notes contacts that last more than 15 minutes. That’s helpful in screening out spurious events, but it might also screen out some important contacts — like the checkout line in a grocery store, or passing through a TSA checkpoint.
The second issue is that Bluetooth-only tracking doesn’t help with object-based infections. For example, when Singapore studied its early cases, they came to the conclusion that one patient got infected simply by using the same church pew that an infected person had earlier. Since the two people weren’t there at the same time, and no location information is recorded, a pure BLE solution wouldn’t have identified that situation as a possible contact. This would also hold true for the possible case where the virus survives in the air after the infected individual has left the area.
Finally, the BLE-only schemes don’t really make life any easier for those with the task of doing contact tracing manually. Because there isn’t any location data, and the contact data is anonymous, they need to start from scratch with the traditional interviews of the infected person and then painstakingly recreate their potential contacts. That’s one reason some government officials, like North Dakota governor and former Microsoft executive Doug Burgum, have urged that the adoption of solutions that include anonymized GPS-based location data, such as the state’s new Care19 app. He used the example of a checkout clerk in a big box store who tested positive. They could opt to share their data, which would allow anyone who had been in that store recently to be alerted.
On a broader level, the Google-Apple plan also isn’t a complete system. It requires public health agencies to implement the servers and the framework. However, many public health agencies have already said they would prefer a system that gave them access to data, including hot spots, rather than simply allowing users to interact essentially peer-to-peer. For these reasons, despite the obvious clout of Apple and Google, other groups are turning to solutions that include location data, typically acquired by logging GPS data.
MIT Private Kit: Safe Paths — A Proposal for “Safe” GPS-Based Tracking
Many people are concerned by the amount of location tracking that already takes place, so MIT researchers led by Ramesh Raskar realized they had taken on a difficult challenge when they set about designing a system to allow digital contact tracing while preserving privacy. Like the Google and Apple solution, their Private Kit mobile app uses Bluetooth to help determine possible contacts.
But it also uses GPS data and combines that with the Bluetooth data to create a location trail. If the user is infected, they can upload a 28-day history of their locations to the complementary web app Safe Places, where their health care provider can anonymize it. The user can specify certain locations such as their home to be removed from the log before it is shared. A redacted and hashed version is then distributed to other app users. By comparing the hashed results, that user can then be notified if they might have come into contact with an infected person.
There are a couple of major practical advantages to this approach. First, you can see where the contact occurred and thereby get a sense of how important it was likely to be (on a bike path or in a store, for example). The system also gains the ability to show locations you visited where an infected person had been there previously, even if they had already left by the time you arrived.
To help protect privacy, location data doesn’t leave your phone unless you are infected and opt to share your location trail with your healthcare provider. That data is then redacted and hashed before being shared. However, the current process for redacting, uploading, and then comparing location trails for matches currently involves a lot of manual steps. That helps with privacy but may not make it ideal for broad adoption.
Will Any Digital Contact Tracing System Work in the US?
There are good reasons to suspect that no contact tracing solution is going to become wildly popular or universally adopted in the US and in many countries in Europe. Getting people to do anything voluntarily is hard, and that’s especially true if it involves opting into a system that has potential for leaking yet more of their personal data — no matter how many promises are made by the organizations involved. Similar efforts fielded for flu or other pandemics have had fairly low take-up rates.
The approach of several Asian countries has been much more aggressive, partially because of new procedures put in place after the SARS epidemic. South Korea publishes the travel history of anyone who is confirmed to have Covid-19 — including what public transit they’ve taken — and broadcasts their location. Singapore’s popular TraceTogether app is similar to the Google/Apple proposal except instead of an automated, private, broadcast, contact tracers can access the information of all the other users that an infected individual was in contact with, and follow up with them directly. Even there, though, the TraceTogether app has only been downloaded by a minority of people. The most extreme is China, where the government has gone full Big Brother with travel and medical histories combined with various kinds of online data and scanned QR codes to control access to locations and even purchases.
It seems unlikely that the US, or most European countries, are willing to come close to the type of strong-arming it would take to mandate universal adherence to a digital contact tracking system. We may, however, get one or more solutions deployed broadly enough to at least make the job of human contact tracers a little easier.
Ding dong, the butterfly switch is dead! After five years of unpleasant typing, Apple computer users will be able to purchase any MacBook they want without fear of being stuck with the reviled and easily broken butterfly mechanism. The new 13-inch MacBook Pro has filled the final gap in Apple’s Magic Keyboard portfolio, and it can be yours today, starting at $1,300.
Apple insisted for years that there was nothing wrong with the Butterfly keyboard switch, which the company designed to be thinner than traditional scissor-switch mechanisms. The keys on Apple’s butterfly keyboards had extremely low travel as a result, and even tiny specs of dust under the key could prevent them from registering presses. What’s worse, repairing the keyboard often involved completely disassembling the laptop.
Apple eventually extended the warranty for laptops with butterfly keyboards, but it didn’t start replacing the mechanism in new models until late last year with the 16-inch MacBook Pro and its Magic Keyboard. Just a few months later, it launched a revamped MacBook Air with the same keyboard tech. Now, the 13-inch MacBook Pro has pushed the last Butterfly mechanism out of Apple’s product lineup in a mere six months. The new MacBook Pro does have a Touch Bar with Touch ID sensor above the board in place of the F-row, but there’s a physical escape key on the far left.
In addition to a better keyboard, the top-end version of the 13-inch Pro also has the latest 10th Gen Intel chip, and the model line starts at 256GB of storage. That’s double the storage from the old base model 13. You also get 8GB of RAM, with the option to increase that to 32GB on the more expensive models. Apple promises 500 nits of display brightness with a resolution of 2560 x 1600. The screen also supports Apple’s True Tone technology to be easier on the eyes.
The laptop still has USB-C/Thunderbolt 3 connectors as the only data ports, but you only get two ports on the low and mid-specced models. The most expensive versions of the laptop with 16GB of RAM and 512GB-1TB of SSD storage increase that to four ports. All the models do at least have a headphone jack. The best version of the 13-inch MacBook Pro starts at a cool $2,000, but adding a faster CPU, double the RAM, and 4TB of storage pumps the price up to $3,600.
Microsoft launched Xbox Game Pass in 2017, seeking to become the long-fabled “Netflix for games.” The company has never talked about subscriber counts, until now. In its most recent investor call, Microsoft revealed Xbox Game Pass has seen strong growth in the past year and now has a whopping 10 million subscribers. Netflix has somewhere north of 160 million customers, but you gotta start somewhere. No doubt some of this growth is thanks to the pandemic, but Microsoft hopes people will stick around even after they can go outside.
As the name implies, Xbox Game Pass started on the Xbox One console, but it expanded to PC last year. Both versions of the service have a $10 monthly subscription tier that gives you access to more than 100 games and some exclusive discounts. There’s also a $15 plan that has both PC and Xbox support, along with Xbox Live Gold — that alone is $10 per month. Unlike game streaming services, Game Pass simply gives subscribers the option to download and play any game included in the catalog.
The service has managed to grow even though it doesn’t always get the newest games. Titles from Microsoft Game Studio launch on day one, but many developers keep their latest titles off Game Pass. Some of the top titles on Game Pass are GTA V, Minecraft, and Doom (2016). The selection is decidedly better on the Xbox, though. None of those games are included for PC gamers. The top PC games include Gears 5, Alien: Isolation, and TABS.
Microsoft says Game Pass subscribers are much more into their games, though. They play twice as much as non-subscribers, and multiplayer engagement has increased 130 percent. Despite its relatively short run, Game Pass now has more subscribers than services like EA Access, PlayStation Now, and GeForce Now. EA and Sony claim 5 million subscribers, but Nvidia is at barely 1 million for a service it has been developing for more than six years.
Microsoft has the advantage of pushing Game Pass via the Xbox and Windows, and it doesn’t rely on streaming technology like GeForce Now. Microsoft does plan on moving into streaming soon, though. It’s already conducting a test of its xCloud game streaming technology, which will eventually become part of Game Pass. The company hasn’t talked about what such a combination service would cost, though. xCloud could also expand Microsoft gaming to smartphones. There’s already an Android client, but Microsoft is working through various roadblocks with Apple’s restrictive App Store policies.
For the past three months, I’ve been working on what I’ve named the Deep Space Nine Upscale Project (DS9UP). The goal of DS9UP is to create a new, much-improved version of the show by applying modern processing techniques to the original DVD source before using AI-based software to create a higher-resolution version of the show. It’s had me thinking about upscaling and upscalers in general. Upscaling isn’t a feature we talk about much, but how your TV handles it (or, alternately, how you use the capability on a PC) can have a significant impact on how you experience content.
The word “upscale” generically means “to improve the value or quality of something.” In the video and PC space, it’s almost always a reference to increasing the effective resolution of a piece of content. There is typically an understood difference between upscaling and native resolution. If you upscale a 1080p video into 4K, it means you are taking a 1080p input and using a combination of hardware and software to create a larger image. This upscaled image will not be identical to a native 4K signal, but it should offer a better picture than what was previously available on your 720p or 1080p television.
Keyword: “should.” Video scalar quality in TVs can vary widely between different product families. In some cases, you might be better off using a GPU to drive a picture than relying on the TV’s native rescaling capability, while other TVs have excellent upscalers. Manufacturers rarely disclose their upscaling hardware choices, but higher-end TVs should have improved upscaling capabilities. If you have a UHD Blu-ray player paired with an older or lower-quality 1080p or 4K TV, you might even get better results by running all video signals through the Blu-ray player rather than the television. Generally speaking, a good TV upscaler is considered to be as good or better than a GPU.
How the Scalar Sausage Gets Made
The most basic function of a video scaler is to take whatever image it receives — 480i, 720p, 1080p — and stretch it across the entire screen. Without this functionality, a 1080p signal would take up just a fraction of a 4K television’s display. This simple resizing is typically done by taking each individual 1080p pixel and creating four pixels out of it (remember, 4K is four times the pixels of 1080p).
But many TVs and Blu-ray players do more than just perform a simple 1:4 mapping. They also use video processing techniques to extrapolate what details ought to be present in the scene. How well this works depends on the type of content being
In the image above, you can see how the upscaled 4K is much more nuanced than the simple 1:4 mapping in the second grid from the left. If you’re having trouble seeing the difference between the 1080p upscale and the native 4K, look at the left-side blocks in the very first row and the right-side blocks in the very last row. The native 4K image resolves into distinctly different colors than the 1080p image in R1C2 (That’s 1st row, 2nd column), R1C3, and R8C8. As the amount of available horsepower in televisions has improved, the quality and sophistication of their integrated upscalers have grown as well. Some modern TVs have sophisticated sharpening algorithms to reverse the blur created by upscaling and interpolation algorithms good enough to almost match the precision of a native 4K signal.
How does all this look with real content? A 2017 Rtings article can help answer that question. The first image below is from a 4K set displaying 1080p in upscaled 4K, while the second is native 1080p.
If you have trouble seeing a difference between the two images, open both of them in a new tab and focus your eyes near the center of the image. See the house with a brown roof near the center of the image, with three windows facing approximately south-southwest and a fourth pointed east? (All directional cues based on north being “up”, not the direction of the sunlight). Look at that specific spot in both images, and the roofs in the buildings immediately adjacent. The difference should jump out at you. In this case, even using TVs that date back to 2015, the 1080p upscale to 4K is better than the 4K image.
Image by Rtings
If you have an older TV or a budget 4K model, there’s one obvious method of improving your TV’s upscaling: Buy a better television. Unfortunately, it’s impossible to predict how well this will work without knowing exactly what you own now and what you plan to purchase to replace it. The older your current TV, the better the chances that a new set will deliver upgrades in all respects, but many of those improvements may have nothing to do with the way your upscaler handles <4K content.
If you aren’t happy with your current TV, can’t replace it at the moment, and happen to own a high-end Blu-ray or UHD player, you can also try running content through its upscaler rather than relying on the television to handle it. In some cases, a top-end UHD Blu-ray player may deliver a better experience than an entry-level 4K TV from a few years back. If you’re still using a DVD player to feed a picture to a mediocre 1080p or 4K panel when/if you play DVDs, and you can swap over to a high-end Blu-ray / UHD Blu-ray player instead, I’d try it. It may or may not help, but it definitely won’t hurt. What you’re trying to do here is route the signal through the upscaler that’ll give it the best quality kick.
Still need a higher-quality picture? You’re in luck.
Real-Time AI Processing
I haven’t tested the most recent Nvidia Shield myself, but there’s a demo you can actually play with on Nvidia.com to apply the effect the TV offers. Here’s a screenshot of the effect. I’ve positioned the slider over the lizard’s eye because it’s the easiest place to see the upscaler’s impact:
Left: Regular upscale
Right: Nvidia Shield
Still not clear? Here’s an enlarged version of the same screenshot.
The image on the left is a traditional upscaler, the image on the right is Nvidia’s Shield when asked to scale up 720p or 1080p content to 4K (content below 720p is not supported for upscaling, at least not yet). The AI component of the upscaler obviously improves the overall image quality. In my experience with applications like TVEAI, this is a fair representation of the improvements that can be achieved.
Third-party reviews of the Shield agree. Slashgear writes that when it works, the effect is “fairly astonishing.” So far as I’m aware, the Shield is currently the only set-top or 2D box offering this kind of functionality.
Video Upscaling via Third-Party Software
Finally, there’s the option to use a third-party upscaler, like Topaz Video Enhance AI. I’ve made extensive use of TVEAI as part of the Deep Space Nine Upscale Project, and can confirm that the application is capable of yielding stunning results. One major limitation of TVEAI, however, is that it currently only supports Intel and Nvidia platforms for GPU-accelerated processing. CPU processing is available, but likely too slow to be all that useful.
Thanks to AI-based upscaling, historic sci-fi canards like the “Enhance” function are now a reality. It’s a truism in video encoding that no application on Earth can put data back where it never existed, and that’s still true today. The reason we can now “enhance” images to improve their clarity is that AI-based applications are capable of analyzing a video field and estimating what detail would exist if the image were in higher quality already.
One of the typical ways to train a video-enhancing application like TVEAI is to provide the neural net with the same image or video in both high and low quality. The neural net is then tasked with finding a way to make the low-quality source look as much like the high-quality source as possible. Instead of trying to teach a computer what lines and curves look like by providing painstaking examples, we’ve developed the ability to make the computer do the work of teaching itself. That’s why “Enhance” has gone from a complete joke to a plausible reality in a matter of a few years.
You may need to zoom to see subtle differences, but this isn’t an upscale comparison. It’s a comparison of performing my upscale work in separate applications and steps (left-side) versus ingesting the entire video workload into Topaz Video Enhance AI using the AVFS virtual file system and performing the entire operation at once. If you’re thinking “Wow, that’s a tiny difference, who would even care?” well, you may be right — but I wasn’t kidding when I said I was going to use the highest-quality source possible.
Applications like Topaz Video Enhance AI can cost several hundred dollars and they don’t run in real-time — the RTX 2080 appears capable of 90-110 frames per minute when upscaling 640×480 video to 2560×1920. The result of using these applications, however, is a vastly better picture than you’ll see from any other source.
DVD source on the left, upscale on the right.
I suspect we’ll see AI video processing and upscaling become more important over time as Intel, Nvidia, and AMD introduce their next-generation graphics processors. There’s an awful lot of old content orphaned on bad-quality source, and building specialized AI processors to fix it will likely consume some silicon for all of the concerned parties over the next few years.
Finally, I’ve embedded the current version of DS9UP’s opening credits for the show below. This is new footage that hasn’t appeared in a previous DS9UP article. There is no audio in this clip and you’ll need to raise the resolution to 4K, but I’ve created this file based on the DVD source with modifications in AviSynth, DaVinci Resolve, and Topaz Video Enhance AI.
Compare that to the actual credits ripped from the DVD and uploaded to YouTube by yours truly:
This is what the credits look like if you watch them on the source DVDs. The improvements from this version to my own are not small.
Upscalers are amazing and only getting better. That’s true no matter how you consume content or what technology you use to do it. Depending on the shows you like and how much time you want to sink into the project, there are tremendous improvements to be had… or you can just wait a few years, and buy a better TV. You can read more about DS9UP at the links below.
