Microsoft Word now has a new ‘Read Aloud’ feature that has been finely tuned for users with dyslexia. The Read Aloud feature is similar to the existing Read Mode that came out in December, The Verge reported on Wednesday.
The software giant has been testing text-to-speech features in Word for quite some time. The new feature has come out of the Office 365 pipeline through which users with reading difficulties can easily change speed and voice.
It has the capabilities to let the user change voice and speed and interact with edits in real-time, the report added. Read Aloud feature is currently available to Insider versions of Office 365.
Apart from Windows desktops, it will be available for other operating systems later this year. Dyslexia is a specific learning disability who have trouble reading accurately and fluently. They may also have trouble with reading comprehension, spelling, and writing.
A recent Windows 10 Insider Preview build revealed a new feature that is expected to arrive with the Windows 10 Fall Creators Update – smart search for photos uploaded to OneDrive. Spotted in the updated Photos app, the feature used machine learning to categorise images, for quicker search later.
The new Photos’ smart search feature reportedly takes a second per image to search. The feature is very similar to Google Photos, and the recently Photos app on iOS, it also has face detection that will group photos of what the app believes is the same person.
AMD has formally announced a return to the enthusiast-class gaming space with new graphics cards based on its next-generation Vega architecture. The new AMD Radeon RX Vega series takes on Nvidia’shigher-end GeForce GTX 10-series cards, targeting gamers who want 4K quality and variable refresh rates. The new cards will be positioned above the existing Radeon RX 500 series.
There are two primary models, the Radeon RX Vega 56 and Radeon RX Vega 64. As their names suggest, they have 56 or 64 of AMD’s next-gen Vega compute units, for a total of 4,096 or 3,584 execution blocks called “stream processors”. This makes these cards capable of delivering 10.5 Teraflops and 12.66 Teraflops of compute power respectively. Both GPUs have 8GB of HBM2 memory on a 2048-bit bus. Memory bandwidth is 410GBps for the Vega 56 and 483.8GBps for the Vega 64.
There is also a Radeon RX Vega 64 Liquid Cooled Edition which has an integrated closed-loop liquid cooler with a 120mm radiator, but is otherwise no different from its namesake. It can push out 13.7 Teraflops because of its clock speed can reach 1677MHz as opposed to 1546MHz for the is the regular Vega 64 and 1471MHz for the Vega 56. Its power consumption is also rated at a massive 345W, rather than 295W and 210W for the two air-cooled cards.
AMD’s own cards use blower-style coolers similar to the ones used on previous reference designs, but third-party manufacturers will be launching their own cards with the same GPUs. Reference cards will have three DisplayPorts and one HDMI output, plus hardware switches to control the colour of the LED accents.
The Vega 56 is priced at $399 (approximately Rs. 25,625) while the standard Vega 64 costs $499 (approximately Rs. 32,045) and its liquid-cooled counterpart costs $699 (approximately Rs. 44,890). They will all go on sale in the US on August 14. Pricing and availability in India are not yet known. The company also teased a small-form-factor Radeon RX Vega Nano card, though no information about its specifications or capabilities is yet known, as well as Project 47, a server product that packs 1 Petaflop of processing power in a single rack.
Because of the likelihood that these cards will be snapped up by cryptocurrency miners just like the Radeon RX 500 series, prices could be driven up and gamers could end up frustrated. AMD is trying to even the playing field by selling a number of each card as part of what it is calling “Radeon Packs”, at least in the US. These cost $100 extra but give users a $200 discount on Samsung’s CF791 34-inch Freesync-enabled curved monitor, a $100 discount on a Ryzen 7 CPU and motherboard bundle, and coupons for Wolfenstein II and Prey, adding up to another $120. AMD hopes that the extra cost will dissuade miners and be helpful to gamers building a new PC.
AMD also confirmed the existence of a third member of its upcoming Ryzen Threadripper enthusiast CPU lineup. The Ryzen Threadripper 1900X will have 8 cores and 16 threads, joining the 12-core and 16-core Threadripper 1920X and 1950X. It has a base clock speed of 3.8GHz, a boost clock of 4.0GHz and an XFR limit of 4.2GHz. It will have a $549 price tag and use the same X399 platform as its bigger siblings, which sets it apart from the octa-core Ryzen 7 family because it will be able to work with the full complement of 64 PCIe lanes, and has a 180W thermal ceiling for overclocking.
This appears to be a response to Intel’s Core-X family, which includes mainstream Kaby Lake-X CPUs with fewer cores and PCIe lanes. The Ryzen Threadripper 1950X and 1920X will be on store shelves in the US on August 10, while the 1900X will launch on August 31.
Apple on Tuesday delivered surprisingly strong fiscal third-quarter earnings and signalled that its upcoming 10th-anniversary phone lineup is on schedule, driving the stock up 6 percent to an all-time high in after-hours trading.
The stock climbed above its intraday record high to $159.10 after the company reported better-than-expected iPhone sales, revenue and earnings per share. The stock price move was expected to help drive the Dow Jones Industrial Average over the 22,000 mark on Wednesday.
Apple also said it hit a milestone of 1.2 billion iPhones sold.
The April-June quarter is traditionally a soft one for Apple as the market waits for the September launch of new iPhone models. But Tuesday’s results show that iPhone buyers may be less inclined than they once were to delay purchases until a new model is out.
The iPad product lines also showed unexpected strength, service revenue continues to grow at a healthy clip, and even the much-maligned Apple Watch showed a 50 percent sales increase.
Apple is widely tipped to adopt higher-resolution OLED displays for the latest iPhone, along with better touchscreen technology and wireless charging – which could come with a $1,000 plus price tag.
The phone is expected to launch in September.
The company forecast total revenue of between $49 billion (roughly Rs. 3,14,198 crores) and $52 billion (roughly Rs. 3,33,452 crores) for the current fourth quarter, while analysts on average were expecting $49.21 billion, according to Thomson Reuters I/B/E/S.
Apple’s fourth quarter generally includes first-weekend sales of the company’s latest devices.
The forecast “makes it fairly certain that at least some new iPhone models will be released on the normal schedule,” said analyst Jan Dawson of Jackdaw Research. “That doesn’t necessarily mean all new models will go on sale then, or that they’ll all be in abundant supply, but I would think it means that at the very least the successors to the current phones will be available.”
But Bob O’Donnell, chief analyst at TECHnalysis Research, cautioned that if Apple releases cheaper models before the premium models in its 10th anniversary phone lineup, the cheaper models could dampen sales of more expensive units released closer to the holidays.
The company said iPhone sales rose 1.6 percent to 41.03 million in the third quarter ended July 1, above analysts’ average estimate of 40.7 million units, according to FactSet StreetAccount. Apple sold 40.4 million iPhones a year earlier.
But a lower average iPhone selling price of $606, well below Wall Street expectations of $621, caused iPhone revenue to come in at $24.8 billion, below expectations of $25.5 billion.
Apple Chief Financial Officer Luca Maestri told Reuters the weak price was partly explained byApple lowering the flow of inventory by 3.3 million units, which he said were “entirely at the high end of the range.”
Apple reports how many phones it sells to retailers, not how many phones it sells to consumers, what is known as a sell-in basis. When factoring how many existing “high end” phones the company cleared out of retail inventory, Maestri said average selling prices were higher.
The company’s net income rose to $8.72 billion (roughly Rs. 55,911 crores), or $1.67 per share, from $7.80 billion, or $1.42 per share, a year earlier.
Revenue rose to $45.41 billion (roughly Rs. 2,91,161 crores) from $42.36 billion in the quarter, typically the company’s weakest, beating expectations of $44.89 billion.
Samsung has already announced that the company will launch the Galaxy Note 8 smartphone on August 23 and several leaked renders have given a fairly good idea about the handset’s design. Now, the final specifications that will be offered by the smartphone have also been leaked and suggest that the upcoming Galaxy Note series flagship will pack an impressive 6GB of RAM.
After leaking the renders of Samsung Galaxy Note 8 earlier, Venture Beat’s Evan Blass aka @evleaks has now leaked the alleged final specifications of the smartphone. As per the report, Galaxy Note 8 will sport a 6.3-inch QHD (1440×2960 pixels) Infinity Display with an aspect ratio of 18:5:9. It is expected to be powered by Exynos 8895 SoC globally, but use Qualcomm Snapdragon 835 in the US, just like the Samsung Galaxy S8 and Galaxy S8+.
The highlight feature of the Samsung Galaxy Note 8, apart from its S Pen stylus, is expected to be its camera. The Samsung Galaxy Note 8 is expected to come with a dual camera setup with two 12-megapixel sensors. The primary wide-angle lens comes with an f/1.7 aperture and dual-pixel autofocus, while the secondary telephoto lens has an f/2.4 aperture and enables a 2x optical zoom, as per the report. Both the lenses are also said to offer optical image stabilisation as well.
As mentioned earlier, the Samsung Galaxy Note 8 will be packing 6GB of RAM, an improvement over Galaxy S8 models that were launched with 4GB of RAM. The Galaxy Note 8 has been tipped to come with 64GB of built-in storage, which will be further expandable via microSD card. The handset is expected to measure 162.5×74.6×8.5mm. Galaxy Note 8 has been tipped to house a 3300mAh battery that can be charged either wirelessly or through USB Type-C. The handset is expected to come with a a fingerprint scanner at back.
The Samsung Galaxy Note 8 has also been tipped to be offered in Midnight Black and Maple Gold colours initially but is expected to be launched in Orchid Grey and Deep Sea Blue colours later. To recall, Blass recently shared the renders of the smartphone in these colours recently. As per the report, the Galaxy Note 8 will cost around EUR 1,000 (roughly Rs. 75,400) in Europe when it will start to ship in September.
LG is set to launch the much rumoured LG V30 smartphone soon, and new information about the smartphone keeps trickling in regularly. In fresh reports, LG has now confirmed that the company is making the switch to OLED in its upcoming flagship, which will sport a FullVision display – meaning really less bezel. Also, more spec information about the smartphone has been leaked revealing its display size and camera details.
LG has now confirmed that its next flagship, highly rumoured to be the LG V30, will switch to OLED with a QHD+ (1440 x 2880 pixels) resolution. This means more battery life and durability. The company also says that the plastic OLED aka P-OLED display tech will allow for curved edges on the sides, but the shared image showing the bottom part of the smartphone suggests that it won’t copy Samsung’s Edge feature, and the display will only be slightly tapered.
The LG V30 display will take on the 18:9 FullVision aspect ratio, just like the LG G6, and the company says it will cover 109 percent of the DCI-P3 colour space and support HDR10 as well. LG also says that the upper and lower bezels have been reduced by 20 to 50 percent, despite the upcoming flagship being lower in overall form size than last year’s LG V20. The logo, LG confirms, has also been moved to the back panel.
Commenting on the impending launch, LG Electronics Mobile Communications President Juno Cho said, “Expertise in OLED has long been a core competency of LG, and the technology has always been seen as a potential value-add for smartphones. With competition in the global smartphone space fiercer now than ever, we felt that this was the right time to reintroduce OLED displays in our mobile products.”
Android Authority also shared some exclusive information about the LG V30 smartphone, particularly about the second screen seen on the predecessors. It claims that the secondary display is being ditched, in favour of a new ‘floating bar’. It essentially will provide quick access to notifications, shortcuts, and other things; however details on how it will look and work were scarce. The report also states that the LG V30 may sport Gorilla Glass 5 protection, and Daydream support. As per the report, the camera on the LG V30 will have an f/1.6 aperture, Crystal Clear Glass Lens, and “improved transmittance”. It will also have an improved audio experience, military standard protection, IP68 water resistance, and better cooling management.
Separately, an outline sketch of the LG V30 has also been leaked recently. In the image, claimed to be extracted from the user manual, the smartphone is set to have a bezel-less design, no home button, a horizontal dual camera setup at the back located in the centre, a fingerprint sensor right below it, and the LG logo at the bottom.
Previous reports suggest that the LG V30 may be offered in 32GB, 64GB, and 128GB storage capacities, and the dimensions could measure at 151.4×75.2×7.4mm. The smartphone has been tipped to be powered by Qualcomm Snapdragon 835 SoC and house a 3200mAh battery.
The LG V30 smartphone is expected to be announced on August 31 with US pre-orders set to begin on September 17, and the release date to be September 28.
Samsung launched its W2017 flip phone in China last year and now the South Korean company has introduced its successor – Samsung SM-G9298 – for the same market. Notably, the Samsung G-9298, aka Leader 8 aka Leadership 8 (translated from Chinese), comes with a more powerful processor and improved optics over the W2017 and has been made available only in Black colour for purchase.
The new dual-SIM (hybrid) Samsung SM-G9298 comes with two 4.2-inch full-HD (1080×1920 pixels) Super AMOLED displays – with one on the inside and one on the outside. The smartphone is powered by a quad-core Snapdragon 821 processor with two cores clocked at 2.15GHz and the other two clocked at 1.6GHz. The Samsung SM-G9298 packs 4GB of RAM.
In terms of optics, the Samsung SM-G9298 packs a 12-megapixel rear camera with f/1.7 aperture and a 5-megapixel front camera with f/1.9 aperture for taking selfies. It comes with 64GB of built-in storage, which is further expandable via microSD card up to 256GB.
The connectivity options offered by the Samsung SM-G9298 include 4G connectivity, micro USB, USB 2.0, Bluetooth v4.1, NFC, Wi-Fi a/b/g/n/ac, and GPS. It houses a 2300mAh battery that is rated to provide standby time of 68 hours. The Samsung G-9298 measures 130.2×62.6×15.9mm and weighs 235 grams. Other features offered by the smartphone include Samsung Pay, S Voice, and Secure Folder.
The onboard sensors on the Samsung SM-G9298 include accelerometer, barometer, a fingerprint sensor, and gyroscope. While Samsung has not announced the pricing of the smartphone, it will be made available with China Mobile in the country.
Oppo R11 and R11 Plus were announced sometime in June. These smartphones were the first ones in the global market to employ the Qualcomm Snapdragon 660 mobile platform.
However, a new Geekbench benchmark listing that has surfaced online has come as a surprise. We say so as the listing shows the Oppo R11 smartphone running the powerful Qualcomm Snapdragon 835 SoC under its hood. Also, the listing shows that this processor is teamed up with 6GB RAM. Going by the benchmark listing, the smartphone will be based on Android 7.1.1 Nougat out of the box. The Oppo R11 scores 1953 and 6329 points in the single-core and multi-core tests respectively in the Geekbench listing.
Currently, the Qualcomm Snapdragon 660 platform is the leader in the mid-range processor market segment. Given that this processor can deliver a high level of performance, there is no issue with Oppo making use of the same for its high-end and flagship devices. Moreover, the Chinese manufacturer Oppo is known for the practice of not using the flagship processors in its flagship smartphones for quite a few years. Also read: Oppo R11 to launch outside China in the coming week However, a new Geekbench benchmark listing that has surfaced online has come as a surprise. We say so as the listing shows the Oppo R11 smartphone running the powerful Qualcomm Snapdragon 835 SoC under its hood. Also, the listing shows that this processor is teamed up with 6GB RAM. Going by the benchmark listing, the smartphone will be based on Android 7.1.1 Nougat out of the box. The Oppo R11 scores 1953 and 6329 points in the single-core and multi-core tests respectively in the Geekbench listing. Also read: Oppo R11 receives 500,000 registrations in just 3 days As mentioned above, since the past few years, Oppo hasn’t been using flagship processors in its flagship smartphones. Eventually, the listing of the Oppo R11 with Snapdragon 835 SoC appears to be strange. We can expect the smartphone spotted on the benchmark database to be the upcoming Oppo Find 9 that is masked as the Oppo R11 in the listing.
Robots are reliable in industrial settings, where recognizable objects appear at predictable times in familiar circumstances. But life at home is messy. Put a robot in a house, where it must navigate unfamiliar territory cluttered with foreign objects, and it’s useless.
Now researchers have developed a new computer vision algorithm that gives a robot the ability to recognize three-dimensional objects and, at a glance, intuit items that are partially obscured or tipped over, without needing to view them from multiple angles.
“It sees the front half of a pot sitting on a counter and guesses there’s a handle in the rear and that might be a good place to pick it up from,” said Ben Burchfiel, a Ph.D. candidate in the field of computer vision and robotics at Duke University.
In experiments where the robot viewed 908 items from a single vantage point, it guessed the object correctly about 75 percent of the time. State-of-the-art computer vision algorithms previously achieved an accuracy of about 50 percent.
Burchfiel and George Konidaris, an assistant professor of computer science at Brown University, presented their research last week at the Robotics: Science and Systems Conference in Cambridge, Massachusetts.
Like other computer vision algorithms used to train robots, their robot learned about its world by first sifting through a database of 4,000 three-dimensional objects spread across ten different classes — bathtubs, beds, chairs, desks, dressers, monitors, night stands, sofas, tables, and toilets.
While more conventional algorithms may, for example, train a robot to recognize the entirety of a chair or pot or sofa or may train it to recognize parts of a whole and piece them together, this one looked for how objects were similar and how they differed.
When it found consistencies within classes, it ignored them in order to shrink the computational problem down to a more manageable size and focus on the parts that were different.
For example, all pots are hollow in the middle. When the algorithm was being trained to recognize pots, it didn’t spend time analyzing the hollow parts. Once it knew the object was a pot, it focused instead on the depth of the pot or the location of the handle.
“That frees up resources and makes learning easier,” said Burchfiel.
Extra computing resources are used to figure out whether an item is right-side up and also infer its three-dimensional shape, if part of it is hidden. This last problem is particularly vexing in the field of computer vision, because in the real world, objects overlap.
To address it, scientists have mainly turned to the most advanced form of artificial intelligence, which uses artificial neural networks, or so-called deep-learning algorithms, because they process information in a way that’s similar to how the brain learns.
Although deep-learning approaches are good at parsing complex input data, such as analyzing all of the pixels in an image, and predicting a simple output, such as “this is a cat,” they’re not good at the inverse task, said Burchfiel. When an object is partially obscured, a limited view — the input — is less complex than the output, which is a full, three-dimensional representation.
The algorithm Burchfiel and Konidaris developed constructs a whole object from partial information by finding complex shapes that tend to be associated with each other. For instance, objects with flat square tops tend to have legs. If the robot can only see the square top, it may infer the legs.
“Another example would be handles,” said Burchfeil. “Handles connected to cylindrical drinking vessels tend to connect in two places. If a mug shaped object is seen with a small nub visible, it is likely that that nub extends into a curved, or square, handle.”
Once trained, the robot was then shown 908 new objects from a single viewpoint. It achieved correct answers about 75 percent of the time. Not only was the approach more accurate than previous methods, it was also very fast. After a robot was trained, it took about a second to make its guess. It didn’t need to look at the object from different angles and it was able to infer parts that couldn’t be seen.
This type of learning gives the robot a visual perception that’s similar to the way humans see. It interprets objects with a more generalized sense of the world, instead of trying to map knowledge of identical objects onto what it’s seeing.
Burchfiel said he wants to build on this research by training the algorithm on millions of objects and perhaps tens of thousands of types of objects.
“We want to build this is into single robust system that could be the baseline behind a general robot perception scheme,” he said.
Toys that teach kids to code are as hot in 2017 as Cabbage Patch Kids were in 1983, and for good reason. For today’s generation of children, learning how to program is even more important than studying a second language. Though there are many robot kits on the market that are designed for this purpose, Lego Boost is the best tech-learning tool we’ve seen for kids. Priced at a very reasonable $159, Boost provides the pieces to build five different robots, along with an entertaining app that turns learning into a game that even preliterate children can master.
How It Works
Boost comes with a whopping 847 different Lego bricks, along with one motor (which also serves as a dial control on some projects), one light/IR sensor and the Move Hub, a large white and gray brick with two built-in motors that serves as the central processing unit for the robot. The Hub connects to your tablet via Bluetooth, to receive your programming code, and to the other two electronic components via wires.
You can build five different robots with the kit: a humanoid robot named Vernie, Frankie the Cat, the Guitar 4000 (which plays real music), a forklift called the “M.I.R. 4” and a robotic “Auto Builder” car factory. Lego said that it expects most users to start with Vernie, who looks like a cross between film robots Johnny No. 5 and Wall-E and offers the most functionality.
To get started building and coding, kids have to download the Boost app to their iPad or Android tablets. You’ll need to have the app running and connected to the Move hub every time you use the robot. All of the processing and programming takes place on your mobile device, and the sound effects (music, the robot talking) will come out of your tablet’s speaker, not the robot itself.
The Boost App
Lego really understands how young children learn and has designed the perfect interface for them. The Boost app strikes a balance among simplicity, depth and fun. Boost is officially targeted at 7- to 12-year-olds, but the software is so intuitive and engaging that, within minutes of seeing the system, my 5-year-old was writing his own programs and begging me to extend his bedtime so he could discover more.
Neither the interface nor the block-based programming language contains any written words, so even children who can’t read can use every feature of the app. When you launch Boost, you’re first shown a cartoonish menu screen that looks like a room with all the different possible robots sitting in different spots. You just tap on the image of the robot you want to build or program, and you’re given a set of activities that begin with building the most basic parts of the project and coding them.
As you navigate through the Boost program, you need to complete the simplest levels within each robot section before you can unlock the more complicated ones. Any child who has played video games is familiar with and motivated by the concept of unlocking new features by successfully completing old ones. This level-based system turns the entire learning process into a game and also keeps kids from getting frustrated by trying advanced concepts before they’re ready.
Boost runs on modern iPads or Android devices that have at least a 1.4-GHz CPU, 1GB of RAM, Bluetooth LE, and Android 5.0 or above. (I also downloaded Boost to a smartphone, but the screen was so small that it was difficult to make out some of the diagrams.)
Unfortunately, Lego doesn’t plan to list the program in Amazon’s app store, which means you can’t easily use Boost with a Fire tablet, which is the top-selling tablet in the U.S. I was able to sideload Boost onto my son’s Fire 7 Kids Edition, but most users won’t have the wherewithal to do that. Lego makes its Mindstorm app available to Fire devices, so we hope the company will eventually see fit to do the same with Boost.
Unlocking New Levels and Challenges
When you load the Boost app for the first time, you need to complete a simple project that involves making a small buggy before you can build any of the five robots. This initial build is pretty fast, because it involves only basic things like putting wheels onto the car, programming it to move forward and attaching a small fan in the back.
Like the robot projects that come after it, the buggy build is broken down into three separate challenges, each of which builds on the prior one. The first challenge involves building the buggy and programming it to roll forward. Subsequent challenges involve programming the vehicle’s infrared sensor and making the fan in the back move.
After you’ve completed all three buggy challenges, the five regular robots are unlocked. Each robot has several levels within it, each of which contains challenges that you must complete. For example, Vernie’s first level has three challenges that help you build him and use his basic functions, while the second level has you add a rocket launcher to his body and program him to shoot.
If a challenge includes building or adding blocks to a robot, it gives you step-by-step instructions that show you which blocks go where, and only after you’ve gone through these steps do you get to the programming portion.
When it’s time to code, the app shows animations of a finger dragging the coding blocks from a palette on the bottom of the screen up onto the canvas, placing them next to each other and hitting a play button to run the program. This lets the user know exactly what to do at every step, but also offers the ability to experiment by modifying the programs at the end of each challenge.
In Vernie’s case, each of the first-level challenges involve building part of his body. Lego Design Director Simon Kent explained to us that, because a full build can take hours, the company wants children to be able to start programming before they’re even finished. So, in the first challenge, you build the head and torso, then program him to move his neck, while in the later ones, you add his wheels and then his arms.
Block-Based Programming Language
Like almost all child-coding apps, Boost uses a pictorial, block-based programming language that involves dragging interlocking pieces together, rather than keying in text. However, unlike some programming kits we’ve seen, which require you to read text on the blocks to find out what they do, Boost’s system is completely icon-based, making it ideal for children who can’t read (or can’t read very well) yet.
For example, instead of seeing a block that says, “Move Forward” or “Turn right 90 degrees,” you see blocks with arrows on them. All of the available blocks are located on a palette at the bottom of the screen; you drag them up onto the canvas and lock them together to write programs.
Some of the icons on the blocks are less intuitive than an arrow or a play button, but Boost shows you (with an animation) exactly which blocks you need in order to complete each challenge. It then lets you experiment with additional blocks to see what they do.
What makes the app such a great learning tool is that it really encourages and rewards discovery. In one of the first Vernie lessons, there were several blocks with icons showing the robot’s head at different angles. My son was eager to drag each one into a program to see exactly what it did (most turned the neck).
Programs can begin with either a play button, which just means “start this action” or a condition such as shaking Vernie’s hand or putting an object in front of the robot’s infrared sensor. You can launch a program, either by tapping on its play/condition button or on the play button in the upper right corner of the screen, which runs every program you have on screen at once.
Because the programs are mostly so simple, there are many reasons why you might want to have several running at once. For example, when my son was programming for the guitar robot, he had a program that played a sound when the slider on the neck passed over the red tiles, another one for when it passed over the green tiles and yet another for the blue tiles. In a complex adult program, these would be handled by an if/then statement, but in Boost, there are few loops (you can use them in the Creative Canvas free-play mode if you want), so making several separate programs is necessary.
While the program(s) run, each block lights up as it executes, so you know exactly what’s going on at any time. You can even add and remove blocks, and the programs will keep on executing. I wish all the adult programming tools I use at work had these features!
Toolboxes, Custom Programs
Though you write programs as part of each the challenges, if you really want to get creative, you need to head to the Coding Canvas mode. In each robot’s menu, to the right of the levels, there’s a red toolbox that you can tap on to write your own custom programs. As you complete different challenges that feature new functions, your Coding Canvas toolbox gets filled up with more code blocks that you can use.
My son had an absolute blast using the Guitar 4000’s toolbox mode to write a program in which moving the slider over the different colors on the guitar neck would play different clips of his voice.
Users who want to build their own custom robots and program them can head over to the Creative Canvas free-play mode by tapping on the open-window picture on the main menu. There, you can create new programs with blocks that control exactly what the Move Hub, IR sensor and motor do. So, rather than showing an icon with a block of a guitar playing like it does from within the Guitar 4000 menus, Boost shows a block with a speaker on it, because you can choose any type of sound from your custom robot.
In both Creative Canvas and Coding Canvas modes, Lego makes it easy to save your custom programs. The software automatically assigns names (which, coincidentally, are the names of famous Lego characters) and colorful icons to each of your programs for you, but children who can read and type are free to alter the names. All changes to programs are autosaved, so you never have to worry about losing your work.
As you might expect from Lego, Boost offers a best-in-class building experience with near-infinite expandability and customization. The kit comes with 847 Lego pieces, which include a combination of traditional-style bricks, with their knobs and grooves, and Technics-style bricks that use holes and plugs.
The building process for any of the Boost robots (Vernie, Frankie the Cat, M.I.R. 4, Guitar 4000 and Auto Builder) is lengthy but very straightforward. During testing, we built both Vernie and the Guitar 4000 robots, and each took around 2 hours for adults to complete. Younger kids, who have less patience and worse hand-eye coordination, will probably need help from an adult or older child, but building these bots provides a great opportunity for parent/child bonding time. My 5 year old (2 years below the recommended age) and I had a lot of fun putting the guitar together.
As part of the first challenge (or first several challenges), the app gives you a set of step-by-step instructions that show which bricks to put where. The illustrated instruction screens are very detailed and look identical to the paper Lego instructions you may have seen on any of the company’s kits. I just wish that the app made these illustrations 3D so one could rotate them and see the build from different angles like you can on UBTech’s Jimu Robots kit app.
All of the bricks connect together seamlessly and will work with any other bricks you already own. You could also easily customize one of the five recommended Boost robots with your own bricks. Imagine adorning Varney’s body with pieces from a Star Wars set or letting your Batman minifig ride on the MIR 4 forklift.
I really love the sky-blue, orange and gray color scheme Lego chose for the bricks that come with Boost, because it has an aesthetic that looks both high-tech and fun. From the orange wings on the Guitar 4000 robot to Vernie’s funky eyebrows, everything about the blocks screams “fun” and “inviting.”
Boost Versus Mindstorm and the Competition
At $159, the Lego Boost offers more for the money than any of the other robot kits we’ve reviewed, but it’s definitely designed for younger children who are new to programming. Older children or those who’ve used Boost for a while can graduate to Lego’s own Mindstorm EV3 kits, which start at $349 and use their own block-based coding language.
Starting at $129, UBTech’s line of Jimu robots offer a few more sensors and motors than Boost, along with a more complex programming language, but they definitely target older and more experienced kids, and to get a kit that makes more than one or two robots, you need to spend over $300. Sony’s Koov kit is also a good choice for older and more tech-savvy children, but it’s also way more expensive than Boost (starts at $199, but you need to spend at least $349 to get most features), and its set of blocks is much less versatile than Legos.
Tenka Labs’ Circuit Cubes start at just $59 and provide a series of lights and motors that come with Lego-compatible bricks, but these kits teach electronics skills, not programming.
The best robot/STEM kit we’ve seen for younger children, Lego Boost provides turns coding into a game that’s so much fun your kids won’t even know that they’re gaining valuable skills. Because it uses real Legos, Boost also invites a lot of creativity and replayability, and at $159, it’s practically a steal.
It’s a shame that millions of kids who use Amazon Fire tablets are left out of the Boost party, but hopefully, Lego will rectify this problem in the near future. Parents of older children with more programming savvy might want to consider a more complex robot set such as Mindstorms or Koov, but if your kid is new to coding and has access to a compatible device, the Boost is a must-buy.
Fitness-tracking wristbands and bracelets have mostly been used to count steps and monitor heart rate and vital signs. Now engineers have made a 3D-printed sensor that can be worn on the ear to continuously track core body temperature for fitness and medical needs.
The “earable” also serves as a hearing aid. And it could be a platform for sensing several other vital signs, says University of California Berkeley electrical engineering and computer science professor Ali Javey.
Core body temperature is a basic indicator of health issues such as fever, insomnia, fatigue, metabolic functionality, and depression. Measuring it continuously is critical for infants, elderly and those with severe conditions, says Javey. But wearable sensors available today in the form of wristbands and soft patches monitor skin temperature, which can change with the environment and is usually different from body temperature.
Body temperature can be measured using invasive oral or rectal readings. Ear thermometers measure infrared energy emitted from the eardrum and are easier to use than more invasive devices. That’s the route Javey and his colleagues took for their earable sensor, reported in the journal ACS Sensors.
For a customized fit to an individual’s ear, the team printed their sensor using flexible materials and a 3D printer. First they printed a gauzy, disc-shaped base using a stretchable polymer. This base contains tiny channels into which the researchers inject liquid metal to make electrical interconnects in lieu of metal wires. It also has grooves for an infrared sensor; microprocessors; and a Bluetooth module that transmits temperature readings to a smartphone app. They packaged the gadget in a 3D-printed case.
Because the device covers the ear, it could affect hearing, Javey says. So the engineers also embedded a bone-conduction hearing aid, made of a microphone; data-processing circuitry; a potentiometer for adjusting volume; and an actuator. The actuator sits by the temple and converts sound to vibrations, which are transmitted through the skull bone to the inner ear.
The earable accurately measured the core body temperature of volunteers wearing it in rooms heated or cooled to various temperatures, and while exercising on a stationary bicycle.
“It can be worn continuously for around 12 hours without recharging,” he says. “In the future, power can be further reduced by using lower power electronic components, including the Bluetooth module.”
The researchers plan to increase the device’s functionality by integrating sensors for measuring EEG, heart rate, and blood oxygen level. They also plan to test it in various environments.