Tech News - IoT and Hardware

Relayr, an IoT middleware startup based in Berlin, has been purchased by German insurance group Munich Re. The deal, which values relayr at $300 million, gives Munich Re’s subsidiary company HSB 100% equity in the startup. The move is significant, marking an important milestone in relayr’s life as it has moved from a crowdfunded chocolate-shaped IoT kit to an industrial IoT middleware platform used by 130 businesses. Essentially, relayr provides businesses with the software needed to connect industrial infrastructure to the internet in order for information and data about the performance and safety of that machinery to be managed and analyzed from a centralized place. But, perhaps even more importantly, the acquisition is evidence of just how attractive IoT is to an insurance industry that sees data as a potential goldmine in gaining a detailed understanding of behavior and risk in a huge range of contexts and across demographics. It’s worth noting that HSB has invested in relayr before - back in 2016 the company put money into the startup’s series B round of funding. What relayr and Munich Re had to say relayr CEO Josef Brunner had this to say about the acquisition: “We are delighted to strengthen our relationship with Munich Re/HSB to push digitalization in commercial and industrial markets and strive for our mission to help commercial and industrial businesses stay relevant… The unique combination of the companies demonstrates the importance to deliver business outcomes to customers and the need to combine first-class technology and its delivery with powerful financial and insurance offerings. This transaction is a great opportunity to build a global category leader.” Meanwhile, Torsten Jeworrek from Munich Re’s Board of Management said that the acquisition “supports our strategy to combine our knowledge of risk, data analysis skills and financial strength with the technological expertise of relayr. This is our basis to develop new ideas for tomorrow’s commercial and industrial worlds.” You can hear in the enthusiasm of both statements that this is a deal that works incredibly well for both parties. Munich Re now has its hands on an Industrial IoT startup that is already making headway in the market, while relayr now has the stability and support it needs to grow its business further. It will be interesting to see how the acquisition influences relayr’s product development and how involved its parent company will be. Read next Why the Industrial Internet of Things (IIoT) needs Architects Infosys and Siemens collaborate to build IoT solutions on MindSphere IoT Forensics: Security in an always connected world where things talk

Last week, James Carter and Stephen Smalley presented the architecture and security mechanisms of two operating systems, Zephyr and Fuchsia at the Linux Security Summit 2018. James and Stephen are computer security researchers in the Information Assurance Research organization of the US National Security Agency (NSA). They discussed the current concerns in the operating systems and their contribution and others to further advance security of these emerging open source operating systems. They also compared the security features of Zephyr and Fucshia to Linux and Linux-based systems such as Android. Zephyr Zephyr is a scalable real-time operating system (RTOS) for IoT devices, supporting cross-architecture with security as the main focus. It targets devices that are resource constrained seeking to be a new "Linux" for little devices. Protection mechanisms in Zephyr Zephyr introduced basic hardware-enforced memory protections in the v1.8 release and these were officially supported in the v1.9 releases. The microcontrollers should either have a memory protection unit (MPU) or a memory management unit (MMU) to support these protection mechanisms. These mechanisms provide protection by the following ways: They enforce Read Only/No Execute (RO/NX) restrictions to protect the read-only data from tampering. Provides runtime support for stack depth overflow protections. The researchers’ contribution was to review the basic memory protections and also develop a set of kernel memory protection tests that were modeled after subset of lkdtm tests in Linux from KSPP. These tests were able to detect bugs and regression in Zephyr MPU drivers and are now a part of the standard regression testing that Zephyr performs on all future changes. Userspace support in Zephyr In previous versions, everything ran in a supervisor mode, so Zephyr introduced a userspace support in v1.10 and v1.11. This requires the basic memory protection support and MPU/MMU. It provides basic support for user mode threads with isolated memory. The researchers contribution, here, was to develop userspace tests to verify some of the security-relevant properties for user mode threads, confirm the correctness of x86 implementation, and validate initial ARM and ARC userspace implementations. App shared memory: A new feature contributed by the researchers Originally, Zephyr provided an access to all the user threads to the global variables of all applications. This imposed high burden on application developers to, Manually organize application global variable memory layout to meet (MPU-specific) size/alignment restrictions. Manually define and assign memory partitions and domains. To solve this problem, the researchers developed a new feature which will come out in v1.13 release, known as App Shared Memory, having features: It is a more developer-friendly way of grouping application globals based on desired protections. It automatically generates linker script, section markings, memory partition/domain structures. Provides helpers to ease application coding. Fucshia Fucshia is an open source microkernel-based operating system, primarily developed by Google. It is based on a new microkernel called Zircon and targets modern hardware such as phones and laptops. Security mechanisms in Fucshia Microkernel security primitives Regular handles: Through handles, userspace can access kernel objects. They can identify both the object and a set of access rights to the object. With proper rights, one can duplicate objects, pass them across IPC, and obtain handles to child objects. Some of the concerns pointed out in regular handles are: If you have a handle to a job, you can get handle to anything in the job using object_get_child() Leak of root job handle Refining default rights down to least privilege Not all operations check access rights Some rights are unimplemented, currently Resource handles: These are a variant of handles for platform resources such as, memory mapped I/O, I/O port, IRQ, and hypervisor guests. Some of the concerns pointed out in resource handles are: Coarse granularity of root resource checks Leak of root resource handle Refining root resource down to least privilege Job policy: In Fucshia, every process is a part of a job and these jobs can further have child jobs. Job policy is applied to all processes within the job. These policies include error handling behavior, object creation, and mapping of WX memory. Some of the concerns pointed out in job policies are: Write execute (WX) is not yet implemented Inflexible mechanism Refining job policies down to least privilege vDSO (virtual dynamic shared object) enforcement: This is the only way to invoke system calls and is fully read-only. Some of the concerns pointed out in vDSO enforcement are: Potential for tampering with or bypassing the vDSO, for example, processs_writes_memory() allows you to overwrite the vDSO Limited flexibility, for example,  as compared to seccomp Userspace mechanisms Namespaces: It is a collection of objects that you can enumerate and access. Sandboxing: Sandbox is the configuration of a process’s namespace created based on its manifest. Some of the concerns pointed out in namespaces and sandboxing are: Sandbox only for application packages (and not system services) Namespace and sandbox granularity No independent validation of sandbox configuration Currently uses global /data and /tmp To address the aforementioned concerns the researchers suggested a MAC framework. It could help in the following ways: Support finer-grained resource checks Validate namespace/sandbox It could help control propagation, support revocation, apply least privilege Just like in Android, it could provide a unified framework for defining, enforcing, and validating security goals for Fuchsia. This was a sneak peek from the talk. To know more about the architecture, hardware limitations, security features of Zephyr and Fucshia in detail, watch the presentation on YouTube: Security in Zephyr and Fucshia - Stephen Smalley & James Carter, National Security Agency. Cryptojacking is a growing cybersecurity threat, report warns Red Hat Enterprise Linux 7.6 Beta released with focus on security, cloud, and automation Red Hat Enterprise Linux 7.6 Beta released with focus on security, cloud, and automation

Last week, the Yocto Project announced that Arm and Facebook will be joining the project as new platinum members. The Yocto Project is an open source collaboration project (originally an Intel Project) that was launched back in 2011. It aims to allow developers to create customized Linux-based systems for embedded products. The Yocto Project comes with a flexible set of tools and offers a space where embedded developers across the globe share technologies, software, and best practices. This helps them build tailored Linux images for embedded and Internet of Things (IOT) devices. According to Rhonda Dirvin, Senior Director, Marketing, Embedded & Automotive Line of Business, Arm, “The Yocto Project provides an excellent framework to facilitate embedded Linux development, and through our membership we will collaborate with the community to further advance Yocto Project’s custom open-source distribution.” Earlier, Linaro, which consolidates and optimizes open source software and tools for the Arm architecture, was considered a competitor of Yocto Project. However, that’s not entirely the case as both the groups have become complementary and Linaro’s Arm toolchain can be used within Yocto Project. Facebook's role in the Yocto Project and embedded Linux Facebook's role has been minor when it comes to embedded Linux. Facebook is said to join the Yocto Project either because of a new project or may be Facebook just wanted to expand its open source presence. “The Yocto Project is the basis for important open source and embedded firmware initiatives. We are happy to lend our support to the Yocto Project community, and look forward to joining with other members in this important work”, said Aaron Sullivan, Director of Hardware Engineering at Facebook The Yocto Project currently has more than 22 active members. “We are delighted to welcome Arm and Facebook to the Yocto Project at the Platinum level. With their continued support, we are furthering the embedded systems ecosystem and the Yocto Project as a whole.” mentioned Lieu Ta, Senior Director of Governance and Business Operations at Wind River and Chair of the Yocto Project Advisory Board. Yocto Project seems to be continually growing with Facebook and Arms joining in. Yocto will benefit from Facebook and Arm’s technical and financial support to consolidate it as a “secure, stable and adaptable industry standard”. For more information be sure to check out the official Yocto Project blog post. Read next Arm unveils its Client CPU roadmap designed for always-on, always-connected devices Facebook’s AI algorithm finds 20 Myanmar Military Officials guilty of spreading hate and misinformation, leads to their ban A new conservative employee group within Facebook to protest Facebook’s “intolerant” liberal policies

When we hear  the word robot, we may think of large industry sized robots assembling cars or humanoid ones. However there are such tiny robots that you may not even be able to see with the naked eye. Such six microbots are covered in this article which are in early development stages. Harvard's Ambulatory Microrobot (HAMR): A robotic cockroach Source: Hardvard HAMR is a versatile, 1.8-inch-long robotic platform that resembles a cockroach. The HAMR itself weighs in under an ounce and can run, jump and carry small items about twice its own weight. It is fast and can move with the speed of almost 19 inches per second. HAMR has given the researchers a useful base idea from which they can build other ideas. For example, the HAMR-F, an enhanced version of HAMR doesn't have any restraining wires. It can move around independently, it's only slightly heavier (2.8g) and slower than the HAMR. It is powered by a micro 8mA lithium polymer battery. Scientists at Harvard's School of Engineering and Applied Sciences also added footpads recently that allows the microbot to swim on water surface, sink and walk under water. Robotic bees: RoboBees Source: Harvard Like the HAMR, the RoboBee by Harvard has improved over time, it can also fly and swim. Its first successful flight was in 2013 and in 2015 it was able to swim. More recently in 2016, it gained the ability to "perch" on surfaces using static electricity. This allows the RoboBee to save power for loner flights. The 80-milligram robot can take a swim, leap up from the water, and then land. The RoboBee can flap its wings at 220 to 300 hertz in air and 9 to 13 hertz in water. μRobotex: microbots from France Source: Sciencealert Scientists from the Femto-ST Institute in France have built the μRobotex platform. It is a new, extremely small microrobot system. This system has been able to build the smallest house in the world inside a vacuum chamber. The robot used an ion beam to cut a silica membrane to tiny pieces for assembly. The micro house is 0.015 mm high and 0.020 mm broad. In comparison, a grain of sand is anywhere from 0.05 mm to 2 mm in diameter. The completed house was kept on the tip of an optical fiber piece as shown in the image above. Salto: a one-legged jumper Source: Wired Saltatorial locomotion on terrain obstacles (Salto), developed at University of California, is a one-legged jumping robot that is 10.2 inches tall when fully extended. It weighs about 100 grams, and can jump up to 1 meter in air. Salto's skills show when it can do more than just a single jump. It can bounce off walls and can perform several jumps in a row while avoiding obstacles. Salto was inspired by the galago, a small mammal expert at jumping. The idea of Salto was about robots that can leap over rubble, to provide emergency services. The newer model is the Salto-1P. Rolls Royce’s SWARM robots Source: Rolls Royce Rolls-Royce teamed up with scholars from the University of Nottingham and Harvard University to develop independent tiny mobile robots called SWARM. They are about 0.4 inches in diameter. They are a part of Rolls-Royce’s IntelligentEngine program. The SWARM robots are put into position by a robotic snake and use tiny cameras to capture parts of an engine which are hard to access otherwise. This is very useful for mechanics to figure out what is wrong with a car engine with greater accessibility. The future plan for SWARM is to perform inspections of aircraft engines in order to not remove from the airplanes. Short-Range Independent Microrobotic Platforms (SHRIMP) Source: DARPA The Defense Advanced Research Project Agency (DARPA) wants to develop insect-scaled robots with, "untethered mobility, maneuverability, and dexterity." In other words, they want microbots that can move around independently. DARPA is planning to sponsor these robots as part of the SHRIMP program for search and rescue, disaster relief, and hazardous environment inspection. It is also looking for robots that might work as prosthetics or eyes to see in places that are hard to reach. These microbots are in early development stages but on entering production they will be very resourceful. From medical assistance to guided inspection in small areas, these microbots will prove to be useful in a variety of areas. Intelligent mobile projects with TensorFlow: Build a basic Raspberry Pi robot that listens, moves, sees, and speaks [Tutorial] 15 millions jobs in Britain at stake with AI robots set to replace humans at workforce What Should We Watch Tonight? Ask a Robot, says Matt Jones from OVO Mobile [Interview]

Listening to the Arduino developer community, the Arduino team has released a command line interface (CLI) for it. The CLI is a single binary file that performs most of the features present in the IDE. There was a wide gap between using the IDE and being able to use CLI completely for everything in Arduino. The CLI will allow you to Install new libraries, create new projects, and compile projects directly from the command line. Developers will get an advantage to test their projects quickly. You can also create your own libraries and compile them directly, for your own or third-party codes. Installing project dependencies will be as easy as typing the following command: arduino-cli lib install "WiFi101” “WiFi101OTA” In addition, the CLI has a JSON interface added for easy parsing by other programs. There were many requests for makefiles integration and the support has been added for it. The Arduino CLI can run on both ARM and Intel (x86, x86_64) architectures which means it can be installed on a Raspberry Pi or on any server. Massimo Banzi, Arduino founder stated: “I think it is very exciting for Arduino, one single binary that does all the complicated things in the Arduino IDE.” The Arduino team looks forward to people seeing integrating this tool in various IDEs. In the blog post by the Arduino team they have mentioned, “Imagine having the Arduino IDE or Arduino Create Editor speaking directly to Arduino CLI – and you having full control of it. You will be able to compile on your machine or on our online servers, detect your board or create your own IDE on top of it!” CLI is a better alternative to PlatformIO and will work on all three major operating systems, Linux, Windows, and macOS. The code is open source but you will need a license for commercial use. Visit the GitHub repository to get started with Arduino CLI. How to assemble a DIY selfie drone with Arduino and ESP8266 How to build an Arduino based ‘follow me’ drone Should you go with Arduino Uno or Raspberry Pi 3 for your next IoT project?

We have Amazon Alexa, Google Home and Phillips Hue for smart actions in your home. But they are individual and require different controls. What if all of your smart devices can work together with a master hub? That is Home Assistant. Home assistant is an automation platform that can run on Raspberry Pi. It acts as a central hub for connecting and automating all your smart devices. It supports services like IFTTT, Pushbullet, Google cast, and many others. Currently there are over a thousand components supported. It tracks the state of all the installed smart devices in your home. All the devices can be controlled from a single, mobile-friendly, interface. For security and privacy, all operations via Home Assistant are done locally, meaning no data is stored on the cloud. The Home assistant website advertises functions like having lights turn on upon sunset, dimming lights when you watch a movie on Chromecast. There is a virtual image called Hass.io which is an all in one solution and get started with Home Assistant. There is a guide is to install Hass.io on a Raspberry Pi. The requirements for running Home Assistant are: Raspberry Pi 3 Model B+ + Power Supply (at least 2.5A) A Class 10 or higher, Size 32 GB or bigger Micro SD card An SD Card reader Ethernet cable (optional, Hass.io can work with WiFi) For unattended configuration, optionally a USB-Stick Home assistant is a hub, it cannot control anything on its own. Think of it as a hub that passes instructions, a master device that communicates with other devices for home automation. Home assistant can’t do anything if there are no smart devices to work with. Since it is open source, there are dozens of contributions from tinkerers and DIY enthusiasts worldwide. You can check out the automation examples to know more and use them. The installation is very simple and there is a friendly UI to control your automation tasks. There is plenty of information at the Home Assistant website to get your started. They also have a GitHub repository. Cortana and Alexa become best friends: Microsoft and Amazon release a preview of this integration Apple joins the Thread Group, signalling its Smart Home ambitions with HomeKit, Siri and other IoT products Amazon Echo vs Google Home: Next-gen IoT war

Arm, the world’s leading semiconductor IP company, for the first time have disclosed its forward-looking compute performance data and a CPU roadmap for their Client Line of Business from now through 2020. Every year they introduce new world-class CPU designs that have delivered double-digit gains in instructions-per-clock (IPC) performance since 2013. Their aim is to enable the PC industry to overcome their reliance on Moore’s law and deliver a high-performance, always-on, always-connected laptop experience. Key highlights of this client compute CPU roadmap Arm’s client roadmap 2018: Earlier this year, the launch of Cortex-A76 was announced. It delivers laptop-class performance while maintaining the power efficiency of a smartphone. We can expect hearing more on the first commercial devices on 7nm towards the end of the year and coming months. 2019: Arm will be delivering the CPU codenamed ‘Deimos’ to their partners, which is a successor to Cortex-A76. ‘Deimos’ is optimized for the latest 7nm nodes and is based on DynamIQ technology. DynamIQ redefines multi-core computing by combining the big and LITTLE CPUs into a single, fully-integrated cluster with many new and enhanced benefits in power and performance for mobile to infrastructure. With these added improvements, it is expected to deliver a 15+ percent increase in compute performance. 2020: The CPU codenamed ‘Hercules’ will be available to Arm partners. Same as ‘Deimos’, it is also based on DynamIQ technology and will be optimized for both 5nm and 7nm nodes. It is expected to improve power and area efficiency by 10 percent in addition to increase in the compute performance. What does this roadmap tell us? Take advantage of the disruptive innovation 5G will bring to all client devices. The innovations from their silicon and foundry partners will help Arm SoCs (System on Chip) to breakthrough the dominance of x86 and gain substantial market share in Windows laptops and Chromebooks over the next five years. The Arm Artisan Physical IP platform and Arm POP IP will help partners get every bit of performance-per-watt they can out of their SoCs on whatever process node they choose. This latest roadmap highlights that Arm is bringing new innovations and features to the PC industry with its annual cadence design. They will be talking more about their latest product releases and ecosystem developments at Arm TechCon which will be held in October this year. To know more about their CPU roadmap, head over to Arm’s news post. SpectreRSB targets CPU return stack buffer, found on Intel, AMD, and ARM chipsets Intel’s Spectre variant 4 patch impacts CPU performance AMD’s $293 million JV with Chinese chipmaker Hygon starts production of x86 CPUs

Yesterday, Microsoft and Amazon announced a public preview of the integration of their intelligent digital assistants, Cortana and Alexa for US users. Both Cortana and Alexa allow each digital assistant to summon each other and access additional apps and services on their Windows 10 PCs and Harman Kardon Invoke speakers. This digital assistant integration was first announced on 30th August last year and was demonstrated at the Microsoft Build Developer Conference, 2018. https://www.youtube.com/watch?v=KxwjnuhNVIY Why did Microsoft and Amazon collaborate Cortana and Alexa? "I want them to have access to as many of those A.I.s as possible", said Jeff Bezos in an interview with The New York times, while putting forth his vision for users to communicate with AIs as they do with their friends while asking them recommendations about a good restaurant or a famous hiking place nearby, and so on. He further stated, "The world is big and so multifaceted. There are going to be multiple successful intelligent agents, each with access to different sets of data and with different specialized skill areas. Together, their strengths will complement each other and provide customers with a richer and even more helpful experience." Satya Nadella, CEO, Microsoft added,"Bringing Cortana's knowledge, Office 365 integration, commitments, and reminders to Alexa is a great step toward that goal". Cortana users can have another way of making their lives easier with a great shopping experience. For instance, if you’re at work but remember you have to get soft drinks for a dinner party in the evening and you’re using their Windows 10 PC, iPhone or Android phone, you can simply ask Alexa to order soft drinks using the preferred payment method for their Amazon account. “Alexa, open Cortana” “Hey Cortana, open Alexa” For trying out this exciting update for Alexa on Cortana, and vice versa, you can simply say “Hey Cortana, open Alexa” on a Windows 10 PC, or “Alexa, open Cortana” on an Echo device. https://twitter.com/tomwarren/status/1029722099789832200 As explained by Amazon in one of its recent posts, “The goal is to have two integrated digital assistants who can carry out tasks across different dimensions of daily life — at home or work, and on whatever device is most convenient. Currently, Cortana and Alexa can each be enabled as a skill on the other.” In Microsoft Office 365 users can simply ask Cortana to summon Alexa through a PC at work or can use Alexa to order groceries, adjust the thermostat before heading home for the day. Also before heading to work, one could enlist Cortana through an Echo device to preview a daily calendar, add an item to a to-do list or check for new emails while making breakfast in the kitchen. As a part of this latest public preview, users can freely offer their feedback on how they can help both the communities in improving the Alexa+Cortana experience. The feedback will be based on what the users like, what they did not, and what features they use the most. With customer feedback, the experience will keep getting better and more precise as more people use it and as changes are updated to the underlying algorithms. “Engineers will use feedback from the public preview to deepen the collaboration between Cortana and Alexa”, stated Jennifer Langston in Amazon’s official post. Read more about this collaboration in detail on the  Amazon blog and Microsoft blog. Amazon Alexa and AWS helping NASA improve their efficiency Amazon Echo vs Google Home: Next-gen IoT war Microsoft Azure’s new governance DApp: An enterprise blockchain without mining

Rigetti computers are committed to building the world’s most powerful computers and they believe the true value of quantum will be unlocked by practical applications. Rigetti CEO Chad Rigetti, posted recently on Medium about their plans to deploy 128 qubit chip quantum computing system, challenging Google, IBM, and Intel for leadership in this emerging technology. They have planned to deploy this system in the next 12 months and shared their investment in resources at the application layer to encourage experimentation on quantum computers. Over the past year, Rigetti has built 8-qubit and 19-qubit superconducting quantum processors, which are accessible to users over the cloud through their open source software platform Forest. These chips have been useful in helping researchers around the globe to carry out and test programs on their quantum-classical hybrid computers. However, to drive practical use of quantum computing today, Rigetti must be able to scale and improve the performance of the chips and connect them to the electronics on which they run . To achieve this, the next phase of quantum computing will require more power at the hardware level to drive better results. Rigetti is in a unique position to solve this problem and build systems that scale. Chad Rigetti adds, “Our 128-qubit chip is developed on a new form factor that lends itself to rapid scaling. Because our in-house design, fab, software, and applications teams work closely together, we’re able to iterate and deploy new systems quickly. Our custom control electronics are designed specifically for hybrid quantum-classical computers, and we have begun integrating a 3D signaling architecture that will allow for truly scalable quantum chips. Over the next year, we’ll put these pieces together to bring more power to researchers and developers.” While they are focussed on building the 128 qubit chip, the Rigetti team is also looking at ways to enhance the application layer by pursuing quantum advantage in three areas; i.e. quantum simulation, optimization and machine learning. The team believes quantum advantage will be achieved by creating a solution that is faster, cheaper and of a better quality. They have posed an open question as to which industry will build the first commercially useful application to add tremendous value to researchers and businesses around the world. Read the full coverage on the Rigetti Medium post. Quantum Computing is poised to take a quantum leap with industries and governments on its side Q# 101: Getting to know the basics of Microsoft’s new quantum computing language PyCon US 2018 Highlights: Quantum computing, blockchains and serverless rule!

The Siggraph 2018 Conference brought in the biggest announcements from Nvidia unveiling a new turing architecture and three new pro-oriented workstation graphics cards in its Quadro family. This is the greatest leap for Nvidia since the introduction of the CUDA GPU in 2006. The Turing architecture features new RT Cores to accelerate ray tracing and new Tensor Cores for AI inferencing to enable real-time ray tracing. The two engines along with more powerful compute for simulation and enhanced rasterization will usher in a new generation of hybrid rendering to address the $250 billion visual effects industry. Hybrid rendering enables cinematic-quality interactive experience, amazing new effects powered by neural networks and fluid interactivity on highly complex models. The company also unveiled its initial Turing-based products - the NVIDIA® Quadro® RTX™ 8000, Quadro RTX 6000 and Quadro RTX 5000 GPUs. They are expected to revolutionize the work of approximately 50 million designers and artists across multiple industries. At the Annual Siggraph conference, Jensen Huang, founder and CEO, Nvidia mentions, “Turing is NVIDIA’s most important innovation in computer graphics in more than a decade. Hybrid rendering will change the industry, opening up amazing possibilities that enhance our lives with more beautiful designs, richer entertainment and more interactive experiences. The arrival of real-time ray tracing is the Holy Grail of our industry.” Here’s the list of Turing architecture features in detail. Real-Time Ray Tracing Accelerated by RT Cores The Turing architecture is armed with dedicated ray-tracing processors called RT Cores. It will accelerate the computation similar to light and sound travel in 3D environments at up to 10 GigaRays a second. Turing will accelerate real-time ray tracing operations by up to 25x than that of the previous Pascal generation. GPU nodes can be used for final-frame rendering for film effects at more than 30x the speed of CPU nodes. AI Accelerated by powerful Tensor Cores The Turing architecture also features Tensor Cores, processors that accelerate deep learning training and inferencing, providing up to 500 trillion tensor operations a second. It will power AI-enhanced features for creating applications with new capabilities including DLAA (deep learning anti-aliasing). DLAA is a breakthrough in high-quality motion image generation for denoising, resolution scaling and video re-timing. These features are part of the NVIDIA NGX™ software development kit, a new deep learning-powered technology stack. It will enable developers to easily integrate accelerated, enhanced graphics, photo imaging and video processing into applications with pre-trained networks Faster Simulation and Rasterization with New Turing Streaming Multiprocessor A new streaming multiprocessor architecture is featured in the new Turing-based GPUs to add an integer execution unit, that will execute in parallel with the floating point datapath. A new unified cache architecture with double bandwidth of the previous generation is added too. As it is combined with new graphics technologies like variable rate shading, the Turing SM achieves unprecedented levels of performance per core. With up to 4,608 CUDA cores, Turing supports up to 16 trillion floating point operations in parallel with 16 trillion integer operations per second. Developers will be able to take advantage of NVIDIA’s CUDA 10, FleX and PhysX SDKs to create complex simulations, such as particles or fluid dynamics for scientific visualization, virtual environment and special effects. The new Turing architecture has already received support from companies like Adobe, Pixar, Siemens, Black Magic, Weta Digital, Epic Games and Autodesk. The new Quadro RTX is priced at $2,300 for a 16GB version and $6,300 for 24GB version. Double the memory to 48GB and Nvidia expects you to pay about $10,000 for the high-end card. For more information you may visit the Nvidia official blog page. IoT project: Design a Multi-Robot Cooperation model with Swarm Intelligence [Tutorial] Amazon Echo vs Google Home: Next-gen IoT war 5 DIY IoT projects you can build under $50

The Raspberry Pi board developers can now make use of the latest TensorFlow 1.9 features to build their board projects. Most developers use Raspberry Pi for shaping their innovative DIY projects. The Pi also acts as a pathway to introduce people to programming with an added benefit of coding in Python. The main objective of blending TensorFlow with the Raspberry Pi board is to let people explore the capabilities of machine learning on cost-effective and flexible devices. Eben Upton, the founder of the Raspberry Pi project, says, “It is vital that a modern computing education covers both fundamentals and forward-looking topics. With this in mind, we’re very excited to be working with Google to bring TensorFlow machine learning to the Raspberry Pi platform. We’re looking forward to seeing what fun applications kids (of all ages) create with it.” By being able to use TensorFlow features, existing users, as well as new users, can try their hand on live machine learning projects. Here are few real-life examples of Tensorflow on Raspberry Pi: DonkeyCar platform DonkeyCar, a platform to build DIY Robocars, uses TensorFlow and the Raspberry Pi to create self-driving toy cars. Object Recognition Robot The Tensorflow framework is useful for recognizing objects. This robot uses a library, a camera, and a Raspberry Pi, using which one can detect up to 20,000 different objects. Waste sorting robot This robot is capable of sorting every piece of garbage with the same precision as a human. This robot is able to recognize at least four types of waste. To identify the category to which it belongs, the system uses TensorFlow and OpenCV. One can easily install Tensorflow from the pre-built binaries using Python pip package system from the pre-built binaries. One can also install it by simply running these commands on the Raspbian 9 (stretch) terminal: sudo apt install libatlas-base-dev pip3 install tensorflow Read more about this project on GitHub page 5 DIY IoT projects you can build under $50 Build your first Raspberry Pi project How to mine bitcoin with your Raspberry Pi

Microsoft’s tiny two-in-one tablet Surface Go is now shipping! Microsoft launched Surface Go last month, as the smaller, and cheaper version of its expensive counterpart, the Surface Pro device. Surface Pro is Microsoft’s response to the popular 2018 iPad and Chromebooks with features such as a 10-inch screen, front-facing camera with facial recognition, USB-C 3.1 port, and an integrated kickstand among others. Surface Go comes with Intel’s Pentium Gold 4415Y processor. Its processor is a dual-core seventh-generation model. According to Microsoft, this was chosen as it is able to provide the right balance between performance, battery life, and thermal properties which allows for a thin, fanless design. The device comes with a 10-inch display and weighs nearly 500g. The base model of the Surface Go is $399, the upgraded version, however, costs around $549 per model. Those prices don’t include the cost of the Surface keyboard, which comes for $100 extra for a basic model. You can also get the keyboard in $125 Alcantara Signature version. It also supports inking with the Surface Pen costing $99. There’s also a new $34.99 Surface Mobile Mouse. It is a two-button, ambidextrous, Bluetooth mouse which comes with a scroll wheel. It is available in colors like silver, red, and blue. For now Surface Pro is available to purchase online from the Microsoft Store in 25 countries only. Depending on the region the prices may vary. For the US, the price ranges between $399 and $599 depending on the RAM (4 or 8GB), storage (64 or 128GB), as well as the operating system (Windows 10 Home S-mode, or Windows 10 Pro). Microsoft launches Surface Go tablet at just $399 Microsoft launches a free version of its Teams app to take Slack head on Microsoft Edge introduces Web Authentication for passwordless web security

A video went viral in February showcasing a dog like robot opening a door for another robot. These agile robots are the brainchild of Boston Dynamics, an American Robotics company. Fast forward to this month, Boston Dynamics is all geared up to produce thousands of these robot dogs. According to a report by Inverse, the company has set a target date of July 2019 to manufacture 1,000 of its SpotMini robot dogs annually. SpotMini is a smaller variant of Boston Dynamics’ many robots. This four-legged robot weighs around 30 kgs and can comfortably fit in an office or home. It is one of the quietest robots built by the company. SpotMini is completely mobile with a 5 degree-of-freedom arm. It also has multiple perception sensors for navigation and mobile manipulation. SpotMini Spot, SpotMini’s elder version stands at close to four feet and weighs about 75 kgs. This four-legged robot is exclusively made for rough terrain mobility and superhuman stability. Its video has been streamed on Youtube nearly 19 million times. Spot According to founder Marc Raibert, SpotMini is currently being tested for use in construction, delivery, security, and home assistance applications. The company has already announced plans to launch it in 2019 as their short-term goal. They have currently built almost ten robodogs by hand, and are in plans to build 100 models with contract manufacturers at the end of this year. In the long run, the company intends SpotMini to eventually become a multi-use platform of sorts. At TechCrunch’s TC Sessions: Robotics event 2018, Raibert stated that “the goal for us is to become the what Android operating system is for phones: a versatile foundation for limitless applications.” Sony resurrects robotic pet Aibo with advanced AI AI powered Robotics : Autonomous machines in the making How to assemble a DIY selfie drone with Arduino and ESP8266 What we learned at the ICRA 2018 conference for robotics & automation

Last week Intel acquired eASIC, a fabless semiconductor company that makes customizable eASIC chips for use in wireless and cloud environments. The actual transaction amount for this merger was not disclosed by Intel. They believe that this acquisition is more “strategic” than just pure business as the competition for FPGAs is booming due to increasing demand for data and cloud services. The rise of FPGAs and Intel’s strategy to diversify beyond CPUs FPGAs were first introduced back in the 80s and were considered as an evolution in the path of fabless semiconductors. With each passing year, researchers have been trying to find innovative solutions to improve system performance, to meet the needs of big data, cloud computing, mobile, networking and other domains. FPGA is at the heart of this quest to develop high performing systems and is being paired with CPU’s to facilitate compute-intensive operations. Intel has a Programmable Solutions Group (PSG), which they created after acquiring Altera in 2015 for $16.7 billion. Altera is considered to be one of the leading FPGA manufacturers. The idea behind the eASIC acquisition is to complement Altera chips with eASIC’s technology. Dan McNamara, corporate vice president and GM of the PSG division mentioned in the official announcement, “We’re seeing the largest adoption of FPGA ever because of explosion of data and cloud services, and we think this will give us a lot of differentiation versus the likes of Xilinx”. Xilinx leads the race in the FPGA market with Intel being a distant second. The acquisition of eASIC is seen as a step towards catching up with the market leaders. Intel’s most recent quarterly earnings reports showed that PSG division had earned $498 million with 17% compound annual growth rate (CAGR), whereas on the other hand the company’s biggest division ‘Client Computing Division (CCG) made $8.2 billion but with a CAGR of 3%. Although PSG’s overall revenue is small when compared to CCG, it shows potential in terms of future growth. Hence Intel plans to increase their investments in acquiring futuristic companies like eASIC. It wouldn’t be surprising that we will see more such acquisitions in the coming years. You can visit Intel’s PSG blog for more interesting news on FPGAs. Frenemies: Intel and AMD partner on laptop chip to keep Nvidia at bay Baidu releases Kunlun AI chip, China’s first cloud-to-edge AI chip AMD’s $293 million JV with Chinese chipmaker Hygon starts production of x86 CPUs

Microsoft stepped up its tablet game by releasing the all-new Surface Go yesterday. The 10-inch Windows tablet looks exactly likes its expensive and popular counterpart, the Surface Pro device. Only smaller, less powerful and way cheaper, starting at $399. It includes features such as a 10-inch screen, front-facing camera with facial recognition, USB-C 3.1 port, and an integrated kickstand among others. Source: Microsoft Mechanics Let’s have a look at the features that make this tablet all the more alluring: Design Surface Go comes with a  built-in kickstand which includes unlimited positions. It has got corners that are slightly round as compared to the latest Surface Pro and a user familiar magnesium design surface. It weighs 1.15 lbs, making it a bit heavier as compared to the iPad but lighter than the Surface Pro. It consists of large bezels surrounding the screen which provides a place to hold the tablet. You get wider keyboard attachment with these bezels even though they make the tablet look quite dated when compared to the latest versions of the iPad. Display The Go has a smaller 3:2 aspect ratio display (1800 x 1200 pixel resolution). Its 3:2 touchscreen makes it easy for the users to use Go in landscape mode for more productivity. It also supports all the split-screen and multitasking modes that are available in Windows 10. Processor It comes with Intel’s Pentium Gold 4415Y processor with a RAM of either 4GB or 8GB. It provides storage of 64GB  eMMC or a 128GB SSD. Its processor is a dual-core seventh-generation model. According to Microsoft, this was chosen as it is able to provide the right balance between performance, battery life, and thermal properties which allows for a thin, fanless design. Battery Microsoft Surface Go has a USB-C 3.1 port which is Microsoft’s signature surface connector. This helps charge the tablet along with outputting video and data to external devices. Microsoft says the Surface Go tablet comes with up to nine hours of battery life. Additional Features Operating System: Go Tablet runs Windows 10 with S mode enabled. With Go, you can access only Edge browser and apps that are available in the Microsoft Store. Keyboard: The Surface Go consists of an additional keyboard cover which is available in four different colors, and can work with an optional Surface Pen. The Surface Go’s Type Cover provides “laptop-class typing” that comes with a scissor-key mechanism as well as 1 mm of key travel. The trackpad is much larger than the trackpad on the current Type Cover for the Surface Pro. If you add the keyboard, it will increase the price of the Go tablet to $99 or $129 ( depending on which color you choose) while the Pen adds another $99. There’s also a new $34.99 Surface Mobile Mouse. It is an ambidextrous, and two-button Bluetooth mouse which comes with a scroll wheel. It is available in colors like silver, red, and blue which matches the keyboard cover and pen. The new Surface Go is available for pre-order starting today and will start shipping in August. Leap Motion open sources its $100 augmented reality headset, North Star HTC Vive Focus 2.0 update promises long battery life, among other things for the VR headset