Microsoft Technology Licensing, the licensing arm of Microsoft Corp., has been granted an international patent for a “cryptocurrency system using body activity data.” The patent was published by the World Intellectual Property Organization (WIPO) on March 26. The application was filed on June 20 last year. “Human body activity associated with a task provided to a user may be used in a mining process of a cryptocurrency system,” the patent reads, adding as an example: A brain wave or body heat emitted from the user when the user performs the task provided by an information or service provider, such as viewing advertisement or using certain internet services, can be used in the mining process. ... Different types of sensors can be used to “measure or sense body activity or scan human body,” the patent explains. They include “functional magnetic resonance imaging (fMRI) scanners or sensors, electroencephalography (EEG) sensors, near infrared spectroscopy (NIRS) sensors, heart rate monitors, thermal sensors, optical sensors, radio frequency (RF) sensors, ultrasonic sensors, cameras, or any other sensor or scanner” that will do the same job.
It is thought that Samsung has created a processor that is dedicated to protecting the user’s PIN, pattern, password, and Blockchain Private Key with a combination of their security Knox platform. This ensures that security on their new S20 range is secure. Introducing their Blockchain Keystore last year it initially only supported ERC-20 token but added bitcoin in August of last year. Using Samsung devices with Blockchain Keystore means users can store their bitcoin and crypto wallet private keys on the device. One of the most critical issues that is overlooked is the control over a private wallet key and in most cases is the reason why most crypto thefts and hacks happen, because users fail to store their tokens in the wallets they have private keys for. This then means that if bitcoin or crypto are stored on smartphone wallets, it gives users control over their private keys and removes the control and reliance on external companies. The adoption of crypto has fallen short in recent years concerning its expectations. However, user experience developments have helped innovate technology to make using crypto more accessible.
A network of Bitcoin-to-QR-code generators has stolen more than $45,000 from users in the past four weeks, ZDNet has learned. The nine websites provided users with the ability to enter their Bitcoin address, a long string of text where Bitcoin funds are stored, and convert it into a QR code image they could save on their PC or smartphone. Today, it's a common practice to share a Bitcoin address as a QR code and request a payment from another person. The receiver scans the QR code with a Bitcoin wallet app and sends the requested payment without having to type a lengthy Bitcoin addresses by hand. By using QR codes, users eliminate the possibility of a mistype that might send funds to the wrong wallet. Last week, Harry Denley, Director of Security at the MyCrypto platform, ran across a suspicious site that converted Bitcoin addresses into QR codes. While many services like this exist, Denley realized that the website was malicious in nature. Instead of converting an inputted Bitcoin (BTC) address into its QR code equivalent, the website always generated the same QR code -- for a scammer's wallet.
Despite its nascent status, the 5G ecosystem is already swimming in financial might. That same GSMA report predicts 5G technology will add $2.2 trillion to the global economy over the next 15 years. And operators are expected to spend more than $1 trillion on mobile capex between 2020 and 2025, with 80% of that spend directed at their 5G networks. While past technology evolutions primarily targeted the consumer market, the spend and return on 5G has a larger focus on the broader enterprise space. This includes connecting not just traditional enterprise workers and their respective mobile devices but connecting all electronic devices. This will involve a broader push toward edge deployments that can serve what are expected to be billions of connected and IoT devices. “With greater reliability and data speeds that will surpass those of 4G networks, a combination of 5G and local edge compute will pave the way for new business value,” ABI Research noted in a recent report, citing benefits gained from agility and process optimization; better and more efficient quality assurance and productivity improvement.
With automation technologies advancing quickly and early adopters demonstrating their effectiveness, now is the time to understand and prioritize opportunities for Internal Audit robotic process automation. And to take important steps to prepare for thoughtful, progressive deployment. The age of automation is here, and with it comes opportunities for integrating Internal Audit (IA) robotic process automation (RPA) into the third line of defense (aka Internal Audit). IA departments, large and small, have already begun their journey into the world of automation by expanding their use of traditional analytics to include predictive models, RPA, and cognitive intelligence (CI). This is leading to quality enhancements, risk reductions, and time savings—not to mention increased risk intelligence. The automation spectrum, as we define it, comprises a broad range of digital technologies. As shown below, at one end are predictive models and tools for data integration and visualization. At the other end are advanced technologies with cognitive elements that mimic human behavior. Many IA organizations are familiar with the first part of the automation spectrum, having already established foundational data integration and analytics programs to enhance the risk assessment, audit fieldwork, and reporting processes.
Why add classical AI to the mix? Well, we do all kinds of reasoning based on our knowledge in the world. Deep learning just doesn’t represent that. There’s no way in these systems to represent what a ball is or what a bottle is and what these things do to one another. So the results look great, but they’re typically not very generalizable. Classical AI—that’s its wheelhouse. It can, for example, parse a sentence to its semantic representation, or have knowledge about what’s going on in the world and then make inferences about that. It has its own problems: it usually doesn’t have enough coverage, because too much of it is hand-written and so forth. But at least in principle, it’s the only way we know to make systems that can do things like logical inference and inductive inference over abstract knowledge. It still doesn’t mean it’s absolutely right, but it’s by far the best that we have. And then there’s a lot of psychological evidence that people can do some level of symbolic representation.
Apache Flink is an open-source stream processing framework. It is widely used by a lot of companies like Uber, ResearchGate, Zalando. At its core, it is all about the processing of stream data coming from external sources. It may operate with state-of-the-art messaging frameworks like Apache Kafka, Apache NiFi, Amazon Kinesis Streams, RabbitMQ. Let’s explore a simple Scala example of stream processing with Apache Flink. We'll ingest sensor data from Apache Kafka in JSON format, parse it, filter, calculate the distance that sensor has passed over the last 5 seconds, and send the processed data back to Kafka to a different topic. We'll need to get data from Kafka - we'll create a simple python-based Kafka producer. The code is in the appendix. ... Now we need a way to parse JSON string. As Scala has no inbuilt functionality for that, we'll use Play Framework. First, we need a case class to parse our json strings into. For simplicity, we will use automatic conversion from JSON strings to the JsonMessage. To transform elements in the stream we need to use .map transformation. The map transformation simply takes a single element as input and provides a single output. We'll also have to filter the elements that failed to parse.
“We believe that it is AI itself that will provide the means to shorten the chip design cycle, creating a symbiotic relationship between hardware and AI, with each fueling advances in the other,” they write in a paper describing the work that posted today to Arxiv. “We have already seen that there are algorithms or neural network architectures that… don’t perform as well on existing generations of accelerators, because the accelerators were designed like two years ago, and back then these neural nets didn't exist,” says Azalia Mirhoseini, a senior research scientist at Google. “If we reduce the design cycle, we can bridge the gap.” Mirhoseini and senior software engineer Anna Goldie have come up with a neural network that learn to do a particularly time-consuming part of design called placement. After studying chip designs long enough, it can produce a design for a Google Tensor Processing Unit in less than 24 hours that beats several weeks-worth of design effort by human experts in terms of power, performance, and area. Placement is so complex and time-consuming because it involves placing blocks of logic and memory or clusters of those blocks called macros in such a way that power and performance are maximized and the area of the chip is minimized.
The most obvious advice is NEVER to send a six-digit SMS to anyone for any reason. There have been other attacks covering other platforms using the same method. When a code is sent to your phone it relates to your phone. But there is a fix here that will protect your WhatsApp, even if the SMS code was sent onward. This fix will ensure you can’t fall victim to this crime. The code sent by SMS when you set up your WhatsApp account on a new phone comes directly from WhatsApp itself. The platform sets the code and sends it to you. But there is a totally separate setting in your own WhatsApp application that allows you to set your own six-digit PIN number. There is some confusion because these are both six-digit numbers—but they are entirely separate. Most people have still not set up this PIN number—the “Two-Step Verification” setting can be accessed under the Settings-Account from within the app. It takes less than a minute to set up. The PIN is for you to select, and even has the option of a backup email address. WhatsApp will ask you for the PIN when you change phones and also every so often when you’re using the app, that’s how secure it is.
The widespread uptake in this technology use comes at a time when more and more businesses are proactively addressing diversity and inclusivity among their workforce. Reports suggest that the US needs a curious, ethical AI workforce that works collaboratively to make reliable AI systems. In this way, members of AI development teams need to act over deep discussions regarding the implications of their work on the warfighters using them. In order to build AI systems effectively and ethically, defense organizations must encourage an ethical, inclusive work environment and procure a diverse workforce. This workforce should involve curiosity experts, a team of professionals who focus on human needs and behaviors, who are more likely to envision unsolicited and unintended consequences associated with the system’s use and mismanagement, and ask tough questions about those consequences. According to a research report, building cognitively diverse teams solve problems faster than teams of cognitively similar people. This also paves ways for innovation and creativity to flow, minimizing the risk of homogenous ideas coming to the fore.
Quote for the day:
"A leader is not an administrator who loves to run others, but someone who carries water for his people so that they can get on with their jobs." -- Robert Townsend