Return to the office: This company is giving workers beeping wristbands to keep them socially distancing
Getting back into the swing of things will be by no means be easy. With remote workers having been confined to their homes for so long, sharing a workspace with others will require employees to be mindful of their surroundings, not to mention to curb their desire to reform old office huddles. "As the trial began, it became clear that many people were undercutting the correct physical distance," Renner admits. "But, as they got used to wearing the sensors, the trial participants got a better feel for the distance they needed to keep – and the number of beeps heard around the office quickly fell." Renner makes a point that some of the challenges of re-entering office life are things that businesses could very easily overlook. "It may seem straightforward, but one of our challenges has been to work out how people can safely bring in, prepare and eat their own lunch in the office," he says. "Initially, employees were asked not to use the microwaves as a lot of people touch these appliances. But quite a few people wanted to bring in their own food. So, we changed the rules and allowed people to use the kitchen again and, to make things safer, we moved cutlery and plates outside of drawers, so people don't have to touch so many handles and surfaces."
As the BFSI industry turns its attention to Fintechs to meet their digitization challenges; the eventual target areas for their R&D efforts does not waver: Develop and Deploy new technologies to better serve B2B banking customers, Increase profits, improve compliance and security preparedness and reduce infrastructure costs. If the end-goals are similar, then where does the Banking R&D differentiation come from? In one word: Reliability. To infuse reliability as a core rubric in its R&D paradigm means Banks have to check a number of boxes. Firstly, Banks and Technology teams need to bedrock ‘reliability-as-a- yardstick’ in their partnerships; across vendors, across geographies, across platforms. Secondly, Reliability is built over time by adopting a divergent approach. The ‘traditional-hire-and-instruct-engineers-on-a-project-mode’, does not produce optimum test results because to harness advanced technologies necessitates an experimental mindset as opposed to the erstwhile engineering approach. Finally, reliability comes at a cost. To experiment with production in real time comes with a sizable expense – One, the cost of errors can be high, and Two, the multifarious skill base
We are now entering a new phase, with lockdown easing and more aspects of life beginning to move towards something more like normality. But while instinctively one might expect this to reduce the mental strain on people, for a significant proportion this easing is in fact ushering in a whole new phase of worry, concerned about catching the virus or passing it on to members of their household. This just underlines the fact that the Covid-19 crisis and its effects are not a one-off shock – but a long-term shift into a new normal. It becomes essential for tech businesses to ensure they are responsive to this and provide their staff with the support they need, for example by creating online resources, supporting the creation of mental health networks and discussion forums and, potentially, offering staff access to counselling services too. Encouragingly, we found that 56% of companies have increased the level of personal and emotional support to staff since the crisis began. However, half of businesses still don’t offer any formal support for mental health issues. The difference this makes is visible: three quarters of those working for unsupportive companies are either concerned about their mental health now or in the past.
The software may be fool proof, but the same cannot be said about the data. Biases in the initial data the program is learning from will quickly spread to its outputs. Amazon had to scrap its recruitment AI tool because it started penalising CVs for containing the word “women’s”. In the male-dominated IT industry, men had been recruited at a higher rate than women. Words unique to women’s CVs appeared much less in successful hires compared to general words like “leadership”. The AI concluded that these words must be of low value and started penalising them. The lesson to be learned from this example is to identify gaps in the data and apply weightings so that demographics are equally represented. The fidelity with which an AI can classify massive amounts of data can even discourage looking for errors. Who’s going to argue with a program that can classify thousands of people’s faces with 98% accuracy via impenetrable mathematics? This is compounded by the so-called Black Box AIs that never show their workings. Typically, it involves the software projecting the data across high-dimensional mathematical spaces to extract unique features, but it is very abstract. Resist the temptation to outsource your thinking to the program or assume it knows what it’s doing.
“Any kind of technology is a tool that theatre can use, both creatively and to make itself visible. Just as limelight, gas lighting or the Victorian illusion of Pepper’s ghost were once new technologies, digital is another technology that can benefit theatre,” says theatre critic Lyn Gardner. How can the arts survive an uncertain future? Returning to the old ways of visiting museums or mingling in crowds at shows hardly seems viable, now that social distancing seems to be on the table at least in the medium term. Although there might be a day when we're able to enjoy again the unique experiences only the live arts can offer, in the meantime, CIOs and CTOs have an essential role to play in supporting the existing alternatives, and imagining new ones. Augmented reality, mixed reality or virtual reality could be one way forward for this sector, so urgently in need of sustainable recovery. Solomon Rogers, founder and CEO of immersive content studio REWIND and chairman of both the BAFTA Immersive Entertainment Advisory Group and Immerse UK, is of the opinion that these technologies present the arts with limitless opportunities.
Software is powering almost every business and they want to use that as a competitive advantage…. [Companies] need [the] ability to move quickly and they need to be able to change directions quickly to respond to new threats or seize new opportunities." Similar sentiments were expressed on the earnings calls of Fastly, Elastic, and Twilio, and no doubt will continue to be highlighted by others. However, you can't really talk about the importance of software without calling out just how central open source is to the software that every organization on earth builds and uses. While you can absolutely pay others to support open source for you, the companies that want to have the most control over their digital futures will be those that also contribute strategically to open source projects. ... The first is simply to provide funding to a particular project, either to help defray development costs or something else like stage an (almost certainly online) event. The second is to commit your own developers to the project. This can be the most effective way because the more code they contribute, the more influence you can earn over the direction of the project.
“Ensure data is checked for quality as close to the source as possible,” he says. “The more accurate it is upstream, the less correction will be needed at the time of analysis – at which point the corrections are time-consuming and fragile. You should ensure data quality is consistent all the way through to consumption.” This means carrying out ongoing reviews of existing upstream data quality checks. “By establishing a process to report data quality issues to the IT team or data steward, the data quality will become an integral part of building trust and confidence in the data. Ensure users are the ones who advise on data quality,” says Cotgreave. “When you clean data, you often have to find inaccurate data values that represent real-world entities like country or airport names. This can be a tedious and error-prone process as you validate data values manually or bring in expected values from other data sources,” he adds. “There are now tools that validate the data values and automatically identify invalid values for you to clean your data.”
“It is very important for us to apply ML when you start collecting huge amounts of data about your network,” said Sreeni Kancharla, vice president and CISO of Cadence Design Systems, an electronic design-automation software and engineering-services company speaking at the Palo Alto PAN 10 introduction. It’s important to get a faster response time to threats without making the security environment more complex, Kancharla said. On the IoT front PAN 10.0 supports a subscription service that targets IoT systems. “IoT devices present unique challenges for security teams. They are connected to an enterprise’s central network, yet they are generally unmanaged,” Oswal said. “For the most part, they are also unregulated, shipped with unknown or unpatched vulnerabilities, and often their useful life exceeds their supported life.” Oswal noted that a recent Palo Alto Unit 42 IoT threat report that said 57% of IoT devices are vulnerable to medium- or high-severity attacks, and 98% of all IoT-device traffic is unencrypted. Unit 42 is the vendor’s threat-research arm.
Almost everyone who has worked with microservices in the .NET Core probably knows the book of Christian Horsdal, “Microservices in .NET Core: with examples in Nancy” The ways of building an application based on microservices are well described here, monitoring, logging, and access control are discussed in detail. The only thing that is missing is a tool for automating the interaction between microservices. In the usual approach, when developing a microservice, a web client for it is being developed in parallel. And every time the web interface of the microservice changes, additional efforts have to be expended for the corresponding changes in the web client. The idea of generating a pair of web-api / web-client using OpenNET is also quite laborious, I would like something more transparent for the developer. So, with an alternative approach to the development of our application, I would like: The microservice structure is described by the .NET interface using attributes that describe the type of method, route and way of passing parameters, as is done in MVC; Microservice functionality is developed exclusively in the .NET class, implementing this interface...
An employee might follow instructions in a phishing email not only because it looks authentic, but that it conveys some urgency (usually from a manager or someone else of importance). Employee training can help reduce the likelihood of error, but solving the technological shortcoming is more effective: if a phishing email is blocked from delivery in the first place, we can help mitigate the human error factor. This is where artificial intelligence can be a game-changer. We already use AI to simplify our home lives, using it to perform a variety of tasks, from turning on lights, to playing our favourite music. But if AI solutions are deployed in the workplace, we can help address the biggest elephant in the IT room: data security. Data security is a major area of concern, and it’s likely the leading cause for lost hours – and lost sleep – for security and IT professionals. According to a recent survey of over 500 IT professionals in the financial services industry, a whopping 94% said that they lack confidence in the ability of employees, consultants, and partners to safeguard customer data. And because cybersecurity is a complex domain – with many unknowns and moving parts – the rigid, conventional solutions can’t be effective. However, AI solutions can learn, adapt, and dynamically react to an organisation’s cybersecurity needs.
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