How Mindfulness Drives Better Design And Innovation
Mindful by Design draws its ideas from fields of neuroscience, evidence-based mindfulness practices, design and storytelling exercises, and more, in which it’s important to emphasize, with intention, that there is no one right way. I work with a variety of clients, including founders of small startups, CEOs of large multinational companies, school principals, researchers, artists, inventors and educators, guiding them to use a designer mindset. ... Mindful by Design is a toolkit with approaches that invite you to become the agent of change and action, to involve yourself in the moment and to learn to appreciate the quality of what is unfolding when we fully connect. ... Mindful by Design encourages each person to connect with their deeper sense of purpose, to trust, and to go beyond perceived boundaries and divisions, creating connection and bridges. Each individual is involved and empowered as a designer of personal and collective experience, also documenting and reflecting at each stage. This is a mindfulness saying: each moment is an invitation to learn and grow.
Five industries outside of tech being changed by DevOps
Today’s warehouses are substantially more high-tech than the ones from past eras. For example, it’s common for such facilities to use a warehouse management system (WMS) that allows keeping track of all items from the time they arrive on-site to when those products get packaged and shipped to their destinations. A WMS can keep track of stock numbers, product categories and more, telling warehouse workers precisely where to find a desired item within a sprawling warehouse. Implementing a WMS into a facility for the first time is not always easy, but it can become more straightforward with help from DevOps. ... The internet has drastically changed how people research hotels, book rooms, hire special events managers and more. It’s not surprising, then, that many of the companies in the sector turned to DevOps to maintain their competitiveness. ... Depending on DevOps shortens the time required to develop and test new offerings and speeds up the time to market for those products.
Leading your organization to responsible AI
The best solution is almost certainly not to avoid the use of AI altogether—the value at stakecan be too significant, and there are advantages to being early to the AI game. Organizations can instead ensure the responsible building and application of AI by taking care to confirm that AI outputs are fair, that new levels of personalization do not translate into discrimination, that data acquisition and use do not occur at the expense of consumer privacy, and that their organizations balance system performance with transparency into how AI systems make their predictions. It may seem logical to delegate these concerns to data-science leaders and teams, since they are the experts when it comes to understanding how AI works. However, we are finding through our work that the CEO’s role is vital to the consistent delivery of responsible AI systems and that the CEO needs to have at least a strong working knowledge of AI development to ensure he or she is asking the right questions to prevent potential ethical issues. In this article, we’ll provide this knowledge and a pragmatic approach for CEOs to ensure their teams are building AI that the organization can be proud of.
The future of self-service is customer-led automation — Gartner
According to Gartner, organisations are turning to naturalistic engagement methods, such as voice and other AI-powered technologies, to give customers what they want and achieve higher operational efficiency. In fact, 91% of organisations are planning to deploy AI within the next three years. And, by 2030, a billion service tickets will be raised automatically by customer-owned bots. “What’s interesting is that when we begin to look at the dynamics of self-service and continued automation by organisations over a longer time frame, cracks begin to appear,” continued Mullen. “The burden of managing and supporting self-services is being taken from today’s support staff and being pushed into customers’ hands. This level of delegation, from ‘DIY’ to customer-led AI, will be a major force shaping customer self-service.” ... “As customers embrace these DIY mindsets, they will choose providers that allow them to interact easily with these consumer-controlled touchpoints, like smart speakers and VPAs. Enterprise-provided user interfaces will increasingly play second fiddle to customer-controlled experiences,” added Mullen.
Data storage: Everything you need to know about emerging technologies
With the rapid growth of data volumes at the edge and in data centers, it is increasingly difficult to move data to processors. Instead, processing is moving to the storage. There are two different ideas covered under the rubric of intelligent storage. At the edge, data pre-processing and reduction, perhaps using machine learning, reduces bandwidth requirements to data centers. In big data applications, sharing a pool of storage and/or memory allows as many processors as needed to share the data needed to achieve required performance. These concepts are currently labeled intelligent storage by HPE, Dell/EMC, and NGD Systems. It goes beyond the optimizations built into storage array controllers that manage issues with disk latency or access patterns. Call it storage intelligence v2. Consider a petabyte rack of fast, dense, non-volatile memory, attached to dozens of powerful CPUs in the next rack. With proper synchronization and fine-grained locking thousands of VMs could operate on a massive data pool, without moving hundreds of terabytes across a network.
What new collaborations will you be doing in Microsoft's Fluid Framework?
Patton describes the Fluid framework as "A new distributed data structure platform that allows for hyper-performant scenarios with AI included. Think about it as the ability to have, say, simultaneously 18 different people that are around the world in different geographies with not just real-time collaboration, but AI translations happening at the same time in sub milliseconds." In other words, don't think of SharePoint as slow or clunky, or just an intranet site and document library: think of it as "a new hyper-fast and performant cloud platform that has AI built into it." What you work with through that SharePoint storage layer and distributed data structure isn't just a standard Office document; it's an Office document broken up into pieces — "components that can then be shared across other apps that have the ability to collaborate within the end points [with the changes] coming back to the original file." So a 'compound' Word document might include a component that's a table someone can be editing in the Word document, but that can also be shared into a Teams conversation where someone else can be adding more information.
When event-driven messaging is the right choice
With cloud integration, APIs are the prevailing mechanism. But let's say you deploy your CRM, such as Salesforce, in the cloud. First, you need to upload data, such as customer data, into the new CRM system. This is typically a batch process because you can't call an API a million times to populate the customer database in the CRM. So batch data integration is used frequently. We also see varied event-based scenarios where an application sends out a notification and all the applications [that integrate with it] receive the information in parallel. Instead of using the classic request-reply paradigm that [exists] when you use APIs, event technology lets you implement what is called a fire-and-forget mechanism: I send you a message and you receive it when you receive it. A good example of these event processes are the notifications that you get on your mobile device. Occasionally, a notification pops up to tell you, for example, that your plane is delayed. This is classic event processing -- I send you a message and you do whatever you want with my message. But when I send you the message, I'm done.
Amazon Is Working on a Device That Can Read Human Emotions
The notion of building machines that can understand human emotions has long been a staple of science fiction, from stories by Isaac Asimov to Star Trek’s android Data. Amid advances in machine learning and voice and image recognition, the concept has recently marched toward reality. Companies including Microsoft Corp., Alphabet Inc.’s Google and IBM Corp., among a host of other firms, are developing technologies designed to derive emotional states from images, audio data and other inputs. Amazon has discussed publicly its desire to build a more lifelike voice assistant. The technology could help the company gain insights for potential health products or be used to better target advertising or product recommendations. The concept is likely to add fuel to the debate about the amount and type of personal data scooped up by technology giants, which already collect reams of information about their customers. Earlier this year, Bloomberg reported that Amazon has a team listening to and annotating audio clips captured by the company’s Echo line of voice-activated speakers.
US Senate passes anti-robocalling bill
If the bill makes it through the House and is signed into law, it will empower the Federal Communications Commission (FCC) to inflict hefty new fines – as much as $10,000 per call – for illegal robocalls. The legislation would also increase the statute of limitations for bringing such cases, thereby giving FCC regulators more time to track down offenders. The act would also create an interagency task force to address the problem, and it would push carriers like AT&T and Verizon to deploy call authentication systems, such as the pending STIR/SHAKEN call identification protocols, into their networks. That’s now in the works: in September 2018, the Alliance for Telecommunications Industry Solutions (ATIS) announced the launch of the Secure Telephone Identity Governance Authority (STI-GA), designed to ensure the integrity of the STIR/SHAKEN protocols. That move paved the way for the remaining protocols to be established.
Goodbye Passwords: Hello Identity Management
By 2022 there will be an estimated 29 billion connected devices, of which 18 billion will be related to IoT, according to a recent report by telecommunications firm Ericsson. Many of those connected things, plus the mobile apps and autonomous processes that drive them, will need new IAM solutions. “Identity and access management can depend on a lot of different things,” said Noam Liran, director of customer success at CyberArk. “It used to be just based on [the question of], does that identity have a password. Now, companies need to manage identities of microservices, cloud containers and mobile apps seeking access to privileged data in the cloud.” Liran added that even a website with a simple chat system needs access management. “A customer-service chatbot can be another form of identity to manage,” he said. “We have customers who are using a chatbot to grab tracking numbers from UPS or FedEx deliveries and then push the shipping data into a database.” Each one of those interactions requires a privileged relationship.
Quote for the day:
"True leaders bring out your personal best. They ignite your human potential" -- John Paul Warren
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