Project Cortex isn't only for Office documents. Using Azure's Cognitive Services, it can use image and text recognition to work with scanned content, images, and other file formats such as PDF. It can even use rules to define form structures, so that key information can be extracted from scanned forms and other common document types, allowing you to build a model of where projects are spending money by parsing purchase orders and invoices. Extracted information is used as metadata to provide context around documents, helping users find the content they need. You're not limited to structured document types. Another Azure Cognitive Service, LUIS, forms the basis of Project Cortex's Machine Teaching. Here you can build new document models that look for key terms, allowing classification of, say, contracts which will differ from contract to contract, with different content and different formatting. Once a model is trained it can be used across your entire document store, improving search and increasing your organisation's underlying knowledge model.
The company recently revealed that its trials with Rust over C and C++ to remove insecure code from Windows had hit its targets. But why did Microsoft do this? The company has partially explained its security-related motives for experimenting with Rust, but hasn't gone into much detail about the reasons for its move. All Windows users know that on the second Tuesday every month, Microsoft releases patches to address security flaws in Windows. Microsoft recently revealed that the vast majority of bugs being discovered these days are memory safety flaws, which is also why Microsoft is looking at Rust to improve the situation. Rust was designed to allow developers to code without having to worry about this class of bug. 'Memory safety' is the term for coding frameworks that help protect memory space from being abused by malware. Project Verona at Microsoft is meant to progress the company's work here to close off this attack vector. Microsoft's Project Verona could turn out to be just an experiment that leads nowhere, but the company has progressed far enough to have detailed some of its ideas through the UK-based non-profit Knowledge Transfer Network.
The platform has been developed to enable global trade. It brings together a number of emerging technologies including blockchain, internet of things sensors (IoT), as well as data and analytics tools to provide transparency and traceability to trading partners across complex industries. KPMG Origins allows these trading partners to communicate unique product information across their supply chains, and in particular to end users, while reducing operational complexities. Laszlo Peter, KPMG Head of Blockchain Services for Asia Pacific, said: “KPMG Origins is the result of several successful initial trials with clients to understand industry pain and trust points, map incentive structures, and create a platform to add real value. To move beyond the hype, it is necessary to introduce complex technology across a diverse set of corporate stakeholders. The platform is based upon in-depth work across highly specialised areas, as well as collaboration across multiple jurisdictions to deliver a multi-lingual, standards and taxonomy driven platform that accelerates the development of distributed ecosystems.”
Historically, secured credit cards have been among the most prominent solutions for people who are new to credit or have poor credit history. But secured credit cards typically require an upfront deposit, as much as $500, which can be prohibitive for the very people who need such a tool to improve their credit. The solution to helping consumers build credit without an upfront security deposit is to offer more of an installment plan, using equity from a credit builder loan as a deposit for a secured card and on-time payment history in lieu of a hard inquiry. The tool itself is not new – credit builder loans have existed in credit unions for 40-50 years. But many people are unaware of this offering and do not have the tools to use it; FinTechs provide a delivery model that reaches and resonates with today’s tech and mobile-savvy consumers, particularly Millennials. Instead of taking time away from one of several jobs (44 percent of workers aged 25-34 report taking additional jobs to make ends meet) to go to a physical bank during business hours, borrowers are empowered to manage their finances directly from their phones at any time, day or night.
The framework uses ‘Seldonian’ algorithms, named for the protagonist of Isaac Asimov’s “Foundation” series, a continuation of the fictional universe where the author’s “Laws of Robotics” first appeared. According to the team’s research, the Seldonian architecture allows developers to define their own operating conditions in order to prevent systems from crossing certain thresholds while training or optimizing. In essence, this should allow developers to keep AI systems from harming or discriminating against humans. Deep learning systems power everything from facial recognition to stock market predictions. In most cases, such as image recognition, it doesn’t really matter how the machines come to their conclusions as long as they’re correct. If an AI can identify cats with 90 percent accuracy, we’d probably consider that successful. But when it comes matters of more importance, such as algorithms that predict recidivism or AI that automates medication dosing, there’s little to no margin for error.
The Flow System™ is not a new Agile or Lean framework. Indeed, it is not a framework at all, and it’s certainly not a one-size-fits-all solution. What is presented is a system of understanding, a system of learning. Many project management methods and agile frameworks concentrate on taskwork and planning with no regard to how an organization is structured to support these activities, seeing them simply as a linear progression of tasks. Scaling frameworks tend to struggle or simply not work as they do not recognize that they are operating in a complex adaptive system which can only scale through continuous decomposition and recombination, which they are unable to do with their rigid doctrines. Organizations and institutions utilize teams but fall short of developing teamwork skills and fail to restructure leadership to maximize the benefits that can be obtained from the utilization of teams. These shortcomings introduce additional constraints and barriers that prevent organizations and institutions from achieving a state of flow.
Healthcare is definitely a data-rich sector, so scarcity of information is not a problem – and the NHS database is particularly valuable with respect to other countries, since it has comprehensive records that go back decades. However, access to health data is often very difficult from a regulatory point of view, and there are extreme differences in terms of quality and accessibility. Typically, health data is messy, disperse and often siloed in a multitude of medical imaging archival systems, pathology systems, EHRs, electronic prescribing tools and insurance databases. While things are moving in the right direction, i.e., with the development of unified data formats such as Fast Healthcare Interoperability Resources, there is no easy and quick fix. No fancy algorithm can be developed without proper data collection and cleaning – and in many cases, this phase can take months. Until companies keep reinventing the wheel and developing their own internal tools for data cleaning with huge costs in terms of time and money, progress will be slow.
Many organizations don't know how to gain value from threat intelligence, and intelligence — cyber or not — doesn't help people who aren't willing to help themselves. If someone tells you that thieves are planning to rob your house tonight, what steps would you take to try to prevent it? You could lock the doors, hide your valuables, and maybe stay at a friend's house. However, none of that would guarantee that the crime wouldn't happen. I've noticed that organizations don't truly understand what it means to be "agile" when acting on threat intelligence. In my experience, an agile security team rapidly operationalizes and incorporates intelligence into detection processes, and deploys tools that work quickly to deliver detection. If you learn that a group is planning to hack your systems using a certain method, but you can't adjust your infrastructure or existing controls to defend against that method, intelligence is wasted. You are only as secure as the next steps you take after learning about a threat — and if you take them in the time you have before it hits.
According to CompTIA’s end-user data, there is a very slow technology adoption curve across various new trends, with only IoT and AI reaching critical mass. “Even amid all the hype, companies in the business of technology are starting to pull back on adopting new technology as part of their portfolio,” CompTIA noted in its IT industry outlook 2020 report. “This slight tap on the brakes suggests that classic situation where companies move too quickly into a new technology discipline or business model, only to have a reality check in year two or three.” CompTIA’s research also found that small and medium-sized businesses are struggling to integrate the various platforms, applications and data they need. While large businesses are able to use internal resources for integration, CompTIA noted that companies of all sizes may outsource to third parties for integration activities
We like blockchain. At least, that's the takeaway from a recent TechRepublic Premium survey where the majority of respondents (87%) stated that blockchain will have a 'positive' effect on their industry, and 27% indicated a 'very positive' effect. However, thinking something and actually doing it are two different actions. Despite the enthusiasm for the technology, only 10% of those respondents actively use blockchain at their company. Blockchain appears on 13% of the strategic roadmaps for respondents' organizations, compared to 7% in 2018. Which industries will blockchain most likely impact? IT and technology was chosen by 58% of respondents, with professional services -- including finance, insurance, legal, and consulting -- a close second at 56%. Rounding out the top five cited industries were logistics & transport (45%), healthcare (41%), and retail & wholesale (37%). What needs to happen for the widespread adoption of blockchain? Two-thirds of respondents (66%) indicated the need for a clearly-stated business use case. A cryptocurrency operated by a government entity was suggested by 35% of respondents, while a company-controlled cryptocurrency was favored by 20%.
Quote for the day:
"Superlative leaders are fully equipped to deliver in destiny; they locate eternally assigned destines." -- Anyaele Sam Chiyson