Low-code proponents point to what they claim is another distinct advantage: LDCP technologies help businesses do more with less. What is more, they promise to free skilled software engineers to focus on hard problems, on creative solutions, on what they (i.e., proponents) call “value-creating” work, as distinct to the types of recurrent, repeatable problems that MDSD and LDCP technologies aim to formalize and encapsulate in reusable applications and workflows. “We have four or five developers that … work in Mendix and they accomplish more than a team of, no lie, probably 15 to 20 developers,” Conway Solomon, CEO with Mendix customer WRSTBND, a company that provides event-management software and services, told Kavanagh. “So, what kind of cost savings is that? Especially as a small company that has a lot of ambitions, where you know, like, a lot of extra money has been [spent] on payroll, you can do it in a fraction of the cost and have the same outcome … if not better, and so we use that to our advantage.”
The more popular branch of ML is supervised learning, in which models are trained on labeled examples. While supervised learning has been very successful at various applications, its requirement for annotation by an outside actor (mostly humans) has proven to be a bottleneck. First, supervised ML models require enormous human effort to label training examples. And second, supervised ML models can’t improve themselves because they need outside help to annotate new training examples. In contrast, self-supervised ML models learn by observing the world, discerning patterns, making predictions (and sometimes acting and making interventions), and updating their knowledge based on how their predictions match the outcomes they see in the world. It is like a supervised learning system that does its own data annotation. The self-supervised learning paradigm is much more attuned to the way humans and animals learn. We humans do a lot of supervised learning, but we earn most of our fundamental and commonsense skills through self-supervised learning.
There is a clear generational divide in where people want to work and how they see the purpose of the office. For young people, flexibility is key. They want to be in the office and connect and collaborate with co-workers face to face. That helps them onboard, form working relationships, receive guidance and soak up the company culture – all issues that workers have struggled with during the pandemic, a Microsoft and YouGov study highlighted in December. The office is often the vehicle for knowledge transfer between generations. But they also want to work from home when they need to – to look after a sick relative or wait for a repair engineer, for example. They don’t see this as a major issue, because their view isn’t based on traditional ways of working in an office every day. For them, the office space no longer stops at the office. They want to work where they want, when they want. And they want their bosses to provide the tools to help them do that. Last year, Microsoft’s Work Trend Index found that 42 percent of employees who worked from home lacked office essentials, and one in 10 didn’t have an adequate internet connection to do their job.
The Scrum team delivers a valuable Increment every single Sprint. As a framework, Scrum is focusing on delivery. Admittedly, this comes with many challenges. However, if a Scrum team is not regularly creating value for the (internal and external) stakeholders, everything else is of lesser importance. (A secondary positive effect of regularly delivering valuable Increments is building trust among stakeholders. Typically, building trust with them results in less supervision, for example, in the form of reporting duties or committees messing with Scrum—you get the idea. All of this is bolstering self-management, thus making working as a Scrum team more effective and enjoyable.) ... Other people want to join the Scrum team because nothing succeeds like success. (People voting with their feet is an excellent indicator for Scrum Master success, and it applies in both directions. My tip: Run regular, anonymous surveys in the Scrum team and ask whether team members would recommend an open position in the organization to a good friend with an agile mindset and track the development of this “employer NPS®” regularly to spot trends.)
The Knox Wire system was built by utilising world-class distributed ledger technology while further integrating artificial intelligence to facilitate its efficiency. It facilitates security, information authentication, and information storage on the network. It believes in the combined effort of its team to create the global settlement network through extensive experience in the development and finance sectors. Also, it holds professionalism throughout its interactions with institutions, hoping to revolutionise financial systems through innovation. The endgame is to benefit users, institutions, and eventually, governments. The onboarding process for financial institutions is straightforward, involving the beginning of an agreement with the platform. The institution will sign a contract with the settlement network and set all favourable employees by creating accounts on the Knox Wire system. Then, the network will provide AI integrations alongside its API parameters to support all the processes.
We all knew – or at least some of us did, ahem – that this was likely not sustainable in the long term. Investors appeared to be backing some startups in part due to FOMO, and that’s not necessarily a good thing. So as the first quarter draws to a close, it’s clear that while in no way have fundraises come to a screeching halt, investors are starting to pump the brakes. Generally, it appears we are experiencing a market pullback – which Alex touches on in this piece – precipitated by a number of things, not the least of which – the conflict in Ukraine and disappointing performances by companies who went public in the last year. And fintech, last year’s rising star of venture, is not immune. My former colleague, Joanna Glasner, at Crunchbase News published a story on March 7 indicating that venture capitalists’ enthusiasm for fintech seems to be waning as of late. Her data point, according to Crunchbase data, was that in the two weeks leading up to her post, a total of 51 fintech companies across the globe collectively had raised $1.1 billion in seed through late-stage venture funding.
Safety would be easier to achieve if there was only one type of problematic behaviour online, but there are so many different categories in places you don’t expect. It’s become more difficult for consumers to protect their privacy when there’s so much software beyond the layperson’s understanding. Over a decade ago, a Cambridge Analytica-linked firm abused platforms to deceive people who held too much trust in what they saw online, swaying an election in Trinidad by encouraging people to abstain from voting, ultimately leading to the opposition party winning. It was made to look like a natural resistance movement, but it was engineered through corrupt practices. Coronavirus disinformation online has been a major battleground in the last few years. It’s hard to estimate how many lives have been potentially lost because people trusted unverified sources. The need for platforms to moderate user-generated content has never been more severe. Schwartz points to the importance of detecting issues early, saying, “If harmful online activity is left unchecked, its reach can grow rapidly and fester, exposing countless users to violent, extremist, or misleading content.”
Catherine Southard, vice president of engineering at D2iQ, says her company hasn’t had much success finding new grads with experience in Kubernetes and the Go programming language, in which D2iQ’s product is primarily developed. “Part of that is because the tech landscape changes so quickly. It would be great for a representative from tech companies -- maybe a panel of CTOs -- to sit down with curriculum developers every couple of years and talk through industry trends and where technology is headed, and then brainstorm how to bridge the gap between university and industry,” she says. Southard added something students can do is research jobs that look interesting, then see what tech stack those companies are using. They can then equip themselves to land those jobs by studying up on that technology by using free resources online or taking courses. She sees another area of improvement in support for internship programs. Historically, D2iQ had a program in the US, but it was expensive to operate, and it didn't lead to long-term employee retention, except for a couple of stand-out talents.
Never have an organization’s technical capabilities mattered less to its long-term differentiation and competitiveness. The rise of accessible, affordable outsourced vendors, SaaS platforms, and capabilities-on-demand means that most companies have the ability to acquire whatever leading-edge technologies and skill sets are needed at the moment. Leaders know the companies that win are the ones that get the most out of their people and teams. Resumes don’t tell us much about the skills that matter most in our current climate, and the computers we “hire” to read resume keywords tell us even less. These workers, having seen and been through countless configurations of teams, conflict, and trends have figured out how to focus on what makes a difference. We might learn more from them on how to spot and hire the unique capabilities that real people bring to real-people solutions in our workforce. ... As our work becomes physically less proximate, we need to find ways to seek out guidance – not just in classes and courses, but in real time, from our colleagues.
Quote for the day:
"Your first and foremost job as a leader is to take charge of your own energy and then help to orchestrate the energy of those around you." -- Peter F. Drucker