The Linux desktop is so easy. It really is. Developers and designers of most distributions have gone out of their way to ensure the desktop operating system is easy to use. During those early years of using Linux, the command line was an absolute necessity. Today? Not so much. In fact, Linux has become so easy and user-friendly, that you could go your entire career on the desktop and never touch the terminal window. That's right, Linux of today is all about the GUI and the GUIs are good. If you can use macOS or Windows, you can use Linux. It doesn't matter how skilled you are with a computer, Linux is a viable option. In fact, I'd go so far to say that the less skill you have with a computer the better off you are with Linux. Why? Linux is far less "breakable" than Windows. You really need to know what you're doing to break a Linux system. One very quick way to start an argument within the Linux community is to say Linux isn't just a kernel. In a similar vein, a very quick way to confuse a new user is to tell them that Linux is only the kernel. ... Yes, Linux uses the Linux kernel. All operating systems have a kernel, but you don't ever hear Windows or macOS users talk about which kernel they use.
There’s a broader redefinition of purpose that’s underway both for organizations and individuals. Today, people don’t have just one single career in a lifetime but five or six—and their goals and purpose vary at each stage. At the same time, organizations can’t address or engage with the broad range of stakeholders they deal with through just one single purpose. In combination, these shifts are ushering in the concept of purpose as a “cluster” of goals and experiences, with different aspects resonating with different stakeholders at different times. The same cluster concept holds true for career paths. It is vital to expand the conversation about the varied, unique options people have to fulfill their goals. Companies must strive to make those options more transparent, more individualized, and more flexible, and less linear. For today’s employees, the point of a career path is not necessarily to climb a ladder with a particular end-state in mind but to gain experience and pursue the individual’s purpose—a purpose that may shift and evolve over time. To that end, it may make sense for organizations to create paths that allow employees to move within and across, and even outside, an organization—not just up—to achieve their goals.
Mewies says bias in automated systems generates significant risks for employers that use them to select people for jobs or promotion, because it may contravene anti-discrimination law. For projects involving systemic or potentially harmful processing of personal data, organisations have to carry out a privacy impact assessment, she says. “You have to satisfy yourself that where you were using algorithms and artificial intelligence in that way, there was going to be no adverse impact on individuals.” But even when not required, undertaking a privacy impact assessment is a good idea, says Mewies, adding: “If there was any follow-up criticism of how a technology had been deployed, you would have some evidence that you had taken steps to ensure transparency and fairness.” ... Antony Heljula, innovation director at Chesterfield-based data science consultancy Peak Indicators, says data models can exclude sensitive attributes such as race, but this is far from foolproof, as Amazon showed a few years ago when it built an AI CV-rating system trained on a decade of applications, to find that it discriminated against women.
The best CCOs partner with the business to really understand how to place gates and controls that mitigate risk, while still allowing the business to operate at maximum efficiency. One area of the business that is particularly valuable is the IT department, which can help CCOs to maintain and provide systematic proof of both adherence to internal policies and the external laws, guidelines or regulations imposed upon the company. By having a dedicated IT resource, CCOs do not have to wait for the next programme increment (PI), sprint planning or IT resourcing availability. Instead, they can be agile and proactive when it comes to meeting business growth and revenue objectives. Technical resourcing can be utilised for project governance, systems review, data science, AML and operational analytics, as well as support audit / reporting with internal / external stakeholders, investors, regulators, creditors and partners. Ultimately this partnership between IT and CCOs will allow a business to make data-driven decisions that meet compliance as well corporate growth mandates.
An unhappy sysadmin can breed apathy, and an apathetic attitude is especially problematic when sysadmins are responsible for cybersecurity. Even in organizations where cybersecurity and IT are separate,sysadmins affect cybersecurity in some way, whether it’s through patching, performing data backups, or reviewing logs. This problem is industry-wide, and it will take more than just one person to solve it, but I’m in a unique position to talk about it. I’ve held sysadmin roles, and I’m the co-founder and CTO of a threat detection and response company in which I oversee technical operations. One of my top priorities is building solutions that won’t tip over and require significant on-call support. The tendency to paper over a problem with human effort 24/7 is a tragedy in the IT space and should be solved with technology wherever possible. As someone who manages employees that are on-call and is still on-call, I need to be in tune with the mental health of my team members and support them to prevent burnout. I need to advocate for my employees to be compensated generously and appreciate and reward them for a job well done.
Brian Goetz has a funny way of explaining the phenomenon, called Goetz’s Law: “Every declarative language slowly slides towards being a terrible general-purpose language.” Perhaps a more useful explanation comes from Stephen Kell who argues that “the endurance of C is down to its extreme openness to interaction with other systems via foreign memory, FFI, dynamic linking, etc.” In other words, C endures because it takes on more functionality, allowing developers to use it for more tasks. That’s good, but I like Timothy Wolodzko’s explanation even more: “As an industry, we're biased toward general-purpose tools [because it’s] easier to hire devs, they are already widely adopted (because being general purpose), often have better documentation, are better maintained, and can be expected to live longer.” Some of this merely describes the results of network effects, but how general purpose enables those network effects is the more interesting observation. Similarly, one commenter on Bernhardsson’s post suggests, “It's not about general versus specialized” but rather “about what tool has the ability to evolve.
As of late, be that as it may, open exploration endeavours like Eleuther AI have brought the boundaries down to the section. The grassroots agency of man-made intelligence analysis, Eleuther AI expects to ultimately convey the code and datasets expected to run a model comparable (however not indistinguishable) to GPT-3. The group has proactively delivered a dataset called ‘The Heap’ that is intended to prepare enormous language models to finish the text and compose code, and that’s just the beginning. (It just so happens, that Megatron 530B was designed along the lines of The Heap.) And in June, Eleuther AI made accessible under the Apache 2.0 permit GPT-Neo and its replacement, GPT-J, a language model that performs almost comparable to an identical estimated GPT-3 model. One of the new companies serving Eleuther AI’s models as assistance is NLP Cloud, which was established a year prior by Julien Salinas, a previous programmer at Hunter.io and the organizer of cash loaning administration StudyLink.fr.
While taking the NoSQL road is possible, it’s cumbersome and slow. Take an individual applying for a mortgage. To analyze their creditworthiness, you would create a data application that crunches data, such as the person’s credit history, outstanding loans and repayment history. To do so, you would need to combine several tables of data, some of which might be normalized, some of which are not. You might also analyze current and historical mortgage rates to determine what rate to offer. With SQL, you could simply join tables of credit histories and loan payments together and aggregate large-scale historic data sets, such as daily mortgage rates. However, using something like Python or Java to manually recreate the joins and aggregations would multiply the lines of code in your application by tens or even a hundred compared to SQL. More application code not only takes more time to create, but it almost always results in slower queries. Without access to a SQL-based query optimizer, accelerating queries is difficult and time-consuming because there is no demarcation between the business logic in the application and the query-based data access paths used by the application.
In France, security pros tended to find tender and bidding processes more of an issue, but also cited a lack of trusted partners, budget, and ignorance of cyber among organisational leadership. German responders also faced problems with tendering, and similar problems to both the British and French. From a technological perspective, UK-based respondents cited endpoint detection and response (EDR) and extended detection and response (XDR) and cloud security modernisation as the most mature defensive solutions, with 37% saying they were “fully deployed” in this area. Zero trust tailed with 32%, and multi-factor authentication (MFA) was cited by 31% – Brits tended to think MFA was more difficult than average to implement, as well. The French, on the other hand, are doing much better on MFA, with 47% of respondents claiming full deployment, 35% saying they had fully deployed EDR-XDR, and 33% and 30% saying they had fully implemented cloud security modernisation and zero trust respectively. In contrast to this, the Germans tended to be better on cloud security modernisation, which 40% claimed to have fully implemented, followed by zero trust at 32%, MFA at 30% and EDR-XDR at 27%.
The reasons Scrum Masters violate the spirit of the Scrum Guide are multi-faceted. They run from ill-suited personal traits to pursuing their agendas to frustration with the Scrum team. Some often-observed reasons are: Ignorance or laziness: One size of Scrum fits every team. Your Scrum Master learned the trade in a specific context and is now rolling out precisely this pattern in whatever organization they are active, no matter the context. Why go through the hassle of teaching, coaching, and mentoring if you can shoehorn the “right way” directly into the Scrum team?; Lack of patience: Patience is a critical resource that a successful Scrum Master needs to field in abundance. But, of course, there is no fun in readdressing the same issue several times, rephrasing it probably, if the solution is so obvious—from the Scrum Master’s perspective. So, why not tell them how to do it ‘right’ all the time, thus becoming more efficient? Too bad that Scrum cannot be pushed but needs to be pulled—that’s the essence of self-management; Dogmatism: Some Scrum Masters believe in applying the Scrum Guide literally, which unavoidably will cause friction as Scrum is a framework, not a methodology.
Quote for the day:
"No organization should be allowed near disaster unless they are willing to cooperate with some level of established leadership." -- Irwin Redlener