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AI in the workplace

In this post, we discuss AI in the workplace with our Chief Digital Officer, Felix Lemaignent.


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Who are the that AI revolution will affect employees affected and what are their challenges?

Artificial Intelligence

There are two categories of employees who will face different impacts. Firstly, those whose jobs will be directly transformed by AI. They will have to use it on a daily basis to accomplish their tasks, or work on its development. These are often technical or technology-related profiles. These employees absolutely must stay up to date on AI and understand how to integrate it into their work.

Then there are employees in more traditional professions. They will experience an indirect impact. As with those who have already mastered Excel or Google, those who know how to use generative AI will have an advantage. They will be more productive and versatile, completing their tasks faster and more autonomously. However, this does not always guarantee a better quality of work.

AI is already integrated into many tools, often invisibly. But here, we’re talking about generative AI, that works via prompts or a chatbot interface. This type of AI raises questions about the digital divide. Digital inequalities could increase with the rise of AI.


In this AI expert job description you will find everything you need to know about this profile.


AI in workplace: between challenge and opportunity for employees

Artificial Intelligence

Another main challenges is job-related fear. Many wonder whether AI will replace their jobs. Does using AI mean it can do the same job as them? In the case of budgets cuts, will they have to compete with their colleagues to keep their jobs? The ability to use AI to stay competitive will be essential in many areas. For some, AI represents a survival issue.
For others, it is fascinating. Many people are already accustomed to learning new tools, but generative AI marks an important change.

Unlike traditional tools with menus and buttons, AIs like ChatGPT work with text queries. This requires a new way of interacting with technology and developing critical thinking skills. It’s important to understand that the answers provided by AI are not always based on facts. They follow a probabilistic logic.

As with the transition from fax machine to computer, generative AI marks a turning point. The computer has transformed employees into “equipped workers”. Those who master AI will become “augmented workers”.

What are the risks for profiles that don’t train at the IAG?

Artificial Intelligence

The digital divide, already visible between generations, will widen between “augmented workers” and “outdated workers”. AI in workplace is here to stay. Those who train will become more competitive, more productive and more versatile. Employees need to be trained, whether in AI or in skills not covered by AI.

But training alone will not suffice. Mastery of generative AI will come with experience and regular use. This process will develop the digital acuity that is essential to remain competitive.

This reasoning also applies to companies. Companies that don’t invest in training their staff run the risk of being left behind. They will also have to deal with data protection and security issues. They can’t afford to have their employees blindly following the mistakes of an AI or copying unverified content.

Will IAG become a criterion for employability?

Artificial Intelligence

Companies are looking to optimize productivity while reducing costs. A candidate capable of using AI is an asset. However, mentioning this skill on a CV is not enough. During an interview, the candidate must provide concrete evidence of the impact of these technologies on business problem-solving.

Workers who have mastered AI show their curiosity, adaptability and versatility. These qualities make them capable of evolving and taking on new challenges – profiles that are highly sought-after.
Generative AI is also becoming a valuable training tool. Coupled with lifelong learning, it makes it possible to rapidly deepen knowledge and put new concepts into practice. This capacity for self-training will be crucial to staying competitive.

In career terms, the adoption of generative AI offers a competitive advantage. It accelerates skills development and broadens the scope of users’ tasks.
Take the example of office tools: thanks to AI, a professional can use a wider range of Excel formulas without having to memorize them. Similarly, AI can suggest page layouts or structure PowerPoint content more effectively.

In written communication, AI transforms the drafting of emails and reports. It speeds up the process and improves accuracy, clarity and tone. Employees gain in efficiency and credibility.
These improvements go far beyond increased productivity. They enable employees to devote more time to high value-added tasks, such as strategic thinking or human interaction, which are essential for career development.


Also, read Top 5 Strategies to Overcome the AI Talent Gap


AI in workplace: what does Mindquest do for its employees and customers?

Mindquest

Mindquest offers AI awareness workshops to train its employees, as well as personalized coaching. We actively monitor prompting best practices, AI-related risks and the latest innovations.

We also develop in-house AI tools to meet our needs while maintaining control over our data. Integrating AI into our recruitment processes is nothing new, but generative AI marks a major step forward.

However, we remain vigilant about possible AI biases. At Mindquest, we have put safeguards in place to prevent these biases. AI is not a substitute for human expertise. Properly used, it improves efficiency and ensures fairness in our recruitment processes.


Find your next assignment on our freelance and permanent IT recruitment platform, or join Mindquest so you don’t miss out on any job opportunity!


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Data & Business Intelligence Job Descriptions

AI expert: Job description

Use our template to create a compelling and comprehensive AI Expert job description to attract top talent.

Certainly, artificial intelligence (AI) is already part of our daily lives (personal assistants, smartphones with facial recognition, etc.) and it is becoming increasingly important in the business world, with numerous technological applications (chatbots, maintenance of installations, etc.). In this AI expert job description you will find everything you need to know about the AI expert job, required skills, training, education, and salary expectations.


Need advice on how to start or develop your freelance consulting business in tech or IT? Need to start a new permanent or freelance assignment? Join Mindquest and get support from our team of experts.


AI expert: the job

Technical skills

What is the role of the artificial intelligence expert?

The main task of the Artificial Intelligence (AI) Expert is to design computer programs capable of performing tasks similar to those performed by a human being. Both a researcher and a computer scientist, an AI expert can work in a wide range of fields.


Also, discover Top 5 Strategies to Overcome the AI Talent Gap


Keeping a constant watch

The mission of the artificial intelligence expert is to solve complex problems. Research and analysis are therefore at the heart of the job. The AI expert must possess very advanced computer skills, as his or her expertise is constantly sought in the development of artificial intelligence projects. Since AI is still a relatively new field of expertise, the AI expert must constantly keep abreast of technological developments.

Understanding and analyzing problems

Since the role of the AI expert is to create software that mimics human reasoning, the expert must be able to analyze the human brain in relation to a problem and thus develop intuitive human-machine interfaces.

Developing and designing solutions

The AI expert can work on extremely diverse and varied projects. His or her day-to-day tasks are generally algorithm design, error checking, and programming.

Required skills of the AI expert

AI expert required skills

Strong technical skills

The job of Artificial Intelligence Expert requires advanced technical skills because AI-based applications cross many technologies (web crawling, data mining, data science, machine learning, deep learning, etc.).

Strength of proposal, and ability to listen

As far as soft skills are concerned, the AI Expert must show a strong spirit of initiative, interpersonal skills, and good listening skills. Since these qualities will enable him/her to carry out his/her projects successfully, communicate with all stakeholders, and call on external experts.

Ability to work in a team

To conclude, research in Artificial Intelligence is definitely not a solitary job. In fact, the AI Expert will have to work with various experts and will have to know how to federate these experts and listen to their advice to make progress in his research.


Also discover the differences between Business Intelligence and Big Data


Context

AI expert context

Expertise in Artificial Intelligence is very rare and therefore highly sought after. As a researcher and computer scientist, the AI Expert is highly qualified and can work in different fields of activity. Such as in ESN, in industrial companies, in research laboratories…


In this post, we discuss AI in the workplace with our Chief Digital Officer, Felix Lemaignent.


Salary

AI expert salary

The average daily rate of an Artificial Intelligence Expert is between 700 and 1500€.

Training and education

AI expert education

To become an Artificial Intelligence Expert, you need to have a 5-year degree. You can enter this profession by having studied mathematics or computer science. However, you will need to continue your education and obtain a master’s degree or an engineering diploma. A specialized master’s degree or even a doctorate.


Also read 5 Online Courses to Get You Up-To-Speed with AI


After years of research and a lot of work, an AI expert can easily move on to new projects and join innovative start-ups in R&D, large companies, or research centers.

You can also read : 20 AI Experts You Should Follow

Find an Artificial Intelligence Expert job with Mindquest
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About us Featured Podcast Interviews

Why An Economist Turned Data Scientist Is Now Pursuing a PhD

Maxence Azzouz-Thuderoz is a data scientist specialising in AI and natural language processing at French consulting firm Axys Consultants. Here is how he went from studying economics and econometrics to embracing data science, and why he is now thinking of pursuing a PhD in automatic speech recognition.

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Interested in more AI and data science tips? Here’s how to unlock the power of data through a career in data science.

Your background is in economics. How did you end up working as a data scientist?

I went into economics and econometrics because I wanted to be an economist when I was younger. But at the end of my graduate education, I discovered data science.

I got some short lessons and, in the last year of my studies, I decided to change my plans and move to data science.

That’s how I started with economics and ended with a data scientist job.

What did the shift to data science require of you, how was the process?

It requires coding. In economics we didn’t study code that much, so I learned coding. But the transition was kind of easy because I had the mathematical and statistical background that we have in economics and specifically in econometrics, a domain of statistics and economics.

And the transition to data science and traditional machine learning tools was kind of easy because it is about the same mathematical tools, the same statistical tool. So, it was kind of easy.

What was the most challenging part then?

To work with real data. You can find open-source data that is very clean, very nice for studying something, but when you are working with real-world data it can be very complicated.

So, how did you actually manage to get from your economic studies to your current position as a data scientist?

I got a very good friend that found a job in a consulting company in northern France, and he knew that I was looking for an internship. So, he called me and said “Max, I have an opportunity for an internship as a data analyst that I think could be a nice first step for you.”

So, I started at the of commerce with a little internship for my studies and then, when I finished my studies, I went for an internship as a data analyst. Then I found a data scientist job in the consulting industry.

What’s a typical day like in your current role as a data scientist?

Our days are very different because we are always making different things, but, in general, the data scientist job is 70% working with data and 30% is about modelling. No, actually, I would say it’s 70/20 and then maybe 10% is for industrialization. That’s something we have to consider.

What’s the hardest part of working with data these days?

It’s about the information you have about the data.

Some time ago, I was working with a big French banking group, and we did not have all the documentation about the data. Documentation is a very important aspect because you can have the data, but, if you don’t know what it corresponds to, how to work with it, that is a big problem. Sometimes we were working with data that we didn’t completely understand, so we didn’t really understand what we were doing.

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It’s about the information you have about the data.

Some time ago, I was working with a big French banking group, and we did not have all the documentation about the data. Documentation is a very important aspect because you can have the data, but, if you don’t know what it corresponds to, how to work with it, that is a big problem. Sometimes we were working with data that we didn’t completely understand, so we didn’t really understand what we were doing.

Where do you see data science and AI 5 years from now?

I think we will see the first industrial applications of quantum computing in AI.

Additionally, 5G is going to change many things. We will have super-connected houses, apartments, etc. So maybe we will have new projects for AI.

Also, cell phones are becoming more powerful every year. So, I would not be surprised if we have AI technology that today we cannot make work on our phones become a reality in coming years.

For example, automatic speech recognition needs a lot of resources. It’s a big challenge. A big part of current research in automatic speech recognition is about the reduction of the parameters in models so that it all needs fewer resources. So, in the years to come, we might see some kind of automatic speech recognition technology working on smartphones, for instance.

You have decided to pursue a PhD. Why is that?

In my current job, I discovered what it was like to work on research and development projects. It was the first time I was working on such ambitious projects, and I found it very interesting. And I really became aware of the difference in understanding between someone who is simply a skilled data scientist and the scientists, PhD people.

People with a PhD were working on the same project as me, and we were absolutely not at the same level of understanding. I think this is one of the reasons why I want to go ahead with a PhD program. Because I want to reach another level.

And the other reason is that I’ve always been interested in research, the university research system. So yes, it’s a little dream, an old dream that I have and that I think could be nice to realise soon.

So, I recently started to check out universities, looking for a PhD program around automatic speech recognition. It’s a big area.


For more tips on data science, AI and automatic speech recognition, make sure to follow Maxcence on LinkedIn.


Check out more of our interviews in our podcast episodes.

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Featured Tech Magazine TOP 10 experts' articles

10 Top AI Experts in the UK to Follow Online

With artificial intelligence evolving so rapidly, it can be hard to keep up with new developments, best practices and the industry’s overall state of the art. For this reason, we at Mindquest suggest you this list of top AI experts in the UK that will help you stay in the know and future-proof your career in AI.

You can also read 5 Online Courses to Get You Up-To-Speed with AI and AI expert: Job Description


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Top AI experts in the UK to follow

As the IT environment is constantly evolving, it is crucial, if not necessary, to connect with the brightest minds to keep up with innovation. In other words, the more contacts you get, the more likely you are to solve IT challenges. Therefore, we at Mindquest to provide you with a list of the AI experts in the uk to follow.

Disover A Career in Data Science: Unlocking The Power of Data with AI

Tabitha Goldstaub

Twitter | LinkedIn

To start, Tabitha, board member of Luminate, is the co-founder of CogX, the chair of the UK Government’s AI Council and an advisor for The Alan Turing Institute. She is also the author of How To Talk To Robots: A Girl’s Guide to a Future Dominated by AI.

Rob McCargow

Twitter | LinkedIn

To continue, Rob is the director of AI at PwC UK and a champion for the responsible use of technology and AI. He is also an advisor for the IEEE and the UK’s All-Party Parliamentary Group on AI and a TEDx speaker.

Sarah Porter

Twitter | Linkedin

Then, Sarah is the founder and CEO of InspiredMinds, a global community and strategy group focusing on the use and development of AI for good in line with the UN’s sustainable development goals.

Yarin Gal

Twitter | LinkedIn

Let’s go on with Yarin, an Associate Professor of Machine Learning at the University of Oxford’s Applied and Theoretical Machine Learning Group, helping produce groundbreaking work like this set of Bayesian Deep Learning benchmarks.

Elena Sinel

Twitter | LinkedIn

Elena, on the other hand, is the founder and CEO of Teens in Ai, a global initiative launched at the UN’s 2018 AI for Good Global Summit and that seeks to inspire the next generations of ethical AI researchers and practitioners.

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Danilo Rezende

Twitter | LinkedIn

Danilo, then, is a Senior Staff Researcher and lead of the Generative Models and Inference group at DeepMind, London. His research focuses on scalable inference and generative models for decision-making and hard science problems.


In this post, we discuss AI in the workplace with our Chief Digital Officer, Felix Lemaignent.


Allison Gardner

Twitter | LinkedIn

Next, recently MP for Stoke-on-Trent South at UK Parliament, a lecturer and data science apprenticeships program director at Keele University, Dr Allison Gardner is co-founder of Women Leading in AI, which brings together AI and business leaders to discuss the future of AI. 

Edward Grefenstette

Twitter | LinkedIn

Further, Edward is Director of Research for Google DeepMind, he has been a Scientist and RL Area Lead at Facebook AI (FAIR) and an Honorary Professor at the Deciding, Acting, and Reasoning with Knowledge (DARK) Lab at the UCL Centre for AI.

Wendy Hall

Twitter

Then there is Wendy Hall, a Dame Commander of the British Empire (DBE) and a champion for UK AI skills and women in science. She is Chair of the Ada Lovelace Institute and joined the BT Technology Advisory board earlier this year.

Ankur Handa

Twitter | LinkedIn

Last but but not least, Ankur is a Robotics Research Scientist at NVIDIA AI and a Research Scientist at OpenAI working at the intersection of computer vision and control for robotics. He did a post-doc at Cambridge University and has a PhD from Imperial College London.


Do you have any other AI experts in the UK who should be featured in this or future lists? Shoot us an email.

Also discover our articles 10 of the Best Software Developers in the UK to Follow Online

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Press review Tech Magazine

AI, IBM Chips, and a Novel Cloud Security Concept: The Week in Tech News

In the world of IT, real news can easily get mixed with eye-catching headlines and promotional buzz. From AI and chips to cloud security: filter out the noise with our selection of the top 3 tech news stories of the week.


Full podcast episode:

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AI is everywhere

The AI hype is so strong we often forget that artificial intelligence is already an integral part of our everyday lives. 

Firstly, AI played a key role in the development of Covid-19 vaccines. But there are many other, less conspicuous ways we benefit from it directly. 

For example, from anti-spam email filters to fraud detection for your banking account, silent, tiny AI helpers accompany us throughout the day without us necessarily being aware. Whether it is by dimming our phone’s screen brightness or suggesting sentences we tend to use, low-level AI tools do exactly what the best kind of technology does: help out without being noticed. 

But not everything’s about the little things, other common applications have positive effects on our society, like smart city traffic management or energy grid optimisation. 

World Economic Forum 

IBM makes chip breakthrough

For all its innovation potential, the technology industry still has an over-reliance on the diminishing effects of the long/established Moore’s Law, by which the number of transistors in computer chips tends to double in number and halve in size every two years. 

Unfortunately, recent years have seen this rule of thumb falter, with chip manufacturers struggling to keep the good ratio going.  

Enter IBM. The company announced this week a significant breakthrough in the way computer processors can be effectively made. IBM created a 2nm chip it claims can boost performance by 45% over 7nm chips while cutting down energy consumption by 75%.

BBC

A scalable approach to cloud security

Making sure that evolving cloud environments remain protected against malware is becoming increasingly difficult in a world where multi-cloud is the new norm and a single weakness can compromise an entire network

As if human fallibility and the cloud’s sheer size were not enough, attackers are using increasingly sophisticated methods of bypassing traditional security measures and protocols.

Malware is often only valuable until its detected, as its signature can then be easily identified by the system. Yet, scanning an entire cloud ecosystem for irregularities still involves too much complexity and resources due to its sheer size. 

A research initiative by Microsoft’s, Projet Freta, proposes a novel approach: a cloud-centric in-memory scanning system that focuses on virtual machine instances to deliver scalable protection.

TechRepublic

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About us Featured Podcast Interviews

Interview with microsoft Wesley Backelant: Becoming data-driven is more than just saying you are data-driven (Part 2)

The second part of our interview with Microsoft cloud solution architect Wesley Backelant, in which he talked about his role, what the job entails and what’s ahead for the cloud industry.

A Microsoft insider, Wesley Backelant is a Belgian cloud solutions architect who works together with the company’s customers to engineer and deploy impactful data and advanced analytics projects. Among other things, Wesley is an expert on the various components of the Azure AI platform. He is also a frequent speaker at numerous community events and regularly shares Azure news and tips.  

🔊 Check out the first part of the interview if you missed it.


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Interview with Wesley Backelant: What part of being a cloud architect at Microsoft do you enjoy the most?

There are a couple of aspects that make it very interesting to me, personally. One of them, and that’s probably one of the benefits of being at a company like Microsoft, is leading the space in terms of innovation and cloud. You are at the forefront of technology, and that’s what I like. I like new stuff. Every time I get to learn something new, I see it as an incredible challenge, and I really love doing these things and getting my hands on new stuff and new technologies. That’s what drives me from a technological standpoint.

But the other thing that I really like about being in the data and BI space is that it puts you in a position where you are not just talking about technology, you’re also talking about business and societal outcome. One of our customers, for example, is in the public transportation space, and the fun part there is that, when you do something that’s innovative with them, you know that it´s going to have an impact on people and that it’s going to improve the experience of a hundred thousand or millions of people. To me, that’s one of the more rewarding parts of my job. Seeing a project succeed is fun, but seeing it drive real impact is the real deal.

At the technical level, what do you love most doing as part of your job?

Making it all work together. Azure is a continuously evolving platform. New things pop up all the time. Figuring out where all those things fit together and how you can make things more efficient and cost-effective is one of the role’s key drivers and, honestly, quite fun. Matching what we deliver as a technology to something that can actually provide value to the customer by leveraging existing building blocks.

Also, coding is not so much part of my job officially, but it’s still something I love to do, because it’s quite tangible. You get to see the result pretty immediately, and that’s a lot of fun.

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What tools do you like using the most?

I would be obliged to say Azure SQL Database is my favourite tool, as SQL is my old love, but that wouldn’t be entirely fair, especially, if you look at what we’re doing today with open source. I’d like to split my answer between cloud and open source.

Containers and Kubernetes are clearly changing the way people are building software these days. I talk a lot with start-ups and partners, and pretty much all of them are building stuff based on containers and mostly Kubernetes as an orchestrator. It’s impressive to see what the impact of these tools has been in the relatively little time that they’ve been around for. We are also seeing them as a big foundation for our own services.

Then there’s open source. For example, something people sometimes forgets is that, whenever you have a service that has to run in production, you need proper monitoring and alerting. It’s not the most fun part of building a solution, but it’s one of the most crucial steps when you want to do something seriously. We have Azure Monitor, which is a great tool that I strongly recommend, but at the same time, I’m a huge fan of open-source solutions like Prometheus and Grafana. Luckily, they have integrations with Azure Monitor, so that makes them even more interesting. What amazes me of the open-source world is the community, and the power of the community, how the community sets the direction in a lot of ways. Even the big players follow the direction set by the community. That’s quite nice to see.

As a data expert, what’s the biggest issue you are seeing with data these days?

I think we all know the challenges from a more technical point of view, so data quality, governance, etc, to me things that between quotes we can easily solve with technology. But one of the biggest challenges I see with customers is being more data-driven. It sounds like a marketing term, but it really is not.

I really believe most companies are aware there’s a lot of value in the data they have, in applying machine learning or even good reporting. But getting into thinking what’s the difference I can make with this data, and do I have the proper environment and organisation in place to really benefit from it? That’s where I still see a lot of companies struggle. If I were a c-level person, that’s probably the question I would ask myself – are we organised to benefit from all the data and what it can bring to our company? Becoming data-driven is more than just saying you are data-driven. It also means having a proper organisational structure in place together with technology and tools.

Interview with microsoft Wesley Backelant: What’s next for cloud?

One of the things is that I still see too much of is that there’s still a strong focus on infrastructure. I still see a lot of IT departments that can tell you what server or specific IP address is hosting an application or service.

Things can change, the infrastructure can scale in or out. It shouldn’t matter to you. I really believe that infrastructure part is one of the things will see disappearing over time. One of the best things about cloud is agility, and when people start really to adopt the whole serverless idea, and also DevOps as a philosophy, that’s the point where we’ll really see the whole power of cloud.

Secondly, at Microsoft we strongly believe in the intelligent cloud and edge. Bringing some part of that computing power, or at least how it works closer to where the data is, is definitely also an area where there is a lot of innovation happening these days. The big challenge is, obviously, making it all work seamlessly together. We are definitely doing progress there. But I still think there’s going to be a lot of new developments in this area still. And, thirdly, there is the abstraction of where things are running. If you look at tools like Azure Arc, basically, Kubernetes is having a big impact on that whole story. Being able to host your solutions be it on the public cloud, your own cloud or multiple clouds and having it all seamlessly work together from an operational standpoint and management point of view – that’s also where cloud is going.


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You can follow Wesley on Twitter and LinkedIn.

Also, make sure to check out his blog: My long term memory for data and development related information.

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About us Featured Podcast Interviews

Interview with Wesley Backelant from microsoft: Playing with technology is one thing, but you only start learning when you have requirements (Part 1)

The first part of the interview with Microsoft cloud solution architect Wesley Backelant to discuss his career trajectory and share some tips on how you can gain new skills and become a self-made IT pro like him.

A Microsoft insider, Wesley Backelant is a Belgian cloud solutions architect who works together with the company’s customers to engineer and deploy impactful data and advanced analytics projects. Among other things, Wesley is an expert on the various components of the Azure AI platform. He is also a frequent speaker at numerous community events and regularly shares Azure news and tips.  


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Check out the second part of the interview 

So, Wesley, tell us a bit about your professional trajectory. How did you get started in your career?

I’m actually what they call a self-made man. I started studying ICT or IT, but I had been doing an internship at a company during high school, and that’s the company I got started in. They were looking for someone to help them and support them with software development and, because I worked there as an intern, they asked me to go work with them in my first year of university. They offered to teach me. There were some very senior people working there, who knew everything about development and so on. So, I left my studies and joined the company.

I decided to do that the first year because, to be honest, the education system in Belgium at the moment was not that strong at this level, so I was kind of frustrated. I finished high school and I thought, okay, now I am going to study IT stuff, I am going to learn how to program, and when I got there, there was a lot of stuff that I had to do that was completely unrelated to IT. There was accounting, economics, different languages. It was all super interesting, of course, but I was there to learn how to develop, and even when we did that, it was only old school stuff that we learnt, COBOL, and so on.   

When I got that opportunity to get hands-on, I said, okay, let’s do this. It was a leap of faith too, but it turned out to be okay! A small company, so I was the IT department together with a few colleagues. We did a bit of everything.

Interview with Wesley Backelant from microsoft: What sort of career path eventually took you to become a cloud architect at Microsoft?

Well, sometime after that, I started getting interested in the database side of things, more than on development. I needed bigger challenges, so I got into outsourcing to have more variation, customers and technologies to get in touch with.

Learn more about Microsoft Technologies Careers Overview

I then had the opportunity to become a database architect at a large enterprise in Belgium, and I took it because I knew they were hosting one of the most transaction-intensive SQL environments in Belgium at that moment. I thought it would be a great learning opportunity, which kind of proved to be true, because it put me on the next level of data, focusing on database design, performance tuning, and so on. They were also looking into some business intelligence solutions and, given my passion for data, I had been doing some reporting services work. We implemented together with a colleague the first reporting solution there, and that’s how I got into contact with some people at Microsoft. I figured that, with that experience, it was the right time to apply for a position at Microsoft, as they were looking for a pre-sales for their data and BI.

Back then I was not really a BI specialist, I was more focused on the database engine, but I figured, hey, new stuff to learn, fantastic, let’s take that leap. It was the same year I first saw the demo for what back then was called Red Dog, which is now known as Azure, at an internal event. Looking back, it was hard to imagine. It was the early, early days of Azure, and, seeing that demo, it was still hard to grasp what cloud would mean nowadays.

It was fun being there. Being at the birth of Azure, so to speak, put me in a nice position. I actually grew up and worked together with Azure at Microsoft, meaning that I was blessed to be able to go through this whole cycle of innovation and new services coming up. You know, looking back at something like SQL Server 6.5 and what keeps me awake at night today, it’s really amazing. We are so far from the traditional idea of the database now.

What educational resources do you turn to as someone who is constantly learning new things?

Well, at Microsoft there’s a huge focus on learning these days. It’s one of the key priorities to make sure everyone is up-to-speed with technology. Especially with our roles as cloud architects, we need to be ahead of the curve in many ways. But it’s a broader concept, of course. Everyone at Microsoft needs to at least have some part of technical knowledge, and there’s a strong push for that. Most of that is coming from Microsoft learn these days, which is also open for external people, so I really would encourage people to look at it, as there is great content on the platform.

Additionally, I like to look at blogs, from the official Microsoft blogs to the heroes in the industry. For me that’s actually the queue, when I see something on a blog post, I say, okay, let’s see how can I learn this, how can I get my hands dirty with this.

Is that what you tend to favour, a more practical approach to education?

What I’ve noticed works best for me — I have these “production-like” pet projects. It could be something you do at home, but where you try to have a scenario in mind. Playing with technology is one thing, but you only start to learn when you have requirements, I think.

At first, I had zero knowledge of Linux, for example. I saw it was going to become important. Since I had a server at home running Windows, I decided to make it a Linux server – that was before cloud, to be clear – so I said, okay, let’s use Linux, let’s start building RAID arrays, save some pictures on a central server, etc. I broke the server several times. Luckily, I had backups, thanks to experience. I think I had to re-install it like 3 times because I did something wrong with permissions and partitions in Linux, but that’s learning.

The point is that you need something that has real requirements so that you challenge yourself to try new things. And for me that’s what works best, getting your hands dirty with technology. It, of course, starts by reading and learning the basics. But then you need to start pushing yourself.


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You can follow Wesley on Twitter and LinkedIn.

Also, make sure to check out his blog: My long term memory for data and development related information.

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Weekly News: One Algorithm to Save the World

Software development has been accelarated by the pandemic, and that’s great news for technologists. Weekly news and one algorithm to save the world.


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Also discover our article: IT Pros: How to Work On Remote in the Post-Pandemic World

Preparing for the next time around with an algorithm

So, was it a pangolin or not? 

At this point, the scientific community can more or less confidently say that the coronavirus that is wrecking havoc across the globe came originally from bats. But they are not so sure about which animal acted as the intermediary host.  

Identifying animal species that might become the source of the next pandemic is one of the main pillars of our strategy to future-proof our public health. It is, however, not an easy task, as the potential lines of investigation are just too many and new virus strains can be quite unpredictable. Well, it turns out AI can help with that too. 

A group of British researchers have built a computer algorithm that allows them to predict which animals are most susceptible to new coronavirus infections. The results of the algorithm were somewhat alarming, as many more mammals were identified as potential hosts when compared to previous studies based on screenings.

But hey — information is power. Better to know where to look for the next time around. 

BBC

How to develop software remotely

Software development has been accelarated by the pandemic, and that’s great news for technologists. But IT leaders have to juggle the rise in demand with other, more uncomfortable consequences of Covid-19. 

Not considered essential employees for the most part, software developers are largely working from home these days. As it is happening with other locked-down professional; coders and integrators are dealing with challenging situations, having to coordinate family duties with work assignments and falling victim to the isolation and the lack of direct contact. 

This of course, impacts overall team performance. Which is why development team leaders are coming up with new ways to work and support their teams. While there is no single best approach to the problem; a few common patterns emerge when interviewing some of these managers. 

These include greater, more frequent communication between team members. But also visibility over the current status of projects via collaboration tools like Slack and a profound revision of existing workflows. Fostering socialising among peers is also key.

Computer Weekly

The low-code explosion

According to a new forecast by Gartner, the need for more agile and decentralised software development brought about by the pandemic will continue to boost low-code adoption in the coming months.

Low-code platforms let non-IT experts develop solutions without requiring hardcore coding and technical skills. Something which, of course, is very advantageous in a time of rapid digital transformation and overclocked IT departments. 

Gartner estimates that 41% of all employees outside IT; the so-called business technologists; are customising or building digital solutions to accelerate their projects and integrate workflows. 

The firm predicts that half of all the demand for low-code applications will come from business users by the end of 2025. 

Information Age


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The Top 10 Belgian Cloud Pros to Follow on Twitter

Are you Belgian and into cloud? Looking to relocate to Belgium to pursue a career in cloud computing? These are the experts you should be following on Twitter. From industry insiders to technology evangelists, all of them are worth your attention. Top 10 Belgian Cloud Pros to Follow on Twitter.

Cloud: also read our article: Data security : Is your cloud data secure?

Top 20 – Belgian Cloud Pros to Follow on Twitter

Christian Verstraete 

@christianve 

Now happily retired, Christian is a cloud expert and advocate with over 35 years of experience working at tech behemoths like HPE, where he served as the chief technologist of the firm’s cloud advisory services. He is an avid tweeter and blogger and regularly shares news and analysis about the global cloud industry.  

Jan Tielens  

@jantielens 

Jan is a senior program manager at Microsoft, where he helps the company’s customers and partners design and develop their cloud ecosystems, with a focus on IoT, machine learning and cognitive services. He has been a Microsoft MVP for many years, conducting training and speaking at industry events across the world. 

Sam Vanhoutte 

@SamVanhoutte 

Chief Technology Officer (CTO) at Codit, an Azure-focused integrated solutions company, Sam is a Microsoft Azure MVP and frequently speaks on the topics of AI, IoT, Integration and API management. Highly experienced in IoT and cloud-based solutions, Sam posts regularly about these industries. 

Frederik Denkens 

@fdenkens 

Frederik is a business development and cloud expert who, back in 2001, founded Skyscrapers, a company looking to accelerate SaaS development with a combination of AWS, Cloud Native, DevOps, and Kubernetes. He shares his insight and expertise in these areas through his company’s blog

Wim Matthyssen 

@wmatthyssen 

Wim is a cloud architect with over a decade worth of experience working with Microsoft’s infrastructure technologies. He works for cloud services provider Synergics, where he focuses on designing Azure hybrid solutions. A true Microsoft cloud advocate, Wim is a Microsoft MVP and founding board member of the MC2MC Microsoft cloud community and writes regularly about hybrid cloud on his blog.  

Peter De Tender 

@pdtit 

Peter is part of the company’s Azure Technical Trainer team. A Microsoft MVP and certified trainer, he is devoted to teaching partners and customers the ways of Azure – from guidance on how to deploy and manage workloads to helping other experts get Azure certified. He is also a coveted public speaker and shares his knowledge via his blog.      

Karel De Winter 

@kareldewinter 

This cloud solutions architect at managed cloud services provider DexMach is a devoted Azure expert and advocate. Whether it is on Twitter, on his blog, or at an industry event, Karel is passionate about helping the Azure community grow, constantly sharing news and educational resources about the platform. 

Glenn Colpaert 

@GlennColpaert 

Glenn is CTO and founder of Zure Belgium, where he helps clients design, deploy and maintain scalable Azure PaaS solutions. A Microsoft MVP and certified trainer, he is an active member of the Belgian Azure user group AZUG, as well as a frequent speaker at industry events.  

Geert Baeke 

@GeertBaeke 

Geert is a cloud architect and Microsoft incubator at De Cronos Groep. There he helps kick-start new initiatives based on the Microsoft tech stack and designs cloud-native solutions on the Azure platform. A frequent speaker at industry events, Geert regularly shares his Azure expertise through his blog and YouTube channel

Wesley Backelant 

@WesleyBackelant 

A Microsoft insider, Wesley is a cloud solutions architect focused on ensuring that the company’s customers are successful with their data and advanced analytics projects. In particular, Wesley is an expert in working with the various components of the Azure AI platform. He is a frequent speaker at numerous community event and regularly shares Azure news and tips. 

Continue here with our Top 10 Developers in Belgium to Follow on Twitter

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Weekly News: Open Source Coders Could Be Worth Millions


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Open source gold

Focusing on open source software solutions could save the European Union billions of euros a year. That’s according to a new report conducted by OpenForum Europe (OFE) under the European Commission’s direction, which concluded that a mere increase of 10% in open source production could increase the EU’s GDP by nearly €100bn.

The study estimated that in 2018 alone there were over 260,000 open source contributors in the EU. The volume of code they produced amounted to the full-time work of 16,000 developers, generating between 65 and 95 billion euros in value.  

The reveal comes as another study by IBM and O´Reilly suggests 94% of developers and technology managers prioritise open source skills over proprietary technology. Expertise in open-source tech like Linux and Kubernetes is almost twice (64.6%) as popular as skills tied to specific platforms like AWS or Azure. 

All thanks to the rise of the hybrid cloud, which requires a unified, flexible IT infrastructure and is expected to grow by 47% in the next three years. 

ITProPortal / TechRadar

Filling the AI skills gap

Artificial intelligence could change all our lives for the better, freeing us from repetitive tasks and allowing us to enjoy more free time and devote our energy to higher-level activities. That is, of course, if governments and business leaders around the world are able to promote the re-skilling of the workforce and bridge the already problematic talent gap.

That was the conclusion of a panel of European institutional experts at The Economist´s recent Innovation@Work summit, which acknowledged AI must be regulated to ensure it is an assistance to people’s lives rather than a hindrance. Ensuring data quality is key, while nations need to set up technology training efforts that produce the talent companies need. 

AI is one of the areas of IT where the talent gap is more apparent, especially as the technology keeps evolving at breakneck speed. Companies are a bit clueless regarding AI skills themselves. According to Gartner, 53% of business leaders believe the inability to identify skilled expertise is the number one impediment to workforce transformation. 

Diginomica

Also discover our article: How AI will allow recruiters to focus on people

Big tech goes green

One of the biggest critiques that can be made about big tech companies, besides their near economic monopoly is the carbon footprint they produce. Server farms and data centres, mining of the precious resources need to build hardware, emissions tied to the distribution of products. You name it. 

It is no surprise then that companies like Amazon, Google and Microsoft have made in recent years a pledge to reduce their impact on the environment and established ambitious goals for the near future. A move that has become all the more necessary considering mounting regulatory scrutiny by the US and EU governments.  

The solution? Investing in clean energy. 

According to an analysis by Bloomberg and the Financial Times, technology groups are the world’s biggest corporate buyers of green energy. From solar to wind farms, their clean-energy projects expand all across the globe, providing a growing portion of all their energy needs. 

Financial Times


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