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.
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AI expert: the job
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.
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
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.
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…
Salary
The average daily rate of an Artificial Intelligence Expert is between 700 and 1500€.
Training and 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.
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.
data scientist, maxence azzouz-thuderoz, ai, nlp, automatic speech recognition, data science phd, interview, behind the screens
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.
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.
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.
With AI evolving so rapidly, it can be hard to keep up with new developments. This list of top AI experts in the UK will help you stay in the know.
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.
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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.
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.
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.
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, 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.
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.
Next, 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.
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.
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 anemail.
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.
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.
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%.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
From industry insiders to technology evangelists, all of them are worth your attention. Top 10 Belgian Cloud Pros that you should 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.
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 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.
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 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 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 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.
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 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 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.
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.
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.
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.
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.
Enter Edna's Garden Chapter 2. How an 8-year-old girl with a passion for nature turns the world upside down with her data experiments. By Horizon 2050.
Edna’s Garden: An 8-year-old girl with a passion for nature will turn the world upside down with her data experiments
“Edna?” an old voice croaked from above. From beneath the pile of dead leaves she had fallen on, Edna could hear the man struggling to breathe. Wheezes and sudden bursts of dry cough formed a rhythmic pattern that spoke of one-too-many cigarette puffs while walking the dog. “For the love of Christ, Edna! Where are you? Where do you think you are going?” The man’s voice was full of urgency and rage, his British accent more noticeable than usual. Edna could not remember the last time she had seen him this mad. Maybe she simply had not.
“Edna!” In her leafy igloo, Edna could hear his steps coming down the hill as he fought his way through the dense vegetation. She held her breath. “Of all the days you could have lost your mind… It had to be today, ah? Of course it had to be today!” Just a few feet away from Edna’s face, a loose branch broke into a dozen pieces under the furious step of a muddy leather shoe. Edna held onto her precious cargo in a protective embrace. It was still warm, much like the pulsating heat that had started emanating from her ankle. She must have sprinkled it upon touching the ground. A stinging pain stabbed her leg in agreement. Great.
“I am losing my patience, little lady. Come out of wherever you are hiding. Now!” The man’s voice was now further away. It was clear that he had assumed that Edna was no longer there and was venturing deeper into the thicket. No, she would not come out! She was tired of all the stupid rules and impositions. And all because of Her. “One last time, lady! Do you want me to tell your father? Is that what you want?” No, he would not tell Dad. He never did. He loved her way too much to want her any harm. “I am going to count to three, Edna. And then, I am going to pick up my phone and call your father.” Nice try, buddy. “One…” Just a ruse. “Two… Picking up the phone, Edna!” “Peter, no!” Darn it.
Edna had just a few seconds to hide her hunting prize in one of the inner pockets of her navy blue trench coat before a hand started digging into the pile of leaves. An angry pair of tired eyes peeped through a hole in the leafy dome. There stood Peter Kahn, the family’s butler. He was soaked in sweat and covered with dirt. He was holding Edna’s Totoro backpack in one hand and a cellphone on the other.
More hurt, than angry, Edna stared back at the man with a defiant expression. “Where is it.” said the butler. “Where did you put it?” Nothing. He proceeded to unlock his phone. “I lost it while running, ok?” said Edna. “Are you happy now?” The man directed her a suspicious look. “Peter,” said Edna pointing at the swollen ankle. “I can’t walk.”
All things considered, Edna was having a great time. She was really trying to keep herself from smiling as passerby directed inquisitive and confused looks at the man dressed in dirty, eccentric butler clothes carrying in his arms a little girl with even dirtier clothes across Central Park on a Tuesday afternoon. She could have easily piggybacked her way through the park and made it a bit less awkward, but Peter was too much of a gentleman to allow that to happen.
Edna looked at the face of the sixty-year-old butler for a moment. His eyes were focused in the winding path ahead, his face as stoic as straight was his posture. He had not spoken a single word since discovering her under the leafage. Neither was Edna expecting him to do so. She knew that look very well after spending most of her life under the care of the man. He would briskly carry her all the way across the park until reaching The Pond, where he would slow down so Edna could mentally annotate the number of swimming ducks at the time and what they were doing.
It was her dad that had introduced her to nature when she was a little kid, before everything changed. She had been studying The Pond’s ecosystem for over a year now. She had built a database and tracking computer program where she carefully registered all the data in hopes that one day her research might be of use to the cool scientists at the American Museum of Natural History. Over the months, the data she collected was enough to start building a model that simulated the little natural environment she so loved. And that was only the beginning.
But this time, Peter did not slow down. Trying to get a quick glimpse of the water over the butler’s shoulders, Edna considered for a moment dropping her precious cargo where it belonged. No. It was too vital to her project’s success.
The outlandish butler and his broken princess did not look any more fitting while crossing Grand Army Plaza. Peter even had to stop for a couple of minutes in order to explain to a concerned police officer that they were neither part of an anticapitalist street performance nor had they been involved in a limousine crash.
Edna felt sorry for Peter. The gallantry had always been there, but his new attire was simply too much. It did not use to be that way. Not until she broke into their lives and proclaimed that “elegance and taste had to be conquered one outfit at a time.” Peter, like most modern-day family butlers, used to wear what adults called “business casual” clothes.
Edna knew this from the few occasions in which she had been invited – and forced to go – to a classmate’s birthday party. She hated those kids. They were always talking about either cars or horses, summer houses and the coolest technological gadget of the season. It seemed as though their only goal in life was to copy the nearsighted lives of their parents, the superfluous, clean, organized and ultimately sombre lives of wealthy New Yorkers.
She thought for a moment of Tom Collins, that little spoiled brat. She could picture him at the school gates, leaving for home on his ridiculous hoverboard after making fun at the fact that Edna still had to be walked home by “the nanny.” She had heard those things could catch on fire. And she certainly hoped so.
Distant church bells chimed way too many times. They were pretty late. She would be furious, thought Edna with satisfaction. She had been planning this for weeks, yet another fake jewel on her crown of shiny ego.
It all started when Dad announced over dinner that he had decided to invest some money in the new restaurant of a famous art critic he recently met at a fundraising event. The guy’s name was Jeremy Talbot, and, apparently, he was as enthusiastic as Dad about saving the endangered populations of North Pacific short-tailed albatross. “So, how short is its tail compared to that of a normal albatross?” had jumped an excited Edna when her dad mentioned that fact.
But, before she could ask more about that majestic-yet-not-too-majestic-sounding bird, Bianca Salazar – Her – had come up with the brilliant idea. “That’s it, darling. We are having a dinner party!” For a moment, Edna had thought the veins on the woman’s neck would burst out of pure elation. Of course – She had been desperately waiting for such an occasion. Bianca Salazar was tall, thin and evil; her beauty extraordinary enough to make everyone else oblivious to the latter.
She had shown up at their 57th Street penthouse three years after Mom’s death. Edna was only one year old when her mother finally succumbed to the cancer. It was impossible for Edna to recall a single thing about her. She simply had this feeling, a foggy impression of having had a mother a long time ago. Somehow, she knew she came from somewhere – or rather from someone – as opposed to just having been summoned into this world by pure chance. That was definitely what it felt like with her.
Bianca Salazar had simply come along with fake smiles and pretended she had always been there. It did not work that well with Edna. She would not go as far as calling it hate at first sight – Edna was simply too young in the beginning to understand what was going on. It had been more of an awakening. By the age of four, Edna reckoned, she had had enough interactions with well-meaning human beings to recognize one without a soul when she saw it.
Dad was probably the golden standard when it came to evaluating a person’s qualities. He had taught Edna everything cool she knew or cared about, from zoology and astronomy to The Beatles and good adventure stories – The NeverEnding Story was one of her favourites.
Then there was Peter, of course. He had taught her substantially different things, the kind of things Edna wished no one cared about: how to properly eat at the table, how a lady should introduce herself to a stranger, the list of words she was not supposed to use. Well, no – That was unfair.
With her father travelling so much and the witch being, well, a witch, Peter provided Edna and her siblings with the valuable concepts of reliability and selfless generosity.
Edna looked at the butler’s face as they crossed Fifth Avenue on a red light. Peter was an honourable man. The most honourable. Edna wished they had known each other as kids. They would have been really good friends.
