Vattenfall is one of Europe's largest producers and retailers of electricity and heat. Our main markets are Sweden, Germany, the Netherlands, Denmark, and the UK. The Vattenfall Group has approximately 20,000 employees. We have been electrifying industries, powering homes and transforming life through innovation for more than 100 years. We now want to make fossil free living possible within one generation and we are driving the transition to a sustainable energy system.

According to a study, published in the journal Genome Medicine, a team of researchers at Rutgers University was able to develop an artificial intelligence (AI) method that may provide more insight into Crohn's disease. Crohn's disease, an inflammatory bowel disease, is characterized by various traits that can affect any part of the gut. It is estimated that the disease could affect close to 800,000 adults in the U.S., according to the study's co-authors. As such, researchers have pivoted their attention to AI for a more comprehensive understanding of identifying and treating Crohn's disease. For the study, the team investigated genetic signatures associated with the illness in 111 participants.

NVIDIA has been a presence in the financial industry for more than 15 years. Financial institutions harness NVIDIA's full stack accelerated computing platform to power AI and high-performance computing applications that utilise vast amounts of data to increase revenues, reduce costs, and mitigate risk across the enterprise. NVIDIA works with the largest banks, credit card issuers, and insurers across the globe helping financial institutions deliver AI-powered solutions. Financial institutions bring a range of problems and opportunities to NVIDIA to solve through AI. Ultimately, financial institutions, including fintechs, seek NVIDIA's expertise in accelerated computing to AI-enable hundreds of applications to drive better insights, increase revenues and remove operational inefficiencies.

The medical industry is sitting on a huge trove of data, but in many cases it can be a challenge to realize the value of it because that data is unstructured and in disparate places. Today, a startup called Mendel, which has built an AI platform both to ingest and bring order to that body of information, is announcing $18 million in funding to continue its growth and to build out what it describes as a "clinical data marketplace" for people not just to organize, but also to share and exchange that data for research purposes. It's also going to be using the funding to hire more talent -- technical and support -- for its two offices, in San Jose, CA and Cairo, Egypt. The Series A round is being led by DCM, with OliveTree and MTVLP, and previous backers Launch Capital, SOSV, Bootstrap Labs and Chairman of UCSF Health Hub Mark Goldstein also participating. The funding comes on the heels of what Mendel says is a surge of interest among research and pharmaceutical companies in sourcing better data to gain a better understanding of longer-term patient care and progress, in particular across wider groups of users, not just at a time when it has been more challenging to observe people and run trials, but in light of the understanding that using AI to leverage much bigger data sets can produce better insights.

Even though Data Scientist is no longer the topmost sought job in 2021, according to Glassdoor, it is still one of the most paying jobs in America. The trend came from having market insights and analysis. Everyone was adopting a method involving analytics, and those who were reluctant faced a major setback in company development and expansion. Initially, companies used Microsoft Excel or spreadsheets for the purpose. But soon there were a lot of tools to make the process easier.

Data science is the discipline of making data useful. There is absolutely no doubt that this decade has bought loads of innovation in Artificial Intelligence. Besides Artificial Intelligence, we are witnessing a massive boost in the data generated from thousands of sources. The fact that millions of devices are responsible for this enormous spike in data brings us to the topic of its smart utilization. The domain of Data Science brings with itself a variety of scientific tools, processes, algorithms, and knowledge extraction systems from structured and unstructured data alike, for identifying meaningful patterns in it.

With the diversity in data problems and requirements, comes a broad range of innovative solutions. These solutions often bring with themselves a host of data science trends granting businesses the agility they require while offering them deeper insights into their data. With data flowing in from all directions, it becomes harder to analyze. Graph Analytics aims to solve this problem by acting as a flexible yet powerful tool that analyzes complicated data points and relationships using graphs. The intention behind using graphs is to represent the complex data abstractly and in a visual format that is easier to digest and offers maximum insights.

As a long-time part of this industry, I have spent a good part of the last decade talking about the digital transformation. Call it the digital transformation or the data-led transformation, but this transformation has been the talk of the town for a long time now. Not only are organizations geared toward achieving a better analytics setup, but they are also on the lookout for a more efficient data policy in the process. With many cloud service providers around us offering AI as a service, companies can tap into these ready-made options and enjoy a certain extent of customization options. Creating an AI setup of your own can be a tiresome task, as you have to feed different algorithms into the setup, and wait for it to deliver the right analysis on the data fed into it.

After winning 74 consecutive games and earning $3.3 million in prize money, he finally lost to his fiercest opponent -- a newcomer, no less, that went by a single name: Watson. Really, though, it was no contest. With four years of training and a huge research budget, Watson had been born for this moment. If a computer can be born, that is. Created by IBM to answer questions posed in natural language, Watson was initially designed to excel at Jeopardy! but after its win it began tackling other projects: assisting in the treatment of lung cancer patients at New York's Memorial Sloan-Kettering Cancer Center; conversing with kids via smart toys; teaming up with education company Pearson to tutor college students; even helping H&R Block customers file their taxes.

Big data isn't quite the term de rigueur that it was a few years ago, but that doesn't mean it went anywhere. If anything, big data has just been getting bigger. That once might have been considered a significant challenge. But now, it's increasingly viewed as a desired state, specifically in organizations that are experimenting with and implementing machine learning and other AI disciplines. "AI and ML are now giving us new opportunities to use the big data that we already had, as well as unleash a whole lot of new use cases with new data types," says Glenn Gruber, senior digital strategist at Anexinet. "We now have much more usable data in the form of pictures, video, and voice [for example].