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06/09/2022

What You Need to Know About Web3

Web3 promises to revolutionize online life. Here's a look at the changes that are headed your way.
Web3 is the next-generation internet technology that supporters believe will redefine everyday digital experiences. With the help of cryptography and distributed-ledger technology, Web3 promises to create a user-owned and user-controlled internet. Numerous Web3 projects have already emerged, opening new opportunities in fields such as entertainment, retailing, financial services, gaming, and esports.
Web3 will enable users to transact and engage with each other in entirely new ways, says Alex Manders, partner and global blockchain leader with technology research and advisory firm ISG. “Most importantly, it will enable the creators of data to retain ownership of the data and be incentivized to share it.”
Web3 promises an entirely new generation of online services, decentralized and leveraging the same types of technologies found in cryptocurrencies, such as Bitcoin. “Web3 is the underpinning for many services and functions that will, over the next three to seven years, become minimum success requirements for continued Internet function and growth,” says Mark Thiele, co-founder and CEO of Edgevana, a company that's developed a global marketplace for automating data center procurement processes. “Web3 will lead to safer and more personal web interactions.”

What Will Web3 Mean?
Web3 promises to spur innovation across nearly all industries and markets. It will change the way people and enterprises interact with each other, offering new income streams for major brands and individual creators alike, says Markus Levin, co-founder of XYO, which offers a decentralized crypto-location network that's designed to provide accurate location data from cars to smartphones.
Web3 is an enhancement to the current Web2, which frequently fails to adapt to Internet users' individual needs and preferences. “Web2 led to the rise of companies gatekeeping our data,” Levin says. Web3 will enable users to pivot to a more inclusive model. “It will allow users to take control of both their own data and monetize their content,” he says.
When viewed in a business-to-business context, Web3 promises to revolutionize supply chain and business process optimization. “It offers new ways for enterprise partners, vendors, and suppliers to transact via e-commerce and collaborate in virtual realities,” Manders says. “There's a large opportunity for enterprises to explore, and design new revenue streams and business models beyond the technology.”
Web3 is also designed to allow consumers to interact directly with enterprises, including through tokenization, NFTs, and digital twins of products showcased on consumer avatars. New e-commerce models will allow consumers to pay for goods and services with digital currencies either in person, online, or in an extended reality environment, Manders notes.

What Are Web3’s Benefits?
Web3 promises to give users greater control over how they use the Internet as well as the people and enterprises they interact with. “With power to the people comes the vision of democratized access to services, payment systems, and business transactions that will facilitate a global boom in new small businesses,” Thiele predicts.
Online social behavior will also likely change. “Currently it seems as if we're all sitting at a digital dining table, fighting for attention,” says Jan Daniel Semrau, founder and CEO of Ternary Capital Group (TGC), an investment firm specializing in the convergence of traditional and decentralized finance. “In Web3, we're going back to a ‘single player’ experience where personal needs are met through a much quieter and less ‘social’ online experience.”
Manders notes that Web3 will put personal data back into the hands of the originator, effectively preventing unauthorized parties from exploiting private facts and habits. Additionally, by decentralizing data assets, Web3 promises to reduce the threat of large, targeted data breaches.

What Are the Drawbacks to Web3?
Web3 applications and use cases are rapidly appearing (and disappearing), making it challenging to predict which technologies and business models will thrive on the next-generation Internet platform. “At times, it can be confusing to understand how or why an application or use case is being developed,” Manders says.
Capital investment in Web3 technologies and services is both fluid and erratic. Some investment areas are more active than others, depending on what's being designed and proven out, Manders says. Complicating the situation is that many distributed applications lack strong governance models, which can lead to security gaps. Usability is yet another concern. “Many of the things developed today are highly technical and lack a good customer/user experience design,” Manders notes.

When Will Web3 Arrive?
Web3 is still an emerging concept, indicating that there will likely be a subtle transition from Web2 to Web3. “Developers are working tirelessly to make this new iteration of the internet scalable and more user-friendly,” XYO’s Levin says. “Additionally, regulatory bodies around the globe are having a constructive dialogue about what kind of regulation will safeguard Web3 users without stifling innovation.”
This content was originally published: https://www.informationweek.com/big-data/what-you-need-to-know-about-web3

23/08/2022

AI Is Now Mature Enough to Drive Revenue Growth

Some companies have made a breakthrough in using artificial intelligence to spur innovation and growth, not just for cost savings. Their advanced AI maturity has five success factors.

Many technology leaders associate artificial intelligence primarily with making processes more efficient. New research from Accenture shows that those who do so severely underestimate the technology's role in generating business value. Having analyzed the performance of 1,200 companies across 16 industries and 15 countries, we found that a small group of organizations (12%) outperforms their peers on AI and, as a result, enjoys 50% greater revenue growth.
These AI achievers have reached a much higher level of AI maturity than others. They master a set of AI capabilities in the right combination, including the technology (data, AI, and cloud), organizational strategy, responsible AI, C-suite sponsorship, talent, and culture. Essentially, AI achievers have moved beyond “pilot-it-is” -- a common occurrence where the perfection of a product or tool becomes detrimental to scaling technology – into integrating AI across their businesses.
For example, to harness AI for their growth initiatives, a major retail pharmacy built about 100 high-value AI products that create detailed customer profiles and help the company better optimize inventory and prices. The company has been committed to its data- and AI-led transformation since 2020 with no intention to slow down anytime soon.
On the other end of the spectrum are AI experimenters. This group accounts for the majority (63%) of companies. It includes industries heavy with legacy technology, such as banks, which will likely take only small steps toward AI maturity. For instance, we expect only 11% of the health care and insurance industries and 12% of the financial sector to reach achiever status by 2024, compared to 50% of the technology sector in the same time frame.
Experimenters wanting to advance their AI maturity should take a page from the achievers' book, which contains five success factors:

1. Deliberately create a culture of innovation: Championing AI starts with leaders that empower their teams to innovate. Consequently, four in five achievers have CEO and senior sponsorship, compared to 56% of experimenters. Emboldened by leadership, a global digital platform is disrupting construction by harnessing AI and generative design to create autonomous buildings that fit together like pieces of a Lego set.

2. Invest heavily in talent and skills training: Hiring professionals with data and AI skills remains challenging, which is why incorporating AI into the workplace requires investing in reskilling and training to produce better AI literacy across teams. “Gamified” training has proved successful in achieving these goals. A major US. utility firm emphasized upskilling to transition their maintenance employees into quantitative engineers. One such employee then used his training to write predictive software that saved the company $1 million on equipment maintenance.

3. Create an AI core that integrates AI across all functions: Companies need infrastructure in place to transform ideas into products. Creating an AI core -- an operational data and AI platform that taps into companies’ talent, technology, and data ecosystem -- helps balance experimentation with ex*****on. A European energy company developed a digital factory that trained its field engineers to work with and improve machine learning models. The investment shortened the build time for AI-powered apps from 18 months to five months, boosting the company's annual bottom line by $1.5 billion within the next three years.

4. Design responsibly, from the start: With more technology comes more responsibility. Designing, developing, and deploying AI with good intentions is a must. Companies that successfully apply responsible AI can empower and build trust with employees, businesses, and customers. A central bank partnered with the financial industry to produce the first practical methodology and toolkit with detailed guidance on using AI to leverage the fair, ethical, accountable, and transparent (FEAT) principles.

5. Remember there is no finish line: To avoid being left behind, most companies need to increase their spending on AI aggressively. Achievers get more out of AI simply because they invest more in it. We found that in 2018, achievers devoted 14% of their total technology budgets to AI, while in 2021, they devoted 28%. In 2024, they expect to devote 34%. Achievers also understand that their AI investment journey does not have a finish line. They frequently note, there is no “peak AI.”
Investments in AI are rising across the patch. Nearly half (49%) of all analyzed companies will invest more than 30% of their technology budgets in AI by 2024, up from 19% in 2021. That makes it every technology leader's responsibility to ensure these funds will advance their organization's AI maturity. Technology is transforming every part of a business, sometimes leading to total enterprise reinvention. AI will play a key role, and technology leaders can no longer limit it to making a company more efficient. They must harness AI as a lever for growth and innovation

This content was originally published: https://www.informationweek.com/big-data/ai-is-now-mature-enough-to-drive-revenue-growth

08/08/2022

TOP 10 BEST APPS TO LEARN DATA SCIENCE AS A BEGINNER IN 2022

Today, data is ruling the world and there’s no second thought to it. With so much importance given to data, organizations are in constant search of the people who make the best of data. This is why being efficient in data science helps. On the same lines, let us have a look at the top 10 best apps to learn data science as a beginner in 2022.

QPython
This python app was developed by QPython lab and is an exclusive one for Android users. This application boasts several features including an interpreter, a runtime environment, a script editor, QPYI, and the SL4A library.

Data Science 101
This is an all-in-one mobile app that encompasses all the machine learning applications in data science. This application has been developed by Successcrazzy. This app focuses on education in machine learning algorithms. Not only will you be able to study machine learning algorithms, download Python code examples and their datasets, and build machine learning models but also visualize them all within the app.

Coursera
Coursera is a huge provider of varied courses and data science stands to be one among them. It has a massive library of data science and data analytics-related courses exclusively designed for beginners. Here, you get endless opportunities for learning on your mobile through video and lecture content.

Enki
Enki is one of those data science apps that covers a wide range of data science topics such as SQL, Data Science, and Python. The courses are suitable for both non-technical beginners and developers of all levels. A point worth a mention is that the Enki app supports your learning through interactive quizzes that further help you learn and remember new concepts.

Datacamp
Datacamp is a mobile application that offers interactive coding courses to help you grasp the fundamentals of coding. In addition to this, you will also learn how to import, analyze, and visualize data all within your smartphone.

Brilliant
Considering how data science is all about science and maths, brilliant is an application that caters to the same. Here, the content is taught to you in the simplest manner possible which can be understood quite easily by beginners thereby allowing more time to apply the knowledge on the quizzes.

Basic statistics
As evident as it can get, this data science application is an ultimate guide for beginners. It covers various topics, such as basic statistical definitions, data descriptions, counting techniques, probability, and so on.

Learn Data Science, Big Data, and Data Analytics
This is a data-oriented application that boasts numerous amount of code examples and comments, and a simple and intuitive user interface. No wonder why this application makes it to the list of the top 10 best apps to learn data science as a beginner in 2022.

SoloLearn
If you are looking for the right application to develop basic programming concepts, then SoloLearn is all that you need. With one of the largest collections of free learning content for programming in data science, data enthusiasts can access free content on Python, R, SQL, Algorithms and Data Structures, and Machine Learning.

Probability distribution
How about an application that allows you to compute probabilities and plot the respective probability mass function diagrams for a whole spectrum of distributions? This is exactly what the “probability distributions” application is all about. Some of the major topics include Poisson, Binomial, Hypergeometric and Geometric distributions.
This content was originally published: https://www.analyticsinsight.net/top-10-best-apps-to-learn-data-science-as-a-beginner-in-2022/

03/08/2022

React Is Used By 75% Of All IT Companies Leaving Far Behind Angular and Vue: TechBehemoths Study

In the tech industry, web development is the segment that progresses at a fast speed. It is a competitive environment where developers shift technology trends and vice-versa. To draw the line of S1 2022 for web development technologies, TechBehemoths surveyed 912 IT Companies and Web Agencies across 49 countries. The study is based on answers between July 12-24, 2022 with one major goal: to identify which web development technologies IT companies use in 2022.

React Is Used By 75% Of All IT Companies Leaving Far Behind Angular and Vue_ TechBehemoths Study

1. JavaScript reaffirms its leading position among programming languages, being used by 89.5% of IT companies.
2. React.Js is used by more than 75% of IT companies leaving far behind its industry competitors - Angular and Vue
3. 73.3% of all IT companies continue to develop projects on WordPress, confirming the position of #1 CMS of all times.
4. Git is the detached leader among web development tools with more than 89% of IT companies using it
5. Google Cloud has the smallest share among all options when it comes to hosting IT projects
6. PHP is used by 75% of all IT companies but not as much as the leader - JavaScript which has a share of 90%.
7. Over 94% of all IT companies continue to use MySQL, which makes it the leader among all databases in the industry. At the other edge, there is Oracle - used by only 13.2% of IT companies worldwide
8. VS Code is the most used web development environment among IT companies' professionals with a share of 53.5%

Web Development Predictions and Trends for 2023:
In the framework of the study conducted by TechBehemoths, tech leaders across 49 countries anticipated how the web development technologies will impact business environments and what to expect in the year to come.
The main ideas focus on Progressive Web Apps as a trend in 2022, and the continuous rule of the JavaScript stack in web development frameworks. At the same time, some tech specialists consider that the .NET suite will be mainstream technology in 2023.
According to Mircea Sirbu, CTO at Mobiteam, we might witness the rise of Deno & Rise which could jeopardize the leading position of Node.Js.
Dmitry Sergienko CEO at Betlace, states that artificial intelligence, machine learning, and Big Data could be the new mainstream in web development in 2023.
On the framework side, Kenneth Metral, CEO at Cosmico Studios considers that React will continue to be dominant, which in its turn will push Vue and Angular out of the picture.
Overall, Sean O'Neill, Founder of MARSWorks thinks that the rapid trends change is the real problem in web development, as it becomes more and more challenging to become proficient in technologies and frameworks and to deliver projects based on them.
The survey has successfully identified the most popular web development technologies companies use nowadays, more about which you can learn by reading the study results
TechBehemoths is one of the fastest-growing platforms, created in Germany, that connects 57,000 reputable IT companies from 140 countries with clients and projects from all over the world.
This content was originally published: https://lnkd.in/dqcNzhFQ

02/08/2022

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01/08/2022

TOP 5 TECH TRENDS TAKING OVER THE UX DESIGN
Find out about some of the most talked-about tech trends and how they might impact your UX design
Technology is the significant tool of the present day that is disrupting all major industries. We are no longer limited to connecting using phones, yet they can now use smart-home speakers taking the help of virtual assistants to play music or even to turn off a stove. New technologies such as motion sensing, and augmented reality are taking over the gaming sector rapidly.
Motion Sensing Technology
Motion can lead a user through a sequence of actions that are mandatory to complete the tasks. Motion can propel the user experience and directly take into account the actions of the user such as visual feedback, animation, or even imagery. The motion-sensing technology is built into the Pixel 4 and is capable of allowing basic controls such as silencing alarms or skipping to the next song. Google has implemented these changes in its Pixel 4, and some other phones have also started to adopt these technologies. Here the job of the US designer is to minimize the gap between the user’s expectation and what they’re perceiving.
Extension of Connected Devices
The craze for smart devices is increasing day by day. For everyday users, these devices can include anything ranging from coffee makers to self-driving cars. Users can link many of these devices together to collect data and perform automated actions. The UX designer can simply create wireframes and send a prototype to participants, gain prompt feedback and quickly make changes.
AR Apps
Augmented Reality is emerging as one of the major technologies right now. It allows you to see the real-life closeup-close waves in the ocean, cats chasing leaves with a digital augmentation replacing it. For UX designers, creating wireframes and high-fidelity mockups for these apps will require deeper animation skills utilising prototyping tools with motion technology.
Cloud Computing
The evolution in cloud computing has witnessed the rise of serverless computing. It can enable both users and enterprises to run software without installing it, providing stability and security. Cloud computing gets rid of the problem of buying and maintaining hardware. UX designers can share their work through most platforms with cloud-based tools. The cloud encourages and facilitates our need to break out of the shackles of a single workstation.
AI and ML
Artificial Intelligence and Machine Learning have already been integrated into the online shopping experience at least the beginning stages of it. ML is the field of study that gives computers the capability to learn without being explicitly and directly programmed. For UX designers and other tech professionals, gathering user data can be complex and ethical. Personalization or customization of preferences before using a service with AI and ML.
Cre: https://lnkd.in/gnPtNU-D

01/08/2022

5 Reasons why Automated Testing is not Replacing Manual Testing
1. Usability testing can’t be automated.
Automating usability tests is just not possible. Usability testing requires a human. You can’t train a computer to identify “good” usability vs “bad” usability. Perhaps you’re thinking, “ok, we will just skip usability testing”. Don’t make that mistake. By skipping usability testing, you’re introducing a tremendous amount of risk.
This step in the QA process is crucial to ensure confidence in the release, and there’s no way around involving a human being in usability testing.
2. Automated testing only tests what is predictable.
Automated tests reassure us that what we expect to happen does in fact happen. We call this the “happy path”. Automation focuses on functionality that already exists. Its coverage is vast, but it is not deep. Automated testing is great for regression tests, especially when resources are limited. But only doing automated testing is sure to introduce some failures and holes in your testing process.

3. We’re all exploratory testers.
The truth is, we all do software testing. Even if you don’t have “tester” or “QA” in your title, chances are you’ve partaken in some exploratory testing. This “choose your own path” type of testing is not possible with automation. Exploratory testing allows us to take areas of our application and peel back the layers to uncover things automated tests will never find. It enables us to ask questions like “what if I do it this way instead?”. Exploratory testing is a manual process, and there’s no changing that.

4. Automated tests can contain bugs/errors.
Just like your application’s code can contain bugs, automated tests can too. If you write automated tests with bugs, you’re going to have false positives. This can lead to major problems for your customers and your team. The human element of manual testing can identify these errors and make sure you’re testing properly.

5. Technical limitations can come into play.
Some test scenarios are just too complicated or downright impossible to automate. A common argument is “automated testing is cheaper”. But it’s not hard to spend a ton of time and money on elaborate automation. Take for example, testing a variety of touch screen devices. How do you automate the experience of a “tap” and a “swipe”. You can’t do that in a way that is equivalent to human usage.
Conclusion
The existence of both manual testing and automated testing forces us to think about our choice of tools, their cost, and the benefit they will provide. Is automated testing replacing manual testing? No, because there is a time and place for both methods of testing. Manual testing helps us understand the entire problem and explore other angles of tests with flexibility. Automated testing helps save time in the long run by accomplishing a large number of surface-level tests in a short time. It’s up to you to determine when and where each method of testing is used.
This content was originally published: https://blog.testlodge.com/is-automated-replacing-manual-testing/

18/07/2022

How Women in Tech Can Create Their Own Opportunities

A Women Who Code leadership fellow shares how women can create their own opportunities, overcome career hurdles, and be the change they wish to see. The key: Take risks, fail, learn, and keep trying.
“Do the one thing you think you cannot do. Fail at it. Try again. Do better the second time. The only people who never tumble are those who never mount the high wire...” — Oprah Winfrey
If anyone knows a thing or two about mounting the high wire -- and setting the bar high -- it’s Oprah.
Today, Oprah is an internationally recognized talk show host, media executive, actress, and billionaire philanthropist. But years ago, she had to navigate gender, economic, and race barriers to create her own opportunities for success. She secured an on-air primetime anchor position in Baltimore, but when ratings dipped, she was fired. Undeterred, Oprah shifted gears. She landed a job co-hosting a daytime talk show and the rest is history. Oprah has proactively sought out opportunities (from acting roles to authoring books), never feared failure, and always learned from each step of her life journey.
I think women in technology can apply a few of Oprah’s lessons to forge their own career paths, navigating career hurdles and roadblocks in the process. And when I mention hurdles, I’m referring to the long-standing underrepresentation of women in technology-related fields. Despite making up nearly half of today’s total workforce, women account for only 25% of those working in technology. And more than half (56%) of women leave the tech industry, by the mid-level point in their careers, often driven out by gender bias and institutional barriers they encounter. How can women best conquer potential hurdles and roadblocks as they pave their path to career success? Keep reading.

1. Don’t be afraid to be the ‘first’ and ‘only’
I grew up in Bangladesh within a large, extended family. I didn’t have a laptop and had to use the big desktop computer we all shared at the house. Imagine 10 people sharing one computer and you can sense the chaos around homework time. When the computer would crash, which was often because it was so heavily used, I would tell my uncle. My uncle’s reply: “I’ll call my friend -- he can fix it.” No one was allowed to touch the computer until this man showed up to repair it.
I was being told we needed a man to fix the computer. I suggested various ways to revive the computer but was told that I couldn’t fix it. This was a man’s job. “If I become a computer scientist,” I thought, “I will be able to fix my computer without having to wait for a man to fix it.” One simple question served as the inspiration for my future career: “Why can’t I learn to fix the computer?” Even though I didn’t have any “women in tech” role models, I built up the confidence to take risks (more on that in a moment). I later moved to Canada to earn a master’s degree in computer science, and now work as an AI research scientist at San Francisco-based Volta Charging, an electric vehicle infrastructure company.

2. Be the change you wish to see
Traditionally, women have endured gender-based stereotyping. This began in the home, where young girls were steered toward compassion-based careers such as nursing or teaching. It’s also assumed that women will take on the majority of household and child-raising responsibilities. What if we, instead, told young girls, “Why not try computer programming? You’re good at math. Keep working at it.” Or “I know you’re interested in space exploration. What if you could work for NASA someday?” This early messaging is key, as the teenage years are often when young people begin to evaluate career options.
Even if they do achieve their dream tech career, many women struggle to balance family and job tasks in the middle of their careers. When women don’t get needed support from family and the workplace, they drop out of the workforce or shift to a different career. This was highlighted during the first two years of the COVID pandemic when more than one million women left the labor force.
I’ve always been aware of these potential gender-related barriers -- and I’ve worked to help break them. As a leadership fellow in Women Who Code, an international nonprofit dedicated to inspiring women to excel in technology careers, I help organize free workshops, tutorials, and “ask me anything” sessions with diverse women leaders from Google, Facebook, and Microsoft. Our attendees are inspired by the talks, as they see other women like themselves and can hear firsthand about their career journeys.

3. Seek opportunities -- and don’t be afraid to fail
Don’t wait for opportunities to fall into your lap. Seek out opportunities to try, fail, learn, and improve your skills. I’m a big proponent of hackathons, and I’ve participated in several contests and conferences. When I submitted a paper to a specific conference or applied for a job and didn’t get an offer, I always sought out feedback and ways I could improve the next time. I trained myself to remember that these were not personal rejections, and I focused on the lesson I could learn.
Speaking of lessons learned, it was a hackathon that actually helped me land my first job. When I was in graduate school, I took part in an AI hackathon in Canada. I was a finalist in the contest and networked with one of the event judges. A year later, I was applying for jobs and had gotten a few rejections. I then remembered the hackathon judge I had spoken with and sent her my resume. I was thrilled when she replied that her team was looking for a data scientist. I later marveled at the fact that I was sitting on the same couch where only a year before I was a hackathon participant -- but now I was a full-time data scientist.
Hackathons and conferences not only help you sharpen your problem-solving and presentation skills, but you are exposed to people you otherwise may not meet -- from fellow participants to judges and organizers. These days, I try and pay it forward by taking part in hackathons and competitions -- but this time as a judge. For example, I was honored to be selected as a judge for TigerGraph’s “Graph for All Million Dollar Challenge,” a global search that tasks participants with using graph technology to solve pressing world problems. I hope to eventually engage with promising participants to offer advice, mentorship, and guidance.
There’s an old proverb that proclaims that a journey of a thousand miles begins with a single step. The same principle applies when it comes to your technology career. As Oprah said, the only people who never fall are those who never dare to climb. Take steps, fail, fall, get up, learn, and keep walking. This is the way forward and the path to success.
This content was originally published: https://www.informationweek.com/it-life/how-women-in-tech-can-create-their-own-opportunities

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