Category Archives: Artificial Intelligence

Artificial intelligence (AI) is a field of computer science that is engaged in the development of intelligent computer systems

Artificial Intelligence

How an AI-based Digital Narrator Makes Reading More Flexible

A sort of text-to-speech (TTS) programme called an AI-based digital narrator for e-books employs artificial intelligence to read e-books out loud. The AI can produce synthetic speech that sounds realistic and human-like after being trained on a sizable collection of text and audio samples.

In addition to offering a convenient option for users to listen to ebooks while they are on the road or engaged in other activities, digital narrators may be used to increase accessibility of e-books for those with visual impairments or other disabilities. Digital narrator feature is available on many e-book platforms and reading apps, and it is also feasible to create audio versions of e-books using independent TTS software or websites.

Using an AI-based digital narrator for e-books may look something like this:
Using a screen reader or other assistive technology, a person with visual impairments might utilize an AI-based digital narrator to listen to an ebook on their smartphone or tablet.
Making better use of their time, a student may utilize a digital narrator to listen to an e-book while they are driving to school or finishing their homework.
A busy worker who wants to multitask and squeeze in more reading may employ a digital narrator to listen to an e-book while exercising or engaging in other activities.

To exercise listening skills and expand their vocabulary, someone learning a new language may utilize a digital narrator to listen to e-books in that language.

A digital narrator might be a feature on an e-book platform or reading software, giving consumers the option to have their ebooks read aloud to them rather than reading the content themselves.

Overall, AI-based digital narrators provide a practical and easy approach for people to consume e-books, and they may be applied in a wide range of contexts and circumstances.

AI-based digital narrators for e-books are a type of text-to-speech (TTS) software that uses artificial intelligence to read e-books aloud. Apple users can now have their novels and texts read out to them by an AI-based narrator through the Apple Books marketplace.

The AI-based narrators have names – such as ‘Madison’ – likely so that users can tell apart the different voices and intonations. Digital narrators can be used to make e-books more accessible to people with visual impairments or other disabilities, as well as to provide a convenient way for people to listen to e-books while they are on the go or doing other activities.

Many e-book platforms and reading apps offer digital narrator functionality, and it is also possible to use standalone TTS software or websites to generate audio versions of e-books.”

Artificial Intelligence

AI and Machine Learning professionals – Exploring Global Opportunities

Discover the best opportunities to maximize your earning potential in the United States, Canada, the UK, and Germany.

A positive development for AI professionals is that countries and businesses are competing for the best talent.

As artificial intelligence and machine learning industries grow at a mind-boggling rate, the demand for qualified IT experts is increasing rapidly.

Supply, however, lags far behind demand. The AI market needs people to fill millions of roles, but only 300,000 researchers and practitioners exist worldwide, according to a report by Chinese tech giant Tencent.

This assertion has been backed up by LinkedIn researchers, who report that machine learning engineers are the most sought-after position in the industry, with demand increasing by about 1000% in the last year.

On a global level, artificial intelligence and machine learning are major challenges. Capgemini’s global study found that 55% of organizations recognized not only that there was a wide gap, but that it was also getting wider. The US corporation recognizes the skill gap 70% of the time, compared to 64% of companies in India, 57% of companies in the UK, 55% of companies in Germany, and 52% of companies in France.

There has been a lack of AI engineers to hire even in the largest and most well-known tech corporations.

Due to a rise in demand, salary levels have soared absurdly. Based on The New York Times’ analysis of the AI sector, the very best can sometimes earn millions of dollars with only a few years’ of experience. In the world, only 10,000 people possess the necessary skills to lead significant AI initiatives, according to an independent AI lab.

Therefore, if you are an AI expert, you should exercise discretion now. Choosing where to live, working for what company, and how much you will receive is all up to you.

The following nations are in dire need of talented Artificial Intelligence and Machine Learning practitioners:

The Unite States

AI professionals in the United States can find a variety of opportunities in the tech-driven world of today. AI professionals are in high demand and the demand is expected to continue to grow as businesses increasingly rely on AI solutions. AI professionals can find job opportunities in a wide range of industries such as finance, healthcare, retail, manufacturing, and more.

In the US, most AI specialists possess a bachelor’s degree in computer programming, engineering, or a closely similar subject. Some employers may also require experience in programming, data science, or machine learning. AI professionals can pursue certifications or specialized degrees in AI to demonstrate their expertise.

AI professionals in the United States can earn a competitive salary. The median salary for AI professionals in the United States is $105,000, according to Indeed.com. Salary varies according on geography, job title, and experience. Professionals in AI with experience can make considerably more money, with some making six figures.

In addition to salaries, AI professionals in the United States can receive benefits such as 401(k) plans, health insurance, and vacation time. AI professionals can also find opportunities to advance their careers by taking on more responsibility or pursuing additional training or certifications.

Europe

Digital capabilities, particularly AI and machine learning, are lacking in every nation in Europe. Berlin, London, Paris, Eindhoven, Amsterdam, and Stockholm are all major European IT hubs where AI specialists can find jobs.

In a Dispatches Europe article last November, the absence of digital experts in Europe’s industries was highlighted as the top shortage of talent in the region. Sweden had the greatest lack of technology expertise among the 33 highly developed economies.

The highest-paying high-tech positions in Europe are:

  • Game Developer
  • Artificial intelligence and deep machine learning
  • Blockchain/fintech
  • Cloud security/encryption
  • Robotics

A shortage of qualified specialists in the EU forces European nations to hire experts from outside the bloc to fill the positions. Members of the EU compete fiercely not only with each other, but also with other leading economies.

As a result of a growing economy and aging population, Finland, a neighbor of Sweden, plans to need 15,000 software engineers by 2020.

In addition to the UK, Finland was the first EU nation to adopt a national AI policy, providing government support and a legal framework for digital enterprises.

Digital professionals from India, China, Russia, and the United States are actively being sought after to bridge the skills gap in Finland’s digital game business.

Germany

German companies are likely to face a 3-million-person skilled worker shortfall by 2030, with a sizable portion of them being IT specialists, according to a new study by the consulting company Prognos AG.

Artificial intelligence poses no threat to German tech companies. Experts believe that artificial intelligence developments might allow companies to replace even mid-level staff with artificial intelligence, even if they are able to replace experienced individuals.

AI and machine learning technology cannot be developed and adopted due to a shortage of skilled workers, according to their concern. It is estimated that almost half of businesses are not able to make innovation-related investments due to the difficulty of recruiting qualified employees.

Over 60,000 highly skilled workers have come to Germany since 2012 as a result of the EU’s Blue Card program.

It would be necessary to increase immigration significantly to compensate for a lack of competent workers. In the near future, it is unlikely to come from the domestic labor force. AI, machine learning, and information technology aren’t the most popular jobs among young Germans; they rank fifth behind office administration and vehicle mechanics.

The United Kingdome

UK employers have nearly tripled their need for AI capabilities over the last three years, according to employment site Indeed. The demand for data scientists in the AI sector is increasing as businesses try to leverage the data they’ve collected over the years.

A typical UK income is significantly lower than that of AI and machine learning positions. The average annual salary for listed AI positions is £60,000, with 10% of the highest-paid jobs paying an average of £105,500.

There are a large number of AI jobs available on Indeed, many of which have salaries over £70.000. Depending on the contract, some contracts may cost up to £700 every day.

In high-level positions, the majority of salaries are competitive, so you can apply to several companies and negotiate the best salary with them.

China

Machine learning and AI professionals will find China to be an exciting market. Artificial intelligence development has exploded in the country, and skilled professionals are in high demand. In China, AI and machine learning professionals are paid competitive salaries compared to their counterparts in other countries. A Chinese AI and machine learning professional earns an average salary of $20,000 to $40,000.

Qualifications and experience determine salaries. The average annual salary for an experienced professional is $50,000. Professionals in AI and machine learning have a variety of employment options in China. A number of companies are actively hiring for AI and machine learning positions, including Baidu, Tencent, and Huawei. There are also other companies hiring for AI and machine learning positions, including JD.com, and ByteDance. Chinese start-ups are also seeking AI and machine learning professionals in addition to traditional companies. It is also possible to be a part of a rapidly growing and innovative team at these start-ups in addition to receiving competitive salaries. AI is also heavily invested in by the Chinese government, and the possibility of AI and mac are endless.

Canada

Developing Artificial Intelligence is one of Canada’s top priorities. AI ethics, policies, and legal ramifications, as well as science related to AI, are heavily invested in by the nation. Across Canada, AI-related jobs have increased by 1,069% since 2013, according to Indeed Canada.

DevOps engineer, full stack developer, and machine learning engineer were the most sought-after jobs.

The annual salary for specialists with some experience ranges from $70,00 to $90,000. Advertised incomes for individuals with more than five years’ experience can reach $130,000 and beyond.

Artificial intelligence positions average $85,978 per year, or $44 per hour. The median wage in this country is approximately 2.6 times higher than this. Entry-level roles start at $60,000. Experts earn up to $120,000, while seasoned experts earn up to $200,000.

An Indeed Canada search reveals that most senior positions do not include predetermined salaries but are accompanied by “competitive” pay packages, giving job seekers the opportunity to negotiate.

There are a number of organizations actively seeking candidates with AI skills in Canada, including the Royal Bank of Canada, Capital One, IBM, Huawei, Scotiabank, KPMG, TD Bank, Loyalty One, and Amazon.

Moving to Canada has become increasingly attractive to AI and machine learning professionals due to its booming tech industry, its highly regarded universities, and its Express Entry System.

In addition, some of the most cutting-edge and inventive technological startups in the world are located in Canada. Moving to Canada has numerous advantages and opportunities for AI and machine learning professionals to pursue careers in their fields. Finally, Canada is known for its passion for innovation and its commitment to promoting a culture of inclusivity, making it an attractive destination for AI and machine learning professionals.

India

Several of the most interesting applications of artificial intelligence in industries ranging from farming to healthcare are being tested in India according to a LinkedIn report on the future of the digital workforce. With the nation moving toward becoming a “Digital India,” the IT sector will require 50% more digitally proficient workers.

According to Kelly OCG India, experts in AI and machine learning would be in great demand this year. There is a special demand for (and a scarcity of) Ph.D. candidates in fields relating to artificial intelligence.

Due to of lack local people who are knowledgeable about user interfaces and user experiences (UI/UX), artificial intelligence, and machine learning. According to the data, deep learning is a hot field with a qualified professional ratio of 0.53, and machine learning is a hot field with a qualified professional ratio of 0.63.

In India, the average salary for AI experts rises with experience: for those with 2-4 years of experience, the salary ranges from Rs 15 to Rs 20 lacs ($ 22,000 to $29,000), Rs 20 to Rs 50 lacs ($ 73,000 to 147,000), and Rs 50 to Rs 1 crore ($ 73,000 to 147,000).

Artificial Intelligence

Data Analytics To AI Implementation: How To Build A Great Team

The booming industry of Information Technology has made it possible for data analytics and AI to work together. Many successful businesses use data analytics and AI to build stronger teams in the workplace. A great team can increase employee performance, encourage innovation and bring many benefits to a company’s future. To begin with, let’s take a look at Data Analytics and Artificial Intelligence before moving on to how to build a great team with the same.

Data Analytics and AI

Data Analytics is the science of analysing raw data to make conclusions about that information. Many data analytics techniques and processes have been automated into mechanical methods and algorithms that work over raw data for human consumption.

Data analytics help a business optimise its performance, perform more efficiently, maximise profit, or make more strategically-guided decisions. Data analytics relies on various software tools ranging from spreadsheets, data visualisation, reporting tools, data mining programs, or open-source languages for the most significant data manipulation.

Whereas AI Implementation incorporates AI technology into a company to improve its performance. AI tremendously benefits companies, improving efficiency and accuracy in many different areas. Implementing AI can help a company to keep up with the competition and continue growing.

AI Implementation In Data Analytics

Artificial intelligence (AI) is growing rapidly by intriguing and fascinating people with its benefits. Analysing data is made easier, more accessible, and more automated by using AI. It is employed in various industries and businesses to aid in repetitive processes. Companies use AI analytics to make better decisions about their business. AI technology has vast applications, including data analysis, decision-making and information dissemination. A few of the ways AI can contribute to analytics:

  • Help report generation and makes data easy to understand.
  • Streamlines processes, allowing for insights to be generated faster.
  • Analyses data using machine learning algorithms.
  • Predict future outcomes and reveal trends and patterns.
  • AI eliminates errors and offers a greater level of accuracy.

No matter how AI is implemented in Data Analytics, it is sure to bring benefits to any company that incorporates it into its operations. If your company is looking for a way to stay ahead of the competition, implementing AI is something to consider. To become proficient in AI, you must also have coding skills. You can nurture coding skills from a young age. The benefits of Coding for kids are innumerable. Remember, it’s never too early to start learning new skills.

From Data Analytics to AI Implementation: Building a Great Team

An organisation needs the right data analytics and AI talent at the right time in the right place to take advantage. So how do you go about building a great data analytics or AI team? Here are a few tips:

  1. Hire people with the proper skill set
  2. Create a culture of collaboration
  3. Foster a learning environment.
  4. Set clear goals
  5. Encourage collaboration
  6. Help team members stay motivated.
  7. Be open to change.
  1. Hire people with the proper skill set

This seems obvious, but it’s worth reiterating. When hiring for your data analytics or AI team, look for candidates with the necessary technical skills. But also keep an eye out for soft skills like problem-solving, critical thinking, and creativity.

  • Create a culture of collaboration

Data analytics and AI are team-based disciplines, so creating a culture of collaboration within your team is essential. Encourage open communication and ensure everyone feels like they can contribute to the collective goal.

  • Foster a learning environment.

Data analytics and AI are constantly evolving, so creating an environment where learning is encouraged is essential. Fostering a learning environment means investing in training and development opportunities for your team or simply creating a space where people feel comfortable sharing new ideas.

  • Set clear goals

Data analytics and AI can be used for various purposes, so it’s essential to set clear goals for your team from the outset. What exactly do you want to achieve with these technologies? Once you have a good understanding of your goals, you can start to put together a plan for how to achieve them best.

  • Encourage collaboration

Data analytics and AI are complex topics, so it’s important to encourage cooperation between team members. This could mean setting up regular brainstorming sessions or ensuring everyone feels comfortable sharing their ideas.

  • Help team members stay motivated.

Data analytics and AI can be challenging, so it’s important to help team members remain motivated throughout the process. This could mean providing regular feedback or offering incentives for meeting milestones.

  • Be open to change

Data analytics and AI are constantly changing, so it’s essential to be available to change. This means being willing to experiment with new methods and technologies. Data analytics and AI are constantly evolving, so it’s essential to be available to change. Being open to these changes means adapting to new technologies and processes as they become available. It also means being willing to learn new skills and techniques. By being open to change, you can ensure that you and your team remain at the forefront of these rapidly changing fields.

Wrapping Up

Artificial intelligence and data analytics have become more widespread. They are applied to numerous business operations, both big and small. Since AI and Data analytics plays a significant part in the growth of any business, it has become a necessity to build a team capable of handling them. Data analytics and AI can be challenging, but by following these tips, you can make a great team capable of meeting any challenge. With the right team in place, you can achieve success with data analytics and AI.

Artificial Intelligence

Google Presents Minerva AI

Google offers Minerva the first AI capable of solving math-related problems step-by-step.


Minerva is a built-in PaLM ( Pathways Language Model ) in which additional training was added, consisting of the 118 GB of scientific research articles from arXiv and webpages that include mathematical expressions written in LaTeX and MathJax as well as other formats.

The model has been taught the ability to “converse using standard mathematical notation,” according to researchers. In other words, the process is like other language models that generate various solutions, and Minerva gives probabilities for different results.

Each answer arrives (almost always) with the same effect, with distinct stages. The way the model works is to employ majority voting to pick the most commonly-used answer and then give the answer as the final one.

According to Google, Minerva is wrong now and then; however, his errors can be “easily interpretable.” According to the research, “about half are calculation errors, and the other half are reasoning errors, resulting in nonlogical reasoning.”

To better solve math-related problems, Minerva also uses contemporary methods of prompting and grading. They include majority voting and chains of thought, also known as scratchpads. Like many language models, Minerva offers probabilities to various possible outcomes.

Minerva generates a range of possible answers by randomly sampling every viable product while answering the question. Although these techniques’ stages differ, they usually produce the same result. Minerva chooses the most commonly used answer as the answer, making use of majority voting.

Artificial Intelligence

Can we identify by the person’s breath?

A group of researchers has developed an olfactory sensor that is capable of being able to identifying a person’s breath. Utilized in combination with an AI, the “artificial nose” authenticated up to 20 people, with an average accuracy of more than 97%.

In the current age of technology and information, the present biometric authentication is an essential security measure to protect precious assets. Breath detection is currently in addition to the plethora of biometric data machines already have to identify us.

These methods are built on the physical distinctiveness of every individual, but they’re not foolproof. Physical traits can be replicated and even altered through trauma,” explains Chaiyanut Jirayupat, the primary researcher of the study published in Chemical Communications. “Recently, the human scent has been identified as a novel type of biometric authentication, and it’s essentially using your unique chemical makeup to verify who you are.”

Percutaneous gas is comprised of the compounds created through the skin. The theory is that machines recognize these gasses. But, the skin is not producing enough chemicals that the machines can recognize. Therefore, the team looked into the use of breath as a method to identify compounds. “There can be quite a few parts per billion or trillion of volatile compounds in the skin, while exhaled compounds can have a multiple of a million,” Jirayupat continues. “Human breath has already been used to identify whether a person has cancer, diabetes, and even COVID-19 .”

The scientists first identified substances that could be utilized to authenticate biometrics. To accomplish this, they examined breath samples of participants and discovered 28 substances that could be used as options. They then created a set of olfactory sensors with 16 channels, each of which identified a specific spectrum of compounds. The sensors’ data were fed to an AI to study the composition of each individual’s breath and create a unique profile for each individual.

This system was tested with breath samples taken from six individuals. The results were positive, and it could identify the individual with an accuracy average of 97.8 percent if the sample were expanded to include 20 individuals. The level of accuracy was maintained. “This was a diverse group of individuals of different ages, genders, and nationalities. It is encouraging to see such high precision in all cases,” Explains Takeshi Yanagida, who led the study.

The researcher, however, acknowledges that we need to continue working to improve the technology before it is available on smartphones.

“In this work, we required our subjects to fast for six hours before testing,” Yanagida concludes. “We have developed a good foundation, and the next step will be refining this technique to work independently of diet. Fortunately, our current study has shown that adding more sensors and collecting more data can overcome this hurdle.”