As businesses are increasingly transitioning to a remote setup, learning how to adjust and thrive in these settings is integral for success. The books mentioned in this article give real-life advice on how to thrive as an employer/employee in this never-before-seen virtual workspace revolution and maintain a healthy personal life. Readers can gain numerous insights from these recommended reads and truly make the best out of their virtual workspace journey. These recommended readings teach how to be more productive and solve dysfunctional traits (miscommunication, reduced engagement, mishandling of disputes) towards a more competent and self-sufficient team. Deep Work is a type of book that doesn't just give reasons as to why concentration is important but creates a detailed plan for its readers to actively participate in deep concentration to become the best version of themselves.

Artificial intelligence (AI) is a topic that's been in the news before, but it's never been more relevant than now. With the emergence of new technologies such as machine learning and deep learning, experts are predicting that AI will affect job markets, relationships, education, and more. Here's what you need to know about artificial intelligence: Artificial intelligence (AI) is a computer system that can learn and think like a human. This is not the same as machine learning, where computers are programmed to learn from data without being explicitly told how to do it. AI is also not automation: it does not replace the work of people with robots, but expands their capabilities, making them smarter and more efficient in what they do, the use of artificial intelligence ChatGPT to generate voluminous articles is now gaining popularity, but it will be difficult for them to compare on works which people create with their own hands and hard work, as an example, you can take Paperap, where you can see completely free essays online that will be much better than the generated content.

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The assessment of data systems as they actually are, as opposed to what they were previously or are predicted to be, is arguably the paragon of contemporary analytics. Coupling this capability with machine learning enables organizations to not just make the right business decisions, but to capitalize on them in real-time. Achieving this ideal requires more than streaming platforms such as Kafka. The tooling doesn't just involve the right data science models, networking capabilities, or cloud providers. At some point, it comes down to the performance of the underlying database, particularly in regards to concurrency and scale.

The first step to follow in a literature review requires the identification of the text to review. The reviewer must read and then critique the text. The literature reviewed can include books or published scientific papers. Reports published by an institution or government can also be reviewed. In literary studies, the application of data analytics has been considered. It is done using specialized systems and software.

Joining a startup accelerator program is an opportunity that many entrepreneurs vie for. With only 1,300 programs around the world, startup accelerators exclusively invest their time and resources into the most promising companies. A startup accelerator is an intensive, typically mentor-based, program that aims to expedite a young company's growth. Accelerators bring a plethora of knowledge and experience, which can be crucial for first-time founders and the success of their companies. Beyond the mentorship opportunities, startup accelerators can also connect founders to investors and help them with fundraising.

The 20th century was rich in tech innovations, revolutionary ideas, and scientific concepts that significantly changed people's lives. Many of the technologies we use today, such as computers, the Internet, printers, the World Wide Web (WWW), and even the first artificial intelligence (AI) computer, were created in the previous century thanks to many great scientists. Alan Turing was and still is one of the greatest mathematicians and computer scientists of the 20th century, often considered the father of computer science. Hence, in this article, we talk about the life of Alan Turing and his mathematical and technical discoveries. If you are looking for more information on modern technology, check out these AITJ articles: 5 Ways AI can Improve Environmental Sustainability and The Law of Accelerating Returns, Superintelligence, and The Technological Singularity.

When looking into the world of content creation we find ourselves drawn toward the personality and relatability of those we watch. We follow these people through good times and bad because of that human connection we share. Unbeknownst to some though, there is a wide variety of AI posing as people to do jobs like reporting the news. One of these jobs is content creation with robots starting to become more prevalent in many spaces online taking over many communities once occupied solely by humans. This is not an overnight phenomenon either, it has been a gradual rise in popularity as the technology has become more accessible for companies to implement.

This article was updated after publishing the results of our survey of 20 prominent data scientists, in which we asked them, amongst other things, what books had helped them grow the most in their career. In the past weeks, we asked successful data scientists in different industries what books they believe are the best to learn and master the necessary skills to become a data scientist. The books selected on this list come from their suggestions. Data science, business analytics, and machine learning have become critical to numerous aspects of business, while the data scientist profession keeps soaring as one of the most in-demand and well paid in the tech industry. The books reviewed in this article have all received positive feedback from their readers, and they cover a wide range of skills and aspects that a successful data scientist has to master in their career, including statistics, data mining, machine learning, Python, business analytics, and more.

Contrary to what mass media might have you believe, artificial intelligence (AI) is not a new concept. AI was first mathematically conceptualized in 1950 by Alan Turing, a British polymath. Turing proposed that machines could use available information and logic to solve problems and make decisions the same way humans do. Although no tangible program came out of Turing's speculations, Allen Newell, Cliff Shaw, and Herbert Simon soon proved that AI was not simply science fiction. In 1955, Newell, Shaw, and Simon created the first "artificial intelligence" program, Logic Theorist.