The rise of artificial intelligence (AI) means that it is more important than ever for developers and engineers to deploy AI projects more quickly and at greater scale across an organization. At the same time, there has been a boom of AI tools and services designed for different purposes, which has made it challenging to evaluate all of them in the quickly evolving environment.
Read MoreThe term “MLOps” has become increasingly popular with the rise of artificial intelligence (AI), but many business leaders across industries have yet to learn what it is. Born at the intersection of DevOps, data engineering, and machine learning (ML), MLOps is a set of practices that deploy and maintain machine learning models in production reliably and efficiently.
Read MoreTo close out this series on big data in business, which has covered the entire transformation of an organization into an AI-driven business, it only makes sense to conclude with the possible business applications following the implementation of an AI solution.
Read MoreAn AI project is a big deal. It marks the high point of an organization’s transition into an AI-driven business, so it should come as no surprise when it impacts all aspects of the company. AI projects are multidisciplinary and often massive undertakings, requiring a competent development team and effective business leaders.
Read MoreArtificial intelligence (AI) is revolutionizing nearly every industry, creating incredible amounts of economic value in the process. It is one of the greatest tools that have ever been available to businesses, as it provides valuable insights that were previously unattainable by humans alone. At the same time, it is also disrupting almost every domain and industry. And as Andrew Ng puts it, “AI is the new electricity.”
Read MoreCompanies are sitting on a goldmine of data that is becoming increasingly valuable for their growth. The value of information is at an all time high, and the transformation into a data-driven business can greatly improve revenue streams and valuations. A data-driven business is one that transitions from experienced-based, leader-driven decision making to data-driven decision making.
Read MoreThe driving factor behind the success of many today’s organizations is the implementation of artificial intelligence (AI) and data solutions, which is why so many are pouring resources into the area. Whether the company’s activities involve AI, data science, advanced analytics, machine learning, or some other related process, the goal is to use data to increase revenues and efficiency.
Read MoreArtificial Neural Networks, or ANNs, are one of the most common types of deep learning networks. These biologically inspired computational networks consist of three layers and are used to solve a wide range of problems involving speech recognition, text translation, fraud detention, and much more.
Read MoreOne of the subfields of machine learning (ML), deep learning (DL) is focused on artificial neural networks, which are inspired by the structure and function of the human brain. Deep learning attempts to mimic the brain by enabling systems to cluster data and make extremely accurate predictions.
Read MoreNatural language processing (NLP) intersects the fields of computer science, artificial intelligence, and linguistics to enable computers to process and “understand” natural language. This in turn helps them carry out tasks like language translation and text summarization. NLP is quickly becoming one of the most crucial technologies of our day, especially given the rapid rise of voice interfaces and chatbots. It is extremely impressive how far NLP has come in a short time, since human language is incredibly complex and hard to represent.
Read MoreNatural language processing (NLP) intersects the fields of computer science, artificial intelligence, and linguistics to enable computers to process and “understand” natural language. This in turn helps them carry out tasks like language translation and text summarization. NLP is quickly becoming one of the most crucial technologies of our day, especially given the rapid rise of voice interfaces and chatbots. It is extremely impressive how far NLP has come in a short time, since human language is incredibly complex and hard to represent.
Read MoreNatural language processing (NLP) is one of the most innovative and consequential artificial intelligence (AI) technologies. It is becoming increasingly apparent in our everyday lives and is disrupting many industries. NLP applications rely on complex language models, which are extremely difficult and tedious to develop from start-to-finish. Because of this, AI developers often turn to pre-trained language models that can be repurposed for various NLP functions and new datasets.
Read MoreNatural language processing (NLP) is one of the most widely used subfields of artificial intelligence (AI) thanks to its incredible ability to analyze and manipulate human language. Whenever you are interacting with chatbots and digital assistants, which are increasingly becoming part of our everyday lives, NLP is at play. However, its real-world applications don’t stop there as NLP is utilized in a wide range of industries like finance, healthcare, legal, insurance, and autonomous vehicles.
Read MoreNatural language processing, or NLP, can be defined as the study and application of specific tools that enable computers to process, analyze, and interpret human language. NLP combines the different fields of linguistics and computer science, and it is a component of artificial intelligence (AI).
Read MoreThe view that journalism will be heavily impacted by AI is held all around the globe. In 2019, the London School of Economics published a global survey of journalism and AI based on interviews with 71 newsrooms in over 32 countries. One of the conclusions was that AI will reshape journalism, at first in an incremental way, but there will be long-term structural effects. The technology is set to disrupt the field in many ways involving data analytics, prediction making, plagiarism detection, NLP, fake news detection, and more.
Read MoreThe conversation around artificial intelligence (AI) often involves things like business applications, nefarious tools like deepfakes, medical advancements, government regulation, and other “serious” topics. But what about pure entertainment? AI is becoming increasingly prominent in the gaming industry, with nearly every game developer implementing some aspect of the technology. And what is more entertaining than highly realistic, open-worlds run by complex non-player characters driven by AI? With the help of AI tools, gaming is quickly evolving into a new realm humans have never experienced before.
Read MoreCyber attacks, information operations, deepfakes, political and social subversion, financial influence, and the exploitation of social tensions are quickly becoming the new way to target nations in recent years. With the rise of artificial intelligence (AI), these become even more threatening. AI-enabled disinformation will become one of the top tools available to any individual or nation with the right capabilities. While AI can be weaponized and used to attack, it also plays a key role in combating such tactics.
Read MoreThe U.S. National Security Commission on Artificial Intelligence has released its Final Report that includes conclusions, observations, and recommendations in 16 highly-detailed chapters. One of the most interesting points of the entire report is it’s admission that the U.S. government is not prepared to defend the nation in an artificial intelligence (AI) era.
Read MoreOne of the next big moves for AI is the advancement of AI edge chips. These state-of-the-art chips, designed by leaders like Nvidia and IBM, will lessen both consumers’ and enterprises’ reliance on the cloud. As of right now, many technologies like Siri and other voice assistants can only operate with a cloud connection. But with AI chips, your smartphone, watch, or tablet will be able to make language translations, recommend songs, and complete many other complex tasks without a wireless or wifi connection.
Read MoreThe Gamestop, or GME, frenzy that shocked the institutionalized world a few weeks back has become hot once again with another surge in the stock. The entire ordeal has resulted in an increased interest by financial companies in tracking online social media sites like Reddit to extract critical data regarding stocks.
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