JCMR recently announced market survey which covers overall in-depth study including additional study on COVID-19 impacted market situation on Global Artificial Intelligence Software Market. The Research Article Entitled Global Artificial Intelligence Software Market provides very useful reviews & strategic assessment including the generic market trends, upcoming & innovative technologies, industry drivers, challenges, regulatory policies that propel this Universal market place, and major players profile and strategies. The research study provides forecasts for Artificial Intelligence Software investments till 2029. There are following 15 Chapters to display the Global Artificial Intelligence Software Market. Table of Contents 1 Market Overview 1.1 Global Artificial Intelligence Software Introduction 1.2 Market Analysis by On-Premise Cloud-based 1.3 Market Analysis by Voice Processing Text Processing Image Processing 1.4 Market Analysis by North America, Europe, China, Japan, Rest of the World 1.5 Market Dynamics 1.5.1 Market Opportunities 1.5.2

Senate Minority Whip Dick Durbin apologizes to Sen. Tim Scott for the remark on the Republican police reform plan. Fox Nation host David Webb on Thursday blasted Senate Minority Whip Dick Durbin for calling Sen. Tim Scott's role in crafting the GOP-led police reform bill a "token approach." "I don't know what's in Dick Durbin's heart," Webb told "Fox & Friends." "But it's the hypocrisy that if anyone had used that word'token,' which is a legitimate word in the English language, in any way, pointed toward blacks from the right, they [the left] would have gone crazy. They would have been protesting. They would have been claiming the egregious nature of its use."

Natural language processing (NLP) is a field of artificial intelligence in which computers analyze, understand, and derive meaning information from human language in a smart and useful way. By utilizing NLP, developers can organize and structure knowledge to perform tasks such as automatic summarization, translation, named entity recognition, relationship extraction, sentiment analysis, speech recognition, and topic segmentation. NLP is characterized as a difficult problem in computer science. Human language is rarely precise or plainly spoken. To understand human language is to understand not only the words but the concepts and how they're linked together to create meaning.

Many times we listen to speak about machine learning, but it is important to know that there are other pipelines before machine learning which play a significant role in the study of Big Data. Some examples are ETL (extract, transform and load) or NLP(natural language processing). Nowadays, in particular, NLP pipeline is taking more and more space in Data Science. So, what is Natural Language Processing? Natural Language Processing is a process that permits Data Scientist or Data Analyst to extract important information from human language. For example, with NLP it is possible to find an important pattern by studying texts in posts or comments available on a social network.

WASHINGTON (The Borowitz Report)--Accusing it of treating him "very unfairly," Donald Trump lashed out on Wednesday at the widely used spelling tool spell-check. "Almost every time I type a word, spell-check puts a red squiggly line under it," he tweeted. "It never put a red squiggly line under Obama's words." "Spell-check is rigged against conservatives," he charged. Trump accused spell-check of infringing on his First Amendment rights by interfering with what he called "freedom of spelling."

Computer Vision--Advanced text extraction: The most advanced text extraction capability for Computer Vision, Read 3.0, is now generally available and expanding its language coverage beyond English and Spanish to include French, German, Portuguese, Italian, and Dutch. Read 3.0 in containers is also available in preview. Language Understanding and Text Analytics sentiment analysis in containers are now generally available. Language Understanding--Enhanced portal experience: The Language Understanding service has revamped the labeling experience, making it easier to build apps and bots that can understand the complex language structures people tend to use. For example, in this order: "I want a large chicken pizza without sauce and a medium pizza with olives," there are two different language structures within the same order.

In this tutorial I will guide you on how to detect emotions associated with textual data which can be either classified as either positive or negative and how can you apply that knowledge in variety of applications depending on what you wanna do. In this tutorial I will guide you on how to detect emotions associated with textual data which can be either classified as either positive or negative and how can you apply that knowledge in variety of applications depending on what you wanna do. For instance you want to perform automatic analysis of customer feedback with directly reading them as either positive or negative feedback you will need to Sentiment analyzer to check the negativity or positivity of the textual data.

The founders of OST believed that these challenges could be solved by developing new algorithms and data structures specifically designed to support efficient reasoning even with rapidly changing rules and data. This intuition was the starting point for the design and implementation of RDFox. RDFox is a high-performance knowledge graph and semantic reasoning engine which can evaluate complex queries and rules at scale and on the fly. Its speed and flexibility have unlocked a new wave of enterprise applications which had previously been unimaginable.

A team from the Allen Institute for Artificial Intelligence and the University of Washington this week introduced TLDR generation, a new automatic summarization task for scientific papers. The researchers also provide an associated dataset and propose a multitask learning approach for generating TLDR using pretrained language models. Here is a quick read: AI2 & UW Researchers Propose'TL;DR' Paper Summarization Task The paper TLDR: Extreme Summarization of Scientific Documents is on arXiv.

New Delhi, Jan 11 (IANS) When it comes to programming languages in India, Python is most popular among the students for its role in Artificial Intelligence (AI) applications, data science, Machine Learning (ML) and data analytics, US-based online education company Coursera has said. Python dominated the top 10 list with courses like "Programming for Everybody", "Python Data Structures", "Python for Data Science and AI" and more. Python is also easy to get started with, offers a lot of flexibility and is versatile. "Its open source nature makes it easy to learn. A large number libraries for tasks like web development, text processing, calculations add to its appeal," the repor said.