Goto

Collaborating Authors

Results


The Future Of Artificial Intelligence: A Complete Overview - 1 Blog Online

#artificialintelligence

Before diving into Artificial Intelligence's future, Let's have a look at what is Artificial Intelligence. Artificial Intelligence is a machine Intelligence. In contrast with natural intelligence, machine intelligence is more accurate and efficient because it demonstrated by machines, not by humans or animals. Today, AI properly knowns as narrow AI (or weak AI), just because of designed it for narrow tasks. But, for a long-term goal, many researchers go for general AI (AGI or strong AI).


A hyperdimensional computing system that performs all core computations in-memory

#artificialintelligence

Hyperdimensional computing (HDC) is an emerging computing approach inspired by patterns of neural activity in the human brain. This unique type of computing can allow artificial intelligence systems to retain memories and process new information based on data or scenarios it previously encountered. Most HDC systems developed in the past only perform well on specific tasks, such as natural language processing (NLP) or time series problems. In a paper published in Nature Electronics, researchers at IBM Research- Zurich and ETH Zurich presented a new HDC system that performs all core computations in-memory and that could be applied to a variety of tasks. "Our work was initiated by the natural fit between the two concepts of in-memory computing and hyperdimensional computing," Abu Sebastian and Abbas Rahimi, the two lead researchers behind the study, told TechXplore.


Artificial Intelligence Growing

#artificialintelligence

Artificial Intelligence (AI) is growing in spite of COVID-19. Though AI is not new, it has made major advancements recently in many fields. I will highlight five artificial intelligence trends for 2020. AI in digital marketing has ushered in unprecedented change on social media. It forecasts 24/7 chatbots, analyzes data and trends, manages custom feeds to generate content, search for content topics, create custom based personalized content, and make recommendations when required.


Natural Language Processing (NLP) with Python: 2020

#artificialintelligence

BESTSELLER Created by Ankit Mistry, Vijay Gadhave, Data Science & Machine Learning Academy English English [Auto] PREVIEW THIS COURSE - GET COUPON CODE Description Recent reviews: "Very practical and interesting, Loved the course material, organization and presentation. Thank you so much" "This is the best course to learn NLP from the basic. According to statista dot com which field of AI is predicted to reach $43 billion by 2025? If answer is'Natural Language Processing', You are at right place. How Android speech recognition recognize your voice with such high accuracy.


Getting Girls Into the Artificial Intelligence Pipeline

#artificialintelligence

The term artificial intelligence (AI) was coined 64 years ago at a scholarly conference. The AI field hasn't remained the theoretical province of computer scientists and mathematicians; it now is a pervasive part of everyday life. With a technology this powerful, it is critical to include the perspectives of all women, including those from underrepresented communities. AI applications -- based on algorithms -- are found in robotics, machine learning, natural language processing, machine vision, speech recognition and more. These applications are found in homes, vehicles and myriad other aspects of daily life.


AI is Transforming Digital Marketing Landscape in 2020 - The Next Scoop

#artificialintelligence

Understanding text, images, and sounds is not a uniquely human prerogative anymore. Artificial intelligence is transforming virtually every business. AI's ability to derive data-driven insights is paving the road to better digital marketing. From the vast data analysis, marketers gain valuable consumer insights and change how they connect brands with their audiences. Why artificial intelligence cannot be separated from digital marketing anymore?


How Having Bigger AI Models Can Have A Detrimental Impact On Environment

#artificialintelligence

The COVID crisis has skyrocketed the applications of artificial intelligence -- from tackling this global pandemic, to being a vital tool in managing various business processes. Despite its benefits, AI has always been scrutinised for its ethical concerns like existing biases and privacy issues. However, this technology also has some significant sustainability issues – it is known to consume a massive amount of energy, creating a negative impact on the environment. As AI technology is getting advanced in predicting weather, understanding human speech, enhancing banking payments, and revolutionising healthcare, the advanced models are not only required to be trained on large datasets, but also require massive computing power to improve its accuracy. Such heavy computing and processing consumes a tremendous amount of energy and emits carbon dioxide, which has become an environmental concern. According to a report, it has been estimated that the power required for training AI models emits approximately 626,000 pounds (284 tonnes) of carbon dioxide, which is comparatively five times the lifetime emissions of the average US car.


Artificial Intelligence Market Research Report (2020-2025) by Future Trend, Growth rate …

#artificialintelligence

Artificial intelligence uses the techniques such as natural language processing, machine learning, adaptive learning, deep learning, and computer vision …


Roadmap to Natural Language Processing (NLP)

#artificialintelligence

Natural Language Processing (NLP) is the area of research in Artificial Intelligence focused on processing and using Text and Speech data to create smart machines and create insights. One of nowadays most interesting NLP application is creating machines able to discuss with humans about complex topics. IBM Project Debater represents so far one of the most successful approaches in this area. All of these preprocessing techniques can be easily applied to different types of texts using standard Python NLP libraries such as NLTK and Spacy. Additionally, in order to extrapolate the language syntax and structure of our text, we can make use of techniques such as Parts of Speech (POS) Tagging and Shallow Parsing (Figure 1).


Introduction to Word Embedding

#artificialintelligence

Humans have always excelled at understanding languages. It is easy for humans to understand the relationship between words but for computers, this task may not be simple. For example, we humans understand the words like king and queen, man and woman, tiger and tigress have a certain type of relation between them but how can a computer figure this out? Word embeddings are basically a form of word representation that bridges the human understanding of language to that of a machine. They have learned representations of text in an n-dimensional space where words that have the same meaning have a similar representation.