Here is a quick read: Meet ByteDance AI's Xiaomingbot: World's First Multilingual and Multimodal AI News Agent The paper Xiaomingbot: A Multilingual Robot News Reporter is on arXiv.

As AI and machine-learning tools become more pervasive and accessible, product and engineering teams across all types of organizations are developing innovative, AI-powered products and features. AI is particularly well-suited for pattern recognition, prediction and forecasting, and the personalization of user experience, all of which are common in organizations that deal with data. A precursor to applying AI is data -- lots and lots of it! Large data sets are generally required to train an AI model, and any organization that has large data sets will no doubt face challenges that AI can help solve. Alternatively, data collection may be "phase one" of AI product development if data sets don't yet exist.

Well, that's where it started. I've still got a lot of work to do, but I'm working on a game that will be similar to but different than AI Dungeon. I want to build something similar but with my own flavor - maybe not as open-ended and with some other systems in place. I'm happy to announce that work has begun! Here's the latest video describing a bit more about the project and what's to come... Latest incarnation with plans and notes to turn it into a game of sorts... Here's a video from about a week ago before I had the idea to turn it into an RPG of sorts...

July 21, 2020 at 5:28 p.m.. E Source Cos. LLC, a Boulder research and consulting firm for the utilities industry, has acquired artificial intelligence …

The scope of a lucrative career promoted by Google through its video distribution platform YouTube has attracted a large number of users to become content creators. An important aspect of this line of work is the feedback received in the form of comments which show how well the content is being received by the audience. However, volume of comments coupled with spam and limited tools for comment classification makes it virtually impossible for a creator to go through each and every comment and gather constructive feedback. Automatic classification of comments is a challenge even for established classification models, since comments are often of variable lengths riddled with slang, symbols and abbreviations. This is a greater challenge where comments are multilingual as the messages are often rife with the respective vernacular. In this work, we have evaluated top-performing classification models for classifying comments which are a mix of different combinations of English and Malayalam (only English, only Malayalam and Mix of English and Malayalam). The statistical analysis of results indicates that Multinomial Naive Bayes, K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Random Forest and Decision Trees offer similar level of accuracy in comment classification. Further, we have also evaluated 3 multilingual transformer based language models (BERT, DISTILBERT and XLM) and compared their performance to the traditional machine learning classification techniques. XLM was the top-performing BERT model with an accuracy of 67.31. Random Forest with Term Frequency Vectorizer was the best performing model out of all the traditional classification models with an accuracy of 63.59.

We will also cover some unique and cutting-edge methods leveraging artificial intelligence/machine learning (AI/ML) to counter these threats and …

Advanced artificial intelligence (AI) and machine learning tools are becoming increasingly critical in detecting and combatting cyber threats.

Sisu is built on a novel machine-learning engine, purpose-built to handle the kind of high-volume, high-dimensional data enterprises are collecting in …

The use of artificial intelligence in agriculture is expected to surge as interest increases and technology develops, researchers say. "It is already very …

The CEO of a startup that purportedly used artificial intelligence to deliver customer insights from internet videos fraudulently raised at least $11 million …