Generation


Defending Against Neural Fake News

Neural Information Processing Systems

Recent progress in natural language generation has raised dual-use concerns. While applications like summarization and translation are positive, the underlying technology also might enable adversaries to generate neural fake news: targeted propaganda that closely mimics the style of real news. Modern computer security relies on careful threat modeling: identifying potential threats and vulnerabilities from an adversary's point of view, and exploring potential mitigations to these threats. Likewise, developing robust defenses against neural fake news requires us first to carefully investigate and characterize the risks of these models. We thus present a model for controllable text generation called Grover.


Adversarial Ranking for Language Generation

Neural Information Processing Systems

Generative adversarial networks (GANs) have great successes on synthesizing data. However, the existing GANs restrict the discriminator to be a binary classifier, and thus limit their learning capacity for tasks that need to synthesize output with rich structures such as natural language descriptions. In this paper, we propose a novel generative adversarial network, RankGAN, for generating high-quality language descriptions. Rather than training the discriminator to learn and assign absolute binary predicate for individual data sample, the proposed RankGAN is able to analyze and rank a collection of human-written and machine-written sentences by giving a reference group. By viewing a set of data samples collectively and evaluating their quality through relative ranking scores, the discriminator is able to make better assessment which in turn helps to learn a better generator.


How AI-Powered Content Generation Software Solves Five Business Pains

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The advances you hear about most when it comes to AI are the technologies once discussed in science fiction novels: nanobots that root disease out of the body; cars that navigate relentless traffic better than a human driver; scanners that detect potential skin cancer as well as a dermatologist. What you don't hear about nearly as much, however, are the myriad ways that technologies powered by AI are transforming routine processes and common frustrations, and helping businesses handle mundane tasks so employees can focus on more interesting work. There is perhaps no better example of this than content generation software, powered by AI and Natural Language Processing (NLP). Content generation software is incredibly intuitive and easy to use: most companies can start generating content like BSS reports, e-commerce product descriptions, news content like weather reports, and more within a manner of minutes by inputting basic information via an Excel spreadsheet. The natural language generation (NLG) market includes my company, AX Semantics, as well as other leaders like Arria, Narrative Science, Yseop and Automated Insights.


Natural Language Generation

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"Arria Is A Perfect Fit For You" "Arria is a Leader with robust writing automation and analytics capabilities. We found Arria's writing automation capabilities to be the most comprehensive among all participants. Its founders have written definitive books on NLG and hold more than a dozen patents on the technology… Arria is best for companies that need a "space shuttle" for writing automation. If your writing automation and NLG for analytics call for the top-of-the-line capabilities with a comprehensive IDE, and a myriad of rules and templates, Arria is a perfect fit for you.


The Past and the Present of Natural Language Generation ai-jobs.net

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Rome wasn't built in a day. It has taken years for computers to exhibit the level of intelligence they do today and be able to produce text that sounds and read human-like. It's time to appreciate this revolutionary journey. In 2007, The first step was taken by Robbie Allen, who was a veteran engineer at Cisco. He created an online college basketball website that automatically published game reviews, real-time updates, recaps, and incidents of injury.


Here's How This AI Automates Content Generation In 110 Languages

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AX Semantics an artificial intelligence (AI)-powered, natural language generation (NLG) company said it could create AI-produced content in more than 110 languages. The Stuttgart-based company which launched in the US today, 12 December 2019 already works with hundreds of customers, including several Fortune 500 companies such as Deloitte for BSS reporting, Porsche and Nestlé. The demand for digital content continues to rise. And technology like AI is considered to be instrumental in helping companies keep pace. The global NLG market size is expected to reach $1,150.9


The accessibility of GPT-2 -- text generation and fine-tuning

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Natural Language Generation (NLG) is a well studied subject among the NLP community. With the rise of deep learning methods, NLG has become better and better. Recently, OpenAI has pushed the limits, with the release of GPT-2 -- a Transformers based model that predicts the next token at each time space. Nowadays it's quite easy to use these models -- you don't need to implement the code yourself, or train the models using expensive resources. HuggingFace, for instance, has released an API that eases the access to the pretrained GPT-2 OpenAI has published.


Artificial Intelligence Use Cases in FinTech

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Quill is an automation platform developed by a Chicago-based company Narrative Science. Quill helps in financial reporting with natural language generation (NLG), an AI technology that converts your data into plain English to make you understand the insights in simple words, just like a human data analyst would do in your company. Quill also understands the most relevant part of a report from past records and tries to give the reports in similar words, sentence length, and structure to make it legible for non-technical people. It saves significant time for the enterprises analyzing data and creating hand-written summaries and reports.


5 Ways AI Will Work Its Way Further Into Your Life In 2018 - [INFOGRAPHIC] Decide Consulting

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Facial Recognition Will Become The New Credit Card – instead of swiping your card, AI will match your face Alexa and Siri Will Get Smarter – they will begin learning about you and predicting your preferences Increased Integration With Medical Diagnostics – Medical testing tools will begin predicting illnesses and conditions Content Creation – Natural language generation (NLG) is will begin producing content. AI Will Be Both The Problem and Solution For Cyber Security – AI will create more threats and solutions.


Andrew Quixley talks natural language generation

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Human brains are singularly special in the animal kingdom, writes Andrew Quixley, Data Science and AI Sales Lead, IBM South Africa. We are the curious, communicative collaborators who rose from a simple foraging existence on the savannahs to build structures of incredible complexity. Sure, other animals are curious, communicative and collaborative too. An octopus will investigate and solve problems; elephants use infrasound to communicate over vast distances; termites collaborate to build structures that are millions of times larger than any individual; but none of these feats comes close to the scale of human complexity. And the key to this complexity is our ability to generate language.