Our model, called GPT-2 (a successor to GPT), was trained simply to predict the next word in 40GB of Internet text. Due to our concerns about malicious applications of the technology, we are not releasing the trained model. As an experiment in responsible disclosure, we are instead releasing a much smaller model for researchers to experiment with, as well as a technical paper. GPT-2 is a large transformer-based language model with 1.5 billion parameters, trained on a dataset[1] of 8 million web pages. GPT-2 is trained with a simple objective: predict the next word, given all of the previous words within some text. The diversity of the dataset causes this simple goal to contain naturally occurring demonstrations of many tasks across diverse domains. GPT-2 is a direct scale-up of GPT, with more than 10X the parameters and trained on more than 10X the amount of data. GPT-2 displays a broad set of capabilities, including the ability to generate conditional synthetic text samples of unprecedented quality, where we prime the model with an input and have it generate a lengthy continuation. In addition, GPT-2 outperforms other language models trained on specific domains (like Wikipedia, news, or books) without needing to use these domain-specific training datasets. On language tasks like question answering, reading comprehension, summarization, and translation, GPT-2 begins to learn these tasks from the raw text, using no task-specific training data.

San Francisco (CNN Business)A new artificial intelligence system is so good at composing text that the researchers behind it said they won't release it for fear of how it could be misused. Created by nonprofit AI research company OpenAI (whose backers include Tesla CEO Elon Musk and Microsoft), the text-generating system can write page-long responses to prompts, mimicking everything from fantasy prose to fake celebrity news stories and homework assignments. It builds on an earlier text-generating system the company released last year. Researchers have used AI to generate text for decades with varying levels of success. In recent years, the technology has gotten particularly good.

Last week, the nonprofit research group OpenAI revealed that it had developed a new text-generation model that can write coherent, versatile prose given a certain subject matter prompt. However, the organization said, it would not be releasing the full algorithm due to "safety and security concerns." Instead, OpenAI decided to release a "much smaller" version of the model and withhold the data sets and training codes that were used to develop it. If your knowledge of the model, called GPT-2, came solely on headlines from the resulting news coverage, you might think that OpenAI had built a weapons-grade chatbot. A headline from Metro U.K. read, "Elon Musk-Founded OpenAI Builds Artificial Intelligence So Powerful That It Must Be Kept Locked Up for the Good of Humanity."

Last week, OpenAI released GPT-2, a conversational AI system that quickly became controversial. Without domain-specific data, GPT-2 achieves state-of-the-art performance in seven of eight natural language understanding benchmarks for things like reading comprehension and answering questions. A paper and some code were released when the unsupervised model, trained on 40GB of internet text, went public, but the entirety of the model wasn't released due to concerns by its creators about "malicious applications of the technology," alluding to things such as automated generation of fake news. As a result, the wider community cannot fully verify or replicate the results. Some, including Keras deep learning library founder François Chollet, called the OpenAI GPT-2 release (or lack thereof) an irresponsible, fear mongering PR tactic and publicity stunt.

A recent decision by research lab OpenAI to limit the release of a new algorithm has caused controversy in the AI community. The nonprofit said it decided not to share the full version of the program, a text-generation algorithm named GPT-2, due to concerns over "malicious applications." But many AI researchers have criticized the decision, accusing the lab of exaggerating the danger posed by the work and inadvertently stoking "mass hysteria" about AI in the process. The debate has been wide-ranging and sometimes contentious. It even turned into a bit of a meme among AI researchers, who joked that they've had an amazing breakthrough in the lab, but the results were too dangerous to share at the moment.

Is it possible that an AI could exist or will exist in the near future that is too dangerous to release as open source and should not be uploaded to the public or even released even within companies' private networks? Were movies like Tron, Matrix, Terminators and others warning us of such a scenario? Surprisingly such a dangerous AI algorithm may already exist although for now it focuses on text and natural language processing. Click here to view original webpage at www.forbes.com

AI safety research needs social scientists to ensure AI succeeds when humans are involved. That's the crux of the argument advanced in a new paper published by researchers at OpenAI ("AI Safety Needs Social Scientists"), a San Francisco-based nonprofit backed by tech luminaries Reid Hoffman and Peter Thiel. "Most AI safety researchers are focused on machine learning, which we do not believe is sufficient background to carry out these experiments," the paper's authors wrote. "To fill the gap, we need social scientists with experience in human cognition, behavior, and ethics, and in the careful design of rigorous experiments." They believe that "close collaborations" between these scientists and machine learning researchers are essential to improving "AI alignment" -- the task of ensuring AI systems reliably perform as intended.

GPT2 represents a major advancement in what's known as unsupervised learning. With most neural networks, the training consists of supervised learning. That means you have to feed in labeled data sets and evaluate the outcome to tune the various processing nodes until the network functions as intended. Unsupervised networks like GPT2 can assimilate large volumes of data without human involvement. Many researchers believe this is key to the future of AI, and OpenAI just showed that it can work and produce impressive results.

OpenAI's researchers knew they were on to something when their language modeling program wrote a convincing essay on a topic they disagreed with. They'd been testing the new AI system by feeding it text prompts, getting it to complete made-up sentences and paragraphs. Then, says David Luan, VP of engineering at the Californian lab, they had the idea of asking it to argue a point they thought was counterintuitive. In this case: why recycling is bad for the world. For decades, machines have struggled with the subtleties of human language, and even the recent boom in deep learning powered by big data and improved processors has failed to crack this cognitive challenge.

Artificial Intelligence is rapidly becoming more advanced. One of the organisations working on AI is OpenAI; the not-for-profit artificial intelligence research organisation co-founded by Elon Musk. Last week, they produced a paper demonstrating the progress they have made on predictive text software. The AI that they developed, called GPT2, is so efficient in writing a text based on just a few lines of input, that OpenAI decided not to release the comprehensive research to the public. Already, GPT2 has been described as the text version of deep fakes.