from the coming-to-a-PHB-near-you? dept.
College student Liam Porr used the language-generating AI tool GPT-3 to produce a fake blog post that recently landed in the No. 1 spot on Hacker News, MIT Technology Review reported. Porr was trying to demonstrate that the content produced by GPT-3 could fool people into believing it was written by a human. And, he told MIT Technology Review, "it was super easy, actually, which was the scary part."
So to set the stage in case you're not familiar with GPT-3: It's the latest version of a series of AI autocomplete tools designed by San Francisco-based OpenAI, and has been in development for several years. At its most basic, GPT-3 (which stands for "generative pre-trained transformer") auto-completes your text based on prompts from a human writer.
[...] OpenAI decided to give access to GPT-3's API to researchers in a private beta, rather than releasing it into the wild at first. Porr, who is a computer science student at the University of California, Berkeley, was able to find a PhD student who already had access to the API, who agreed to work with him on the experiment. Porr wrote a script that gave GPT-3 a blog post headline and intro. It generated a few versions of the post, and Porr chose one for the blog, copy-pasted from GPT-3's version with very little editing.
The post went viral in a matter of a few hours, Porr said, and the blog had more than 26,000 visitors. He wrote that only one person reached out to ask if the post was AI-generated, although several commenters did guess GPT-3 was the author.
(2020-08-14) OpenAI's New Language Generator GPT-3 is Shockingly Good
GPT-3 is the most powerful language model ever. Its predecessor, GPT-2, released last year, was already able to spit out convincing streams of text in a range of different styles when prompted with an opening sentence. But GPT-3 is a big leap forward. The model has 175 billion parameters (the values that a neural network tries to optimize during training), compared with GPT-2's already vast 1.5 billion. And with language models, size really does matter.
Sabeti linked to a blog post where he showed off short stories, songs, press releases, technical manuals, and more that he had used the AI to generate. GPT-3 can also produce pastiches of particular writers. Mario Klingemann, an artist who works with machine learning, shared a short story called "The importance of being on Twitter," written in the style of Jerome K. Jerome, which starts: "It is a curious fact that the last remaining form of social life in which the people of London are still interested is Twitter. I was struck with this curious fact when I went on one of my periodical holidays to the sea-side, and found the whole place twittering like a starling-cage." Klingemann says all he gave the AI was the title, the author's name and the initial "It." There is even a reasonably informative article about GPT-3 written entirely by GPT-3.
Nvidia and Microsoft have teamed up to create the Megatron-Turing Natural Language Generation model, which the duo claims is the "most powerful monolithic transformer language model trained to date".
"Each model replica spans 280 NVIDIA A100 GPUs, with 8-way tensor-slicing within a node, and 35-way pipeline parallelism across nodes," the pair said in a blog post.
[...] However, the need to operate with languages and samples from the real world meant an old problem with AI reappeared: Bias. "While giant language models are advancing the state of the art on language generation, they also suffer from issues such as bias and toxicity," the duo said.
Related: OpenAI's New Language Generator GPT-3 is Shockingly Good
A College Student Used GPT-3 to Write a Fake Blog Post that Ended Up at the Top of Hacker News
A Robot Wrote This Entire Article. Are You Scared Yet, Human?
OpenAI's Text-Generating System GPT-3 Is Now Spewing Out 4.5 Billion Words a Day