Mixed-initiative dialogue tasks involve repeated exchanges of information and conversational control. Conversational agents gain control by generating responses that follow particular dialogue intents or strategies, prescribed by a policy planner. The standard approach has been fine-tuning pre-trained language models to perform generation conditioned on these intents. However, these supervised generation models are limited by the cost and quality of data annotation. We instead prompt large language models as a drop-in replacement to fine-tuning on conditional generation. We formalize prompt construction for controllable mixed-initiative dialogue. Our findings show improvements over fine-tuning and ground truth responses according to human evaluation and automatic metrics for two tasks: PersuasionForGood and Emotional Support Conversations.

PETA has given the Bible's Book of Genesis a "vegan" makeover, using ChatGPT to recreate the story and "send a can't-be-missed animal rights message filled with vegan teachings." In PETA's vegan version of the Bible, animals are referred to as "beings" rather than "beasts" or "creatures" and plants like hemp and bamboo are used for clothing instead of animal skins because "no one with any fashion or moral sense would wear animal skins in the 21st century." Volunteers serve vegan hot dogs at the PETA Congressional Veggie Dog Lunch outside the Longworth House Office Building July 21, 2021 in Washington, DC. (Win McNamee/Getty Images) "The Bible has long been used to justify all forms of oppression, so we've used ChatGPT to make it clear that a loving God would never endorse exploitation of or cruelty to animals," says PETA President Ingrid Newkirk. "It took God only six days to create the entire world, but we realized it would take us years to rewrite the whole Bible, which is why we've started with just the first book." PETA OFFERS TO PAY FOR OSCAR MAYER WIENERMOBILE'S STOLEN CATALYTIC CONVERTER IF IT BECOMES VEGAN MOBILE In Genesis Chapter 22, Abraham travels to the land of Moriah, where instead of slaughtering a ram to demonstrate his faith, he "befriends a gentle lamb to show his reverence and respect for God's creation."

Kurt "The CyberGuy" Knutsson explains how an AI-generated radio DJ powered by the latest ChatGPT-4 technology can service across radio stations in the U.S. and Canada. ChatGPT has done it once again. The AI-powered chatbot is seemingly the answer to all. From assisting students with study materials to helping Twitter engineers with code corrections, ChatGPT has become a reliable source of information and assistance. Some preachers have even turned to ChatGPT for help in writing sermons.

Google has been warned by one of its engineers that the company is not in a position to win the artificial intelligence race and could lose out to commonly available AI technology. A document from a Google engineer leaked online said the company had done "a lot of looking over our shoulders at OpenAI", referring to the developer of the ChatGPT chatbot. However, the worker, identified by Bloomberg as a senior software engineer, wrote that neither company was in a winning position. "The uncomfortable truth is, we aren't positioned to win this arms race and neither is OpenAI. While we've been squabbling, a third faction has been quietly eating our lunch," the engineer wrote.

As a journalist, one thing I appreciate about Gary Marcus is that he always makes time for a chat. The last time we met face-to-face was late last year in New York City, where he fit me in between a series of press interviews, including NPR, CNN, the BBC, and the Big Kahuna, a taping of 60 Minutes with Leslie Stahl. When I called Marcus this week for an update on his Never Ending Tour to critique AI, he made sure to Zoom with me the next day, tweaking his schedule to avoid conflict with a Morning Joe hit. It was a good day for Marcus: the New York Times Sunday Magazine had just gone online with a lengthy Marcus interview conducted by its talk maven, David Marchese, whose previous subjects have included Thomas Piketty, Tom Stoppard, and Iggy Pop. The success of large language models like OpenAI's ChatGPT, Google's Bard, and a host of others has been so spectacular that it's literally scary.

That business is driven by a simple equation: how much it costs to create an article vs. how much revenue it can bring in. The main goal is to attract as many clicks as possible, then serve the readers ads worth just fractions of a cent on each visit -- the classic form of clickbait. That seems to have been the model of many of the AI-generated "news" sites in NewsGuard's report, said Gordon Crovitz, NewsGuard's co-CEO. Some sites fabricated sensational news stories, such as a report that President Biden had died. Others appeared to use AI to rewrite stories trending in various local news outlets.

Harry Potter and the Philosopher's Stone was published in 1997 Both artificial intelligences were developed by private firm OpenAI and trained on huge amounts of data, but exactly which texts make up this training data is unknown.

In an unassuming office on a quiet, mostly residential street in Mountain View, California -- located eight minutes from Google's sprawling headquarters -- a couple of ex-Googlers and their team of 50 are trying to build a search engine they hope will someday rival their former employer's. The company, Neeva, was started in 2020 by Sridhar Ramaswamy, who ran Google's $162 billion advertising arm before stepping down in 2018, and Vivek Raghunathan, a former Google vice president who worked on monetizing YouTube and other parts of the company. For a few years, the startup, which has raised over $77 million from some of Silicon Valley's top investors, focused on differentiating itself from Google by shunning invasive advertising and allowing power users to pay for extra features. Then, around the end of last year, the team at Neeva watched as a chatbot called ChatGPT created by the San Francisco–based startup OpenAI went viral. ChatGPT's ability to divine answers to nearly every question with an eerily humanlike sentience made it an instant hit, unleashing a modern AI wave. Suddenly, people around the world were talking about replacing Google search with ChatGPT. After all, if a chatbot could instantly answer any question for you, why would you need a search engine that simply spat out a bunch of links for you to trawl through?

With the King's coronation happening tomorrow, millions of Britons across the UK will be getting their celebration picnics ready. No decent spread would be complete without scones slathered in clotted cream and jam, but the big question is - how do you pronounce'scone'? While many people argue that the baked good should rhyme with'cone', others are convinced that it should rhyme with'gone'. To settle the debate once and for all, MailOnline turned to everyone's favourite AI bot, ChatGPT. But do you agree with its claims?

Harnessing logical reasoning ability is a comprehensive natural language understanding endeavor. With the release of Generative Pretrained Transformer 4 (GPT-4), highlighted as "advanced" at reasoning tasks, we are eager to learn the GPT-4 performance on various logical reasoning tasks. This report analyses multiple logical reasoning datasets, with popular benchmarks like LogiQA and ReClor, and newly-released datasets like AR-LSAT. We test the multi-choice reading comprehension and natural language inference tasks with benchmarks requiring logical reasoning. We further construct a logical reasoning out-of-distribution dataset to investigate the robustness of ChatGPT and GPT-4. We also make a performance comparison between ChatGPT and GPT-4. Experiment results show that ChatGPT performs significantly better than the RoBERTa fine-tuning method on most logical reasoning benchmarks. With early access to the GPT-4 API we are able to conduct intense experiments on the GPT-4 model. The results show GPT-4 yields even higher performance on most logical reasoning datasets. Among benchmarks, ChatGPT and GPT-4 do relatively well on well-known datasets like LogiQA and ReClor. However, the performance drops significantly when handling newly released and out-of-distribution datasets. Logical reasoning remains challenging for ChatGPT and GPT-4, especially on out-of-distribution and natural language inference datasets. We release the prompt-style logical reasoning datasets as a benchmark suite and name it LogiEval.