Knowledge-intensive tasks, such as open-domain question answering (QA), require access to a large amount of world or domain knowledge. A common approach for knowledge-intensive tasks is to employ a retrieve-then-read pipeline that first retrieves a handful of relevant contextual documents from an external corpus such as Wikipedia and then predicts an answer conditioned on the retrieved documents. In this paper, we present a novel perspective for solving knowledge-intensive tasks by replacing document retrievers with large language model generators. We call our method generate-then-read (GenRead), which first prompts a large language model to generate contextutal documents based on a given question, and then reads the generated documents to produce the final answer. Furthermore, we propose a novel clustering-based prompting method that selects distinct prompts, resulting in the generated documents that cover different perspectives, leading to better recall over acceptable answers. We conduct extensive experiments on three different knowledge-intensive tasks, including open-domain QA, fact checking, and dialogue system. Notably, GenRead achieves 71.6 and 54.4 exact match scores on TriviaQA and WebQ, significantly outperforming the state-of-the-art retrieve-then-read pipeline DPR-FiD by +4.0 and +3.9, without retrieving any documents from any external knowledge source. Lastly, we demonstrate the model performance can be further improved by combining retrieval and generation. Our code and generated documents can be found at https://github.com/wyu97/GenRead.

Conversational information seeking (CIS) is concerned with a sequence of interactions between one or more users and an information system. Interactions in CIS are primarily based on natural language dialogue, while they may include other types of interactions, such as click, touch, and body gestures. This monograph provides a thorough overview of CIS definitions, applications, interactions, interfaces, design, implementation, and evaluation. This monograph views CIS applications as including conversational search, conversational question answering, and conversational recommendation. Our aim is to provide an overview of past research related to CIS, introduce the current state-of-the-art in CIS, highlight the challenges still being faced in the community. and suggest future directions.

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The past several months have been turbulent for Microsoft. In December, its $69 billion deal to acquire the video game maker Activision was challenged by regulators in the United States, and last week it began laying off about 10,000 workers. On Monday, Microsoft announced a major new investment in OpenAI, the start-up behind ChatGPT and other generative artificial intelligence breakthroughs, and signaled plans to include A.I. in an array of Microsoft products. The biggest slowdown came from Microsoft's personal computing business, where sales fell 19 percent and operating income fell 47 percent. The business boomed during the first part of the pandemic.

Like many big tech companies, Microsoft is preparing for the worst after announcing plans to lay off 10,000 employees in the upcoming third quarter. It turns out that the company's second quarter was a mixed bag: It earned $52.7 billion in revenue, which was up 2 percent from last year, but a slight miss from the $52.9 billion analysts expected. Profits also fell by 12 percent to $16.4 billion, a trend that may continue throughout the year. Despite the faltering PC market, Microsoft has been riding high on cloud revenues for years, and that seems to be continuing. Microsoft's belt tightening didn't stop the company from potentially investing $10 billion more in ChatGPT creator OpenAI, yet another sign that AI is going to play a major role in its future projects. The company plans to add ChatGPT to its Azure OpenAI service soon, and it's reportedly planning to integrated that technology in Bing.

Over the last few months, his manager began noticing a decided improvement. Timothy's reports were more detailed, more persuasive, and more original. They were also written entirely by a chatbot. Since its launch late last year, ChatGPT, an artificial-intelligence bot that can create original content that's all but indistinguishable from that of a human being, has raised thorny ethical questions in numerous quarters--from school districts, where educators worry about cheating, to the political arena, where experts have raised concerns about automated lobbying. The business world hasn't been a focus of these debates, but its leaders are also uneasy about work product created by AI.

While Paul Budde is an expert in the field of technology, this week he's letting artificial intelligence speak for itself to discuss the current state of AI. Recently, a new AI service was launched called ChatGPT. I have used it now several times and I am amazed at the accuracy of this AI tool. ChatGPT is a large language model developed by OpenAI. It is a variant of the Generative Pre-trained Transformer (GPT) model, which uses deep learning techniques to generate human-like text. The model is trained on a massive dataset of text from the internet, allowing it to generate a wide range of text on various topics.

AI text generator ChatGPT, released to the public late last year, is so sophisticated that it has already demonstrated its ability to write coherent essays, generate sound legal documents and otherwise interact with humans in a convincingly conversational manner. One CEO even treats the tool from parent company OpenAI like a perennially available member of his executive team. "I ask ChatGPT to become aware of where my biases and blindspots might be, and the answers it gives are a really, really good starting point to check your thinking," Jeff Maggioncalda, CEO of online course provider Coursera, told CBS MoneyWatch. He said the tool helps him to be more thoughtful in his approach to business challenges, as well as look at topics from vantage points that differ from his own. For example, last week at the World Economic Forum meeting in Davos, Switzerland, Maggioncalda entered the following prompt: "What should I consider when giving a speech to prime ministers at Davos?" Another useful entry for business leaders would be: "What should I consider when I am restructuring my company?"

The fruit of more than a decade of research inside companies like OpenAI, Google and Meta, these technologies are poised to remake everything from online search engines like Google Search and Microsoft Bing to photo and graphics editors like Photoshop. The deal follows Microsoft's announcement last week that it had begun laying off employees as part of an effort to cull 10,000 positions. The changes, including severance, ending leases and what it called "changes to our hardware portfolio" would cost $1.2 billion, it said. Satya Nadella, the company's chief executive, said last week that the cuts would let the company refocus on priorities such as artificial intelligence, which he called "the next major wave of computing." Mr. Nadella made clear in his company's announcement on Monday that the next phase of the partnership with OpenAI would focus on bringing tools to the market, saying that "developers and organizations across industries will have access to the best A.I. infrastructure, models and tool chain."