There are vanishingly few places in Microsoft's business ecosystem that remain untouched by January's OpenAI deal, with GPT-4 backed chatbot and generative capabilities coming to Office products like Word and Excel, Bing Search, and integrated directly into the Edge browser. During the Microsoft Build 2023 conference on Tuesday, company executives clarified and confirmed that its 365 Copilot AI -- the same one going into Office -- will be "natively integrated" into the Edge browser. Microsoft 365 Copilot essentially takes all of your Graph information -- data from your Calendar, Word docs, emails and chat logs -- and smashes them together, using the informatic slurry in training an array of large language models, to provide AI-backed assistance personalized to your business. "You can type natural language requests like'Tell my team how we updated the product strategy today,'" Lindsay Kubasik, Group Product Manager, Edge Enterprise wrote in a Tuesday blog post. "Microsoft 365 Copilot will generate a status update based on the morning's meetings, emails and chat threads."

ChatGPT no longer needs to rely on its own models or plugins to provide information to users: Microsoft has announced Bing Search is integrating into ChatGPT to provide more relevant -- and potentially newer -- responses. Bing will act as the "default search experience," allowing ChatGPT to pull answers from the internet and provide citations. Microsoft and OpenAI have worked together closely over the last few months, with Bing, itself, running on GPT-4 (with some tailoring for searches). Bing works by displaying responses in detailed or summary form and sources facts and suggestions with footnotes of sorts -- features it can bring to ChatGPT to, possibly, provide more precise information. Previously, ChatGPT relied solely on individual plugins to access any recent information.

If you have a work PC, chances are you'll soon see the latest twist on Microsoft's browser: Microsoft Edge for Business, complete with (of course) AI. At its Microsoft Build developer conference this week, Microsoft will announce several tweaks to Edge, including its first dedicated business browser. Microsoft calls the new Edge the "standard browser experience for organizations," with its own separate logo and icon on your taskbar. You'll see more in the Edge sidebar, too: the inclusion of Microsoft 365 Copilot, web apps, and a new "Workspaces" collection of tabs that can be simultaneously shared and browsed with coworkers. Microsoft Edge already allows you to browse and open windows in both a personal and business account.

OpenAI Chief Executive Officer Sam Altman said part of the reason for his current tour of European cities is to discover a suitable location for a new office. "Poland would be an interesting place," Altman said in an interview Tuesday when asked about European offices. "We want to do a research and engineering office in Europe, not a regulatory one. We are trying to figure it out. This is part of the goal of this trip."

This is part of the data recipe for Facebook's new large language model, which the company claims is able to detect and rein in harmful content in over 100 languages. Bumble uses similar technology to detect rude and unwanted messages in at least 15 languages. Google uses it for everything from translation to filtering newspaper comment sections. All have comparable recipes and the same dominant ingredient: English-language data. For years, social media companies have focused their automatic content detection and removal efforts more on content in English than the world's 7,000 other languages.

Rapid advances in artificial intelligence (AI) such as Microsoft-backed OpenAI's ChatGPT are complicating governments' efforts to agree to laws governing the use of the technology. The government is consulting Australia's main science advisory body and is considering the next steps, a spokesperson for the industry and science minister said in April. The Financial Conduct Authority, one of several state regulators tasked with drawing up new guidelines covering AI, is consulting with the Alan Turing Institute and other legal and academic institutions to improve its understanding of the technology, a spokesperson said. Britain's competition regulator said on May 4 it would start examining the effect of AI on consumers, businesses and the economy, and whether new controls were needed. Britain said in March it planned to split responsibility for governing AI between its regulators for human rights, health and safety, and competition, rather than creating a new body. China's cyberspace regulator in April unveiled draft measures to manage generative AI services, saying it wanted firms to submit security assessments to authorities before they launch offerings to the public.

Fox News correspondent Grady Trimble has the latest on fears the technology will spiral out of control on "Special Report." Artificial intelligence can't bring back the dead, but it may be able to simulate speaking to a lost loved one in an effort to help humans through the grieving process. The high-tech revamp of the traditional seance comes amid the wild growth of large language models, a form of AI that is trained on copious amounts of text. ChatGPT's release year has sparked discussion on how far the tech can go as the chatbot mimics human conversation and answers prompts from humans. Jarren Rocks, product designer and manager at the Los Angeles-based software development company AE Studio, is working on a program called Seance AI, which will allow people to talk with a chatbot that mimics their dead loved ones.

The increasing scale of large language models (LLMs) brings emergent abilities to various complex tasks requiring reasoning, such as arithmetic and commonsense reasoning. It is known that the effective design of task-specific prompts is critical for LLMs' ability to produce high-quality answers. In particular, an effective approach for complex question-and-answer tasks is example-based prompting with chain-of-thought (CoT) reasoning, which significantly improves the performance of LLMs. However, current CoT methods rely on a fixed set of human-annotated exemplars, which are not necessarily the most effective examples for different tasks. This paper proposes a new method, Active-Prompt, to adapt LLMs to different tasks with task-specific example prompts (annotated with human-designed CoT reasoning). For this purpose, we propose a solution to the key problem of determining which questions are the most important and helpful ones to annotate from a pool of task-specific queries. By borrowing ideas from the related problem of uncertainty-based active learning, we introduce several metrics to characterize the uncertainty so as to select the most uncertain questions for annotation. Experimental results demonstrate the superiority of our proposed method, achieving state-of-the-art on eight complex reasoning tasks. Further analyses of different uncertainty metrics, pool sizes, zero-shot learning, and accuracy-uncertainty relationship demonstrate the effectiveness of our method. Our code will be available at https://github.com/shizhediao/active-prompt.

The rapid growth of web pages and the increasing complexity of their structure poses a challenge for web mining models. Web mining models are required to understand the semi-structured web pages, particularly when little is known about the subject or template of a new page. Current methods migrate language models to the web mining by embedding the XML source code into the transformer or encoding the rendered layout with graph neural networks. However, these approaches do not take into account the relationships between text nodes within and across pages. In this paper, we propose a new approach, ReXMiner, for zero-shot relation extraction in web mining. ReXMiner encodes the shortest relative paths in the Document Object Model (DOM) tree which is a more accurate and efficient signal for key-value pair extraction within a web page. It also incorporates the popularity of each text node by counting the occurrence of the same text node across different web pages. We use the contrastive learning to address the issue of sparsity in relation extraction. Extensive experiments on public benchmarks show that our method, ReXMiner, outperforms the state-of-the-art baselines in the task of zero-shot relation extraction in web mining.

Language models have graduated from being research prototypes to commercialized products offered as web APIs, and recent works have highlighted the multilingual capabilities of these products. The API vendors charge their users based on usage, more specifically on the number of ``tokens'' processed or generated by the underlying language models. What constitutes a token, however, is training data and model dependent with a large variance in the number of tokens required to convey the same information in different languages. In this work, we analyze the effect of this non-uniformity on the fairness of an API's pricing policy across languages. We conduct a systematic analysis of the cost and utility of OpenAI's language model API on multilingual benchmarks in 22 typologically diverse languages. We show evidence that speakers of a large number of the supported languages are overcharged while obtaining poorer results. These speakers tend to also come from regions where the APIs are less affordable to begin with. Through these analyses, we aim to increase transparency around language model APIs' pricing policies and encourage the vendors to make them more equitable.