The deal is the latest in a stampede as tech companies seek to deploy "generative AI tech" into their products. Microsoft announced a multibillion dollar deal with OpenAI in January into use its tech to answer questions directly in its Bing search engine, while Google has said its bot, called Bard, will be available to the public soon, too. Proponents of the tech say the chatbots will revolutionize how people interact with computers and software, while skeptics point out that the bots make glaring mistakes and question whether the big companies are simply piling onto a trend to keep up their reputations for being innovative.

Yuxin Guo is a master's student studying at a Beijing University. For a few months, she had been following online discussions about ChatGPT, the generative AI tool that produces almost natural-sounding language in response to text prompts. One video she found on social media platform Weibo showed how college students in the US were using the technology to write research papers. In February, she finally decided to try it out for herself. "I got curious because so many people are talking about it," Guo says, "although not a lot of people seem to clearly know how to access it."

Last week, Meta announced LLaMA, its latest stab at making a GPT-style "large language model"*. If AI is the future of tech, then big tech companies need to control their own models or be left behind by the competition. LLaMA joins OpenAI's GPT (licensed by Microsoft for Bing and underpinning OpenAI's own ChatGPT) and Google's LaMDA (which will power Bard, its ChatGPT rival) in the upper echelons of the field. It says that LLaMA is a "smaller, more performant model" than its peers, built to achieve the same feats of comprehension and articulation with a smaller footprint in terms of compute*, and so has a correspondingly smaller environmental impact. But the company also sought to differentiate itself in another way, by making LLaMA "open", implicitly pointing out that despite its branding, "OpenAI" is anything but.

The most high-profile of the chatbot announcements, Seattle-based Microsoft said Tuesday that it will integrate an updated software developed by OpenAI, the same company behind ChatGPT, into its search engine Bing. It didn't come as a huge surprise, since Microsoft made a multi-billion-dollar investment in OpenAI. The company held an invite-only event for journalists who got to try out the new "Prometheus" chat before it's released to the public. The takeaway from Semafor's Reed Albergotti: "It was a complete reorientation of Microsoft around this new breed of AI that has taken the world by storm." Google has been working on AI software behind the scenes for years, and announced this week that it plans to build a chatbot named Bard into its search function.

OpenAI's announcement of the release of ChatGPT and Whisper could spark a new AI goldrush, with companies able to experiment with the chatbot to create fully-fledged businesses. The release of API access to ChatGPT and Whisper makes it much easier and cheaper for companies to add AI capabilities to their applications. OpenAI has also changed its data retention policy, which could reassure businesses thinking of experimenting with ChatGPT. Businesses can now get paid for services built on the large language model, meaning chatbots are going to start appearing everywhere. Read the complete article at: www.wired.com

Erik Brynjolfsson is in great demand. The US professor whose research focuses on the relationship between digital tech and human productivity is nearing the end of a European speaking tour that's lasted nearly a month. Speaking via Zoom as he prepares for his imminent lecture in Oxford, the director of the Digital Economy Lab at the Stanford Institute for Human-Centered AI is enthused by recent "seminal breakthroughs" in the field. Brynjolfsson's tour – which has included appearances at the World Economic Forum in Davos and the Institute for the Future of Work in London – is neatly timed, because the recent arrival of ChatGPT on the scene has been capturing human minds, if not yet hearts. The large-scale language model, fed 300 billion words by developer OpenAI, caused a sensation with its powerful capabilities, attracting 1 million users within five days of its release in late November 2022.

ChatGPT has cast long shadows over the media as the latest form of disruptive technology. For some, ChatGPT is a harbinger of the end of academic and scientific integrity, and a threat to white collar jobs and our democratic institutions. How concerned should we be about generative artificial intelligence (AI)? The developers of ChatGPT describe it as "a model… which interacts in a conversational way" while also calling it a "horrible product" for its inconsistent results. It can write emails, summarize documents, review code and provide comments, translate documents, create content, play games, and, of course, chat.

Amrit Jassal is the Chief Technology Officer (CTO) and cofounder of Egnyte, a leading cloud-based collaboration and governance platform. ChatGPT and Dalle-E are the talks of the town as the new shiny object that could potentially disrupt Google's hegemony. The hype cycle, as usual, is high. AI dominated conversations around tech at this year's World Economic Forum in Davos, Switzerland. Even at this year's CES trade show, hundreds of exhibitors were listed under the show's artificial intelligence category--double those categorized as metaverse, cryptocurrency and blockchain combined.

Microsoft today introduced what it's calling the "next generation" of AI product updates across its business apps portfolio. They touch on both Power Platform, Microsoft's set of low-code tools for building apps and workflows, and Dynamics 365, the company's suite of enterprise resource planning (ERP) and customer relationship management (CRM) tools. In an interview with TechCrunch, Charles Lamanna, CVP of business apps and platform at Microsoft, described the updates as the logical next step on Microsoft's automation journey. Powered by tech from AI startup OpenAI and built using the Azure OpenAI Service, Microsoft's service that provides enterprise-tailored access to OpenAI's API, the new capabilities follow the rollout of OpenAI text-generating AI models in Power Platform four years ago and the more recent debut of generative AI capabilities in Viva Sales, Microsoft's seller experience app. "Over the last four years, we've been on a journey to bring generative AI and foundation models to the workplace," Lamanna said via email, noting that Microsoft has a longstanding partnership with OpenAI to commercialize the vendor's tech in Microsoft's own products and through the Azure OpenAI Service.

Recently, ChatGPT, along with DALL-E-2 and Codex,has been gaining significant attention from society. As a result, many individuals have become interested in related resources and are seeking to uncover the background and secrets behind its impressive performance. In fact, ChatGPT and other Generative AI (GAI) techniques belong to the category of Artificial Intelligence Generated Content (AIGC), which involves the creation of digital content, such as images, music, and natural language, through AI models. The goal of AIGC is to make the content creation process more efficient and accessible, allowing for the production of high-quality content at a faster pace. AIGC is achieved by extracting and understanding intent information from instructions provided by human, and generating the content according to its knowledge and the intent information. In recent years, large-scale models have become increasingly important in AIGC as they provide better intent extraction and thus, improved generation results. With the growth of data and the size of the models, the distribution that the model can learn becomes more comprehensive and closer to reality, leading to more realistic and high-quality content generation. This survey provides a comprehensive review on the history of generative models, and basic components, recent advances in AIGC from unimodal interaction and multimodal interaction. From the perspective of unimodality, we introduce the generation tasks and relative models of text and image. From the perspective of multimodality, we introduce the cross-application between the modalities mentioned above. Finally, we discuss the existing open problems and future challenges in AIGC.