People haven't exactly been impressed in the short time since Google released its "experimental conversational AI service" Bard. Coming up against OpenAI's ChatGPT and Microsoft's Bing Chat (also powered by OpenAI's GPT-4) users have found its responses to not be as knowledgeable or detailed as its rivals. That could be set to change, however, after Google CEO Sundar Pichai confirmed on The New York Times podcast "Hard Fork" that Bard will soon be moving from its current LaMDA-based model to larger-scale PaLM datasets in the coming days. When asked how he felt about responses to Bard's release, Pichai commented: "We clearly have more capable models. Pretty soon, maybe as this goes live, we will be upgrading Bard to some of our more capable PaLM models, so which will bring more capabilities, be it in reasoning, coding." To frame the difference, Google said it had trained LaMDA with 137 billion parameters when it shared details about the language-based models last year.

Mark Standen, who runs the staffing business for artificial intelligence, machine learning and automation at Hays in the UK, told Bloomberg the prompt engineer market was the'fastest-moving for 25 years'. He added that although salaries start at £40,000 ($49,000), expert prompt engineers'can name their price' and charge up to £200,000 ($247,000) or £300,000 ($371,000) per year. Sam Altman, the CEO of OpenAI which created ChatGPT, has previously spoken about a need for prompt engineers. Last month he tweeted how'writing a really great prompt for a chatbot persona is an amazingly high-leverage skill'. OpenAI, a private company backed by Microsoft Corp, made ChatGPT available to the public for free in late November.

In the last 24 hours alone, we've had hoaxes, FTC complaints and… ads. We'll get into how Microsoft is bringing ads to its Bing chatbot – bound to happen – while OpenAI may have to halt ChatGPT releases in the face of FTC complaints. The nonprofit research organization, Center for AI and Digital Policy (CAIDP), says OpenAI's models are "biased, deceptive" and threaten privacy and public safety. The CAIDP says OpenAI also fails to meet Commission guidelines calling for AI to be transparent, fair and easy to explain. There's no guarantee the FTC will act on the complaint.

While some prominent voices in the tech industry are calling for a temporary pause in ChatGPT's upgrades, the CEO of America's largest crypto exchange Coinbase made it clear he opposes the move. "Count me among the people who think this is a bad idea," Brian Armstrong wrote in a recent tweet. "There are no'experts' to adjudicate this issue, and many disparate actors will never agree. Committees and bureaucracy won't solve anything." Armstrong's comments came shortly after the publication of an open letter calling for a six-month moratorium on developing artificial intelligence (AI) more powerful than GPT-4, the latest iteration of ChatGPT, an AI chatbot created by OpenAI.

Microsoft has launched a tool to help cyber security professionals identify breaches, threat signals and better analyse data, using OpenAI's latest GPT-4 generative artificial intelligence model. The tool, named Security Copilot, is a simple prompt box that will help security analysts with tasks like summarising incidents, analysing vulnerabilities and sharing information with co-workers on a pinboard. The assistant will use Microsoft's security-specific model, which the company described as "a growing set of security-specific skills" that is fed with more than 65 trillion signals every day. The launch comes amid a flurry of announcements from Microsoft to integrate AI into its most popular offerings. The company has sought to outpace peers through multi-billion dollar investments in ChatGPT owner OpenAI, which recently released GPT-4 to perform a range of tasks from creating a real website through a hand-drawn mock-up to helping individuals calculate their taxes.

Generative AI, ChatGPT, Dall-E - it seems everyone's so excited about AI at the moment that they've forgotten all about the hot technology trends of just a short while back. Are The Metaverse And Web3 Still Relevant? This is the nature of the "hype cycle" that those of us who follow the latest developments in technology have become very accustomed to. New ideas get a lot of attention – not always of the right sort – then the excitement dies off when something even newer emerges. But does that mean that they're dead and forgotten?

AI has exploded in popularity in recent years, to the point where it's no longer considered a luxury in the business world, but a necessity. A PricewaterhouseCoopers (PwC) study revealed that the adoption of AI will fuel a 14 percent increase in the global GDP by 2030, representing an additional $15.7 trillion surge to the global economy.1 Businesses using AI solutions are discovering new ways to tap into vast amounts of data to get clear insights and accelerate innovation. Thanks to advancements in graphics processing unit (GPU) computational power and the availability of tech services through cloud marketplaces, AI is now more accessible than ever. As companies look to do more with less, AI will play an increasingly critical role--particularly generative AI, a category of AI algorithms that generate new outputs based on data. Unlike traditional AI systems that are designed to recognize patterns and make predictions, generative AI can analyze large data sets and create entirely new content in a variety of media formats--including text, images, audio, and data--based on what's described in the input.

Artificial intelligence in some shape or form has been a part of everyday life for years, but the meteoric rise of ChatGPT and the resulting aggressive development pace of conversational and generative AI models is, for the first time ever, putting the underlying technology into the hands of the general public. Even though current large language models are primarily able to guess the best-fitting next word in a sentence based on the corpus of content they were fed, CEOs, researchers and AI experts are now urging the industry to pump the brakes on training and developing models more capable than OpenAI's GPT-4. The company's latest large language model is currently available in a limited capacity for ChatGPT Plus subscribers and will soon be integrated into Microsoft productivity and security products. According to an open letter signed by influential figures like Elon Musk and Stability AI CEO Emad Mostaque, « powerful AI systems should be developed only once we are confident that their effects will be positive and their risks will be manageable. The Musk Foundation is a primary donor to the organization.

Social Honeypots are tools deployed in Online Social Networks (OSN) to attract malevolent activities performed by spammers and bots. To this end, their content is designed to be of maximum interest to malicious users. However, by choosing an appropriate content topic, this attractive mechanism could be extended to any OSN users, rather than only luring malicious actors. As a result, honeypots can be used to attract individuals interested in a wide range of topics, from sports and hobbies to more sensitive subjects like political views and conspiracies. With all these individuals gathered in one place, honeypot owners can conduct many analyses, from social to marketing studies. In this work, we introduce a novel concept of social honeypot for attracting OSN users interested in a generic target topic. We propose a framework based on fully-automated content generation strategies and engagement plans to mimic legit Instagram pages. To validate our framework, we created 21 self-managed social honeypots (i.e., pages) on Instagram, covering three topics, four content generation strategies, and three engaging plans. In nine weeks, our honeypots gathered a total of 753 followers, 5387 comments, and 15739 likes. These results demonstrate the validity of our approach, and through statistical analysis, we examine the characteristics of effective social honeypots.

This paper discusses OpenAIs ChatGPT, a generative pre-trained transformer, which uses natural language processing to fulfill text-based user requests (i.e., a chatbot). The history and principles behind ChatGPT and similar models are discussed. This technology is then discussed in relation to its potential impact on academia and scholarly research and publishing. ChatGPT is seen as a potential model for the automated preparation of essays and other types of scholarly manuscripts. Potential ethical issues that could arise with the emergence of large language models like GPT-3, the underlying technology behind ChatGPT, and its usage by academics and researchers, are discussed and situated within the context of broader advancements in artificial intelligence, machine learning, and natural language processing for research and scholarly publishing.