Every time you post a photo, respond on social media, make a website, or possibly even send an email, your data is scraped, stored, and used to train generative AI technology that can create text, audio, video, and images with just a few words. This has real consequences: OpenAI researchers studying the labor market impact of their language models estimated that approximately 80 percent of the US workforce could have at least 10 percent of their work tasks affected by the introduction of large language models (LLMs) like ChatGPT, while around 19 percent of workers may see at least half of their tasks impacted. In other words, the data you created may be putting you out of a job. When a company builds its technology on a public resource--the internet--it's sensible to say that that technology should be available and open to all. But critics have noted that GPT-4 lacked any clear information or specifications that would enable anyone outside the organization to replicate, test, or verify any aspect of the model.

In today's world of generative AI chatbots, we've witnessed the sudden rise of OpenAI's ChatGPT, introduced in November, followed by Bing Chat in February and Google's Bard in March. We decided to put these chatbots through their paces with an assortment of tasks to determine which one reigns supreme in the AI chatbot arena. Since Bing Chat uses similar GPT-4 technology as the latest ChatGPT model, we opted to focus on two titans of AI chatbot technology: OpenAI and Google. We tested ChatGPT and Bard in seven critical categories: dad jokes, argument dialog, mathematical word problems, summarization, factual retrieval, creative writing, and coding. For each test, we fed the exact same instruction (called a "prompt") into ChatGPT (with GPT-4) and Google Bard.

The pace of change in generative AI right now is insane. OpenAI released ChatGPT to the public just four months ago. It took only two months to reach 100 million users. Google, scrambling to keep up, has rolled out Bard, its own AI chatbot, and there are already various ChatGPT clones as well as new plug-ins to make the bot work with popular websites like Expedia and OpenTable. GPT-4, the new version of OpenAI's model released last month, is both more accurate and "multimodal," handling text, images, video, and audio all at once.

After getting beat to the punch by its primary rival, Google plans to add conversational AI to its flagship Search product, CEO Sundar Pichai told The Wall Street Journal in an interview. "Will people be able to ask questions to Google and engage with LLMs [large language models] in the context of search? Google has already said it would integrate LLMs into search, but this is the first time the company has announced plans for conversational features. The move isn't unexpected, particularly after Microsoft released a version of its own Bing search engine that used OpenAI's ChatGPT AI engine. However, Google's implementation would potentially have more impact, considering its 93.4 percent worldwide share of the search market.

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Chinese tech giants Alibaba and Huawei are reportedly ready to satisfy local demand for generative AI chatbots in coming weeks. Since the release of OpenAI's ChatGPT, Chinese users have been eager to get their hands on the technology. Cities like Beijing have pledged to assist developers, while academia and private industry alike have made progress. A university-developed ChatGPT analog crashed within a mere four hours under the weight of a crushing traffic surge. Meanwhile, private industry versions like Baidu's ERNIE have had their own troubles – including managing censorship and botching some requests.

The AI bot, known for providing restaurant recommendations and answering privacy policy questions, has now managed to concoct a sexual harassment scandal involving a real-life law professor., Technology & Science News, Times Now

Do large language models create a moat? In this given hype, what type of businesses should you invest your time and money in? While the technology of Large Language Models (LLMs) is new, the approach to analyzing the business moat is still the same. AI-driven businesses have a combination of either a model moat, a data moat, or the brand moat. The new LLMs, like OpenAI's model, can give an advantage in all areas, but it is by no means a given.

The Office of the Privacy Commissioner of Canada is investigating OpenAI's generative language app ChatGPT after the watchdog received a complaint claiming the software was collecting, using, and disclosing personal information without consent. "AI technology and its effects on privacy is a priority for my Office," the country's privacy commissioner Philippe Dufresne declared in a statement this week. "We need to keep up with – and stay ahead of – fast-moving technological advances, and that is one of my key focus areas as commissioner." Launched last November, ChatGPT went viral as hundreds of millions of netizens flocked to the free tool to generate all types of text. While it may be fun to get the engine to write bad jokes or essay drafts, authorities are growing increasingly concerned about the privacy risks the technology poses.

This article explores the ethical problems arising from the use of ChatGPT as a kind of generative AI and suggests responses based on the Human-Centered Artificial Intelligence (HCAI) framework. The HCAI framework is appropriate because it understands technology above all as a tool to empower, augment, and enhance human agency while referring to human wellbeing as a grand challenge, thus perfectly aligning itself with ethics, the science of human flourishing. Further, HCAI provides objectives, principles, procedures, and structures for reliable, safe, and trustworthy AI which we apply to our ChatGPT assessments. The main danger ChatGPT presents is the propensity to be used as a weapon of mass deception (WMD) and an enabler of criminal activities involving deceit. We review technical specifications to better comprehend its potentials and limitations. We then suggest both technical (watermarking, styleme, detectors, and fact-checkers) and non-technical measures (terms of use, transparency, educator considerations, HITL) to mitigate ChatGPT misuse or abuse and recommend best uses (creative writing, non-creative writing, teaching and learning). We conclude with considerations regarding the role of humans in ensuring the proper use of ChatGPT for individual and social wellbeing.