Large Language Models (LLMs) offer new avenues to simulate online communities and social media. Potential applications range from testing the design of content recommendation algorithms to estimating the effects of content policies and interventions. However, the validity of using LLMs to simulate conversations between various users remains largely untested. We evaluated whether LLMs can convincingly mimic human group conversations on social media. We collected authentic human conversations from Reddit and generated artificial conversations on the same topic with two LLMs: Llama 3 70B and GPT-4o. When presented side-by-side to study participants, LLM-generated conversations were mistaken for human-created content 39\% of the time. In particular, when evaluating conversations generated by Llama 3, participants correctly identified them as AI-generated only 56\% of the time, barely better than random chance. Our study demonstrates that LLMs can generate social media conversations sufficiently realistic to deceive humans when reading them, highlighting both a promising potential for social simulation and a warning message about the potential misuse of LLMs to generate new inauthentic social media content.

CyberGuy explains the new iPhone 15 Pro Max. Every day, AI seems to flip a coin between being our tech hero or digital villain. In this mix, Bing Chat made a splash by teaming up with OpenAI, turning the mundane task of searching into a friendly chat. With Microsoft leading the way, these tech giants were able to integrate the capabilities of ChatGPT into the Bing search engine. This integration was meant to change the search engine game.

Developers and data scientists often struggle to write command-line inputs, even though graphical interfaces or tools like ChatGPT can assist. The solution? "ai-cli," an open-source system inspired by GitHub Copilot that converts natural language prompts into executable commands for various Linux command-line tools. By tapping into OpenAI's API, which allows interaction through JSON HTTP requests, "ai-cli" transforms user queries into actionable command-line instructions. However, integrating AI assistance across multiple command-line tools, especially in open source settings, can be complex. Historically, operating systems could mediate, but individual tool functionality and the lack of a unified approach have made centralized integration challenging. The "ai-cli" tool, by bridging this gap through dynamic loading and linking with each program's Readline library API, makes command-line interfaces smarter and more user-friendly, opening avenues for further enhancement and cross-platform applicability.

Some pairings create an exquisite experience that's simply not otherwise imaginable. The same is true of artificial intelligence (AI) and 5G networks. As all types of 5G-capable devices become more widely available, 5G networks roll out globally delivering greater than 10 times the speed at a fraction of the latency of 4G. Meanwhile, AI use cases for consumers and enterprises also continue to mature quickly. These two trends are significantly interrelated, and together have huge implications for consumers, enterprises and communication service providers (CSPs) alike.

The sense of discovery and surprise at something that matches an unrecognized yearning can be exhilarating. But the sheer size of many stores is exhausting -- with some, I need a site map, flashlight, and overnight bag to take it all in. In others, the inventory is specialized and packed in so tightly that online seems a better way to find what I want. If you're primarily an online shopper, you may be asking how relevant brick-and-mortar stores are. The answer is: quite relevant.

Turn around in almost any city, and you're likely to see a bank or lender or brokerage on the corner. In fact, in my family's small town, we have two financial institutions by the same name on either side of a two-lane street. And, while I love the personal experience I get from visiting my hometown banker, I also appreciate being able to conduct my business after the bankers have gone home to dinner, and knowing that my fraud protection never sleeps. Financial services institutions (FSIs) of all sizes recognize that they are in fierce competition to deliver differentiated services while meeting stringent regulatory and compliance requirements. Among the earliest adopters of digital transformation, FSIs satisfy these requirements with a range of emerging technologies, including artificial intelligence (AI).

Do we really know the potential and the pitfalls of artificial intelligence? Maybe not, say the experts and innovators at the TED conference in Vancouver. Jane Wakefield hears from the creator of the infamous "fake Obama" videos, Dr Supasorn Suwajanakorn. And AI expert and pioneer Max Tegmark of MIT explains why we can't make any assumptions about the future, and must decide now how to navigate the problems of AI such as whether to ban autonomous weapons. Plus we hear from Pierre Barreau about his AI music, and why computers sometimes need reminding that human musicians need to take a breath.

Chatbots, artificial intelligence (AI), and natural language user interfaces (NLUIs) are making it increasingly feasible for humans to have realistic conversations with software applications. For example, chatbot developer Kore, Inc., is working with the SAP Co-Innovation Lab to create solutions that suggest possible actions to users when a sales opportunity has changed, an order is delayed, or an expense needs approval. While these solutions are not self-aware, experts are working to create networks that emulate the way information traverses the brain. Such groundbreaking research may eventually result in AI that is able to learn, improve, and converse naturally with users. Kris Hammond, founder of the University of Chicago's AI laboratory, envisions a type of applied AI that will enable this type of seamless dialogue between humans and machines.

As an IBM futurist and influencer, I was honored to be part of the World of Watson event (#ibmwow) two months ago in Vegas. Since then, one presentation has been rambling around my soul and my brain. Shannon Vallor, is Chair of the Department of Philosophy at Santa Clara University, and author of Technology and the Virtues. She gave a brilliant talk on AI, Ethics and the Future of Human Flourishing. She pinpointed why AI raises ethical questions we must answer, and conversations we must have.

Discussion of artificial intelligence has skyrocketed since the end of the last decade, according to a new analysis looking at public perception of the technology. The paper by Stanford computer science PhD Ethan Fast and Eric Horvitz, technical fellow and a managing director at Microsoft Research, looked at more than three million articles published in the New York Times between January 1986 and May 2016. The study is under review to become a conference paper at the Thirty-First AAAI Conference on Artificial Intelligence. According to the authors, no other collection of text aimed at a general audience extends so far into the past, making it a good proxy for public opinion. They found that from 1985 to 2009 AI was discussed in somewhere between 5 and 10 out of every 10,000 articles.