OpenAI released initial estimates about the share of users who may be experiencing symptoms like delusional thinking, mania, or suicidal ideation, and says it has tweaked GPT-5 to respond more effectively. For the first time ever, OpenAI has released a rough estimate of how many ChatGPT users globally may show signs of having a severe mental health crisis in a typical week. The company said Monday that it worked with experts around the world to make updates to the chatbot so it can more reliably recognize indicators of mental distress and guide users toward real-world support. In recent months, a growing number of people have ended up hospitalized, divorced, or dead after having long, intense conversations with ChatGPT. Some of their loved ones allege the chatbot fueled their delusions and paranoia.

Think of what it feels like to be in love. What comes to your mind? For a handful of people, love is opening up their laptop or phone and waiting for a wall of text or a synthetic voice to come streaming in from their preferred AI chatbot. With so many tech platforms encouraging us to interact with their newly-introduced chatbots and talk to them as if they are real humans, people are increasingly turning to these large language model-powered functions for companionship, emotional support and, sometimes, love. This might raise an eyebrow or elicit a snigger.

Development in digital technologies has continuously reshaped how individuals seek and receive social and emotional support. While online platforms and communities have long served this need, the increased integration of general-purpose conversational AI into daily lives has introduced new dynamics in how support is provided and experienced. Existing research has highlighted both benefits (e.g., wider access to well-being resources) and potential risks (e.g., over-reliance) of using AI for support seeking. In this five-week, exploratory study, we recruited 149 participants divided into two usage groups: a baseline usage group (BU, n=60) that used the internet and AI as usual, and an active usage group (AU, n=89) encouraged to use one of four commercially available AI tools (Microsoft Copilot, Google Gemini, PI AI, ChatGPT) for social and emotional interactions. Our analysis revealed significant increases in perceived attachment towards AI (32.99 percentage points), perceived AI empathy (25.8 p.p.), and motivation to use AI for entertainment (22.90 p.p.) among the AU group. We also observed that individual differences (e.g., gender identity, prior AI usage) influenced perceptions of AI empathy and attachment. Lastly, the AU group expressed higher comfort in seeking personal help, managing stress, obtaining social support, and talking about health with AI, indicating potential for broader emotional support while highlighting the need for safeguards against problematic usage. Overall, our exploratory findings underscore the importance of developing consumer-facing AI tools that support emotional well-being responsibly, while empowering users to understand the limitations of these tools.

In this work, our goal is to develop a theoretical framework that can eventually be used for analyzing the effectiveness of visual stories such as feature films to comic books. To develop this theoretical framework, we introduce a new story element called moments. Our conjecture is that any linear story such as the story of a feature film can be decomposed into a set of moments that follow each other. Moments are defined as the perception of the actions, interactions, and expressions of all characters or a single character during a given time period. We categorize the moments into two major types: story moments and discourse moments. Each type of moment can further be classified into three types, which we call universal storytelling moments. We believe these universal moments foster or deteriorate the emotional attachment of the audience to a particular character or the story. We present a methodology to catalog the occurrences of these universal moments as they are found in the story. The cataloged moments can be represented using curves or color strips. Therefore, we can visualize a character's journey through the story as either a 3D curve or a color strip. We also demonstrated that both story and discourse moments can be transformed into one lump-sum attraction parameter. The attraction parameter in time provides a function that can be plotted graphically onto a timeline illustrating changes in the emotional attachment of audience to a character or the story. By inspecting these functions the story analyst can analytically decipher the moments in the story where the attachment is being established, maintained, strengthened, or conversely where it is languishing.

Likes and dislikes, preferences and options, clicks and cache are the moves in the game. With neoteny later moves in a data pattern resemble earlier moves. By the 6th move[1] in a 16 move sequence, for example, the onsumer has provided sufficient data, enabling Al.

Much of today's discussion around the future of artificial intelligence is focused on the possibility of achieving artificial general intelligence. Essentially, an AI capable of tackling an array of random tasks and working out how to tackle a new task on its own, much like a human, is the ultimate goal. But the discussion around this kind of intelligence seems less about if and more about when at this stage in the game. With the advent of neural networks and deep learning, the sky is the actual limit, at least that will be true once other areas of technology overcome their remaining obstructions. For deep learning to successfully support general intelligence, it's going to need the ability to access and store much more information than any individual system currently does.

In the age of Artificial Intelligence and automation, machines have taken over many key managerial tasks. Replacing managers with AI systems may have a negative impact on workers outcomes. It is unclear if workers receive the same benefits from their relationships with AI systems, raising the question: What degree does the relationship between AI systems and workers impact worker outcomes? We draw on IT identity to understand the influence of identification with AI systems on job performance. From this theoretical perspective, we propose a research model and conduct a survey of 97 MTurk workers to test the model. The findings reveal that work role identity and organizational identity are key determinants of identification with AI systems. Furthermore, the findings show that identification with AI systems does increase job performance.

Man always has been haunted, and simultaneously thrilled, by the idea we are not alone. Long before computers were invented, monsters like Frankenstein and Jewish golem folklore normalized the fantasy of artificial intelligence. Today, companies like Google, Facebook and Microsoft, along with Chinese tech giants like Baidu, are investing billions of dollars in AI. International Data Corp. estimates AI solutions are now a $12.5 billion industry, expected to rake in $46 billion in annual revenues by 2020. But this technological progress comes with complex risks.

Retail Real Estate is experiencing greater change than ever before. The impact of changes in real estate and the consumer retail world is comparable to tectonic plates shifting across the surface of the earth, producing an energy force that few know how to harness or predict the outcome. The way we conduct retail and real estate are rubbing, creating friction & forces, sometimes against, and sometimes in harmony with each other. Year-end 2016 came and went with little time to pause and reflect as Amazon Go made the headlines in the final few weeks and continues to do so. We asked some of the Movvo team to share their predictions for 2017, the trends & innovations that will have an impact on retail real estate as we know it. "2016 is going to be remembered as the year a retail platform came from nowhere to hit Apple & Google where it hurts. Alexa from Amazon is an intuitive AI interface already flexing its muscle and proving incredible popular. Alexa is already present in 4% of US households and dozens of Alexa-enabled devices launched at CES Las Vegas from fridges to cars. It's an early vision of the death of the keyboard as an interface & will have an impact on the way consumers shop".

While there are fears robots may rise up to take over the world if artificial intelligence progresses too quickly, some of us may find ourselves simply marrying machines in the future. A leading computer scientist has predicted that as robots become more human-like, people may start turning to them for companionship. His predictions mirror the plot of the hit TV series Humans, where people formed emotional attachments to robots brought in to help out around the home. Robots could soon become intimate companions for humans and some people may even seek to marry them as they become more human-like. Unlike other technology, such as mobile phones and computers, robots will have the ability to interact with us in a far more realistic way.