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 Generative AI


As the AI world gathers in Seoul, can an accelerating industry balance progress against safety?

The Guardian

This week, artificial intelligence caught up with the future – or at least Hollywood's idea of it from a decade ago. "It feels like AI from the movies," wrote the OpenAI chief executive, Sam Altman, of his latest system, an impressive virtual assistant. To underline his point he posted a single word on X – "her" – referring to the 2013 film starring Joaquin Phoenix as a man who falls in love with a futuristic version of Siri or Alexa, voiced by Scarlett Johansson. For some experts, that new AI, GPT-4o, will be an unsettling reminder of their concerns about the technology's rapid advances, with a key OpenAI safety researcher leaving this week following a disagreement over the company's direction. For others the GPT-4o release will be confirmation that innovation continues in a field promising benefits for all. Next week's global AI summit in Seoul, attended by ministers, experts and tech executives, will hear both perspectives, as underlined by a safety report released before the meeting that referred to potential positives as well as numerous risks.


Human-Generative AI Collaborative Problem Solving Who Leads and How Students Perceive the Interactions

arXiv.org Artificial Intelligence

This research investigates distinct human-generative AI collaboration types and students' interaction experiences when collaborating with generative AI (i.e., ChatGPT) for problem-solving tasks and how these factors relate to students' sense of agency and perceived collaborative problem solving. By analyzing the surveys and reflections of 79 undergraduate students, we identified three human-generative AI collaboration types: even contribution, human leads, and AI leads. Notably, our study shows that 77.21% of students perceived they led or had even contributed to collaborative problem-solving when collaborating with ChatGPT. On the other hand, 15.19% of the human participants indicated that the collaborations were led by ChatGPT, indicating a potential tendency for students to rely on ChatGPT. Furthermore, 67.09% of students perceived their interaction experiences with ChatGPT to be positive or mixed. We also found a positive correlation between positive interaction experience and a sense of positive agency. The results of this study contribute to our understanding of the collaboration between students and generative AI and highlight the need to study further why some students let ChatGPT lead collaborative problem-solving and how to enhance their interaction experience through curriculum and technology design.


The OpenAI team tasked with protecting humanity is no more

Engadget

In the summer of 2023, OpenAI created a "Superalignment" team whose goal was to steer and control future AI systems that could be so powerful they could lead to human extinction. Less than a year later, that team is dead. OpenAI told Bloomberg that the company was "integrating the group more deeply across its research efforts to help the company achieve its safety goals." But a series of tweets from Jan Leike, one of the team's leaders who recently quit revealed internal tensions between the safety team and the larger company. In a statement posted on X on Friday, Leike said that the Superalignment team had been fighting for resources to get research done.


The Toilet Theory of the Internet

The Atlantic - Technology

Allow me to explain my toilet theory of the internet. The premise, while unprovable, is quite simple: At any given moment, a great deal of the teeming, frenetic activity we experience online--clicks, views, posts, comments, likes, and shares--is coming from people who are scrolling on their phones in the bathroom. Mindless scrolling isn't limited to the bathroom, and plenty of idle or bored swiping happens during other down moments--while waiting in line, or sitting in gridlocked traffic. Right now, somebody somewhere is probably reading an article or liking an Instagram post with a phone in one hand and an irritable infant in the other. The toilet theory is mostly a reminder to myself that the internet is a huge place that is visited countless times each day by billions of people in between and during all the mundane things they have to do.


OpenAI's Long-Term AI Risk Team Has Disbanded

WIRED

In July last year, OpenAI announced the formation of a new research team that would prepare for the advent of supersmart artificial intelligence capable of outwitting and overpowering its creators. Ilya Sutskever, OpenAI's chief scientist and one of the company's cofounders, was named as the colead of this new team. OpenAI said the team would receive 20 percent of its computing power. Now OpenAI's "superalignment team" is no more, the company confirms. That comes after the departures of several researchers involved, Tuesday's news that Sutskever was leaving the company, and the resignation of the team's other colead.


It's Time to Believe the AI Hype

WIRED

Tech pundits are fond of using the term "inflection points" to describe those rare moments when new technology wipes the board clean, opening up new threats and opportunities. But one might argue that in the past few years what used to be called out as an inflection point might now just be called "Monday." Certainly that applied this week. OpenAI, denying rumors that it would unveil either an AI-powered search product or its next-generation model GPT-5, instead announced something different, but nonetheless eye-popping, on Monday. It was a new flagship model called GPT-4o, to be made available for free, which uses input and output in various modes--text, speech, vision--for disturbingly natural interaction with humans. What struck many observers about the demo was how playful and even provocative the emotionally expressive chatbot was--but also imbued with the encyclopedic knowledge of data sets encompassing much of the world's knowledge.


Can AI-generated inventions be patented? A Tokyo court says no.

The Japan Times

A Tokyo court on Thursday ruled against granting patents to inventions generated by artificial intelligence in a dispute over whether AI -- not human beings -- can be recognized as an inventor. The ruling comes amid ongoing debates on how to regulate generative AI and is part of a transnational class action lawsuit launched by Ryan Abbott, a law and health science professor at the University of Surrey in England. The plaintiff filed for a patent in 2021 for a device generated by AI, listing the inventor's name as "DABUS, an artificial intelligence that autonomously invented this invention." Device for the Autonomous Bootstrapping of Unified Sentience (DABUS) is an AI system developed by Stephen Thaler, a computer scientist and president of Imagination Engines, an AI technology company.


Reddit Partners With OpenAI to Bring Content to ChatGPT and AI Tools to Reddit

TIME - Tech

Reddit Inc. forged a partnership with OpenAI that will bring its content to the chatbot ChatGPT and other products, while also helping the social media company add new artificial intelligence features to its forums. Shares of Reddit, which had their initial public offering in March, jumped as much as 15% in late trading following the announcement. The agreement "will enable OpenAI's AI tools to better understand and showcase Reddit content, especially on recent topics," the companies said Thursday in a joint statement. The deal allows OpenAI to display Reddit's content and train AI systems on its partner's data. Reddit will also offer its users new AI-based tools built on models created by OpenAI, which will place ads on its partner's site.


Revolutionizing Process Mining: A Novel Architecture for ChatGPT Integration and Enhanced User Experience through Optimized Prompt Engineering

arXiv.org Artificial Intelligence

In the rapidly evolving field of business process management, there is a growing need for analytical tools that can transform complex data into actionable insights. This research introduces a novel approach by integrating Large Language Models (LLMs), such as ChatGPT, into process mining tools, making process analytics more accessible to a wider audience. The study aims to investigate how ChatGPT enhances analytical capabilities, improves user experience, increases accessibility, and optimizes the architectural frameworks of process mining tools. The key innovation of this research lies in developing a tailored prompt engineering strategy for each process mining submodule, ensuring that the AI-generated outputs are accurate and relevant to the context. The integration architecture follows an Extract, Transform, Load (ETL) process, which includes various process mining engine modules and utilizes zero-shot and optimized prompt engineering techniques. ChatGPT is connected via APIs and receives structured outputs from the process mining modules, enabling conversational interactions. To validate the effectiveness of this approach, the researchers used data from 17 companies that employ BehfaLab's Process Mining Tool. The results showed significant improvements in user experience, with an expert panel rating 72% of the results as "Good". This research contributes to the advancement of business process analysis methodologies by combining process mining with artificial intelligence. Future research directions include further optimization of prompt engineering, exploration of integration with other AI technologies, and assessment of scalability across various business environments. This study paves the way for continuous innovation at the intersection of process mining and artificial intelligence, promising to revolutionize the way businesses analyze and optimize their processes.


From Sora What We Can See: A Survey of Text-to-Video Generation

arXiv.org Artificial Intelligence

With impressive achievements made, artificial intelligence is on the path forward to artificial general intelligence. Sora, developed by OpenAI, which is capable of minute-level world-simulative abilities can be considered as a milestone on this developmental path. However, despite its notable successes, Sora still encounters various obstacles that need to be resolved. In this survey, we embark from the perspective of disassembling Sora in text-to-video generation, and conducting a comprehensive review of literature, trying to answer the question, \textit{From Sora What We Can See}. Specifically, after basic preliminaries regarding the general algorithms are introduced, the literature is categorized from three mutually perpendicular dimensions: evolutionary generators, excellent pursuit, and realistic panorama. Subsequently, the widely used datasets and metrics are organized in detail. Last but more importantly, we identify several challenges and open problems in this domain and propose potential future directions for research and development.