/AI News/Issue 73
Could AI help fight conspiracy theories?
Published Tuesday, October 8, 2024
We’re used to hearing about the power of artificial intelligence to spread misinformation – but could it also be a tool for persuading people of the truth? Ian Sample speaks to Thomas Costello, an assistant professor of psychology at American University, who has published a study exploring the potential for AI chatbots to lead people away from conspiracy beliefs.
The 2024 PyTorch Conference in San Francisco gathered nearly 1,500 AI researchers, developers, and enthusiasts. Over two days, the event featured engaging discussions, insightful keynotes, and hands-on sessions focused on artificial intelligence (AI) and advancements in PyTorch, the leading open-source machine learning framework.
This is another fun but helpful machine-learning application: Turning Word documents into pleasing PowerPoint slides. This paper discusses combining embedding models, state machines, perceptrons, and sequence-to-sequence models to convert long Word documents into PowerPoint slides. It shows that combining multiple model architectures can yield some amazing results.
Our paper on ray tracing: https://users.cg.tuwien.ac.at/zsolnai/gfx/adaptive_metropolis/ ❤️ Check out Lambda here and sign up for their GPU Cloud: https://lambdalabs.com/papers
https://research.nvidia.com/labs/par/maskedmimic/ If you wish to appear here or pick up other perks, click here: https://www.patreon.com/TwoMinutePapers
Data Formulator investigates combining UI interactions with natural language input. Powered by AI, it can help users create or adapt visualizations and supports continuous refinement through an iterative process. Now available on GitHub.
Whether you are building customer-facing chatbots to answer repetitive questions and reduce workload from customer service agents, or building a co-pilot for engineers to help them navigate complex user manuals step-by-step, RAG has become a key archetype of the application of LLMs. This has enabled LLMs to provide a contextually relevant response based on ground truth of hundreds or millions of documents, reducing hallucinations and improving the reliability of LLM-based applications.
It's Python 3.13 release day today. The big signature features are a better REPL with improved error messages, an option to run Python without the GIL and the beginnings of the new JIT. Here are some of the smaller highlights I spotted while perusing the release notes.
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