Large language models frequently generate false information, but researchers and companies have developed effective mitigation strategies, according to a comprehensive analysis by Emil Sorensen. The report outlines nine technical approaches across input, design, and output layers to reduce these AI “hallucinations” – instances where AI systems confidently produce incorrect information. These strategies include query optimization, …
MIT startup Liquid AI has developed a new AI framework called STAR (Synthesis of Tailored Architectures) that significantly improves upon traditional Transformer models. As reported by Carl Franzen for VentureBeat, the system uses evolutionary algorithms to automatically generate and optimize AI architectures. The STAR framework achieved a 90% reduction in cache size compared to traditional …
The artificial intelligence industry is grappling with potential limitations in scaling larger language models (LLMs), according to an analysis by Gary Grossman, EVP of technology practice at Edelman. While recent reports suggest that developing more extensive AI models like GPT-5 may face diminishing returns, industry leaders including OpenAI’s Sam Altman and former Google CEO Eric …
Indigenous technologists are working to save their rapidly disappearing languages using artificial intelligence technology. Michael Running Wolf, founder of Indigenous in AI, leads an initiative at the Mila-Quebec Artificial Intelligence Institute to develop speech recognition models for over 200 endangered Native American languages, as one Indigenous language dies every two weeks globally. The effort faces …
AI startup Altera conducted a groundbreaking experiment where up to 1,000 AI agents, powered by large language models, interacted autonomously in Minecraft. As reported by Niall Firth, the AI characters developed distinct personalities, established social hierarchies, created specialized jobs like builders and traders, and even participated in religious and political activities without human intervention. The …
OpenScholar, a new open-source AI system developed by the Allen Institute for AI and the University of Washington, is transforming how researchers analyze scientific literature. As reported by Michael Nuñez for VentureBeat, the system processes over 45 million open-access academic papers to provide citation-backed answers to complex research questions. The AI combines advanced retrieval systems …
Leading AI companies are creating new ways to evaluate increasingly sophisticated AI models as current testing methods prove inadequate. According to Cristina Criddle’s report in the Financial Times, companies like OpenAI, Microsoft, Meta, and Anthropic are developing internal benchmarks because their latest AI systems achieve over 90% accuracy on existing public tests. Meta’s generative AI …
AI tools that can generate realistic images are becoming a significant concern for research integrity specialists. The ease with which these tools can create fake scientific figures that are hard to distinguish from real ones raises fears of an increasingly untrustworthy scientific literature, Nature reports. Companies like Proofig and Imagetwin are developing AI-based solutions to …
The FrontierMath benchmark, developed by Epoch AI, presents hundreds of challenging math problems that require deep reasoning and creativity to solve. Despite the growing power of AI models like GPT-4o and Gemini 1.5 Pro, they are solving fewer than 2% of these problems, even with extensive support, according to Epoch AI. The benchmark was created …
OpenAI is reportedly developing new strategies to deal with a slowdown in AI model improvements. According to The Information, OpenAI employees testing the company’s next flagship model, code-named Orion, found less improvement compared to the jump from GPT-3 to GPT-4, suggesting the rate of progress is diminishing. In response, OpenAI has formed a foundations team …