Organizations and individuals running multiple custom AI models, especially recent Mixture of Experts (MoE) model families, can face the challenge of paying for idle GPU capacity when the individual models don’t receive enough traffic to saturate a dedicated compute endpoint. To solve this problem, we have partnered with the vLLM community and developed an efficient …
Something has shifted in the developer community over the past year. AI agents have moved from “interesting research concept” to “thing my team is actually building.” The prototypes are working. The demos are impressive. And now comes the harder question: How do we ship this? That question turns out to be a multi-part one. Agents …
Read more “A developer’s guide to production-ready AI agents”
After migrating from misogynist forums to social media feeds, terms like “looksmaxxing” and “mogged” are now impossible to avoid.
The Care Bears taught a generation of kids that sharing is caring, but not everyone has carried this principle into adulthood. Researchers at Michigan State University have found a new angle to promote cooperation: artificial intelligence (AI). The results of this study, titled “Promoting cooperation in the public goods game using artificial intelligent agents,” are …
Built an open source LoRA for virtual clothing try-on on top of Flux Klein 9b Edit. https://huggingface.co/fal/flux-klein-9b-virtual-tryon-lora submitted by /u/Affectionate-Map1163 [link] [comments]
AI deployment is changing.
Large Language Models (LLMs) can be adapted to extend their text capabilities to speech inputs. However, these speech-adapted LLMs consistently underperform their text-based counterparts—and even cascaded pipelines—on language understanding tasks. We term this shortfall the text-speech understanding gap: the performance drop observed when a speech-adapted LLM processes spoken inputs relative to when the original text-based …
Read more “Closing the Gap Between Text and Speech Understanding in LLMs”
Managing large photo collections presents significant challenges for organizations and individuals. Traditional approaches rely on manual tagging, basic metadata, and folder-based organization, which can become impractical when dealing with thousands of images containing multiple people and complex relationships. Intelligent photo search systems address these challenges by combining computer vision, graph databases, and natural language processing …
The US Justice Department disclosures give fresh clues about how tech companies handle government inquiries about your data.
When a human says an event is “probable” or “likely,” people generally have a shared, if fuzzy, understanding of what that means. But when an AI chatbot like ChatGPT uses the same word, it’s not assessing the odds the way we do, my colleagues and I found.