Image created with gemini-3.1-flash-image-preview with claude-sonnet-4-5. Image prompt: Wide angle aerial photography of a joyful person freefalling through crisp blue sky, juggling a glowing camera lens, speech bubble, musical notes, and text pages that orbit around them, ground visible far below, bright daylight, dynamic action shot, the word MULTIMODALITY in large bold clean title typography integrated into the upper sky, clean simple composition, vibrant optimistic mood.
Introducing Cinematic Video Overviews, the next evolution of the NotebookLM Studio. Unlike standard templates, these are powered by a novel combination of our most advanced models to create bespoke, immersive videos from your sources. Rolling out now for Ultra users in English!”” https://x.com/NotebookLM/status/2029240601334436080
The Document Arena is now live with leaderboard scores! See which frontier AI models rank highest in document reasoning, all powered by side-by-side evaluations on user-uploaded PDFs from real work use cases. – #1 is Claude Opus 4.6 scoring 1525, +51 pts in the lead – While”” https://x.com/arena/status/2028915403704156581
Microsoft built Phi-4-reasoning-vision-15B to know when to think — and when thinking is a waste of time | VentureBeat https://venturebeat.com/technology/microsoft-built-phi-4-reasoning-vision-15b-to-know-when-to-think-and-when
A vision system can be a universal communication port between AI models. ▪️ Vision Wormhole is a new framework that lets VLMs exchange compact continuous “”thought messages”” through a shared visual channel instead of slow text. The sender model: – Converts its internal”” https://x.com/TheTuringPost/status/2027901044538413504
Humans communicate through language and interact with the world through vision, yet most multimodal models are language-first. What happens when we go beyond language? 🤔 Beyond Language Modeling: a deep dive into the design space of truly native multimodal models Paper:”” https://x.com/__JohnNguyen__/status/2029236083914096756
New paper out! We present a training method for multimodal generative models, called Self-Flow, which combines classic flow matching and representation learning. Why? Unlike most representation alignment methods, our new approach does not require external, pretrained models and”” https://x.com/robrombach/status/2029272803099226425
Train Beyond Language. We bet on the visual world as the critical next step alongside and beyond language modeling. So, we studied building foundation models from scratch with vision. We share our exploration: visual representations, data, world modeling, architecture, and”” https://x.com/TongPetersb/status/2029237530160169286
We present a research preview of Self-Flow: a scalable approach for training multi-modal generative models. Multi-modal generation requires end-to-end learning across modalities: image, video, audio, text – without being limited by external models for representation learning.”” https://x.com/bfl_ml/status/2029212134023020667
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