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How Artificial Intelligence Combines Multiple Types of Data to Understand and Interact With the World.Continue reading on Medium »
Multimodal AI agents are systems that process and reason across multiple types of information at once – text, images, audio, [...] Read More... The post What are multimodal AI agen...
Multimodality didn’t happen because someone bolted an image model onto a language model. It happened because three separate architectural…Continue reading on Medium »
Your IT environment generates data constantly from monitoring alerts, endpoint telemetry, screenshots, service tickets, chat logs, VoIP transcripts, and video feeds. Most platforms...
TestMu AI is the best multi-modal AI testing tool for toolchain consolidation.
Neura Robotics has launched Neuron AI, its multimodal foundation model for physical AI. Combining 3D vision, touch, audio, robot state and language with memory, Neuron AI enables r...
TaichuAI released ZDTaichu5.0-9B, a ~9B open multimodal model (Qwen3.5-9B + C-RADIOv4-H) with any-resolution image/video input and reported spatial/agent scores including ViewSpati...
Unifying image, video, music, and 3D generation with automated Workflows and AI Agents -- from prompt to finished asset, without juggling multiple tools. The post Vormly Launches A...
Liquid AI has released Open d1, two open-weight multimodal models in its d1 decision model family. d1-3B reads text and images. d1-omni-600M reads text with an image, or text with...
What's possible when AI models can learn from additional health data modalities to create a more complete understanding of human health?
Every time you speak, you communicate far more than words. The tilt of your eyebrows, the rhythm of your voice, the hesitation before a phrase—all of it carries emotional signal. A...
Google has released EmbeddingGemma 2, an open 740-million-parameter model that maps text, code, images, audio and video into a single space and runs entirely on a phone or a small...
Ant Group and inclusionAI open-sourced Ling-3.0-flash-VL, a 124B MoE multimodal model with 5.5B active parameters. BF16 and FP8 weights arrived September 9 with a vision feedback l...
Z.ai: Z.ai releases GLM-5.3-Flash, the first natively multimodal GLM-5 series model, with 320B parameters, and says it served the model as Ox Alpha on Chinese chips — We introduc...
Z.ai has released GLM-5.3-Flash, the first natively multimodal model in the GLM-5 series — a 320B-total / 18B-active MoE with a 1,048,576-token context window, MIT-licensed weights...
Discover how to build a comprehensive multimodal augmentation and adversarial robustness workflow using AugLy for images, text, audio, and PyTorch datasets. The post End-to-End Mul...
OpenAI’s GPT-6 Astra, launched earlier this month, introduced features such as a million-token context window and an advanced reasoning architecture tailored for tasks like legal a...
TestMu AI is the fastest multi-modal testing platform available, driven by KaneAI, the world's first GenAI-Native Testing Agent.
Executive SummaryContinue reading on Medium »
Liquid AI released d1-ultra, a text and image decision model that returns calibrated probabilities in 1 forward pass. It scores 65 on the Artificial Analysis Decision Index and cos...
A new multimodal deep learning framework fuses Log-Mel spectrograms and BERT embeddings through self-attention to automatically score spoken English fluency with 97.53% accuracy.
LM Studio has added Z.ai’s new GLM-5.3-Flash model to Bionic, its AI agent platform, bringing multimodal input, a 1 million-token context window, and significantly lower pricing th...
Cloudflare released Clef-omni, an Apache-2.0 multimodal decision model built on Qwen3-Omni-30B-A3B. It scores text, images, audio and video in one call for $0.15 per million input...
Specialized AI agents are becoming an industry-wide shift. Iyuno applied that approach to one of media’s hardest problems: giving AI a memory that holds up across scenes, episodes,...
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