Developing intelligent agents, using LLMs like GPT-4o, Gemini, etc., that can perform tasks requiring multiple steps, adapt to changing information, and make decisions is a core challenge in AI ...
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Fine-Tuning AnomalyCLIP: Class-Agnostic Zero-Shot Anomaly Detection
Zero-shot anomaly detection (ZSAD) is a vital problem in computer vision, particularly in real-world scenarios where labeled anomalies are scarce or unavailable. Traditional vision-language models ...
SigLIP 2: DeepMind’s Multilingual Vision-Language Model
SigLIP-2 represents a significant step forward in the development of multilingual vision-language encoders, bringing enhanced semantic understanding, localization, and dense feature extraction ...
MedGemma: Google’s Medico VLM for Clinical QA, Imaging, and More
Picture this: Dr. Aris, a radiologist with a decade of experience, is staring at his screen. The stack of digital files, chest X-rays, and CT scans seems endless. Each image holds a story, a clue to a ...
Nanonets-OCR-s: Enabling Rich, Structured Markdown for Document Understanding
Traditional Optical Character Recognition (OCR) systems are primarily designed to extract plain text from scanned documents or images. While useful, such systems often ignore semantic structure, ...
Optimizing VJEPA-2: Tackling Latency & Context in Real-Time Video Classification Scripts
The domain of video understanding is rapidly evolving, with models capable of interpreting complex actions and interactions within video streams. Meta AI's VJEPA-2 (Video Joint Embedding Predictive ...
