How I Built an AI-Powered WhatsApp Bot That Analyzes Images Using Python and Vision Models

Learn how to build a low-cost WhatsApp bot that analyzes images using AI vision models like Llama and GPT-4V, with Python and MongoDB.
#visionmodels

Next-Embedding Prediction Makes Strong Vision Learners
Joyce Chai, Saining Xie et al.
Paper
Details
#SelfSupervisedLearning #VisionModels #DeepLearning

AI Vision Models Show Gender and Ethnicity Bias in Healthcare Jobs

The study examined CLIP and OpenCLIP models and found surgeons most associated with Indian male faces, while speech therapists linked to white female faces. getnews.me/ai-vision-models-show-ge... #aibias #healthcare #visionmodels

Pruning Pre‑trained Vision Models Preserves Zero‑Shot Ability

A study shows that pruning a large vision model on a single downstream task preserves its zero‑shot ability on other unseen tasks, and fine‑tuning improves performance. getnews.me/pruning-pre-trained-visi... #visionmodels #zeroshot #pruning

Large Pretraining Datasets May Reduce Robustness After Fine‑Tuning

Fine‑tuning vision models, even those pretrained on LAION‑2B, can sharply cut out‑of‑distribution robustness; the ImageNet‑RIB benchmark quantifies this drop. getnews.me/large-pretraining-datase... #visionmodels #robustness #laion2b

Adversarial Robustness of Discriminative Self‑Supervised Vision Models

Seven SSL models were tested on ImageNet; they outperformed a supervised baseline under adversarial attacks in linear‑eval, but fine‑tuning narrows it. Read more: getnews.me/adversarial-robustness-o... #selfsupervised #adversarial #visionmodels

Parameter-Efficient Fine-Tuning Boosts Vision Models for Atypical Mitotic Figure Detection

LoRA fine‑tuning lifted a vision model’s balanced accuracy to 88.37% for atypical mitotic figure detection in the MIDOG 2025 challenge using Virchow with rank‑8. getnews.me/parameter-efficient-fine... #lora #visionmodels

AI Vision and Language Models Compared for Human Visual Cortex Mapping

A study found response‑optimized models best early/mid‑level, while LLM embeddings and task‑optimized models excel higher areas; a new readout boosted accuracy 3%‑23% #visionmodels #languagemodels getnews.me/ai-vision-and-language-m...

Region-Aware Deformable Convolution Improves Vision Model Flexibility

RAD‑Conv adds four boundary offsets per kernel element to form rectangular sampling regions, improving receptive‑field control; paper submitted on 18 Sep 2025. Read more: getnews.me/region-aware-deformable-... #radconv #deformableconv #visionmodels

PS: 📅 #HELPLINE. Want to discuss your article? Need help structuring your story? Make a date with the editors of Low Code for Data Science via Calendly → calendly.com/low-code-blo...

#datascience #llms #visionmodels #imageediting #workflows #KNIME #lowcode #nocode #opensource #visualprogramming

Apple's FastVLM breakthrough boosts vision-language model speed and accuracy by efficiently handling high-resolution images while reducing latency. Exciting progress in AI vision tech! 🚀🤖 #AI #MachineLearning #VisionModels #TechInnovation https://rpst.cc/Tm6Qb3

Ollama Local LLM Platform Unveils Custom Multimodal AI Engine, Steps Away from Llama.cpp Framework - WinBuzzer Ollama launches its new custom engine for multimodal AI, enhancing local inference for vision and text with improved reliability and performance, moving beyond direct llama.cpp dependency.

Ollama Local LLM Platform Unveils Custom Multimodal AI Engine, Steps Away from Llama.cpp Framework

#Ollama #MultimodalAI #LocalLLM #AI #ArtificialIntelligence #MachineLearning #VisionModels #OpenSourceAI #LLM #AIEngine #TechNews #LocalAI

winbuzzer.com/2025/05/16/o...

A few themes from #RSNA24 scientific sessions and exhibit hall:

➡️ How do we benchmark #LLM performance?

➡️ How do we differentiate between a growing cohort of #visionmodels for similar use cases?

➡️ Can we converge on the latest standards for seamless clinical integration?

@rsnasky.bsky.social

Supercharging CLIP with LLMs: A New Era for Multimodal AI Researchers from Microsoft and Tongji University introduced LLM2CLIP, a novel framework leveraging large language models (LLMs) to dramatically enhance CLIP’s multimodal capabilities. By fine-tuning L...

Supercharging CLIP with LLMs: A New Era for Multimodal AI 🔍🤖📈 www.azoai.com/news/2024111... #AI #MachineLearning #Multimodal #LLM #CLIP #MicrosoftResearch #TongjiUniversity #VisionModels #DeepLearning #Innovation

@ylecun #ai #visionmodels #ml $Meta Segment Anything Model v2 (SAM 2) is out.
Can segment images and videos.
Open source under Apache-2 license.
Web demo, paper, and datasets available.
Amazing performance.

x.com/ylecun/statu...