Multimodal capabilities of large vision language models. Gemini 1.5 is outstanding on this benchmark. @GoogleDeepMind
GENERATIVE AI
-
RAG Explained: Video Guide to Retrieval-Augmented Generation
By
–
This video teaches you more about RAG than a 1000 words blog. xD
-
Gemma 10 Model Released: Access Hub and Technical Documentation
By
–
Get the model here: • : https://
tinyurl.com/gemma10hf
• GitHub: https://
tinyurl.com/gemma10git
• Technical blog: https://
tinyurl.com/gemma10blog -
Cohere Build Day: Enterprise AI Solutions with Command R
By
–
Last chance to register for Cohere Build Day! Our tour ends tomorrow in San Francisco. Come and create innovative solutions with Command R and R+. This is your opportunity to build enterprise-grade knowledge systems and multilingual customer chatbots. Don't miss out on this
-
AI Image Extension with Generative Fill Tool
By
–
It has this! Tap [ Edit ] on a photo Then extend the canvas with crop tool Then select the lasso and select the area to extend, write a prompt on top and fill it in
-
CLIP and Image Semantic Search APIs Available?
By
–
Is there a CLIP (or similar image sem. search) API?
-
AI detects diabetes and cardiovascular risk from chest X-ray imaging
By
–
"Your chest x-ray indicates that you may have type 2 diabetes, your coronary calcium score is 976, your ejection fraction is normal, and your 10-year cardiovascular risk of a heart attack, stroke, or death from cardiovascular disease is 14·1%. Please review with your
-
Assistants API Now Supports Vision Capabilities
By
–
The Assistants API now supports vision! https://t.co/xUonkPGz92
— Romain Huet (@romainhuet) 9 mai 2024The Assistants API now supports vision!
-
Vision Now Available in Assistants API
By
–
Vision is now available in the Assistants API: https://t.co/kR0wt1hyCs
— Greg Brockman (@gdb) 9 mai 2024Vision is now available in the Assistants API:
-
Build Autonomous Research Assistant with LangGraph and GPT
By
–
Build an Autonomous Research Assistant with LangGraph and GPT Researcher See a step-by-step walkthrough by @assaf_elovic on how flow engineering and multi-agent collaboration can help automate in-depth research on any given topic — from architecture to run. In this example,