The AI-native environment for visual data.
Joined March 2023
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- Followers59
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Visual Layer retweeted
Following the first track, we're now diving into our second track at IMVC - how data drives AI in vision. This track covers enhancing model performance and tackling challenges like label noise and domain adaptation. Stay tuned for more! Secure your spot bit.ly/41xoc2U
Visual Layer retweeted
Charting the Uncharted: User Videos in Social Networks
Every day, billions of videos are uploaded—capturing everything from daily life to the unimaginable. What can AI uncover from this vast content?
@BicksonDanny, CEO of @visual_layer, dives into the hidden patterns of user-generated videos, revealing surprising insights into behavior and digital expression.
💡 What trends emerge from this massive video archive?
🔍 How does AI make sense of unfiltered social content?
Don’t miss this fascinating look into the future of AI-driven social analysis.
#AI #SocialMedia #MachineLearning #UserBehavior #TheAIConference
Visual Layer retweeted
If you missed the LLMs / VLMs episode, here is the video for you!
4:20 Fine-Tuning LLMs: An Approach with @clarifai @Sumanth_077
39:52 From raw data to refined datasets for AI Model Dev @alushamir @visual_layer
1:12:17 Reflections on building our first LLM-Based App @_PrivateAI
Visual Layer retweeted
The Monthly Dev is next week!
Topic: LLMs and VLMs
🗓️ Nov 26, 5 pm CET
Speakers:
- Sumanth Papareddy, ML Dev Advocate, Clarifai
- Amir Alush, CTO of Visual Layer
- Graham Miller, Fullstack Developer at Private AI
@Sumanth_077 @alushamir @_PrivateAI @clarifai
@visual_layer
ALT "Promotional banner for 'LLMs and VLMs' event hosted by daily.dev as part of The Monthly Dev series (#47). Scheduled for Tuesday, November 26th, 2024, at 8 AM PST. Features speakers Sumanth Papareddy, Amir Alush, and Graham Miller, with respective icons below their names."
Visual Layer retweeted
What if computers can automatically identify and separate parts of images - like identifying every tree in a forest photo! Segment Anything model from Meta makes this possible!
This post shows how you can auto-label your images using Segment Anything in fastdup, for FREE.
Visual Layer retweeted
Data quality is the cornerstone of a computer vision project. But how do you ensure your dataset is up to the mark?
We show how you can leverage @huggingface PyTorch Image Models (TIMM) to compute embeddings of your dataset and analyze the embeddings in fastdup, all for free.
Visual Layer retweeted
We would like to welcome @visual_layer as our GOLD SPONSOR ⭐️ Hear from them and others at The AI Conference 2023!
#aiconf2023 #ai #aicommunity
Visual Layer retweeted
The @huggingface Datasets Hub hosts hundreds (or more) openly accessible computer vision datasets.
In this post, we show how you can make the most of these massive open datasets by inspecting for quality issues using fastdup, for free, on your CPU machine!
A thread
Visual Layer retweeted
We are excited to announce that Dr. Danny Bickson, founder and CEO of Visual Layer, @visual_layer will be speaking at The AI Conference 2023 in San Francisco!
#aiconf2023 #ai #aicommunity
Visual Layer retweeted
📣 Exciting news from the fastdup team!
For months, we've been hard at work refining our beta features. Today we are announcing all advanced fastdup features are now available to the public, completely free of charge!
Here's what's new 🧵
Visual Layer retweeted
Introducing VL Datasets - A Free Collection of Clean Computer Vision Datasets.
TL;DR: VL Datasets is a collection of clean datasets eliminating common issues like duplicates, mislabels, outliers, and more.
They're accessible for free.
A 🧵
