What we’re about
đź–– This group is for data scientists, machine learning engineers, and open source enthusiasts.
Every month we’ll bring you diverse speakers working at the cutting edge of AI, machine learning, and computer vision.
- Are you interested in speaking at a future Meetup?
- Is your company interested in sponsoring a Meetup?
This Meetup is sponsored by Voxel51, the lead maintainers of the open source FiftyOne computer vision toolset. To learn more, visit the FiftyOne project page on GitHub.
Upcoming events (4+)
See all- Network event138 attendees from 37 groups hostingJune 17 - Databricks Mosaic AI + FiftyOne: Scaling Physical AILink visible for attendees
When and Where
June 17, 2025 | 9:00 AM Pacific
About the Workshop
Ever tried to find something specific in your image or video datasets that weren’t already labeled? It’s always been a frustrating and time-consuming experience.
Until now.
When you combine the FiftyOne computer vision toolkit with Mosaic AI from Databricks, you unlock lightning-fast vector search for the millions of images and videos in your data lake – to find exactly what you are looking for, even if there’s no label for it.
In this technical session with machine learning engineer Dan Gural, he’ll show you how the Mosaic AI integration works inside FiftyOne, featuring real-world mobility and autonomous use cases where you search massive, state-of-the-art datasets in just seconds.
If you’re working with edge cases, building smarter datasets, or just curious about what Mosaic AI vector search can do for you, this one’s for you.
- Network event53 attendees from 38 groups hostingJune 18 - Getting Started with FiftyOne WorkshopLink visible for attendees
When and Where
June 18, 2025 | 9:00 – 10:30 AM Pacific
About the Workshop
Want greater visibility into the quality of your computer vision datasets and models? Then join us for this free 90-minute, hands-on workshop to learn how to leverage the open source FiftyOne computer vision toolset.
At the end of the workshop you’ll be able to:- Object detection
- Embeddings
- Mistakenness
- Deduplication
This workshop will explore the importance of taking a data-centric approach to computer vision workflows. We will start with importing and exploring visual data, then move to querying and filtering. Next, we’ll look at ways to extend FiftyOne’s functionality and simplify tasks using plugins and native integrations. We’ll generate candidate ground truth labels, and then wrap things up by evaluating the results of fine tuning a foundational model.
Prerequisites: working knowledge of Python and basic computer vision concepts.
All attendees will get access to the tutorials, videos, and code examples used in the workshop
About the Instructor
Antonio Rueda-Toicen, an AI Engineer in Berlin, has extensive experience in deploying machine learning models and has taught over 300 professionals. He is currently a Research Scientist at the Hasso Plattner Institute. Since 2019, he has organized the Berlin Computer Vision Group and taught at Berlin’s Data Science Retreat. He specializes in computer vision, cloud technologies, and machine learning. Antonio is also a certified instructor of deep learning and diffusion models in NVIDIA’s Deep Learning Institute.
- Network event163 attendees from 39 groups hostingJune 19 - AI, ML and Computer Vision MeetupLink visible for attendees
When
June 19, 2025 | 10:00 AM PacificWhen and Where
Online. Register for the Zoom.Multi-Modal Rare Events Detection for SAE L2+ to L4
A burst tire on the highway or a fallen motorbiker occur rarely and thus pose extra efforts to Autonomous vehicles. Methods to tackle such edge cases in road scenarios are explained.
About the Speaker
Wolfgang Schulz is Product Owner for Lidar Perception at Continental. He engages in the automotive industry since 2005. With his team he currently works on components for an SAE L4 stack.
Voxel51 + NVIDIA Omniverse: Exploring the Future of Synthetic Data
Join us for a lightning talk on one of the most exciting frontiers in Visual AI: synthetic data. We’ll showcase a sneak peek of the new integration between FiftyOne and NVIDIA Omniverse, featuring fully synthetic downtown scenes of Santa Jose. NVIDIA Omniverse is enabling the generation of ultra-precise synthetic sensor data, including LiDAR, RADAR, and camera feeds, while FiftyOne is making it easy to extract value from these rich datasets. Come see the future of sensor simulation and dataset curation in action, with pixel-perfect labels to match.
About the Speaker
Daniel Gural is a seasoned Machine Learning Engineer at Voxel51 with a strong passion for empowering Data Scientists and ML Engineers to unlock the full potential of their data.
O-TPT: Orthogonality Constraints for Calibrating Test-time Prompt Tuning in Vision-Language Models
We propose O-TPT, a method to improve the calibration of vision-language models (VLMs) during test-time prompt tuning. While prompt tuning improves accuracy, it often leads to overconfident predictions. O-TPT introduces orthogonality constraints on textual features, enhancing feature separation and significantly reducing calibration error across multiple datasets and model backbones.
About the Speaker
Ashshak Sharifdeen is a visiting Student Researcher at Mohamed bin Zayed University of Artificial Intelligence, UAE
- Network event76 attendees from 37 groups hostingJune 20 - AI, ML and Computer Vision Meetup en EspañolLink visible for attendees
When and Where
June 20, 2025 | 9:00 – 11:00 AM Pacific
IA Generativa con Agentes: Transformando el Desarrollo de Software
La charla explora cĂłmo expandir las capacidades de los LLMs utilizando herramientas externas mediante agentes inteligentes. Veremos cĂłmo esta combinaciĂłn transforma el desarrollo de software al automatizar tareas y colaboraciĂłn con la IA.
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Antonio Martinez es Ingeniero de Software en Inteligencia Artificial en Intel, con una maestrĂa en Ciencias de la ComputaciĂłn por la Universidad Estatal de Texas. Tiene más de 10 años de experiencia en liderazgo tĂ©cnico, inteligencia artificial, visiĂłn por computador y desarrollo de software.
Trabajadores Digitales: El Futuro del Trabajo Aumentado por Agentes
En esta charla te cuento cĂłmo, junto a mi esposa, desarrollamos una plataforma de agentes basada en LangGraph y LangChain que ha escalado nuestra atenciĂłn al cliente, aumentado la satisfacciĂłn y mejorado la conversiĂłn de ventas.
Te mostraré mi arquitectura agentica con el patrón React (Reasoning-Action) + Reflection (self-validation) y cómo este agente es capaz no solo de vender, sino de hacer todo el proceso de costear el delivery, validar pagos y más.
Compartiré ejemplos reales de empresas que ya usan microautomatizaciones low-code/no-code para centrar su esfuerzo en el core del negocio.
Reflexionaremos juntos sobre un mundo laboral hiperautomatizado donde cada uno de nosotros estará potenciado por múltiples agentes digitales.
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Soy Jamilton Quintero, Head de Inteligencia Artificial en Apiux TecnologĂa, y me apasiona diseñar arquitecturas agenticas que transformen procesos reales. Soy un apasionado de la tecnologĂa y fiel creyente de que la informaciĂłn tiene que fluir libremente, por lo que me encanta contribuir al OpenSource y en comunidades.
Usando Computer Vision Para Decisiones y Expresiones ArtĂsticas en Entornos Creativos
Uso de un sistema de control gestual para la creaciĂłn de animaciones / efectos visuales creativos. ExploraciĂłn de cĂłmo Machine Learning e Inteligencia Artificial pueden facilitar la creaciĂłn de experiencias inmersivas para entornos de trabajo creativos. CreaciĂłn de un sistema integral que comunica Python con Unreal Engine 5 para controlar entornos 3D.
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TecnĂłlogo Creativo especializado en el uso de tecnologĂas emergentes dentro de entornos creativos 2D/3D para diseños visuales.
Experiencia de trabajo en Realidad Virtual y Efectos Visuales para cine y TV.Tus Datos te Están Mintiendo: Búsqueda Semántica Para Encontrar la Verdad
Los modelos de alto rendimiento comienzan con datos de alta calidad, pero encontrar muestras ruidosas, mal etiquetadas o casos lĂmite dentro de conjuntos de datos masivos sigue siendo un gran obstáculo. En esta sesiĂłn, exploraremos un enfoque escalable para curar y refinar conjuntos de datos visuales a gran escala utilizando bĂşsqueda semántica impulsada por embeddings basados en transformers.
Al aprovechar la bĂşsqueda por similitud y el aprendizaje de representaciones multimodales, aprenderás a descubrir patrones ocultos, detectar inconsistencias y encontrar casos lĂmite. TambiĂ©n discutiremos cĂłmo estas tĂ©cnicas pueden integrarse en lagos de datos y canalizaciones a gran escala para facilitar la depuraciĂłn de modelos, la optimizaciĂłn de conjuntos de datos y el desarrollo de modelos fundacionales más robustos en visiĂłn por computadora. Ăšnete a nosotros para descubrir cĂłmo la bĂşsqueda semántica está transformando la manera en que construimos y refinamos sistemas de inteligencia artificial.
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Paula Ramos tiene un doctorado en VisiĂłn por Computador y Aprendizaje Automático, con más de 20 años de experiencia en el campo tecnolĂłgico. Desde principios de los años 2000 en Colombia, ha estado desarrollando tecnologĂas integradas de ingenierĂa innovadoras, principalmente en VisiĂłn por Computador, robĂłtica y Aprendizaje Automático aplicados a la agricultura.
Durante su investigaciĂłn doctoral y postdoctoral, desplegĂł mĂşltiples tecnologĂas de computaciĂłn en el borde e IoT inteligentes y de bajo costo, diseñadas para agricultores y que pueden ser operadas sin experiencia en sistemas de visiĂłn por computador. El objetivo central de la investigaciĂłn de Paula ha sido desarrollar sistemas y máquinas inteligentes capaces de comprender y recrear el mundo visual que nos rodea para resolver necesidades del mundo real, como las que se presentan en la industria agrĂcola.
Past events (22)
See all- Network event175 attendees from 36 groups hostingMay 30 - Best of WACV 2025This event has passed