This event is organized by TechSpeak.

Our meetup group is collaborating by promoting this event.

This event is FREE to attend!

In order to attend, please register here:

http://www.techspeakforentrepreneurs.com/how-to-cut-product-development-costs-by-up-to-50/?utm=ideatoipo

(Registrants will receive the login info right before the start of the event.)

There is a difference between releasing code and releasing code effectively and efficiently. That difference is having an efficient process
- a repeatable way to produce consistent results over and over again.

In this webinar, Nelly Yusupova, a CTO with 18 years of experience, a startup tech advisor, and the founder of TechSpeak for Entrepreneurs, will share the process she uses to manage teams and projects to deliver projects on time and on budget.

You will learn:

1) The lean way vs. traditional way of building products

2) Two money saving things you should do before you build anything

3) How to define your MVP properly to reduce the cost and time of development

4) How to see the red flags sooner and minimize mistakes

and more!

Please come with your questions and scenarios.

About the Speaker

Nelly Yusupova is a CTO, with over 18 years experience, leading companies to technical excellence. She is a startup tech advisor, outsourced CTO, and the creator of TechSpeak for Entrepreneurs.

Nelly is on a mission to help entrepreneurs minimize technology mistakes. Through her online master class TechSpeak for Entrepreneurs, she provides the roadmap to successfully manage technology teams and projects.

Just recently included in Fast Company’s, “League of Extraordinary Women”, Nelly has been at the forefront of the women’ s movement online since 1999 and is one of the Wall Street Journal’s “Women on the IT Fast Track”.

Nelly is a speaker and presenter for many organizations and major industries events including: Women’s Enterprise Center, New York Entrepreneurs Business Network, Small Business Summit, BlogHer, Social Media Jungle, Mom 2.0, BlogWorld, and more.

She has been featured in Inc. Magazine, NBC's Today Show, Fast Company, NewsDay.com, O’Reilly, Smart Money, Small Biz, TechRepublic, Women’s Radio and more.

Nelly can be reached at:

nelly@techspeak.co

Silicon Valley AI, Robotics, Machine Learning, and Education

How to Cut Product Development Costs by up to 50%!

Online event

Join us for a virtual event to hear talks from experts on the latest developments in Visual Document AI.

**Date and Location**

Nov 6, 2025
9-11 AM Pacific
Online. **[Register for the Zoom!](https://voxel51.com/events/visual-document-ai-because-a-pixel-is-worth-a-thousand-tokens-november-6-2025)**

**Document AI: A Review of the Latest Models, Tasks and Tools**

In this talk, go through everything document AI: trends, models, tasks, tools! By the end of this talk you will be able to get to building apps based on document models

*About the Speaker*

[Merve Noyan](https://www.linkedin.com/in/merve-noyan-28b1a113a/) works on multimodal AI and computer vision at Hugging Face, and she's the author of the book Vision Language Models on O'Reilly.

**Run Document VLMs in Voxel51 with the VLM Run Plugin — PDF to JSON in Seconds**

The new [VLM Run Plugin](https://docs.voxel51.com/plugins/plugins_ecosystem/vlmrun_voxel51_plugin.html) for Voxel51 enables seamless execution of document vision-language models directly within the Voxel51 environment. This integration transforms complex document workflows — from PDFs and scanned forms to reports — into structured JSON outputs in seconds. By treating documents as images, our approach remains general, scalable, and compatible with any visual model architecture. The plugin connects visual data curation with model inference, empowering teams to run, visualize, and evaluate document understanding models effortlessly. Document AI is now faster, reproducible, and natively integrated into your Voxel51 workflows.

*About the Speaker*

[Dinesh Reddy](https://www.linkedin.com/in/dinesh-reddy-hiring-26b95945/) is a founding team member of VLM Run, where he is helping nurture the platform from a sapling into a robust ecosystem for running and evaluating vision-language models across modalities. Previously, he was a scientist at Amazon AWS AI, working on large-scale machine learning systems for intelligent document understanding and visual AI. He completed his Ph.D. at the Robotics Institute, Carnegie Mellon University, focusing on combining learning-based methods with 3D computer vision for in-the-wild data. His research has been recognized with the Best Paper Award at IEEE IVS 2021 and fellowships from Amazon Go and Qualcomm.

**CommonForms: Automatically Making PDFs Fillable**

Converting static PDFs into fillable forms remains a surprisingly difficult task, even with the best commercial tools available today. We show that with careful dataset curation and model tuning, it is possible to train high-quality form field detectors for under $500. As part of this effort, we introduce CommonForms, a large-scale dataset of nearly half a million curated form images. We also release a family of highly accurate form field detectors, FFDNet-S and FFDNet-L.

*About the Speaker*

[Joe Barrow](https://www.linkedin.com/in/joe-barrow-b2048226/) is a researcher at Pattern Data, specializing in document AI and information extraction. He previously worked at the Adobe Document Intelligence Lab after receiving his PhD from the University of Maryland in 2022.

**Visual Document Retrieval: How to Cluster, Search and Uncover Biases in Document Image Datasets Using Embeddings**

In this talk you'll learn about the task of visual document retrieval, the models which are widely used by the community, and see them in action through the open source [FiftyOne App](https://docs.voxel51.com/) where you'll learn how to use these models to identify groups and clusters of documents, find unique documents, uncover biases in your visual document dataset, and search over your document corpus using natural language.

*About the Speaker*

[Harpreet Sahota](https://www.linkedin.com/in/harpreetsahota204/) is a hacker-in-residence and machine learning engineer with a passion for deep learning and generative AI. He’s got a deep interest in VLMs, Visual Agents, Document AI, and Physical AI.

New York AI, Machine Learning and Computer Vision Meetup

Bill Olik

Abhijeet Rajwade

Fausto Pimentel

Umang G

Steve H.

Leona Rubin

Gregory Morris

Akhil Venkataraju

Nov 6 - Visual Document AI: Because a Pixel is Worth a Thousand Tokens

Join the Meetup to hear talks from experts on cutting-edge topics across AI, ML, and computer vision.

**Date and Location**

Nov 6, 2025
5:30-8:30 PM

[Digital Ag Innovation Lab](https://www.isudigitalag.org/)
3800 University Blvd
Suite 1220
Ames, Iowa 50010

**AI in Use Across Corteva R&D**

Corteva Agriscience is a leading global agricultural solutions company based on deep integration of technology and science. Corteva’s core innovation drivers are proprietary seed products and differentiated crop protection, and has sights set on the next horizon of value from gene editing, biologicals, and advanced decision science.

A central theme of innovation at Corteva is the transformative role of artificial intelligence across the entire R&D pipeline. AI has already delivered an increase in the speed of time to discovery and significantly improved development timelines, and manufacturing productivity. Corteva is expanding its capabilities, from leveraging GenAI for creating regulatory documents to an AI-powered agronomy tool for its sales team.

This focus on innovation underpins a robust pipeline of new seed and crop protection products. The overarching goal is to leverage the latest technological capabilities to accelerate AI-guided discovery and fully embed data-driven solutions from the laboratory to the farm.

*About the Speaker*

[Matt Smalley](https://www.linkedin.com/in/matthew-smalley-99b77339/) serves as the Data Science & Data Engineering Leader for R&D at Corteva Agriscience, where he spearheads the integration of advanced analytics, digital technologies, and scientific research to deliver innovative solutions for farmers worldwide. Matt was raised on a crop and livestock farm in northeast Iowa, an experience that instilled in him a deep appreciation for the challenges and opportunities faced by farmers.

**Machine Learning Advances for 3D Phenotyping**

Artificial intelligence and machine learning are reshaping agricultural research by enabling new approaches to plant phenotyping and precision agriculture. This talk presents recent advances in 3D plant reconstruction using Neural Radiance Fields (NeRFs) and related learning-based methods for generating high-fidelity visualizations of plant growth. These techniques support scalable, real-time analysis of complex plant structures, offering efficient alternatives to traditional, equipment-intensive approaches.

The session will also highlight how immersive Virtual Reality (VR) environments, combined with AI-driven reconstructions, create new opportunities for collaborative research, allowing distributed teams to virtually analyze, monitor, and interact with crops. By integrating machine learning with visualization and interaction technologies, this work advances precision agriculture and lowers barriers to access, providing both researchers and practitioners with flexible, data-driven tools for breeding, monitoring, and decision-making.

*About the Speaker*

[Adarsh Krishnamurthy](https://www.linkedin.com/in/adarsh-krishnamurthy-90a7ab1/) is a professor in the mechanical engineering department at Iowa State University, where he currently leads the Integrated Design and Engineering Analysis (IDEA) lab. His research interests include computer-aided design (CAD), GPU and parallel algorithms, cyber-enabled manufacturing, biomechanics, patient-specific heart modeling, solid mechanics, computational geometry, and ultrasonic non-destructive testing. He is a fellow of the Plant Science Institute at Iowa State University. He was elected as a fellow of the American Society of Mechanical Engineers (ASME) in 2024.

**Beyond the Lab: Real-World Anomaly Detection for Agricultural Computer Vision**

Anomaly detection is transforming manufacturing and surveillance, but what about agriculture? Can AI actually detect plant diseases and pest damage early enough to make a difference?

This talk demonstrates how anomaly detection identifies and localizes crop problems using coffee leaf health as our primary example. We'll start with the foundational theory, then examine how these models detect rust and miner damage in leaf imagery.

The session includes a comprehensive hands-on workflow using the open-source FiftyOne computer vision toolkit, covering dataset curation, patch extraction, model training, and result visualization. You'll gain both theoretical understanding of anomaly detection in computer vision and practical experience applying these techniques to agricultural challenges and other domains.

*About the Speaker*

[Paula Ramos](https://www.linkedin.com/in/paula-ramos-phd/) has a PhD in Computer Vision and Machine Learning, with more than 20 years of experience in the technological field. She has been developing novel integrated engineering technologies, mainly in Computer Vision, robotics, and Machine Learning applied to agriculture, since the early 2000s in Colombia.

**Role of AI Foundation Models in Cyber-Agricultural Systems**

The emergence of multi-modal AI foundation models presents a paradigm shift opportunity for cyber-agricultural systems by enabling the integration of diverse data types such as imagery, text, and time-series signals. This talk will explore the core concepts, recent advancements, and domain-specific challenges in building and applying multi-modal models to agricultural problems. I will focus on a few of our recent success stories, driving progress in this space, with applications ranging from crop monitoring and yield prediction to sustainable crop management. I will also discuss some practical considerations such as data curation, computational requirements, and model evaluation in the context of Ag foundation models.

*About the Speaker*

[Soumik Sarkar](https://www.linkedin.com/in/soumik-sarkar-448b2619/) is the Director of the Translational AI Center at Iowa State University and the Associate Director of the NSF/USDA-NIFA AI Institute for Resilient Agriculture (AIIRA). He is a Professor of Mechanical Engineering and Computer Science, and his research focuses on developing AI and machine learning algorithms for cyber-physical systems with applications to manufacturing, transportation, and agriculture. He co‐authored more than 310 peer-reviewed publications and is a recipient of several prestigious honors, including the NSF CAREER Award, the AFOSR Young Investigator Program (YIP) Award, and the Presidential Early Career Award for Scientists and Engineers (PECASE).

Iowa AI, ML and Computer Vision Meetup

Jimmy Guerrero

hanif

Deepak Nallajerla

Nov 6 - In-Person Iowa AI, ML and Computer Vision Meetup

Iowa State University Research Park

**Organizational Sponsor:**

**Startup House**

**Need a place to stay short term in Silicon Valley?**

**Stay at Startup House in Palo Alto - the heart of Silicon Valley - for as low as $50 a night!**

**-Network, socialize and connect with entrepreneurs all over the world!**
**-Enjoy social events and startup and venture capital-related programming!**
**\- Have access to world class amenities\, iconic tech companies\, top tier venture capital firms\, Stanford University\, etc\. \- all within walking or biking distance\!**

**For more info, send an email message to:**

**siliconvalleystartuphousing@gmail.com**

**Put this in the subject header:**

**Silicon Valley Startup Housing**

This event is 100% online.

Participants can be located anywhere in the world!

This event is FREE to attend!

In order to attend, please register here:

[Silicon Valley Business Networking $Online$ Tickets\, Multiple Dates \| Eventbrite](https://www.eventbrite.com/e/silicon-valley-business-networking-online-tickets-516429563727)

(The login link will be sent via email to Eventbrite registrants right before the start of the event.)

Hurry! Slots are limited!

There's no content or speaker at this event -- just business networking.

Build your business network - face to face (online)!

Join a virtual gathering of professionals from all walks of life from all over the world!

You may meet your next business collaborator, client, employer, employee or friend!

Meet Silicon Valley movers and shakers and influencers from all over the world - tech entrepreneurs, developers, engineers, attorneys, bloggers, academics, thought leaders, community organizers, artists, financiers, and investors!

N﻿etwork, socialize and connect!

For more info on Idea to IPO events, visit:

[www.idea-to-ipo.com](www.idea-to-ipo.com) (our main meetup group among 160 meetup groups globally)

[https://www.youtube.com/@ideatoipo2 ](https://www.youtube.com/@ideatoipo2)(videos of online events)

[@﻿ideatoipo](@%EF%BB%BFideatoipo)

Robert

Silicon Valley Business Networking (Online) 

Hear talks from experts on the latest topics in AI, ML, and computer vision on November 13.

**Date and Location**

Nov 13, 2025
9 AM Pacific
Online. **[Register for the Zoom!](https://voxel51.com/events/women-in-ai-november-13-2025)**

**Copy, Paste, Customize! The Template Approach to AI Engineering**

Most AI implementations fail because teams treat prompt engineering as ad-hoc experimentation rather than systematic software engineering, leading to unreliable systems that don't scale beyond proof-of-concepts. This talk demonstrates engineering practices that enable reliable AI deployment through standardized prompt templates, systematic validation frameworks, and production observability.

Drawing from experience developing fillable prompt templates currently being validated in production environments processing thousands of submissions, I'll share how Infrastructure as Code principles apply to LLM workflows, why evaluation metrics like BLEU scores are critical for production reliability, and how systematic failure analysis prevents costly deployment issues. Attendees will walk away with understanding of practical frameworks for improving AI system reliability and specific strategies for building more consistent, scalable AI implementations.

*About the Speaker*

[Jeanne McClure](https://www.linkedin.com/in/jeannemcclure/) is a postdoctoral scholar at NC State's Data Science and AI Academy with expertise in systematic AI implementation and validation. Her research transforms experimental AI tools into reliable production systems through standardized prompt templates, rigorous testing frameworks, and systematic failure analysis. She holds a PhD in Learning, Design and Technology with additional graduate work in data science.

**Multimodality with Biases: Understand and Evaluate VLMs for Autonomous Driving with FiftyOne**

Do your VLMs really see danger? With FiftyOne, I’ll show you how to understand and evaluate vision-language models for autonomous driving — making risk and bias visible in seconds. We’ll compare models on the same scenes, reveal failures and edge cases, and you’ll see a simple dashboard to decide which data to curate and what to adjust. You’ll leave with a clear, practical, and replicable method to raise the bar for safety.

*About the Speaker*

[Paula Ramos](https://www.linkedin.com/in/paula-ramos-phd/) has a PhD in Computer Vision and Machine Learning, with more than 20 years of experience in the technological field. She has been developing novel integrated engineering technologies, mainly in Computer Vision, robotics, and Machine Learning applied to agriculture, since the early 2000s in Colombia.

**The Heart of Innovation: Women, AI, and the Future of Healthcare**

This session explores how Artificial Intelligence is transforming healthcare by enhancing diagnosis, treatment, and patient outcomes. It highlights the importance of diverse and female perspectives in shaping AI solutions that are ethical, empathetic, and human-centered. We will discuss key applications, current challenges, and the future potential of AI in medicine. It’s a forward-looking conversation about how innovation can build a healthier world.

*About the Speaker*

[Karen Sanchez](https://www.linkedin.com/in/karenyanethsanchez/) is a Postdoctoral Researcher at the Center of Excellence for Generative AI at King Abdullah University of Science and Technology (KAUST), Saudi Arabia. Her research focuses on AI for Science, spanning computer vision, video understanding, and privacy-preserving machine learning. She is also an active advocate for diversity and outreach in AI, contributing to global initiatives that connect researchers and amplify underrepresented voices in technology.

**Language Diffusion Models**

Autoregressive models (ARMs) are widely regarded as the cornerstone of large language models (LLMs). Challenge this notion by introducing LLaDA, a diffusion model trained from scratch under the pre-training and supervised fine-tuning (SFT) paradigm. LLaDA models distributions through a forward data masking process and a reverse process, parameterized by a vanilla Transformer to predict masked tokens.

Optimizing a likelihood bound provides a principled generative approach for probabilistic inference. Across extensive benchmarks, LLaDA demonstrates strong scalability, outperforming self-constructed ARM baselines. Remarkably, LLaDA 8B is competitive with strong LLMs like LLaMA3 8B in in-context learning and, after SFT, exhibits impressive instruction-following abilities in case studies such as multi-turn dialogue.

*About the Speaker*

[Jayita Bhattacharyya](https://www.linkedin.com/in/jayita-bhattacharyya/) is an AI/ML Nerd with a blend of technical speaking & hackathon wizardry! Applying tech to solve real-world problems. The work focus these days is on generative AI. Helping software teams incorporate AI into transforming software engineering.

samia

Anna Gonzalez

Aisha

Mercy Kariuki

Nov 13 - Women in AI

AI, Machine Learning and Computer Vision Meetup Network

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{PRO_NETWORK_NAME} is on Meetup Pro with more than {PRO_MEMBER_COUNT} members across {PRO_GROUP_COUNT} Meetups worldwide. Meetup Pro is the professional tool for organizing and communicating a network of users, partners, contributors and members.

This virtual group is for data scientists, machine learning engineers, and open source enthusiasts.

Every month we’ll bring you two diverse speakers working at the cutting edge of data science, machine learning, AI and computer vision.

This Meetup is sponsored by Voxel51, the lead maintainers of the open source FiftyOne computer vision toolset.

AI, Machine Learning and Computer Vision Meetup Network

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