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Join Voxel51 and NVIDIA as they unveil a breakthrough that’s changing how Physical AI systems are built. In this first-ever demo featuring NVIDIA Omniverse NuRec and NVIDIA Cosmos with FiftyOne, you’ll learn how to create validated, simulation-ready data pipelines—cutting testing costs, eliminating manual data audits, and accelerating development from months to days.

Date and Location

Nov 5, 2025 9:00-10:30 AM Pacific Online. Register for the Zoom

Developing autonomous vehicles and humanoid robots requires rigorous simulations that capture real-world complexity. The critical barrier that keeps teams from achieving success isn’t the simulation engine itself, but the data that powers it.

As Physical AI systems ingest petabytes of multisensor data, converting this raw input into validated, simulation-ready data pipelines remains a hidden bottleneck. A camera-to-LiDAR projection off by a few pixels, timestamps misaligned by a few milliseconds, or inaccurate coordinate systems will cascade into flawed neural reconstructions and synthetic data.

Without a well-orchestrated data pipeline, even the most advanced simulation platforms end up consuming imperfect data, wasting weeks of effort and thousands of dollars in testing and compute costs.

In a first-ever demo featuring NVIDIA Omniverse NuRec and NVIDIA Cosmos with FiftyOne, you’ll discover how to:

• Eliminate manual data audits with an automated workflow that calibrates, aligns, and ensures data integrity across cameras, LiDAR, radar, and other sensors
• Curate and enrich the data for neural reconstructions and synthetic data generation
• Reduce Physical AI testing and QA costs by up to 80%
• Accelerate Physical AI development from months to days

Who should attend:

• Data Engineers, MLOps & ML Engineers working with Physical AI data
• Technical leaders and Managers driving Physical AI projects from prototype to production
• AV/Robotics Researchers building safety-critical apps with cutting-edge tech
• Product & Strategy leaders seeking to accelerate development while reducing infra costs and risks.

About the Speakers

Itai H Zadok is a Senior Product Manager l Autonomous Vehicles Simulation at NVIDIA

Daniel Gural is a Machine Learning Engineer and Evangelist at Voxel51

Join Voxel51 and NVIDIA as they unveil a breakthrough that’s changing how Physical AI systems are built. In this first-ever demo featuring NVIDIA Omniverse NuRec and NVIDIA Cosmos with FiftyOne, you’ll learn how to create validated, simulation-ready data pipelines—cutting testing costs, eliminating manual data audits, and accelerating development from months to days.

Date and Location

Nov 5, 2025 9:00-10:30 AM Pacific Online. Register for the Zoom

Developing autonomous vehicles and humanoid robots requires rigorous simulations that capture real-world complexity. The critical barrier that keeps teams from achieving success isn’t the simulation engine itself, but the data that powers it.

As Physical AI systems ingest petabytes of multisensor data, converting this raw input into validated, simulation-ready data pipelines remains a hidden bottleneck. A camera-to-LiDAR projection off by a few pixels, timestamps misaligned by a few milliseconds, or inaccurate coordinate systems will cascade into flawed neural reconstructions and synthetic data.

Without a well-orchestrated data pipeline, even the most advanced simulation platforms end up consuming imperfect data, wasting weeks of effort and thousands of dollars in testing and compute costs.

In a first-ever demo featuring NVIDIA Omniverse NuRec and NVIDIA Cosmos with FiftyOne, you’ll discover how to:

• Eliminate manual data audits with an automated workflow that calibrates, aligns, and ensures data integrity across cameras, LiDAR, radar, and other sensors
• Curate and enrich the data for neural reconstructions and synthetic data generation
• Reduce Physical AI testing and QA costs by up to 80%
• Accelerate Physical AI development from months to days

Who should attend:

• Data Engineers, MLOps & ML Engineers working with Physical AI data
• Technical leaders and Managers driving Physical AI projects from prototype to production
• AV/Robotics Researchers building safety-critical apps with cutting-edge tech
• Product & Strategy leaders seeking to accelerate development while reducing infra costs and risks.

About the Speakers

Itai H Zadok is a Senior Product Manager l Autonomous Vehicles Simulation at NVIDIA

Daniel Gural is a Machine Learning Engineer and Evangelist at Voxel51

Join Voxel51 and NVIDIA as they unveil a breakthrough that’s changing how Physical AI systems are built. In this first-ever demo featuring NVIDIA Omniverse NuRec and NVIDIA Cosmos with FiftyOne, you’ll learn how to create validated, simulation-ready data pipelines—cutting testing costs, eliminating manual data audits, and accelerating development from months to days.

Date and Location

Nov 5, 2025 9:00-10:30 AM Pacific Online. Register for the Zoom

Developing autonomous vehicles and humanoid robots requires rigorous simulations that capture real-world complexity. The critical barrier that keeps teams from achieving success isn’t the simulation engine itself, but the data that powers it.

As Physical AI systems ingest petabytes of multisensor data, converting this raw input into validated, simulation-ready data pipelines remains a hidden bottleneck. A camera-to-LiDAR projection off by a few pixels, timestamps misaligned by a few milliseconds, or inaccurate coordinate systems will cascade into flawed neural reconstructions and synthetic data.

Without a well-orchestrated data pipeline, even the most advanced simulation platforms end up consuming imperfect data, wasting weeks of effort and thousands of dollars in testing and compute costs.

In a first-ever demo featuring NVIDIA Omniverse NuRec and NVIDIA Cosmos with FiftyOne, you’ll discover how to:

• Eliminate manual data audits with an automated workflow that calibrates, aligns, and ensures data integrity across cameras, LiDAR, radar, and other sensors
• Curate and enrich the data for neural reconstructions and synthetic data generation
• Reduce Physical AI testing and QA costs by up to 80%
• Accelerate Physical AI development from months to days

Who should attend:

• Data Engineers, MLOps & ML Engineers working with Physical AI data
• Technical leaders and Managers driving Physical AI projects from prototype to production
• AV/Robotics Researchers building safety-critical apps with cutting-edge tech
• Product & Strategy leaders seeking to accelerate development while reducing infra costs and risks.

About the Speakers

Itai H Zadok is a Senior Product Manager l Autonomous Vehicles Simulation at NVIDIA

Daniel Gural is a Machine Learning Engineer and Evangelist at Voxel51

Join Voxel51 and NVIDIA as they unveil a breakthrough that’s changing how Physical AI systems are built. In this first-ever demo featuring NVIDIA Omniverse NuRec and NVIDIA Cosmos with FiftyOne, you’ll learn how to create validated, simulation-ready data pipelines—cutting testing costs, eliminating manual data audits, and accelerating development from months to days.

Date and Location

Nov 5, 2025 9:00-10:30 AM Pacific Online. Register for the Zoom

Developing autonomous vehicles and humanoid robots requires rigorous simulations that capture real-world complexity. The critical barrier that keeps teams from achieving success isn’t the simulation engine itself, but the data that powers it.

As Physical AI systems ingest petabytes of multisensor data, converting this raw input into validated, simulation-ready data pipelines remains a hidden bottleneck. A camera-to-LiDAR projection off by a few pixels, timestamps misaligned by a few milliseconds, or inaccurate coordinate systems will cascade into flawed neural reconstructions and synthetic data.

Without a well-orchestrated data pipeline, even the most advanced simulation platforms end up consuming imperfect data, wasting weeks of effort and thousands of dollars in testing and compute costs.

In a first-ever demo featuring NVIDIA Omniverse NuRec and NVIDIA Cosmos with FiftyOne, you’ll discover how to:

• Eliminate manual data audits with an automated workflow that calibrates, aligns, and ensures data integrity across cameras, LiDAR, radar, and other sensors
• Curate and enrich the data for neural reconstructions and synthetic data generation
• Reduce Physical AI testing and QA costs by up to 80%
• Accelerate Physical AI development from months to days

Who should attend:

• Data Engineers, MLOps & ML Engineers working with Physical AI data
• Technical leaders and Managers driving Physical AI projects from prototype to production
• AV/Robotics Researchers building safety-critical apps with cutting-edge tech
• Product & Strategy leaders seeking to accelerate development while reducing infra costs and risks.

About the Speakers

Itai H Zadok is a Senior Product Manager l Autonomous Vehicles Simulation at NVIDIA

Daniel Gural is a Machine Learning Engineer and Evangelist at Voxel51

Join Voxel51 and NVIDIA as they unveil a breakthrough that’s changing how Physical AI systems are built. In this first-ever demo featuring NVIDIA Omniverse NuRec and NVIDIA Cosmos with FiftyOne, you’ll learn how to create validated, simulation-ready data pipelines—cutting testing costs, eliminating manual data audits, and accelerating development from months to days.

Date and Location

Nov 5, 2025 9:00-10:30 AM Pacific Online. Register for the Zoom

Developing autonomous vehicles and humanoid robots requires rigorous simulations that capture real-world complexity. The critical barrier that keeps teams from achieving success isn’t the simulation engine itself, but the data that powers it.

As Physical AI systems ingest petabytes of multisensor data, converting this raw input into validated, simulation-ready data pipelines remains a hidden bottleneck. A camera-to-LiDAR projection off by a few pixels, timestamps misaligned by a few milliseconds, or inaccurate coordinate systems will cascade into flawed neural reconstructions and synthetic data.

Without a well-orchestrated data pipeline, even the most advanced simulation platforms end up consuming imperfect data, wasting weeks of effort and thousands of dollars in testing and compute costs.

In a first-ever demo featuring NVIDIA Omniverse NuRec and NVIDIA Cosmos with FiftyOne, you’ll discover how to:

• Eliminate manual data audits with an automated workflow that calibrates, aligns, and ensures data integrity across cameras, LiDAR, radar, and other sensors
• Curate and enrich the data for neural reconstructions and synthetic data generation
• Reduce Physical AI testing and QA costs by up to 80%
• Accelerate Physical AI development from months to days

Who should attend:

• Data Engineers, MLOps & ML Engineers working with Physical AI data
• Technical leaders and Managers driving Physical AI projects from prototype to production
• AV/Robotics Researchers building safety-critical apps with cutting-edge tech
• Product & Strategy leaders seeking to accelerate development while reducing infra costs and risks.

About the Speakers

Itai H Zadok is a Senior Product Manager l Autonomous Vehicles Simulation at NVIDIA

Daniel Gural is a Machine Learning Engineer and Evangelist at Voxel51

Join Voxel51 and NVIDIA as they unveil a breakthrough that’s changing how Physical AI systems are built. In this first-ever demo featuring NVIDIA Omniverse NuRec and NVIDIA Cosmos with FiftyOne, you’ll learn how to create validated, simulation-ready data pipelines—cutting testing costs, eliminating manual data audits, and accelerating development from months to days.

Date and Location

Nov 5, 2025 9:00-10:30 AM Pacific Online. Register for the Zoom

Developing autonomous vehicles and humanoid robots requires rigorous simulations that capture real-world complexity. The critical barrier that keeps teams from achieving success isn’t the simulation engine itself, but the data that powers it.

As Physical AI systems ingest petabytes of multisensor data, converting this raw input into validated, simulation-ready data pipelines remains a hidden bottleneck. A camera-to-LiDAR projection off by a few pixels, timestamps misaligned by a few milliseconds, or inaccurate coordinate systems will cascade into flawed neural reconstructions and synthetic data.

Without a well-orchestrated data pipeline, even the most advanced simulation platforms end up consuming imperfect data, wasting weeks of effort and thousands of dollars in testing and compute costs.

In a first-ever demo featuring NVIDIA Omniverse NuRec and NVIDIA Cosmos with FiftyOne, you’ll discover how to:

• Eliminate manual data audits with an automated workflow that calibrates, aligns, and ensures data integrity across cameras, LiDAR, radar, and other sensors
• Curate and enrich the data for neural reconstructions and synthetic data generation
• Reduce Physical AI testing and QA costs by up to 80%
• Accelerate Physical AI development from months to days

Who should attend:

• Data Engineers, MLOps & ML Engineers working with Physical AI data
• Technical leaders and Managers driving Physical AI projects from prototype to production
• AV/Robotics Researchers building safety-critical apps with cutting-edge tech
• Product & Strategy leaders seeking to accelerate development while reducing infra costs and risks.

About the Speakers

Itai H Zadok is a Senior Product Manager l Autonomous Vehicles Simulation at NVIDIA

Daniel Gural is a Machine Learning Engineer and Evangelist at Voxel51

Join Voxel51 and NVIDIA as they unveil a breakthrough that’s changing how Physical AI systems are built. In this first-ever demo featuring NVIDIA Omniverse NuRec and NVIDIA Cosmos with FiftyOne, you’ll learn how to create validated, simulation-ready data pipelines—cutting testing costs, eliminating manual data audits, and accelerating development from months to days.

Date and Location

Nov 5, 2025 9:00-10:30 AM Pacific Online. Register for the Zoom

Developing autonomous vehicles and humanoid robots requires rigorous simulations that capture real-world complexity. The critical barrier that keeps teams from achieving success isn’t the simulation engine itself, but the data that powers it.

As Physical AI systems ingest petabytes of multisensor data, converting this raw input into validated, simulation-ready data pipelines remains a hidden bottleneck. A camera-to-LiDAR projection off by a few pixels, timestamps misaligned by a few milliseconds, or inaccurate coordinate systems will cascade into flawed neural reconstructions and synthetic data.

Without a well-orchestrated data pipeline, even the most advanced simulation platforms end up consuming imperfect data, wasting weeks of effort and thousands of dollars in testing and compute costs.

In a first-ever demo featuring NVIDIA Omniverse NuRec and NVIDIA Cosmos with FiftyOne, you’ll discover how to:

• Eliminate manual data audits with an automated workflow that calibrates, aligns, and ensures data integrity across cameras, LiDAR, radar, and other sensors
• Curate and enrich the data for neural reconstructions and synthetic data generation
• Reduce Physical AI testing and QA costs by up to 80%
• Accelerate Physical AI development from months to days

Who should attend:

• Data Engineers, MLOps & ML Engineers working with Physical AI data
• Technical leaders and Managers driving Physical AI projects from prototype to production
• AV/Robotics Researchers building safety-critical apps with cutting-edge tech
• Product & Strategy leaders seeking to accelerate development while reducing infra costs and risks.

About the Speakers

Itai H Zadok is a Senior Product Manager l Autonomous Vehicles Simulation at NVIDIA

Daniel Gural is a Machine Learning Engineer and Evangelist at Voxel51

This session features Richard Lewis, Senior Solution Architect at Matillion, in conversation with Daniel Adams, Global Analytics Manager, from Edmund Optics, as they share how data integration, AI, and cloud technologies transformed technical support and accelerated time to value. Edmund Optics’ team of 50 highly skilled engineers faced a flood of repetitive technical inquiries, averaging 25 minutes per response, across a catalog of 34,000+ components. To streamline support, they partnered with Matillion, Snap Analytics, and Snowflake to build an AI-powered chatbot. Deployed in just 10 weeks, the chatbot delivers instant, consistent answers to common queries, freeing engineers to tackle complex issues and dramatically improving support efficiency.

Let's talk about open source cybersecurity tools and how to make your open source project more secure! Want to be involved? Tell us in our OpenUK Slack community!

6:45 pm: Online event opens in case you want to network online. 6:50 pm: Welcome, code of conduct and warmup!

7:00 pm: Security, Privacy and Authenticity, by Daniel Appelquist 7:20 pm: Securing Agentic: Evolution of Security Posture, by Sal Kimmich 7:40 pm: Using LLMs to discover malware and undisclosed vulnerabilities in OS tools, by Oliver Taylor of Aikido Security. A presentation about a multi-year research project that culminated in better open source security (and open source intel) 8:00pm: Online event wraps up.

We are skipping August for the meetup so see you 17 September to talk how to market your open source project!

This remains an intentionally, interactive Hybrid event, however, the meetup invites are split up and RSVPs for the in-person event are opened three weeks out.

For security purposes, the link for the online version of this event will be added about a week before, so please check back.

Thank you to our sponsors Avanade!

By attending this or any OpenUK event, you are adhering to our Code of Respect and OpenUK's Competition Policy. Please read ahead.

If you would like to hear more about OpenUK's other events, you can join our Newsletter. After attending, look out for an email with an invite to our burgeoning Slack community as a way to keep in touch and support each other between activities.

Wednesday 9th July for our next meetup. Let's talk about open source cybersecurity tools and how to make your open source project more secure!

6:30 pm: Arrive on time, grab a bev, a slice and a chat. Scope out our swag table (bring pieces to contribute or trade!) 6:50 pm: Welcome, code of conduct and warmup!

7:00 pm: Security, Privacy and Authenticity, by Daniel Appelquist 7:20 pm: Securing Agentic: Evolution of Security Posture, by Sal Kimmich 7:40 pm: Using LLMs to discover malware and undisclosed vulnerabilities in OS tools, by Oliver Taylor of Aikido Security. A presentation about a multi-year research project that culminated in better open source security (and open source intel) 8:00pm: NPM Imposters Game, a fast, team-based game where players must spot malicious NPM packages hiding in plain sight. A game for in-person attendees only

8:45 pm: Clean up and leave.

We are skipping August for the meetup so see you 17 September to talk how to market your open source project!

This remains an interactive Hybrid event, however, the meetup invites are split up and RSVPs for in-person are opened three weeks out. Please only sign up for this event if you can definitely attend in person. We welcome everyone to signup for the online version even as a save the date!

Please remember to bring your I.D. if you are attending in person, as it is required to access the venue. Note the venue does not permit e-scooters or bicycles within the building. Thank you to our sponsors Avanade for providing this great space and yummy pizza!

The link for the online version of this event will be added about a week before, so please check back.

By attending this or any OpenUK event, you are adhering to our Code of Respect and OpenUK's Competition Policy. Please read ahead.

If you would like to hear more about OpenUK's other events, you can join our Newsletter. After attending, look out for an email with an invite to our burgeoning Slack community as a way to keep in touch and support each other between activities.

Artificial Intelligence is rapidly reshaping how we engage with information and knowledge. Recent advancements in AI, such as OpenAI’s Deep Research and Google Gemini, have sparked widespread excitement—and uncertainty—by promising to accomplish in minutes what traditionally takes weeks or months of human effort.

With premium AI tools often priced at hundreds of dollars per month, many AI enthusiasts and professionals are exploring powerful, affordable alternatives in open-source ecosystems.

But beyond accessibility, critical questions remain: Can AI genuinely match or exceed human judgment, intuition, and nuanced decision-making? How can individuals across all fields leverage AI to enhance their workflows and productivity rather than compete with these intelligent systems?

Join Dr. Daniel Barulli in an engaging event designed to demystify and illuminate the rapidly evolving AI landscape. Dr. Barulli will showcase cutting-edge tools and illustrate the transformative concept of agentic architecture, which amplifies the capabilities of AI models through strategic task automation and advanced reasoning techniques.

In this interactive session, you will:

• Gain insights into how cutting-edge AI tools work and their underlying technologies.
• Understand what "agentic architecture" means and how it can dramatically improve AI performance.
• Learn practical methods to evaluate and optimize AI-generated results.
• Discover how to integrate these powerful tools into your personal or professional workflow effectively and affordably.

Whether you're new to AI, a seasoned professional, or simply curious about the future of technology, this talk promises valuable insights and practical strategies for harnessing AI to elevate your capabilities.

We're delighted to announce our next meetup will be hosted by Monzo.

RSVP opens on the Monday 24th March (2.5 weeks before the event), this is to reduce our drop-off numbers. Set a reminder to not miss out, this event will be over subscribed!

Agenda: 6:00pm: Doors open, networking, food, drinks. 7:00pm: Talks start! 8:00pm: Talks finish, Q&A. 8:30pm: Further drinks and networking - Drinks sponsored by Omni

Speakers:

• Analytics Engineering - Discipline or Buzzword? Measuring real impact - Daniel McNamara Head of Analytics Engineering @ Taptap Send
• DuckDB: your new favourite database - Bill Wallis Software Engineer @ Sainsbury's

We are always looking to improve the event and get new ideas for talks, if you could please fill out a feedback form, this will help us continue to improve!

London Analytics Engineering Meetup is focused on discussing and spreading best practices in the growing field of analytics engineering. Whether you've set up the "Modern Data Stack" many times over or are brand new to tools like dbt, Looker, Snowflake, Bigquery and more, this is the meetup for you.

No-Show Policy:

• If you miss 2 consecutive events or 2 out of 3 events, you wont be able to attend the next event. We hope you understand this is to keep things fair for venues and other attendees.