talk-data.com

Everyone is talking about agents; if you don't have agents already in production you are hopelessly behind. Wasn't vibe coding supposed to take care of everyone's computer problems? How am I behind if AI takes care of everything for me now? Maybe I need an MCP and then I'll be caught up. Wouldn't it be nice if there was a tool where I could just say what I wanted the agent to do and it would vibe it out for me? And then maybe I could tell it what I wanted the app to look like, and it would vibe that out too. That day is today, that tool is called gofannon.

In this talk we'll discuss our motivations for making gofannon, lessons learned that we've incorporated from prior iterations, and a (possibly live) demo where we'll go from idea to deployed app. See you there!

About the presenters Trevor Grant (IBM)

Andrew Musselman is a seasoned technology leader with 20+ years of experience building scalable platforms and data-driven solutions. He is a builder with business focus, and has helped companies realize multiple millions of annual savings and revenue through innovation and modernization. Andrew has been an Apache Software Foundation contributor for over 12 years, and brings together the community-driven value of open source work with concrete business results, ranging from data engineering and platform development to cutting-edge AI solutions.

About the AI Alliance The AI Alliance is an international community of researchers, developers and organizational leaders committed to support and enhance open innovation across the AI technology landscape to accelerate progress, improve safety, security and trust in AI, and maximize benefits to people and society everywhere. Members of the AI Alliance believe that open innovation is essential to develop and achieve safe and responsible AI that benefit society rather than benefit a select few big players.

Join the community Sign up for the AI Alliance newsletter (check the website footer) and join our new AI Alliance Discord.

Everyone is talking about agents; if you don't have agents already in production you are hopelessly behind. Wasn't vibe coding supposed to take care of everyone's computer problems? How am I behind if AI takes care of everything for me now? Maybe I need an MCP and then I'll be caught up. Wouldn't it be nice if there was a tool where I could just say what I wanted the agent to do and it would vibe it out for me? And then maybe I could tell it what I wanted the app to look like, and it would vibe that out too. That day is today, that tool is called gofannon.

In this talk we'll discuss our motivations for making gofannon, lessons learned that we've incorporated from prior iterations, and a (possibly live) demo where we'll go from idea to deployed app. See you there!

About the presenters Trevor Grant (IBM)

Andrew Musselman is a seasoned technology leader with 20+ years of experience building scalable platforms and data-driven solutions. He is a builder with business focus, and has helped companies realize multiple millions of annual savings and revenue through innovation and modernization. Andrew has been an Apache Software Foundation contributor for over 12 years, and brings together the community-driven value of open source work with concrete business results, ranging from data engineering and platform development to cutting-edge AI solutions.

About the AI Alliance The AI Alliance is an international community of researchers, developers and organizational leaders committed to support and enhance open innovation across the AI technology landscape to accelerate progress, improve safety, security and trust in AI, and maximize benefits to people and society everywhere. Members of the AI Alliance believe that open innovation is essential to develop and achieve safe and responsible AI that benefit society rather than benefit a select few big players.

Join the community Sign up for the AI Alliance newsletter (check the website footer) and join our new AI Alliance Discord.

Everyone is talking about agents; if you don't have agents already in production you are hopelessly behind. Wasn't vibe coding supposed to take care of everyone's computer problems? How am I behind if AI takes care of everything for me now? Maybe I need an MCP and then I'll be caught up. Wouldn't it be nice if there was a tool where I could just say what I wanted the agent to do and it would vibe it out for me? And then maybe I could tell it what I wanted the app to look like, and it would vibe that out too. That day is today, that tool is called gofannon.

In this talk we'll discuss our motivations for making gofannon, lessons learned that we've incorporated from prior iterations, and a (possibly live) demo where we'll go from idea to deployed app. See you there!

About the presenters Trevor Grant (IBM)

Andrew Musselman is a seasoned technology leader with 20+ years of experience building scalable platforms and data-driven solutions. He is a builder with business focus, and has helped companies realize multiple millions of annual savings and revenue through innovation and modernization. Andrew has been an Apache Software Foundation contributor for over 12 years, and brings together the community-driven value of open source work with concrete business results, ranging from data engineering and platform development to cutting-edge AI solutions.

About the AI Alliance The AI Alliance is an international community of researchers, developers and organizational leaders committed to support and enhance open innovation across the AI technology landscape to accelerate progress, improve safety, security and trust in AI, and maximize benefits to people and society everywhere. Members of the AI Alliance believe that open innovation is essential to develop and achieve safe and responsible AI that benefit society rather than benefit a select few big players.

Join the community Sign up for the AI Alliance newsletter (check the website footer) and join our new AI Alliance Discord.

Everyone is talking about agents; if you don't have agents already in production you are hopelessly behind. Wasn't vibe coding supposed to take care of everyone's computer problems? How am I behind if AI takes care of everything for me now? Maybe I need an MCP and then I'll be caught up. Wouldn't it be nice if there was a tool where I could just say what I wanted the agent to do and it would vibe it out for me? And then maybe I could tell it what I wanted the app to look like, and it would vibe that out too. That day is today, that tool is called gofannon.

In this talk we'll discuss our motivations for making gofannon, lessons learned that we've incorporated from prior iterations, and a (possibly live) demo where we'll go from idea to deployed app. See you there!

About the presenters Trevor Grant (IBM)

Andrew Musselman is a seasoned technology leader with 20+ years of experience building scalable platforms and data-driven solutions. He is a builder with business focus, and has helped companies realize multiple millions of annual savings and revenue through innovation and modernization. Andrew has been an Apache Software Foundation contributor for over 12 years, and brings together the community-driven value of open source work with concrete business results, ranging from data engineering and platform development to cutting-edge AI solutions.

About the AI Alliance The AI Alliance is an international community of researchers, developers and organizational leaders committed to support and enhance open innovation across the AI technology landscape to accelerate progress, improve safety, security and trust in AI, and maximize benefits to people and society everywhere. Members of the AI Alliance believe that open innovation is essential to develop and achieve safe and responsible AI that benefit society rather than benefit a select few big players.

Join the community Sign up for the AI Alliance newsletter (check the website footer) and join our new AI Alliance Discord.

Everyone is talking about agents; if you don't have agents already in production you are hopelessly behind. Wasn't vibe coding supposed to take care of everyone's computer problems? How am I behind if AI takes care of everything for me now? Maybe I need an MCP and then I'll be caught up. Wouldn't it be nice if there was a tool where I could just say what I wanted the agent to do and it would vibe it out for me? And then maybe I could tell it what I wanted the app to look like, and it would vibe that out too. That day is today, that tool is called gofannon.

In this talk we'll discuss our motivations for making gofannon, lessons learned that we've incorporated from prior iterations, and a (possibly live) demo where we'll go from idea to deployed app. See you there!

About the presenters Trevor Grant (IBM)

Andrew Musselman is a seasoned technology leader with 20+ years of experience building scalable platforms and data-driven solutions. He is a builder with business focus, and has helped companies realize multiple millions of annual savings and revenue through innovation and modernization. Andrew has been an Apache Software Foundation contributor for over 12 years, and brings together the community-driven value of open source work with concrete business results, ranging from data engineering and platform development to cutting-edge AI solutions.

About the AI Alliance The AI Alliance is an international community of researchers, developers and organizational leaders committed to support and enhance open innovation across the AI technology landscape to accelerate progress, improve safety, security and trust in AI, and maximize benefits to people and society everywhere. Members of the AI Alliance believe that open innovation is essential to develop and achieve safe and responsible AI that benefit society rather than benefit a select few big players.

Join the community Sign up for the AI Alliance newsletter (check the website footer) and join our new AI Alliance Discord.

Everyone is talking about agents; if you don't have agents already in production you are hopelessly behind. Wasn't vibe coding supposed to take care of everyone's computer problems? How am I behind if AI takes care of everything for me now? Maybe I need an MCP and then I'll be caught up. Wouldn't it be nice if there was a tool where I could just say what I wanted the agent to do and it would vibe it out for me? And then maybe I could tell it what I wanted the app to look like, and it would vibe that out too. That day is today, that tool is called gofannon.

In this talk we'll discuss our motivations for making gofannon, lessons learned that we've incorporated from prior iterations, and a (possibly live) demo where we'll go from idea to deployed app. See you there!

About the presenters Trevor Grant (IBM)

Andrew Musselman is a seasoned technology leader with 20+ years of experience building scalable platforms and data-driven solutions. He is a builder with business focus, and has helped companies realize multiple millions of annual savings and revenue through innovation and modernization. Andrew has been an Apache Software Foundation contributor for over 12 years, and brings together the community-driven value of open source work with concrete business results, ranging from data engineering and platform development to cutting-edge AI solutions.

About the AI Alliance The AI Alliance is an international community of researchers, developers and organizational leaders committed to support and enhance open innovation across the AI technology landscape to accelerate progress, improve safety, security and trust in AI, and maximize benefits to people and society everywhere. Members of the AI Alliance believe that open innovation is essential to develop and achieve safe and responsible AI that benefit society rather than benefit a select few big players.

Join the community Sign up for the AI Alliance newsletter (check the website footer) and join our new AI Alliance Discord.

Everyone is talking about agents; if you don't have agents already in production you are hopelessly behind. Wasn't vibe coding supposed to take care of everyone's computer problems? How am I behind if AI takes care of everything for me now? Maybe I need an MCP and then I'll be caught up. Wouldn't it be nice if there was a tool where I could just say what I wanted the agent to do and it would vibe it out for me? And then maybe I could tell it what I wanted the app to look like, and it would vibe that out too. That day is today, that tool is called gofannon.

In this talk we'll discuss our motivations for making gofannon, lessons learned that we've incorporated from prior iterations, and a (possibly live) demo where we'll go from idea to deployed app. See you there!

About the presenters Trevor Grant (IBM)

Andrew Musselman is a seasoned technology leader with 20+ years of experience building scalable platforms and data-driven solutions. He is a builder with business focus, and has helped companies realize multiple millions of annual savings and revenue through innovation and modernization. Andrew has been an Apache Software Foundation contributor for over 12 years, and brings together the community-driven value of open source work with concrete business results, ranging from data engineering and platform development to cutting-edge AI solutions.

About the AI Alliance The AI Alliance is an international community of researchers, developers and organizational leaders committed to support and enhance open innovation across the AI technology landscape to accelerate progress, improve safety, security and trust in AI, and maximize benefits to people and society everywhere. Members of the AI Alliance believe that open innovation is essential to develop and achieve safe and responsible AI that benefit society rather than benefit a select few big players.

Join the community Sign up for the AI Alliance newsletter (check the website footer) and join our new AI Alliance Discord.

Deep Research architectures have become increasingly popular over the past three months as users want more complex tasks to be handled by LLMs. The LastMile AI team has gone through a journey to understand what core components are needed for a Deep Research Agent and what qualities enable it to be ready for production. We'll be sharing the core architecture for a Deep Research Agent and how these components influence the behavior of the agent.

About the speaker Andrew Hoh is a co-founder and the CPO of LastMile AI. Previously, he was a Product Leader at Meta AI, driving product for their AI Platform. Previously, he was the Product Manager for the Machine Learning Infrastructure team at Airbnb and a founding team member of Azure Cosmos DB, Microsoft Azure's distributed NoSQL database.

Resources Check out this recent post on the AI Alliance blog: Building a Deep Research Agent Using MCP-Agent

About the AI Alliance The AI Alliance is an international community of researchers, developers and organizational leaders committed to support and enhance open innovation across the AI technology landscape to accelerate progress, improve safety, security and trust in AI, and maximize benefits to people and society everywhere. Members of the AI Alliance believe that open innovation is essential to develop and achieve safe and responsible AI that benefit society rather than benefit a select few big players.

Join the community Sign up for the AI Alliance newsletter (check the website footer) and join our new AI Alliance Discord.

Deep Research architectures have become increasingly popular over the past three months as users want more complex tasks to be handled by LLMs. The LastMile AI team has gone through a journey to understand what core components are needed for a Deep Research Agent and what qualities enable it to be ready for production. We'll be sharing the core architecture for a Deep Research Agent and how these components influence the behavior of the agent.

About the speaker Andrew Hoh is a co-founder and the CPO of LastMile AI. Previously, he was a Product Leader at Meta AI, driving product for their AI Platform. Previously, he was the Product Manager for the Machine Learning Infrastructure team at Airbnb and a founding team member of Azure Cosmos DB, Microsoft Azure's distributed NoSQL database.

Resources Check out this recent post on the AI Alliance blog: Building a Deep Research Agent Using MCP-Agent

About the AI Alliance The AI Alliance is an international community of researchers, developers and organizational leaders committed to support and enhance open innovation across the AI technology landscape to accelerate progress, improve safety, security and trust in AI, and maximize benefits to people and society everywhere. Members of the AI Alliance believe that open innovation is essential to develop and achieve safe and responsible AI that benefit society rather than benefit a select few big players.

Join the community Sign up for the AI Alliance newsletter (check the website footer) and join our new AI Alliance Discord.

Deep Research architectures have become increasingly popular over the past three months as users want more complex tasks to be handled by LLMs. The LastMile AI team has gone through a journey to understand what core components are needed for a Deep Research Agent and what qualities enable it to be ready for production. We'll be sharing the core architecture for a Deep Research Agent and how these components influence the behavior of the agent.

About the speaker Andrew Hoh is a co-founder and the CPO of LastMile AI. Previously, he was a Product Leader at Meta AI, driving product for their AI Platform. Previously, he was the Product Manager for the Machine Learning Infrastructure team at Airbnb and a founding team member of Azure Cosmos DB, Microsoft Azure's distributed NoSQL database.

Resources Check out this recent post on the AI Alliance blog: Building a Deep Research Agent Using MCP-Agent

About the AI Alliance The AI Alliance is an international community of researchers, developers and organizational leaders committed to support and enhance open innovation across the AI technology landscape to accelerate progress, improve safety, security and trust in AI, and maximize benefits to people and society everywhere. Members of the AI Alliance believe that open innovation is essential to develop and achieve safe and responsible AI that benefit society rather than benefit a select few big players.

Join the community Sign up for the AI Alliance newsletter (check the website footer) and join our new AI Alliance Discord.

Deep Research architectures have become increasingly popular over the past three months as users want more complex tasks to be handled by LLMs. The LastMile AI team has gone through a journey to understand what core components are needed for a Deep Research Agent and what qualities enable it to be ready for production. We'll be sharing the core architecture for a Deep Research Agent and how these components influence the behavior of the agent.

About the speaker Andrew Hoh is a co-founder and the CPO of LastMile AI. Previously, he was a Product Leader at Meta AI, driving product for their AI Platform. Previously, he was the Product Manager for the Machine Learning Infrastructure team at Airbnb and a founding team member of Azure Cosmos DB, Microsoft Azure's distributed NoSQL database.

Resources Check out this recent post on the AI Alliance blog: Building a Deep Research Agent Using MCP-Agent

About the AI Alliance The AI Alliance is an international community of researchers, developers and organizational leaders committed to support and enhance open innovation across the AI technology landscape to accelerate progress, improve safety, security and trust in AI, and maximize benefits to people and society everywhere. Members of the AI Alliance believe that open innovation is essential to develop and achieve safe and responsible AI that benefit society rather than benefit a select few big players.

Join the community Sign up for the AI Alliance newsletter (check the website footer) and join our new AI Alliance Discord.

Deep Research architectures have become increasingly popular over the past three months as users want more complex tasks to be handled by LLMs. The LastMile AI team has gone through a journey to understand what core components are needed for a Deep Research Agent and what qualities enable it to be ready for production. We'll be sharing the core architecture for a Deep Research Agent and how these components influence the behavior of the agent.

About the speaker Andrew Hoh is a co-founder and the CPO of LastMile AI. Previously, he was a Product Leader at Meta AI, driving product for their AI Platform. Previously, he was the Product Manager for the Machine Learning Infrastructure team at Airbnb and a founding team member of Azure Cosmos DB, Microsoft Azure's distributed NoSQL database.

Resources Check out this recent post on the AI Alliance blog: Building a Deep Research Agent Using MCP-Agent

About the AI Alliance The AI Alliance is an international community of researchers, developers and organizational leaders committed to support and enhance open innovation across the AI technology landscape to accelerate progress, improve safety, security and trust in AI, and maximize benefits to people and society everywhere. Members of the AI Alliance believe that open innovation is essential to develop and achieve safe and responsible AI that benefit society rather than benefit a select few big players.

Join the community Sign up for the AI Alliance newsletter (check the website footer) and join our new AI Alliance Discord.

Deep Research architectures have become increasingly popular over the past three months as users want more complex tasks to be handled by LLMs. The LastMile AI team has gone through a journey to understand what core components are needed for a Deep Research Agent and what qualities enable it to be ready for production. We'll be sharing the core architecture for a Deep Research Agent and how these components influence the behavior of the agent.

About the speaker Andrew Hoh is a co-founder and the CPO of LastMile AI. Previously, he was a Product Leader at Meta AI, driving product for their AI Platform. Previously, he was the Product Manager for the Machine Learning Infrastructure team at Airbnb and a founding team member of Azure Cosmos DB, Microsoft Azure's distributed NoSQL database.

Resources Check out this recent post on the AI Alliance blog: Building a Deep Research Agent Using MCP-Agent

About the AI Alliance The AI Alliance is an international community of researchers, developers and organizational leaders committed to support and enhance open innovation across the AI technology landscape to accelerate progress, improve safety, security and trust in AI, and maximize benefits to people and society everywhere. Members of the AI Alliance believe that open innovation is essential to develop and achieve safe and responsible AI that benefit society rather than benefit a select few big players.

Join the community Sign up for the AI Alliance newsletter (check the website footer) and join our new AI Alliance Discord.

Deep Research architectures have become increasingly popular over the past three months as users want more complex tasks to be handled by LLMs. The LastMile AI team has gone through a journey to understand what core components are needed for a Deep Research Agent and what qualities enable it to be ready for production. We'll be sharing the core architecture for a Deep Research Agent and how these components influence the behavior of the agent.

About the speaker Andrew Hoh is a co-founder and the CPO of LastMile AI. Previously, he was a Product Leader at Meta AI, driving product for their AI Platform. Previously, he was the Product Manager for the Machine Learning Infrastructure team at Airbnb and a founding team member of Azure Cosmos DB, Microsoft Azure's distributed NoSQL database.

Resources Check out this recent post on the AI Alliance blog: Building a Deep Research Agent Using MCP-Agent

About the AI Alliance The AI Alliance is an international community of researchers, developers and organizational leaders committed to support and enhance open innovation across the AI technology landscape to accelerate progress, improve safety, security and trust in AI, and maximize benefits to people and society everywhere. Members of the AI Alliance believe that open innovation is essential to develop and achieve safe and responsible AI that benefit society rather than benefit a select few big players.

Join the community Sign up for the AI Alliance newsletter (check the website footer) and join our new AI Alliance Discord.

**Update** New Zoom link: https://us02web.zoom.us/j/86507616088?pwd=H2coH9XjPnTtgb3F5DTbDwDavzuRbb.1

Hosts: Andrew Sharp, Principal Consultant/Data Governance, Oakland Group Amy Raygada, Senior Data Product Manager, Swiss Marketplace Wannes Rosiers, Product Manager and Data Enthusiast, Conveyor

Join us for an engaging and informative Data Mesh Meetup where we delve into the evolving landscape of data management with a focus on “Data Catalogs vs. Data Product Catalogs.” In this session, we will explore the critical roles these catalogs play in the data ecosystem and their impact on driving data democratization and self-service analytics.

Data catalogs have long been a staple in organizing and governing enterprise data assets, providing metadata management, data lineage, and search functionalities. However, with the advent of the data mesh paradigm, the concept of data product catalogs has emerged, emphasizing the need to treat data as a product with clear ownership, discoverability, and usability.

Our expert speakers will provide insights into: • The fundamental differences between traditional data catalogs and data product catalogs. • How data product catalogs align with the principles of data mesh. • Real-world case studies highlighting the implementation and benefits of data product catalogs. • Best practices for transitioning from data catalogs to data product catalogs within a data mesh architecture.

Whether you are a data engineer, architect, or business leader, this meetup will equip you with the knowledge to navigate the complexities of modern data management and leverage data catalogs to unlock the full potential of your data assets. Join us to network with like-minded professionals and stay at the forefront of data innovation.

We are welcoming you to join 31st edition of PyData Trójmiasto meetup!

• When: 18th of June, at 18:00

• Where: Room 002, Building B, Gdańsk Science-Technology Park.

• Registration: event is free to join, just let us know you're coming by RSVP on meetup to estimate pizzas.

Agenda: 18:00 - 18:05 - Meeting boarding 18:05 - 18:10 - A few words about PyData 18:10 - 18:50 - Divide and Conquer in the LLM world - LLM agents by Sebastian Chwilczyński 18:50 - 19:35 - Bridging LLM and Databases: Lessons learned in production by Mateusz Hordyński 19:35 - Pizza & Networking

About Divide and Conquer in the LLM world Andrew Ng said that AI agent workflows will drive massive AI progress this year, and all AI practitioners should pay attention to this trend. I'm the last one to undermine his words, so let's dive deep into agentic systems. In this presentation, we are going to explore the four most fundamental design patterns for Agent Systems: Reflection, Tools Use, Planning, and Collaboration. Along the way, we'll learn some best practices and examine recent use cases to see these principles in action.

About Sebastian Sebastian Chwilczynski is a Machine Learning Engineer at deepsense.ai. He graduated in Artificial Intelligence from Poznań University of Technology. Recently, in his professional work, he's been mostly focused on making LLM systems more robust. Good research before the implementation is even more important than a morning coffee.

About Bridging LLM and Databases: Lessons learned in production Prepare to dive into the exciting world of Large Language Models (LLMs) and structured data sources. In this session, we'll shed light on how to link LLMs to relational databases. We'll explore case studies and share different tried-and-tested approaches to achieve this. You'll understand the benefits, the obstacles, and what's on the horizon for integrating LLMs and structured data. Whether you're a seasoned professional in data science or just starting out, this talk has something to help you improve your skills in working with LLMs and external structured data sources.

About Mateusz I'm a software engineer who specializes in creating big data architectures for both cloud and on-premises setups. Currently, I'm a Technical Leader at deepsense.ai, where I design generative AI applications and build data pipelines to support them. I'm also the lead maintainer of the open-source project db-ally. Outside of work, I try to live the digital nomad lifestyle, which has taught me how to work remotely from some pretty weird office setups.

We are deeply thankful to Gdańsk Science-Technology Park for hosting us. Vemco Sp. z o.o. for sponsoring tasty pizzas! And to JetBrains for the possibility to give away a few licenses for their tools - in exchange of interesting questions!;)

See you at PyData!

Please join us on June 5th to listen to the topic: An Engineers Guide To Realtime Data Handling And Analytics

What \~ Toronto Data Professionals Community (Virtual) When \~ Wednesday, 5th June, 2024

Agenda:

• 12:00 PM Networking and Introduction
• 12:15 PM Topic: An Engineers Guide To Realtime Data Handling And Analytics with Paul Andrew
• 1:30 PM End

Where: Online via Microsoft team

Session Details: The velocity of data is getting faster across many industries, fueled by the business demand to gain insights and value from sources in near real-time. This necessity is then allowing decision makers to pivot and ultimately stay ahead of the competition. Furthermore, the growth of the internet of things and ‘smart’ devices now means the volume of that high velocity data has exploded. Meeting this demand requires new concepts and new designs for data/solution architects, with high throughput ingestion endpoints and query stream tools that can perform aggregations ‘on the fly’.

In this session, we will address the above head on. Discussing and designing architectures that can scale and burst for high throughput events. Querying using both SQL and KQL to blend stream and batch data feeds for downstream reporting.

As a platform, we’ll use Azure Event Hub and Azure Stream Analytics to ingest and handle that initial data stream. Before applying the same patterns to other resources in Microsoft Fabric and Azure Data Explorer. Understanding the patterns to apply as an architect vs the tooling available for delivery.

Speaker’s Bio: Paul (AKA @mrpaulandrew) is the Co-Founder & CTO of Cloud Formations, a specialist data consultancy based in the UK. With nearly 20 years’ experience designing and delivering Microsoft data architectures, Paul leads a passionate team of engineers, supporting businesses small and large with scalable cloud platforms. Business value delivered through data insights. Over the years, Paul has covered the breadth and depth of design patterns and industry leading concepts, including Lambda, Kappa, Delta Lake, Data Mesh and Data Fabric.

Paul is also a Microsoft Data Platform MVP, director for the Data Relay community conference, East Midlands user group leader, book author and mentor. In addition to the day job(s), Paul is a father of three, husband, foodie, runner, blood donor, geek, Lego, and Star Wars fan! Lastly, Paul confesses to enjoying a Ramstein playlist when given half a chance to do some coding for a customer project.

Join us for our monthly Data Mesh Learning Roundtable. This is an interactive roundtable that encourages participant interaction. We will divide the group into break-out sessions moderated by our four hosts:

Andrew Sharp, Principal Consultant/Data Governance, Oakland Group Amy Raygada, Senior Data Product Manager, Swiss Marketplace Karin Håkansson, Data Governance/Data Mesh Lead Consultant Wannes Rosiers, Product Manager and Data Enthusiast, Conveyor

with special guest Paolo Platter, CTO - Co-founder at Agile Lab

Navigating the Data Mesh: Designing Data Products for Success

In today's data-driven landscape, organizations are increasingly adopting the data mesh paradigm to manage and leverage their vast data resources effectively. However, navigating the complexities of data product design within a data mesh framework requires a nuanced understanding of both technical and organizational dynamics.

Join us for a dynamic roundtable discussion where industry experts, thought leaders, and practitioners converge to explore the intricacies of designing data products within a data mesh architecture.

Whether you're a seasoned data architect, a data engineer grappling with complex infrastructure challenges, or a business leader seeking to harness the power of data for strategic advantage, this roundtable promises to offer valuable insights and actionable strategies for designing data products within a data mesh framework.

When March 21, 2024 – 10:00 AM Pacific

Where Virtual / Zoom - https://voxel51.com/computer-vision-events/march-2024-ai-machine-learning-data-science-meetup/

Visual Anagrams: Generating Multi-View Optical Illusions with Diffusion Models

Images that change their appearance under a transformation, such as a rotation or a flip, have long fascinated students of perception, from Salvador Dalli to M. C. Escher. The appeal of these multi-view optical illusions lies partly in the challenge of arranging visual elements such that they may be understood in multiple different ways. Creating these illusions requires accurately modeling—and then subverting—visual perception. We propose a simple, zero-shot method for obtaining these illusions from off-the-shelf text-to-image diffusion models. During the reverse diffusion process, we estimate the noise from different views of a noisy image. We then combine these noise estimates together and denoise the image. A theoretical analysis suggests that this method works precisely for views that can be written as orthogonal transformations. An important special case of these transformations are permutations of an image's pixels, which we use to create a variety of "anagram" illusions, such as jigsaw puzzles that can be solved in two different ways.

Speaker: Andrew Owens is an assistant professor at The University of Michigan in the department of Electrical Engineering and Computer Science. Prior to that, he was a postdoctoral scholar at UC Berkeley. He received a Ph.D. in Electrical Engineering and Computer Science from MIT in 2016. He is a recipient of a Computer Vision and Pattern Recognition (CVPR) Best Paper Honorable Mention Award, and a Microsoft Research Ph.D. Fellowship.

Omnidirectional Computer Vision

Omnidirectional cameras are a different camera modality than what we are typically used to, where we sacrifice nice geometry for significantly larger fields-of-view. Ciarán will discuss Omnidirectional cameras, how to represent them geometrically, optical effects of using omnidirectional cameras, neural networks on omnidirectional cameras, and applications that use omnidirectional cameras.

Speaker: Ciaran Eising is an Associate Professor of Artificial Intelligence and Computer Vision at the University of Limerick, Ireland and co-founder of the D2iCE Research Group. Prior to joining the University of Limerick, Ciarán was a Senior Expert of Computer Vision (director level) at Valeo, designing omnidirectional vision algorithms for low-speed vehicle automation.

Illuminating the Underground World with Multimodal Algorithms

Dive deep into the future of underground exploration! This talk introduces a groundbreaking approach that leverages the power of multimodal algorithms, combining advanced computer vision techniques, SLAM algorithms, sensor metadata, and GIS data. By integrating diverse data streams, we unlock unprecedented levels of detail and accuracy in underground inspections, paving the way for safer, more efficient, and insightful subterranean analyses. About the Speaker

Speaker: Adonaí Vera is a Machine Learning Engineer with expertise in computer vision and AI algorithms, specializing in AI solutions for underground inspections using TensorFlow and OpenCV. Recognized by Google as a top TensorFlow developer in Colombia, he is also the founder of a company focused on AI innovations and currently contributes his expertise to Subterra AI.

The Role of AI in Fixing Hiring

From writing job descriptions, to sourcing candidates, to interviews and evaluation – our current hiring practices are often rife with human bias. Even when such bias is unconscious, it can result in expensive mis-hires. This talk explores the types of biases and the pivotal role of AI in mitigating them. We will discuss the common sources of bias in hiring, the current AI landscape that attempts to address these issues and further opportunities.

Speaker: Saurav Pandit is a seasoned AI leader with expertise in natural language understanding, search and language models. He is on the advisory board of AI 2030, an initiative that promotes AI for good.

Don’t Forget

• Voxel51 will make a donation on behalf of the Meetup members to the charity that gets the most votes this month.
• Can’t make the date and time? No problem! Just make sure to register here so we can send you links to the playbacks.

When March 21, 2024 – 10:00 AM Pacific

Where Virtual / Zoom - https://voxel51.com/computer-vision-events/march-2024-ai-machine-learning-data-science-meetup/

Visual Anagrams: Generating Multi-View Optical Illusions with Diffusion Models

Images that change their appearance under a transformation, such as a rotation or a flip, have long fascinated students of perception, from Salvador Dalli to M. C. Escher. The appeal of these multi-view optical illusions lies partly in the challenge of arranging visual elements such that they may be understood in multiple different ways. Creating these illusions requires accurately modeling—and then subverting—visual perception. We propose a simple, zero-shot method for obtaining these illusions from off-the-shelf text-to-image diffusion models. During the reverse diffusion process, we estimate the noise from different views of a noisy image. We then combine these noise estimates together and denoise the image. A theoretical analysis suggests that this method works precisely for views that can be written as orthogonal transformations. An important special case of these transformations are permutations of an image's pixels, which we use to create a variety of "anagram" illusions, such as jigsaw puzzles that can be solved in two different ways.

Speaker: Andrew Owens is an assistant professor at The University of Michigan in the department of Electrical Engineering and Computer Science. Prior to that, he was a postdoctoral scholar at UC Berkeley. He received a Ph.D. in Electrical Engineering and Computer Science from MIT in 2016. He is a recipient of a Computer Vision and Pattern Recognition (CVPR) Best Paper Honorable Mention Award, and a Microsoft Research Ph.D. Fellowship.

Omnidirectional Computer Vision

Omnidirectional cameras are a different camera modality than what we are typically used to, where we sacrifice nice geometry for significantly larger fields-of-view. Ciarán will discuss Omnidirectional cameras, how to represent them geometrically, optical effects of using omnidirectional cameras, neural networks on omnidirectional cameras, and applications that use omnidirectional cameras.

Speaker: Ciaran Eising is an Associate Professor of Artificial Intelligence and Computer Vision at the University of Limerick, Ireland and co-founder of the D2iCE Research Group. Prior to joining the University of Limerick, Ciarán was a Senior Expert of Computer Vision (director level) at Valeo, designing omnidirectional vision algorithms for low-speed vehicle automation.

Illuminating the Underground World with Multimodal Algorithms

Dive deep into the future of underground exploration! This talk introduces a groundbreaking approach that leverages the power of multimodal algorithms, combining advanced computer vision techniques, SLAM algorithms, sensor metadata, and GIS data. By integrating diverse data streams, we unlock unprecedented levels of detail and accuracy in underground inspections, paving the way for safer, more efficient, and insightful subterranean analyses. About the Speaker

Speaker: Adonaí Vera is a Machine Learning Engineer with expertise in computer vision and AI algorithms, specializing in AI solutions for underground inspections using TensorFlow and OpenCV. Recognized by Google as a top TensorFlow developer in Colombia, he is also the founder of a company focused on AI innovations and currently contributes his expertise to Subterra AI.

The Role of AI in Fixing Hiring

From writing job descriptions, to sourcing candidates, to interviews and evaluation – our current hiring practices are often rife with human bias. Even when such bias is unconscious, it can result in expensive mis-hires. This talk explores the types of biases and the pivotal role of AI in mitigating them. We will discuss the common sources of bias in hiring, the current AI landscape that attempts to address these issues and further opportunities.

Speaker: Saurav Pandit is a seasoned AI leader with expertise in natural language understanding, search and language models. He is on the advisory board of AI 2030, an initiative that promotes AI for good.

Don’t Forget

• Voxel51 will make a donation on behalf of the Meetup members to the charity that gets the most votes this month.
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