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Venue: Carnival House, 100 Harbour Parade, Southampton, SO15 1ST 📢 Want to speak 📢: submit your talk proposal

Please note:

1. 🚨🚨🚨A valid photo ID is required by building security. You MUST use your initial/first name and surname on your meetup profile, otherwise, you will NOT make it on the guest list! 🚨🚨🚨
2. This event follows the NumFOCUS Code of Conduct, please familiarise yourself with it before the event.

If your RSVP status says "You're going" you will be able to get in. No further confirmation required. You will NOT need to show your RSVP confirmation when signing in. If you can no longer make it, please unRSVP as soon as you know so we can assign your place to someone on the waiting list.

*** Code of Conduct: This event follows the NumFOCUS Code of Conduct, please familiarise yourself with it before the event. Please get in touch with the organisers with any questions or concerns regarding the Code of Conduct. *** There will be pizza & drinks, generously provided by our host, Carnival UK. ***

Main Talks 1️⃣ Desert Island Docker: Python Edition - Andrew Collier What 3 Docker images would you choose if you were shipwrecked on a desert island? Choosing the right images will determine whether you are rescued or end up in a cannibals' cooking pot (Python images will make you particularly unpalatable).

Docker is an essential tool for survival as a Python developer, regardless of whether you are stranded or not. In this talk I'll describe three Python Docker images that I consider essential for survival on a desert island. I'll demonstrate how to set up and build a custom image. And finally I'll demonstrate how using a Docker image can simplify CI/CD and deployment.

2️⃣ Streaming DataFrames: A New Way to Process Streaming Data in Python - Tomáš Neubauer

Introducing an open source library in Python: Quix Streams. It solves all the complexities of stream processing in a cloud native package with a familiar Pandas DataFrame API interface. This library lets you work with streaming data similarly to static data in your Jupyter Notebook without any hassle associated with streaming technologies. Our mission is to bring masses of Python developers into streaming and make the journey as smooth as possible so real-time applications using ML are not so difficult. I will demonstrate this live on stage with examples of stateless operations and stateful operations like rolling windows and joins. Join me to learn how you can start working with streaming data today.

Lightning Talks ⚡ ⚡1️⃣ The risks posed by the latest developments in Generative AI to young school pupils - Kashif Hussain ⚡2️⃣ TBD

Logistics Doors open at 6.30 pm, talks start at 7 pm. For those who wish to continue networking and chatting we will move to a nearby pub/bar for drinks from 9 pm.

Please unRSVP in good time if you realise you can't make it. We're limited by building security on the number of attendees, so please free up your place for your fellow community members!

Follow @pydatasoton (https://twitter.com/pydatasoton) for updates and early announcements. We are also on Instagram/Threads as @pydatasoton; and find us on LinkedIn.

Last year, NYC.rb members pondered, "Is Ruby on its way to obsolescence?" This year, the burning question is, "When will AI take over as programmers?"

Generative AI has infiltrated all aspects of software development - from coding suggestions in our IDEs to auto-generated tests. Will this AI revolution render human programmers obsolete? Or can it actually elevate the programming experience? Let's delve into one of Ruby's key philosophies: Developer Happiness.

Can programmers and tech leaders harness the power of Generative AI to enhance Developer Happiness? Is this cutting-edge technology already contributing to greater satisfaction among developers? Or is it instigating a decline in Developer Happiness?

Join us for an insightful panel discussion featuring a diverse array of industry leaders as we dive deep into the intersection of Generative AI and Developer Happiness.

Panelist Biographies

• Andrew Berkowitz is an Engineering Leader with more than a decade of experience helping others succeed, and helping computers succeed at doing what he wants. He has an eclectic set of experiences solving problems in mobile apps, robotics (both empathetic, and violent), teaching, healthcare, biotech, and HR. He has not yet walked more than 46 miles in one day, but with ChatGPT anything is possible.
• Manuel Odendahl's passion for programming began at the young age of 6. He started tinkering with languages ranging from assembly to Common Lisp as a teenager. Although he has a soft spot for Lisp, over the years Manuel has embraced practical languages like PHP and Go that get the job done in his day-to-day work. Manuel feels most at home building backends and embedded systems, but he has explored diverse fields including quantum cryptography, 3D printing, and music tech. He has a special fondness for ecommerce, logistics, and accounting. Since GitHub Copilot became available, Manuel has been fascinated with large language models and believes they directly tap into developers' creativity and increase developer happiness. You can contact him at: https://hachyderm.io/@mnl (mastodon) - https://the.scapegoat.dev/ (blog) - https://github.com/wesen (github)
• Eitan is a Software Engineer with a track record of solving deep technical problems for web scale systems. He prides himself on the ability to apply computer science fundamentals to business problems.
• Andrei has been a software engineering professional for 13 years. Among many others he’s been fortunate to make his impact at Spree Commerce (Acquired by First Data), WeddingWire (merged with The Knot), FiscalNote (IPO), National Public Radio, and USA Today. He currently runs a software dev firm, and serves as an Architect/Engineering Manager/Fractional CTO on the client projects. Consumed by the AI wave this year, Andrei pondered what the future holds for Ruby in the world of ever-growing AI/ML needs. Having just completed a massive client project building a keyword search with Elasticsearch, Andrei dove into the current landscape of semantic search capabilities and the vector search databases. This led him to building Langchain.rb, an “original Langchain”-inspired open source library for building LLM-powered applications. In his free time he enjoys playing tennis and going on long runs while listening to podcasts.
• TBA

Agenda (all in Eastern Time zone)

• 5:30pm Meeting start, welcome
• 5:40pm First time attendees introductions, ice breaker
• 6:00pm Panel start
• 7:00pm Jobs & Hiring Announcements

Send us a text Want to be featured as a guest on Making Data Simple? Reach out to us at [[email protected]] and tell us why you should be next.

This week’s guest on the Making Data Simple podcast is Jennifer Sukis, design principal for AI and machine learning at IBM. Jennifer shares her philosophies and ideas on what constitutes as great design, specifically for applications in AI. Be sure to listen to the end, where host Al Martin poses questions for Jennifer to share about her crucial career decisions as well as advice for young women considering a similar path. Show Notes 01:25 - Connect with Jennifer Sukis on LinkedIn and Twitter.  05:49 - Check out this infographic on the The Present and Future of AI in Design. 14:24 - Watch Simon Sinek's TED Talk on the Why, When, How here. 26:23 - Click here to read why transparency matters.  32:04 - Listen to Jennifer's podcast AI Zen with Andrew and Jen.

Connect with the Team Producer Steve Moore - LinkedIn and Twitter. Producer Liam Seston - LinkedIn and Twitter. Producer Rachit Sharma - LinkedIn. Producer Lana Cosic - LinkedIn.

Producer Meighann Helene - LinkedIn.  Host Al Martin - LinkedIn and Twitter. Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

Open data has spurred economic innovation, social transformation, and fresh forms of political and government accountability in recent years, but few people understand how open data works. This comprehensive report, developed with support from Omidyar Network, presents detailed case studies of open data projects throughout the world, along with in-depth analysis of what works and what doesn’t. Authors Andrew Young and Stefaan Verhulst, both with The GovLab at New York University, explain how these projects have made governments more accountable and efficient, helped policymakers find solutions to previously intractable public problems, created new economic opportunities, and empowered citizens through new forms of social mobilization. This report includes: Recommendations and implementation steps for policymakers, entrepreneurs, and activists looking to leverage open data Key challenges, such as resource shortages and inadequate privacy or security protections Four conditions that enable open data to work—including organizational partnerships and collaborations Case studies of open data projects for improving government in Brazil, Sweden, Slovakia, and other countries Projects for empowering citizens in Tanzania, Kenya, Mexico, and Uruguay New business opportunities enabled by open weather, geo-location, and market research data Public problem-solving efforts built on open data for Ebola in Sierra Leone, dengue fever in Singapore, and earthquakes in New Zealand Andrew Young (@_AndrewYoung) is the Associate Director of Research at The GovLab (www.thegovlab.org), where he leads a number of grant-funded research efforts focusing on the impact of technology on public institutions. He is also the Network Coordinator of the GovLab-chaired MacArthur Foundation Research Network on Opening Governance. Stefaan G. Verhulst (@sverhulst) is the Co-Founder and Chief R&D Officer of The GovLab at New York University’s Tandon School of Engineering, responsible for experimentation and evidence gathering on how to transform governance by using advances in science and technology. He was Chief of Research for the Markle Foundation, where he continues to serve as Senior Advisor.