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GBA Public Webinar Digital Asset, Crypto/DeFi Smart Contracts/UXTO vs TradFi Accounting at 12 noon EDT Wednesday, May 21st as part of GBA's Blockchain & Financial Enterprises Series. GBA's banking and finance working group is hosting its monthly webinar next Wednesday May 21 at 12 noon EDT. Join zoom meeting at https://us06web.zoom.us/j/88547602182?pwd=hlSsAML0U2b8NZbS3FpxtEigdU9GQo.1 Hosted by GBA’s Banking & Finance Working Group, and moderated by Paul Dowding, this monthly public webinar on Improving Government with Blockchain with DeFi and Digital TradFi use of Smart Contracts and variations on Bitcoin's UXTO to enhance transactions, all of which in TradFi are recorded through accounting. Paul and Nitin discuss the merits and challenges of both. Host and moderator is Paul Dowding, Co-Founder, Head of Design, L4S Corporation. Joining the conversation is Nitin Gaur, Founder of LedgeLink.ai and Founding Director of IBM Digital Asset Labs and IBM Blockchain Labs. Nitin Gaur is a Senior leader who designs and develops enterprise infrastructures and applications for Fortune 500 companies globally. He has worked with Digital Assets with IBM State Street and various start-ups. He is a renowned and sought after expert and speaker in the digital asset industry. His industry experience covers multiple products and markets as a manager and consultant for major banks, brokers, fund managers and industry utilities. Paul F. Dowding has 35 years of global experience in financial operations and process management, innovation and design. He has designed and launched a differentiating DLT solution - TapestryX. A relevant and topical discussion as Paul Dowding leads a discussion with Nitin Gaur on the merits and challenges of Smart Contracts & UXTO vs Accounting for Blockchain and Distributed Ledger Technology within Crypto/DeFi and Digital TradFi. Join Zoom Meeting https://us06web.zoom.us/j/88547602182?pwd=hlSsAML0U2b8NZbS3FpxtEigdU9GQo.1 Meeting ID: 885 4760 2182 Passcode: 430709 About GBA The Government Blockchain Association (GBA) is a nonprofit (501c6) organization committed to advancing blockchain technology standards, facilitating industry education, and ensuring a trusted, secure ecosystem for blockchain solutions. For more information, visit https://gbaglobal.org/. For more information contact Bob Miko, [email protected] 203 378 2803 Bob Miko GBA Director of Public Relations Editor in Chief/Producer Pacific Dialogue 203 378 2803 [email protected]

RSVP Webinar: https://www.eventbrite.com/e/webinar-generative-ai-on-aws-tickets-45852865154

Talk #0: Introductions and Meetup Updates by Chris Fregly and Antje Barth, Principal Developer Advocate, Gen AI @ AWS

Talk #1: Quantum Artificial General Intelligence (AGI) by Jesse Berwald, Co-founder @ qamia (Quantum AGI Startup)

Talk #2 Multi-Modal Chatbot with OpenSearch incl. Python Interpreter by Danilo Poccia, Chief Technical Evangelist, AI Engineering @ AWS

Talk #3 GenAI Startup by Nitin Wagh, Founder @ Karini.ai

RSVP Webinar: https://www.eventbrite.com/e/webinar-generative-ai-on-aws-tickets-45852865154

Zoom link: https://us02web.zoom.us/j/82308186562

Related Links Generative AI Free Course on DeepLearning.ai: https://bit.ly/gllm O'Reilly Book: https://www.amazon.com/Generative-AWS-Context-Aware-Multimodal-Applications/dp/1098159225 Website: https://generativeaionaws.com Meetup: https://meetup.generativeaionaws.com GitHub Repo: https://github.com/generative-ai-on-aws/ YouTube: https://youtube.generativeaionaws.com

RSVP Webinar: https://www.eventbrite.com/e/webinar-generative-ai-on-aws-tickets-45852865154

Talk #0: Introductions and Meetup Updates by Chris Fregly and Antje Barth, Principal Developer Advocate, Gen AI @ AWS

Talk #1: Quantum Artificial General Intelligence (AGI) by Jesse Berwald, Co-founder @ qamia (Quantum AGI Startup)

Talk #2 Multi-Modal Chatbot with OpenSearch incl. Python Interpreter by Danilo Poccia, Chief Technical Evangelist, AI Engineering @ AWS

Talk #3 GenAI Startup by Nitin Wagh, Founder @ Karini.ai

RSVP Webinar: https://www.eventbrite.com/e/webinar-generative-ai-on-aws-tickets-45852865154

Zoom link: https://us02web.zoom.us/j/82308186562

Related Links Generative AI Free Course on DeepLearning.ai: https://bit.ly/gllm O'Reilly Book: https://www.amazon.com/Generative-AWS-Context-Aware-Multimodal-Applications/dp/1098159225 Website: https://generativeaionaws.com Meetup: https://meetup.generativeaionaws.com GitHub Repo: https://github.com/generative-ai-on-aws/ YouTube: https://youtube.generativeaionaws.com

RSVP Webinar: https://www.eventbrite.com/e/webinar-generative-ai-on-aws-tickets-45852865154

Talk #0: Introductions and Meetup Updates by Chris Fregly and Antje Barth, Principal Developer Advocate, Gen AI @ AWS

Talk #1: Quantum Artificial General Intelligence (AGI) by Jesse Berwald, Co-founder @ qamia (Quantum AGI Startup)

Talk #2 Multi-Modal Chatbot with OpenSearch incl. Python Interpreter by Danilo Poccia, Chief Technical Evangelist, AI Engineering @ AWS

Talk #3 GenAI Startup by Nitin Wagh, Founder @ Karini.ai

RSVP Webinar: https://www.eventbrite.com/e/webinar-generative-ai-on-aws-tickets-45852865154

Zoom link: https://us02web.zoom.us/j/82308186562

Related Links Generative AI Free Course on DeepLearning.ai: https://bit.ly/gllm O'Reilly Book: https://www.amazon.com/Generative-AWS-Context-Aware-Multimodal-Applications/dp/1098159225 Website: https://generativeaionaws.com Meetup: https://meetup.generativeaionaws.com GitHub Repo: https://github.com/generative-ai-on-aws/ YouTube: https://youtube.generativeaionaws.com

Welcome to our September 2024 Data & AI Meetup. The first will be:

Creating cost transparency in multi-cloud enterprise: An OSS Approach

Gringotts is a cloud transparency tool that shows insights into a business enabling product teams spending in multi-cloud ecosystems, allowing them to drill down on current costs, get insights to make informed decisions about your products, and eventually control costs. It also supplies optimization recommendations to these teams to right-size on their cloud workloads to run on optimal costs & also gives them alerts on anomalies that occur on the cloud workloads in terms of daily expenditure. The solution we have built is completely built by using OSS frameworks, which allows it to be cloud agnostic in nature & effectively run at a very minimal operational expense. The solution itself consists of below mentioned components: - Data ingestion: This is done daily by used APIs from different cloud service providers which we consume using ETL services we have developed using .NET running on containerized workloads in Kubernetes. - Data transformation: This is again done used internal business metadata mapping which lets us associate cloud workloads (at a resource level) to business entities within the organization. This association creates the layer of association which helps us relate costs to a business entity & create transparency. - Data acceleration: Here we used an OSS tool called as Dremio (data lake engine) which helps us create a layer of abstraction on top of our data lake & serves the purpose of creating data dimensions & aggregations which can be used by different visualization tools. - Data visualization: Here again we have used an OSS tool called as Apache Superset (a visualization tool) to offer insights into the data that we have collected & transformed for our needs. Apache Superset offers immense capabilities like support for plugging into OAuth based RBAC, row-level security, custom roles, scheduled reports & alerts etc. Enabling it to be a perfect solution for our visualization needs. - Anomaly Detection & Optimization recommendations: Here we have used ML .NET to create a solution which offers anomaly detection to business entities. This is just a sneak peek into the solution, but I would love to talk more about it in depth in the meetup session on how we have solved this problem for our organization

Speaker: Nitin Sapru I am a Senior Software Developer by day, aspiring tech superhero by night. I've been fighting the forces of software chaos in the IT industry for years, armed with my trusty C# and dotnet for better part of 9 years (and a secret stash of coffee).

There will be Pizza and Networking after the session.

Join GBA Finance Webinar June 19th at 10 am EDT

Web 3.0 – Is it the best of times or worst of times? – Webinar Link: https://meet.google.com/joe-rjwn-ibu

GBA Finance Lead Paul F. Dowding interviews Nitin Gaur to discuss the successes and remaining challenges for Web 3.0 for both the Crypto/DeFi and TradFi worlds. As well as the current status, Paul and Nitin will also discuss how the GBA’s Blockchain Maturity Model helps assess blockchain solutions across different use cases and sectors..

Gaur is the co-founder and CTO of Stealth Startup, 20 year IBM veteran an former Global Head of Digital Asset and Technology Design of State Street.

GBA's BMM has been adopted by the Dynamic Coalition for Blockchain Assurance and Standardization within the U.N.’s Internet Governance Forum.

Join us at Call Link: https://meet.google.com/joe-rjwn-ibu

Hosted by GBA’s Banking & Finance Working Group, and moderated by Paul F. Dowding, this monthly webinar is open to members and the general public. The goal is to provide insights and updates on the status and developments of #blockchain in the #financialindustry. The topics will include: -The GBA’s Blockchain Maturity Model – Banking and Finance Services Supplement -Industry overviews, updates, blockchain news across #crypto #defi and #traditionalfinance updates and implementations from GBA Members solutions. -GBA Members are welcome to propose presentation topics and the non-members can suggest topics to be covered. -Come listen for what will be informative presentations and lively, substantive discussions. When: 3rd Wednesday of Each Month at … 7:00 AM Los Angeles 8:00 AM Denver 9:00 AM Dallas 10:00 AM New York 3:00 PM London 4:00 PM Lagos 4:00 PM Paris 4:00 PM Berlin 5:00 PM Beirut 7:00 PM Dubai 8:00 PM Islamabad 8:30 PM New Delhi 11:00 PM Shanghai 11:00 PM Singapore Call Link: https://meet.google.com/joe-rjwn-ibu

Enhance Your Understanding of Scaling Learning Models with Apache Spark

Join a live Workshop with Nitin Bhushan, who will cover the following:

• Distributed ML paradigms
• Scaling ML workflows using Spark
• Practical considerations

About the Workshop:

This session is perfect for anyone looking to dive into distributed ML for the first time or eager to enhance their understanding of scaling learning models with Apache Spark. Whether you're a beginner or have some experience in the field, this interactive and hands-on taster is designed to equip you with the knowledge and practical insights needed to conquer the challenges of scaling machine learning workflows.

This Session is for You If:

• You have no prior experience with distributed ML but want to change that
• You are interested in scaling your ML workflows with Apache Spark
• You want to understand the practical challenges involved in scaling machine learning workflows.

IMPORTANT: You can only register for this event on Eventbrite, here: https://Nov2023LNETM.eventbrite.co.uk/

Can DevSecOps really make developers fall in love with security or is platform engineering the way of the future?

Building secure software is significantly more efficient, cheaper and lower risk than needing to remediate insecure applications after the fact. This has led to an important evolution of the DevOps movement to encompass security awareness throughout the software development lifecycle.

The November LNETM will discuss this progression from DevOps to DevSecOps, in terms of successes and also challenges along the way, including how best to bring developers on this journey (willingly!), how to integrate processes for more efficient/automated development pipelines, how to address the fragmented tool market and the role that open-source tools play relative to proprietary solutions. It will also examine the role of security in the nascent Platform Engineering movement.

We will be joined by a top-quality industry expert panel to discuss this topic, including:

• Amanvir Sangha (Senior Engineering Manager for DevSecOps at London Stock Exchange Group)
• Artem Loenko (Director of Engineering at Bumble)
• Camille Plays (Senior Software Engineer at Wise)

The discussion will be moderated by Miriam Fahim from London Stock Exchange Group. There will be two flash talks at the start of the event:

• Entitle automates how permissions are requested, granted, and managed to eliminate bottlenecks and enable robust least privilege access programs (Ron Nissim, CEO & Co-Founder).
• Semgrep is an open-source platform designed to find bugs and dependency vulnerabilities, run security scans in CI and enforce standards across an organisations (Nitin Nayar, Head of EMEA Solutions Engineering)

We’re excited that Lucy Neal and AJ Phipps will also provide a quick overview of the Women in DevOps and Pride in Tech networks:

• Women in DevOps is a global community on a mission to close the DevOps gender gap and inspire the future leaders of the tech world. Having started life as a small offline network in 2017, they've since evolved into a worldwide initiative aimed at connecting and empowering individuals in both DevOps and the broader tech industry.
• Pride in Tech is a community that exists to make the working world a kinder and safer space for queer people. They host unique networking initiatives working in collaboration with the wider tech community, businesses, and brands who are passionate about creating a more equitable working world.

We are very grateful to London Stock Exchange Group for hosting this event and to all of our annual sponsors for their support.

IMPORTANT NOTES:

1. You must register through Eventbrite in order to attend.
2. Registration will close 48 hours before the event (on the night of Monday 20th November).
3. Please bring photo ID to the event, as it may be required for entry. to the event, as it may be required for entry.

Today I’m chatting with returning guest Tom Davenport, who is a Distinguished Professor at Babson College, a Visiting Professor at Oxford, a Research Fellow at MIT, and a Senior Advisor to Deloitte’s AI practice. He is also the author of three new books (!) on AI and in this episode, we’re discussing the role of product orientation in enterprise data science teams, the skills required, what he’s seeing in the wild in terms of teams adopting this approach, and the value it can create. Back in episode 26, Tom was a guest on my show and he gave the data science/analytics industry an approximate “2 out of 10” rating in terms of its ability to generate value with data. So, naturally, I asked him for an update on that rating, and he kindly obliged. How are you all doing? Listen in to find out!

Highlights / Skip to:

Tom provides an updated rating (between 1-10) as to how well he thinks data science and analytics teams are doing these days at creating economic value (00:44) Why Tom believes that “motivation is not enough for data science work” (03:06) Tom provides his definition of what data products are and some opinions on other industry definitions (04:22) How Tom views the rise of taking a product approach to data roles and why data products must be tied to value (07:55) Tom explains why he feels top down executive support is needed to drive a product orientation (11:51) Brian and Tom discuss how they feel companies should prioritize true data products versus more informal AI efforts (16:26) The trends Tom sees in the companies and teams that are implementing a data product orientation (19:18) Brian and Tom discuss the models they typically see for data teams and their key components (23:18) Tom explains the value and necessity of data product management (34:49) Tom describes his three new books (39:00)

Quotes from Today’s Episode “Data science in general, I think has been focused heavily on motivation to fit lines and curves to data points, and that particular motivation certainly isn’t enough in that even if you create a good model that fits the data, it doesn’t mean at all that is going to produce any economic value.” – Tom Davenport  (03:05)

“If data scientists don’t worry about deployment, then they’re not going to be in their jobs for terribly long because they’re not providing any value to their organizations.” – Tom Davenport (13:25)

“Product also means you got to market this thing if it’s going to be successful. You just can’t assume because it’s a brilliant algorithm with capturing a lot of area under the curve that it’s somehow going to be great for your company.” – Tom Davenport (19:04)

“[PM is] a hard thing, even for people in non-technical roles, because product management has always been a sort of ‘minister without portfolio’ sort of job, and you know, influence without formal authority, where you are responsible for a lot of things happening, but the people don’t report to you, generally.” – Tom Davenport (22:03)

“This collaboration between a human being making a decision and an AI system that might in some cases come up with a different decision but can’t explain itself, that’s a really tough thing to do [well].” – Tom Davenport (28:04)

“This idea that we’re going to use externally-sourced systems for ML is not likely to succeed in many cases because, you know, those vendors didn’t work closely with everybody in your organization” – Tom Davenport (30:21)

“I think it’s unlikely that [organizational gaps] are going to be successfully addressed by merging everybody together in one organization. I think that’s what product managers do is they try to address those gaps in the organization and develop a process that makes coordination at least possible, if not true, all the time.” – Tom Davenport (36:49)

Links Tom’s LinkedIn: https://www.linkedin.com/in/davenporttom/ Tom’s Twitter: https://twitter.com/tdav All-in On AI by Thomas Davenport & Nitin Mittal, 2023 Working With AI by Thomas Davenport & Stephen Miller, 2022 Advanced Introduction to AI in Healthcare by Thomas Davenport, John Glaser, & Elizabeth Gardner, 2022 Competing On Analytics by Thomas Davenport & Jeanne G. Harris, 2007

"Apache Cassandra Essentials" is your guide to understanding and mastering the core concepts of Apache Cassandra. Whether you're setting up your first Cassandra cluster or optimizing performance, this book provides actionable steps and insights to help you design highly responsive database architectures. What this Book will help me do Set up and configure a Cassandra cluster for optimal performance. Design schemas in Cassandra using CQL for evenly distributed data. Employ tools to monitor and maintain Cassandra clusters effectively. Debug queries to improve database query performance. Tune Cassandra to adapt to specific operational environments. Author(s) Nitin Padalia, the author, is an experienced database engineer with a deep understanding of distributed systems. With years of experience working with Apache Cassandra and similar technologies, he has dedicated his efforts to simplifying complex concepts for developers. His clear and straightforward writing helps readers build expertise efficiently. Who is it for? This book is perfect for developers who are already familiar with Cassandra and want a deeper understanding of its architecture and functionality. If you're interested in diving into the non-relational aspects of Cassandra or need guidance on database optimization, you'll find this book invaluable. It's designed for those ready to advance their skills and maximize the potential of their Cassandra deployments.