From Rapid Prototypes to an end-to-end Model Deployment: an AI Hedge Fund Use Case

This is an introduction to KSQL. KSQL is an open source, Apache 2.0 licensed streaming SQL engine that enables stream processing against Apache Kafka.

This document discusses how to successfully implement SAFe (Scaled Agile Framework) Program Increments alongside Google's OKR (Objective and Key Results) framework. It provides an overview of SAFe and OKR, including their benefits and structures. It then gives an example of how an IT infrastructure organization could connect SAFe and OKR, balancing product and organizational goals. Finally, it outlines a process for implementing OKRs within SAFe, with preparation and refinement steps tied to the Program Increment Planning events.

Why estimate user stories using poker planning? What’s the advantage of relative estimation? Why leverage Fibonacci series? These slides explore the reasons for relative estimation using Fibonacci through a collection of exercises and illustrations. Slides assume a basic understanding of user stories and poker planning. Originally presented as an Agile 101 at Agile New England in May 2023.

Large enterprises that develop software cannot function without structure, but often develop structures that cripple productivity and impair responsiveness to customer needs. This Webinar introduces an approach to building effective structures by introducing the concept of Agile governance. Agile governance provides formalized practices for decision making (governance) which incorporate the principles of the Agile Manifesto and Lean Engineering. The result is a set of simple recipes for selecting, planning, organizing, and tracking work at all levels in the organization (the Portfolio, Program, and Project levels), which apply within or across Business Units. We also provide guidance on how to develop new recipes, when needed. This webinar introduces the basic concepts of Agile governance. We will look at some existing concepts (such as Scrum of Scrums and SAFe), and lay the foundations for subsequent webinars that address specific scenarios of common interest.

NEXThink offers desktop monitoring software that provides real-time visibility and reporting on desktop assets, applications, and network connectivity without impacting performance. It uses patented self-learning technology and provides 360-degree visibility. The NEXThink Library allows users to leverage best practices and a malware reference database from the NEXThink community. NEXThink V3 allows users to discover desktop assets 20 times faster, measure security compliance in real-time, and improve support by diagnosing and fixing 80% of issues in 20% less time.

MLflow serving is a great way to deploy any model as a rest API endpoint and start experimenting. But what about taking it to the next level? What if we want to deploy our application to production just like any other server in a containerized environment? What about adding custom middlewares, monitoring, logging and tweaking performance for high scale?

This document discusses different techniques for agile estimation, including story points, planning poker, and fast estimation. Story points represent the relative size of user stories and do not equate to time. Planning poker involves the product owner explaining a story while the team privately assigns estimates in story points, then reveals and discusses them to reach consensus. Fast estimation is a quicker version where the team silently assigns all stories story point estimates within time limits. The goal is for estimates to be relative rather than accurate.

IBM Watson Natural Language Processing allows developers to extract insights from unstructured text to build cognitive apps. It uses techniques like entity extraction, sentiment analysis, keyword extraction and more to analyze text and understand the underlying concepts, entities, and sentiment. Some example uses are to extract people, places and entities from news articles or to gather business intelligence from sources like social media, websites or documents to power applications in areas like customer care, business intelligence, and content recommendation.

Kundenprobleme verstehen, Ideen für passende Lösungen entwickeln und herausfinden, wie gut jene Ideen tatsächlich sind – all das in kurzer Zeit: Dieser Vortrag beleuchtet die Charakteristika und Einsatzmöglichkeiten der Design Sprint-Methode von Google im Vergleich (und Zusammenspiel) mit Design Thinking und Lean Startup. #DesignSprint, #DesignThinking, #LeanStartup #CampusFuerEltern #GoogleForEntrepreneurs

The document discusses using ClickHouse as the backend storage for observability data in SigNoz, an open source observability platform. ClickHouse is well-suited for storing observability data due to its ability to handle wide tables, perform fast aggregation queries, and provide compression capabilities. The document outlines SigNoz's architecture, demonstrates how tracing and metrics data is modeled in ClickHouse, and shows how ClickHouse outperforms Elasticsearch for ingesting and querying logs and metrics at scale. Overall, ClickHouse is presented as an efficient and less resource-intensive solution than alternatives like Druid for storing observability data, especially for open source projects.

As a data driven company, we use Machine learning based algos and A/B tests to drive all of the content recommendations for our members. Traditionally, these recommendations are precomputed in a batch processing fashion, but such a model cannot react quickly based on member interactions, title interests, popularity etc. With an ever-growing Netflix catalog, finding the right content for our audience in near real-time would provide the best personalized experience. We’ll take a deep dive into our realtime Spark Streaming ecosystem at Netflix. Both it’s infrastructure and business use cases. On the infrastructure front, we will delve into scale challenges, state management, data persistence, resiliency considerations, metrics, operations and auto-remediation. We will talk about a few use cases that leverage real-time data for model training, such as providing the right personalized videos in a member’s Billboard and choosing the right personalized image soon after the launch of the show. We will also reflect on the lessons learnt while building such high volume infrastructure.

Presentation on how we at Instana use ClickHouse. The problems we came across and how we solved them.

1. The document discusses building an authorization solution for microservices using Neo4j and OPA. 2. It describes modeling authorization data in a graph database for role-based access control and efficient authorization queries. 3. The proposed solution uses OPA as a centralized decision engine to evaluate authorization policies for microservices in a scalable way.

Presented at Global Scrum Gathering Orlando 2016 Because of benefits like predictability, better quality of products, and faster delivery, many companies have adopted or in the process of adopting Agile. However, there are challenges. David Hawks, CST and Agile Evangelist, explains the common antipatterns of Agile adoption.

There are as many types of agile coaches out there as there are flavors of ice cream. And, their levels of leadership maturity and skill can vary just as widely. It can leave one fretting, “What am I really getting when I bring in an agile coach? And, how do I ‘grow’ my own?” In fact, what are the “must have” skills of an agile coach and how can you tell if your coach has them? The Agile Coach Competency Framework is one big clue to answering these questions. Over the past two years, this framework has guided the development of hundreds of agile coaches. Agile managers and champions also use it to obtain “truth in advertising” to hire the right coach at the right time. We will explore this framework and provide lightening-talk-style case studies that showcase how it has been used in the real world. You’ll leave with ideas and actions to help you become a more savvy purveyor (and/or developer) of agile coaches.

Presentation by Nick Dearden, Direct, Product and Engineering, Confluent It’s 3 am. Do you know how your Kafka cluster is doing? With over 150 metrics to think about, operating a Kafka cluster can be daunting, particularly as a deployment grows. Confluent Control Center is the only complete monitoring and administration product for Apache Kafka and is designed specifically for making the Kafka operators life easier. Join Confluent as we cover how Control Center is used to simplify deployment, operability, and ensure message delivery. Watch the recording: https://www.confluent.io/online-talk/monitoring-and-alerting-apache-kafka-with-confluent-control-center/

You can make a significant impact in the world in your own small way if you expand your horizon and start asking: why? You are supposed to explore and make yourself better, smarter and stay remarkable. Some people are killing their creative instincts without knowing it. Your daily actions either enhance your ability to make a positive impact in your immediate environment or kill your creative habits.

This slide was presented by Dmitry Baev, Pratap Ramamurthy and Karthik Kannappan at our AWS DevDay in Toronto, Canada on July 17, 2019

In this session we kick-start your journey as a woman RPA Developer, by introducing you to RPA and UiPath Studio. From women in RPA, to any woman developer wishing to step into RPA. 🧙‍♀️ Your trainer: Maria Irimias, UiPath MVP, Service Delivery Manager & Solution Architect @accesa.eu Maria has begun her software development journey 15 years ago. She carefully built her expertise in programming languages that stood the test of time, like .NET, and more recently accepted the challenges of RPA technology. Starting with 2021, Maria was chosen as UiPath MVP – the highest distinction within UiPath Community, as an acknowledgement of her RPA expertise and her status of RPA advocate and high community contributor. 🌺 About this event: What is RPA (explain RPA technology) Why RPA (explain technological benefits) Why RPA as a career Platform overview Small automation demo Install Studio demo

1) Learn about Myplanet's Headless CMS solution using Gatsby Preview and Contentful’s UI Extensions (https://www.contentful.com/resources/serverless/) 2) their Serverless project with IBM - using Apache OpenWhisk (https://www.ibm.com/cloud/functions) 3) how Myplanet got involved with AWS DeepRacer - a fun way to get started with Reinforcement Learning (RL), and their racing experience at re:Invent DeepRacer League (https://reinvent.awsevents.com/learn/deepracer/) 4) their Machine Learning (ML) research related to finding DeepRacer’s ideal line (https://medium.com/myplanet-musings/the-best-path-a-deepracer-can-learn-2a468a3f6d64). BONUS: Two TED Talks referenced in the intro 5) When ideas have sex | Matt Ridley | Jul 14, 2010 https://www.ted.com/talks/matt_ridley_when_ideas_have_sex 6) Why The Best Leaders Make Love The Top Priority | Matt Tenney | Dec 5, 2019 https://www.youtube.com/watch?v=qCVoohdyI6I VIDEO: https://youtu.be/ZH1xxmBNx5k

Sri Krishnamurthy presents on practical model risk management in the age of data science and machine learning. He discusses how machine learning and AI are driving paradigm shifts in finance. However, he cautions that claims about machine learning capabilities need to be balanced with realities about data and model quality. Key challenges include ensuring interpretability, transparency, and proper evaluation of models in production. He promotes his company's solutions for addressing these challenges through end-to-end workflow management and model governance tools.

With this very first product training session we kick off the RPA Developer thread of the program and get you started with UiPath Studio in a completely assisted and supportive manner by our very own UiPath MVPs. From women in RPA to all the women who wish to step into the automation world. 🌺 About this event: What is RPA (explain RPA technology) Why RPA (explain technological benefits) Why RPA as a career Platform overview Small automation demo Install Studio demo Q&A Gather your courage and curiosity, and join us on March 9th!! 👩🏽‍🤝‍👩🏼 👩‍🏫 Your UiPath MVP trainers: Maria Irimias, UiPath MVP, Service Delivery Manager, accesa.eu (Romania) Nadia Ghoufa, UiPath MVP, RPA Tech Lead, Talan (France)

These slides are from a recent Red Hat event featuring Steve Willmott, senior director and head of API infrastructure at Red Hat. Overview: Enterprise IT needs are evolving at breakneck speed and are becoming critical to business success. Organizations now face the need to deliver and evolve their software infrastructure more quickly and effectively than ever before. At this event, we'll cover the tools and techniques used by Red Hat's most successful clients. In particular, we'll focus on how application programming interfaces (APIs), combined with containers and integration, create highly effective software systems. We will also discuss how APIs can be used to transform the internal IT landscape, how they combine with containers for effective microservices strategies, and how they fit with integration technologies. The material will cover architecture, technology, and lessons from the field with customer examples.

DevOps provides the ability to increase time to market to an new level. The question is no longer if we need to speed up our delivery. The challenge is to find the right „pace“ for your product. Not every organization and every product needs to run at the speed of Netflix and Spotify, even if we’d like it to be like this. We need to adjust the organization, processes and tools appropriatly and to identify the real bottlenecks in the delivery pipeline continuously. And by the way, we need to justify our investment in the DevOps mission. Are we just automating the current processes or can we use this DevOps thing to really support our business? In this talk, I’d like to discuss with you how to find the right design for your delivery process and your organization to behave as a business enabler and how you can scale DevOps within your organization without loosing agility. Let’s explore how we can listen carefully to the unknown customer out there and to build software they really like in the speed of your business.

👉 Check out our full 'Africa Series - Automation Student Developers (EN)' page to register for the full program: https://bit.ly/Automation_Student_Kickstart In this session, we shall introduce you to the world of automation, the UiPath Platform, and guide you on how to install and setup UiPath Studio on your Windows PC. 📕 Detailed agenda: What is RPA? Benefits of RPA? RPA Applications The UiPath End-to-End Automation Platform UiPath Studio CE Installation and Setup 💻 Extra training through UiPath Academy: Introduction to Automation UiPath Business Automation Platform Explore automation development with UiPath Studio 👉 Register here for our upcoming Session 2 on June 20: Introduction to UiPath Studio Fundamentals: https://community.uipath.com/events/details/uipath-lagos-presents-session-2-introduction-to-uipath-studio-fundamentals/

This document discusses the intelligent enterprise and how companies can transition to become more intelligent. It describes how intelligent technologies like AI, machine learning, IoT, and analytics can help companies in areas like customer experience, manufacturing, supply chain, and more. The key components of an intelligent enterprise are an intelligent suite of business applications, intelligent technologies like machine learning/AI, and a digital platform. The suite and technologies work together to deliver intelligence throughout core business processes. The digital platform provides data management, cloud capabilities, and tools to build new intelligent applications. Examples show how machine learning can be applied in various use cases to help companies operate more intelligently.

The document provides an overview of intelligent automation in finance, including robotic process automation (RPA) and how machine learning can be applied. It discusses the business benefits of RPA, such as increased profit margins, and how machine learning can assist RPA through applications like predictive analytics, fraud detection, and customer experience optimization. The document also outlines career opportunities that are emerging in the growing field of intelligent automation.

Luis Weir, CTO of Capgemini UK's Oracle practice, discusses the role of APIs and microservices in digital transformation. He argues that technology alone does not drive disruption but lack of adaptability to customer needs. Weir outlines the API value chain and how organizations can move from tactical to strategic use of APIs. Case studies of Cargill and IKEA demonstrate how a next-generation API platform unlocked data and enabled their digital supply chains.

This talk touches upon how API Management enables organizations transform by leveraging core assets (data & processes).

Presentation from the technology track at I Love APIs London 2016 featuring Oliver Ogg, Marks & Spencer and Andrew Braithwaite, Laterooms.com. APIs are the modern day version of the Rosetta stone. Learn how to provide standardisation and uniformity for partners and internal teams that want to build their own apps but need to access various IT systems and apps that each speak their own dialects. This session includes case studies from Laterooms and Marks and Spencer and will cover how they help external teams build APIs, and evangelise an API economy organisation.

The document discusses how APIs can help organizations innovate by building ecosystems. It outlines how early integration approaches required point-to-point connections but APIs now allow maximum reuse and open the door to more partners. The document presents examples of how Phillips Hue, Swisscom, and The World Bank used Apigee Edge to build successful digital ecosystems and external developer programs through their API strategies. It emphasizes that ecosystems require frictionless experiences for developers and visibility into the digital value chain.

We will walk through how we are scaling and democratizing the development of intelligent products based on AI with a platform approach. From the culture needed to shape this mindset, to execution which resulted into reducing the time it takes to productionize machine learning by 50%. We will discuss how we leveraged product mindset, coupled with data, to enable data scientists to be 50% more productive, while scaling the knowledge across our internal builder community.

The document outlines an agenda for the Manchester MuleSoft Meetup Group meeting. The agenda includes introductions of organizers, sponsors, and a new attendee poll. It then covers two main topics: API Specification Automation via Platform APIs and 7 Steps to Achieving Effective API Insights. Each topic includes a presentation and Q&A section. The document provides details on the speakers and their backgrounds. It concludes with announcements about Anypoint Studio and Anypoint Flex Gateway updates.

This document provides an overview of a MuleSoft meetup on API-led connectivity. It includes introductions of the organizers and agenda. The agenda discusses designing RESTful reusable APIs, how API-led fits into architecture, and an example use case. It also covers when system APIs may be useful, such as to address security issues, improve error handling, reduce complexity, and improve third party APIs. The document emphasizes that core or business APIs are the essential layer and other layers like system or process APIs are optimizations that need only be built if necessary.

The document discusses 7 steps to achieving effective API insights: 1. Identify the problem of ensuring API metrics evolve in a "virtuous" rather than "vicious" way. 2. Select meaningful metrics that are understandable, measurable, and can drive tangible outcomes. 3. Align metrics to business outcomes and objectives to ensure long-term API value. 4. Apply metrics in practice by connecting them to business goals, establishing a frequency, tracking trends over time, and avoiding "vanity" measures. 5. Instrument metrics and visualize them on a single dashboard using tools like Anypoint Monitoring and the Elastic Stack to provide insights. 6. Measure outcomes around people, processes, the application platform,

Today's enterprise strives to deliver exceptional customer experience, business process efficiency, and customer profitability. Given an enterprise's existing set of products, how do you define a portfolio of digital products to drive innovation and deliver real business results? How does business strategy shape a digital products portfolio? What technical and organizational processes & structures are common among successful digital products? Join Michael Leppitsch and Dan Tortorici for a discussion of what a digital products portfolio looks like, how a portfolio is shaped by your business strategy and by your consumer, and how a robust digital products portfolio leads to customer adoption, satisfaction, and profitability. Join to discuss: - Digital products and how they shape customer experience and behavior - Influences that inform and shape successful digital product portfolios - Common traits and patterns in successful digital products

The document discusses Adobe's Experience Cloud business and analytics solutions. It provides an overview of Adobe's Experience Cloud, Marketing Cloud, Analytics Cloud, and Advertising Cloud offerings. It then compares Adobe Analytics to Google Analytics, highlighting strengths and weaknesses of each. Finally, it proposes a campaign to position Adobe Analytics as the market leader through enhancing the experience of prospective customers by using Adobe's own tools to deliver personalized content and insights. The goal is to practice what is preached to demonstrate leadership in analytics. The expected outcome is delivering the right message to the right person at the right time.

“AGI should be open source and in the public domain at the service of humanity and the planet.”

This document provides an overview of H2O.ai, an AI company that offers products and services to democratize AI. It mentions that H2O products are backed by 10% of the world's top data scientists from Kaggle and that H2O has customers in 7 of the top 10 banks, 4 of the top 10 insurance companies, and top manufacturing companies. It also provides details on H2O's founders, funding, customers, products, and vision to make AI accessible to more organizations.

Here are some key points about benchmarking and evaluating generative AI models like large language models: - Foundation models require large, diverse datasets to be trained on in order to learn broad language skills and knowledge. Fine-tuning can then improve performance on specific tasks. - Popular benchmarks evaluate models on tasks involving things like commonsense reasoning, mathematics, science questions, generating truthful vs false responses, and more. This helps identify model capabilities and limitations. - Custom benchmarks can also be designed using tools like Eval Studio to systematically test models on specific applications or scenarios. Both automated and human evaluations are important. - Leaderboards like HELM aggregate benchmark results to compare how different models perform across a wide range of tests and metrics.

Pritika Mehta, Co-Founder, Butternut.ai H2O Open Source GenAI World SF 2023

The document discusses LLMOps (Large Language Model Operations) compared to traditional MLOps. Some key points: - LLMOps and MLOps face similar challenges across the development lifecycle, but LLMOps requires more GPU resources and integration is faster due to more models in each application. Evaluation is also less clear. - The LLMOps field is around the 5th generation of models, with debates around proprietary vs open source models, and balancing privacy, cost and control. - LLMOps platforms are emerging to provide solutions for tasks like prompting, embedding databases, evaluation, and governance, similar to how MLOps platforms have evolved.

The document discusses optimizing question answering systems called RAG (Retrieve-and-Generate) stacks. It outlines challenges with naive RAG approaches and proposes solutions like improved data representations, advanced retrieval techniques, and fine-tuning large language models. Table stakes optimizations include tuning chunk sizes, prompt engineering, and customizing LLMs. More advanced techniques involve small-to-big retrieval, multi-document agents, embedding fine-tuning, and LLM fine-tuning.

Sandeep Singh, Head of Applied AI Computer Vision, Beans.ai H2O Open Source GenAI World SF 2023 In the modern era of machine learning, leveraging both open-source and closed-source solutions has become paramount for achieving cutting-edge results. This talk delves into the intricacies of seamlessly integrating open-source Large Language Model (LLM) solutions like Vicuna, Falcon, and Llama with industry giants such as ChatGPT and Google's Palm. As the demand for fine-tuned and specialized datasets grows, it is imperative to understand the synergy between these tools. Attendees will gain insights into best practices for building and enriching datasets tailored for fine-tuning tasks, ensuring that their LLM projects are both robust and efficient. Through real-world examples and hands-on demonstrations, this talk will equip attendees with the knowledge to harness the power of both open and closed-source tools in a coherent and effective manner.

Patrick Hall, Professor, AI Risk Management, The George Washington University H2O Open Source GenAI World SF 2023 Language models are incredible engineering breakthroughs but require auditing and risk management before productization. These systems raise concerns about toxicity, transparency and reproducibility, intellectual property licensing and ownership, disinformation and misinformation, supply chains, and more. How can your organization leverage these new tools without taking on undue or unknown risks? While language models and associated risk management are in their infancy, a small number of best practices in governance and risk are starting to emerge. If you have a language model use case in mind, want to understand your risks, and do something about them, this presentation is for you!

Dr. Alexy Khrabrov, Open Source Science Community Director, IBM H2O Open Source GenAI World SF 2023 In this talk, Dr. Alexy Khrabrov, recently elected Chair of the new Generative AI Commons at Linux Foundation for AI & Data, outlines the OSS AI landscape, challenges, and opportunities. With new models and frameworks being unveiled weekly, one thing remains constant: community building and validation of all aspects of AI is key to reliable and responsible AI we can use for business and society needs. Industrial AI is one key area where such community validation can prove invaluable.

The document announces the launch of the H2O GenAI App Store, which provides a collection of applications that make it easier for average users to leverage large language models through custom interfaces for specific tasks like getting gardening advice or feedback on code. The app store is designed to accelerate the development of these GenAI apps using the H2O Wave platform and provides access to H2OGPTE for retrieval augmented generation and language model calls. Developers can also contribute their own apps through the GitHub repository listed.

Megan Kurka, Vice President, Customer Data Scientist, H2O.ai H2O Open Source GenAI World SF 2023 Discover the transformative power of Applied Gen AI. Learn how the H2O team builds customized applications and workflows that integrate capabilities of Gen AI and AutoML specifically designed to address and enhance financial use cases. Explore real world examples, learn best practices, and witness firsthand how our innovative solutions are reshaping the landscape of finance technology.

This document discusses techniques for improving language models (LLMs) discussed in recent papers. It describes building blocks of LLMs like fine-tuning, foundation training, memory, and databases. Specific techniques covered include LIMA which uses 1,000 carefully curated examples, instruction backtranslation to generate question-answer pairs, fine-tuning models on API examples like Gorilla, and reducing false answers through techniques like not agreeing with incorrect user opinions. The goal is to discuss cutting edge tricks to build better LLMs.

Pascal Pfeiffer, Principal Data Scientist, H2O.ai H2O Open Source GenAI World SF 2023 This talk dives into the expansive ecosystem of Large Language Models (LLMs), offering practitioners an insightful guide to various relevant applications, from natural language understanding to creative content generation. While exploring use cases across different industries, it also honestly addresses the current limitations of LLMs and anticipates future advancements.

- Jon McKinney, Director of Research, H2O.ai - Arno Candel, Chief Technology Officer, H2O.ai H2O Open Source GenAI World SF 2023

This document discusses using large language models (LLMs) for text classification tasks. It begins by describing how LLMs are commonly used for text generation and question answering. For classification, models are usually trained supervised on labeled data. The document then explores using LLMs for zero-shot classification without training, and techniques like fine-tuning LLMs on tasks to improve performance. It provides an example of fine-tuning an LLM on a financial sentiment dataset. The document concludes by describing H2O.ai's LLM Studio tool for fine-tuning and a few Kaggle competitions where LLMs achieved success in text classification.

1) Generative AI (GenAI) enables the creation of novel content by learning patterns in unstructured data rather than labeling outputs like traditional AI. 2) Both traditional and generative AI models lack transparency and may contain biases, but generative models can additionally hallucinate or leak private information. 3) To interpret generative models, researchers evaluate accuracy globally by checking for hallucinations or undesirable content, and locally by confirming the quality of individual responses.

Luiz Pizzato, Executive Manager Artificial Intelligence, Commonwealth Bank H2O Open Source GenAI World SF 2023