Send us a text Part 2 : With Roger Premo, General Manager, Corporate Strategy and Ventures. We transition from 5 truths on GenAI to 5 truths on Hybrid Cloud. Everything inquiring minds want to know! 01:40 Hybrid Cloud02:32 Truth #6, ROI on Cloud13:51 #7, Hybrid Multi-cloud is the Norm18:06 Hybrid Landscapes Today20:50 #8, Hybrid is Not Just for Large Enterprises23:17 Multi-cloud Affordability25:40 #9, Open Source Wins32:23 Lock-in34:53 Final #10, Hybrid by Design40:30 Getting Started45:15 Summarizing IT TruthsLinkedin: https://www.linkedin.com/in/ropremo/ Website: https://www.ibm.com 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. 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.
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10 years after its creation, Airflow is stronger than ever: in last year’s Airflow survey, 81% of users said Airflow is important or very important to their business, 87% said their Airflow usage has grown over time, and 92% said they would recommend Airflow. In this panel discussion, we’ll celebrate a decade of Airflow and delve into how it became the highly recommended industry standard it is today, including history, pivotal moments, and the role of the community. Our panel of seasoned experts will also talk about where Airflow is going next, including future use cases like generative AI and the highly anticipated Airflow 3.0. Don’t miss this insightful exploration into one of the most influential tools in the data landscape.
This talk will explore ASAPP’s use of Apache Airflow to streamline and optimize our machine learning operations (MLOps). Key highlights include: Integrating with our custom Spark solution for achieving speedup, efficiency, and cost gains for generative AI transcription, summarization and intent categorization pipelines Different design patterns of integrating with efficient LLM servers - like TGI/vllm/tensor-RT for Summarization pipelines with/without Spark. An overview of batched LLM inference using Airflow as opposed to real time inference outside of it [Tentative] Possible extension of this scaffolding to Reinforcement Learning from Human Feedback (RLHF) and Reinforcement Learning from AI Feedback (RLAIF) for fine-tuning LLMs, using Airflow as the orchestrator. Additionally, the talk will cover ASAPP’s MLOps journey with Airflow over the past few years, including an overview of our cloud infrastructure, various data backends, and sources. The primary focus will be on the machine learning workflows at ASAPP, rather than the data workflows, providing a detailed look at how Airflow enhances our MLOps processes.
Laurel provides an AI-driven timekeeping solution tailored for accounting and legal firms, automating timesheet creation by capturing digital work activities. This session highlights two notable AI projects: UTBMS Code Prediction: Leveraging small language models, this system builds new embeddings to predict work codes for legal bills with high accuracy. More details are available in our case study: https://www.laurel.ai/resources-post/enhancing-legal-and-accounting-workflows-with-ai-insights-into-work-code-prediction . Bill Creation and Narrative Generation: Utilizing Retrieval-Augmented Generation (RAG), this approach transforms users’ digital activities into fully billable entries. Additionally, we will discuss how we use Airflow for model management in these AI projects: Daily Model Retraining: We retrain our models daily Model (Re)deployment: Our Airflow DAG evaluates model performance, redeploying it if improvements are detected Cost Management: To avoid high costs associated with querying large language models frequently, our DAG utilizes RAG to efficiently summarize daily activities into a billable timesheet at day’s end.
Gen AI has taken the computing world by storm. As Enterprises and Startups have started to experiment with LLM applications, it has become clear that providing the right context to these LLM applications is critical. This process known as Retrieval augmented generation (RAG) relies on adding custom data to the large language model, so that the efficacy of the response can be improved. Processing custom data and integrating with Enterprise applications is a strength of Apache Airflow. This talk goes into details about a vision to enhance Apache Airflow to more intuitively support RAG, with additional capabilities and patterns. Specifically, these include the following Support for unstructured data sources such as Text, but also extending to Image, Audio, Video, and Custom sensor data LLM model invocation, including both external model services through APIs and local models using container invocation. Automatic Index Refreshing with a focus on unstructured data lifecycle management to avoid cumbersome and expensive index creation on Vector databases Templates for hallucination reduction via testing and scoping strategies
Every data team out there is being asked from their business stakeholders about Generative AI. Taking LLM centric workloads to production is not a trivial task. At the foundational level, there are a set of challenges around data delivery, data quality, and data ingestion that mirror traditional data engineering problems. Once you’re past those, there’s a set of challenges related to the underlying use case you’re trying to solve. Thankfully, because of how Airflow was already being used at these companies for data engineering and MLOps use cases, it has become the defacto orchestration layer behind many GenAI use cases for startups and Fortune 500s. This talk will be a tour of various methods, best practices, and considerations used in the Airflow community when taking GenAI use cases to production. We’ll focus on 4 primary use cases; RAG, fine tuning, resource management, and batch inference and take a walk through patterns different members in the community have used to productionize this new, exciting technology.
Nowadays, conversational AI is no longer exclusive to large enterprises. It has become more accessible and affordable, opening up new possibilities and business opportunities. In this session, discover how you can leverage Generative AI as your AI pair programmer to suggest DAG code and recommend entire functions in real-time, directly from your editor. Visualize how to harness the power of ML, trained on billions of lines of code, to transform natural language prompts into coding suggestions. Seamlessly cycle through lines of code, complete function suggestions, and choose to accept, reject, or edit them. Witness firsthand how Generative AI provides recommendations based on the project’s context and style conventions. The objective is to equip you with techniques that allow you to spend less time on boilerplate and repetitive code patterns, and more time on what truly matters: building exceptional orchestration software.
In the last few years Large Language Models (LLMs) have risen to prominence as outstanding tools capable of transforming businesses. However, bringing such solutions and models to the business-as-usual operations is not an easy task. In this session, we delve into the operationalization of generative AI applications using MLOps principles, leading to the introduction of foundation model operations (FMOps) or LLM operations using Apache Airflow. We further zoom into aspects of expected people and process mindsets, new techniques for model selection and evaluation, data privacy, and model deployment. Additionally, know how you can use the prescriptive features of Apache Airflow to aid your operational journey. Whether you are building using out of the box models (open-source or proprietary), creating new foundation models from scratch, or fine-tuning an existing model, with the structured approaches described you can effectively integrate LLMs into your operations, enhancing efficiency and productivity without causing disruptions in the cloud or on-premises.
This book teaches solutions architects how to effectively design and implement AI/ML solutions utilizing Google Cloud services. Through detailed explanations, examples, and hands-on exercises, you will understand essential AI/ML concepts, tools, and best practices while building advanced applications. What this Book will help me do Build robust AI/ML solutions using Google Cloud tools such as TensorFlow, BigQuery, and Vertex AI. Prepare and process data efficiently for machine learning workloads. Establish and apply an MLOps framework for automating ML model lifecycle management. Implement cutting-edge generative AI solutions using best practices. Address common challenges in AI/ML projects with insights from expert solutions. Author(s) Kieran Kavanagh is a seasoned principal architect with nearly twenty years of experience in the tech industry. He has successfully led teams in designing, planning, and governing enterprise cloud strategies, and his wealth of experience is distilled into the practical approaches and insights in this book. Who is it for? This book is ideal for IT professionals aspiring to design AI/ML solutions, particularly in the role of solutions architects. It assumes a basic knowledge of Python and foundational AI/ML concepts but is suitable for both beginners and seasoned practitioners. If you're looking to deepen your understanding of state-of-the-art AI/ML applications on Google Cloud, this resource will guide you.
Send us a text Part 1 : Let's talk IBM's view on IT Strategy with Roger Premo, General Manager, Corporate Strategy and Ventures. This is Roger's 5 truths on GenAI.
01:31 Roger Premo is BACK02:37 IBM's Ventures08:06 10 Truths of GenAI and Hybrid Cloud08:39 Let's Start with Facts13:37 The First Truth : Multi-model 18:41 Second Truth : GenAI will be Hybrid Multi-cloud23:36 Third Truth : Gov and Security are a Must27:42 Truth Four : Data is the Competitive Advantage33:00 Five : Scaling for ROI Remains Challenging39:12 How to Start with AI47:38 Roger's LearningLinkedin: https://www.linkedin.com/in/ropremo/ Website: https://www.ibm.com 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. 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.
All the hype around generative AI means that every software maker seems to be stuffing chat interfaces into their products whenever they can. For the most part, the jury is still out on whether this is a good idea or not. However, design goes deeper than just the user interface, so it’s also useful to know about how the designs interact with the rest of the software. Once you move beyond chatbots into things like agents, there are also thorny questions around which bits of your workflow should still be done by a human, and which bits can be completely automated. True insight in this context lies in a gray area, across software, UX and AI. Robb is an AI researcher, technologist, designer, innovator, serial entrepreneur, and author. He is a contributor to Harvard Business Review and the visionary behind, OneReach.ai, the award winning conversational artificial intelligence platform that ranked highest in Gartner's Critical Capabilities Report for Enterprise Conversational AI Platforms. He earned an Academy Award nomination for technical achievement as well as over 130 innovation, design, technology, and artificial intelligence awards, with five in 2019 including AI Company of the Year and Hot AI Technology of the Year. Robb is a pioneer in the user research and technology spaces. He founded EffectiveUI, a user experience and technology research consultancy for the Fortune 500, which was acquired by WPP and integrated into the core of Ogilvy’s digital experience practice. He also created UX Magazine, one of the first and largest XD (experience design) thought leadership communities. In the episode, Richie and Robb explore chat interfaces in software, the advantages of chat interfaces over other methods of interaction with data & AI products, geospatial vs language memory, good vs bad chat interfaces, the importance of a human in the loop, personality in chatbots, handling hallucinations and bad responses, scaling chatbots, agents vs chatbots, ethical considerations for AI and chatbots and much more. Links Mentioned in the Show: Onereach.aiInvisible Machines PodcastGartner: The Executive Guide to Hyperautomation[Skill Track] Developing AI ApplicationsRelated Episode: Building Human-Centered AI Experiences with Haris Butt, Head of Product Design at ClickUpSign up to RADAR: AI Edition New to DataCamp? Learn on the go using the DataCamp mobile app Empower your business with world-class data and AI skills with DataCamp for business
Speaker: Jide Ogunjobi (Founder & CTO at Context Data)
This tech talk is a part of the Data Engineering Open Forum at Netflix 2024. As organizations accumulate ever-larger stores of data across disparate systems, efficiently querying and gaining insights from enterprise data remain ongoing challenges. To address this, we propose developing an intelligent agent that can automatically discover, map, and query all data within an enterprise. This “Enterprise Data Model/Architect Agent” employs generative AI techniques for autonomous enterprise data modeling and architecture.
If you are interested in attending a future Data Engineering Open Forum, we highly recommend you join our Google Group (https://groups.google.com/g/data-engineering-open-forum) to stay tuned to event announcements.
The Generative AI Hub serves as the Generative AI layer on top of the AI Core. As the field rapidly evolves, our goal is not only to keep pace, but also to filter and select the technologies that are most relevant to our users and businesses. But we are not just about making technology accessible. It is about lowering the barriers to using it, providing business AI functionalities and capabilities that simplify and shorten the path to an enterprise-ready application for the SAP ecosystem. In this presentation, I will give a brief overview of our offerings and demonstrate the potential of what can be built with them.
Do you have questions about privacy and compliance when it comes to using or building generative AI applications? Join this session for a deep dive on privacy and compliance challenges and considerations that you should be aware of as you embark on your generative AI journey. Gain insights into different generative AI use cases, and learn about what is happening around the world with regard to AI regulation and standards and the impact that they may have on your applications.
Learn more about AWS re:Inforce at https://go.aws/reinforce.
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ABOUT AWS Amazon Web Services (AWS) hosts events, both online and in-person, bringing the cloud computing community together to connect, collaborate, and learn from AWS experts.
AWS is the world's most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies—are using AWS to lower costs, become more agile, and innovate faster.
reInforce2024 #CloudSecurity #AWS #AmazonWebServices #CloudComputing
Today, we’re joined by Shawn Olds, Co-founder and Co-Chief Executive Officer at boodleAI, providers of BoodleBox, the GenAI GroupChat that brings people, AI assistants, and knowledge together. We talk about:
The value of “flipping the script,” where AI prompts the userWhat needs for human expertise remain as AI advances?2 main ways you can help reduce AI hallucinationsPrepare for meetings & interviews by having AI adopt the role of your colleague
Arguably one of the verticals that is both at the same time most ripe for disruption by AI and the hardest to disrupt is search. We've seen many attempts at reimagining search using AI, and many are trying to usurp Google from its throne as the top search engine on the planet, but I think no one is laying the case better for AI assisted search than perplexity. AI. Perplexity doesn't need an introduction. It is an AI powered search engine that lets you get the information you need as fast as possible. Denis Yarats is the Co-Founder and Chief Technology Officer of Perplexity AI. He previously worked at Facebook as an AI Research Scientist. Denis Yarats attended New York University. His previous research interests broadly involved Reinforcement Learning, Deep Learning, NLP, robotics and investigating ways of semi-supervising Hierarchical Reinforcement Learning using natural language. In the episode, Adel and Denis explore Denis’ role at Perplexity.ai, key differentiators of Perplexity.ai when compared to other chatbot-powered tools, culture at perplexity, competition in the AI space, building genAI products, the future of AI and search, open-source vs closed-source AI and much more. Links Mentioned in the Show: Perplexity.aiNeurIPS Conference[Course] Artificial Intelligence (AI) StrategyRelated Episode: The Power of Vector Databases and Semantic Search with Elan Dekel, VP of Product at PineconeSign up to RADAR: AI Edition New to DataCamp? Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business
As an increasing number of organizations leverage internal data for optimizing outputs in generative AI through Retrieval Augmented Generation (RAG), concerns about potential internal data leaks have grown. This talk delves into strategies for securely transmitting and storing the internal data used in RAG. Additionally, explore methods for identifying sensitive data and learn about best practices for subsequent measures to address these concerns.
Learn more about AWS re:Inforce at https://go.aws/reinforce.
Subscribe: More AWS videos: http://bit.ly/2O3zS75 More AWS events videos: http://bit.ly/316g9t4
ABOUT AWS Amazon Web Services (AWS) hosts events, both online and in-person, bringing the cloud computing community together to connect, collaborate, and learn from AWS experts.
AWS is the world's most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies—are using AWS to lower costs, become more agile, and innovate faster.
reInforce2024 #CloudSecurity #AWS #AmazonWebServices #CloudComputing
Many companies are excited to build products using generative AI, but these large language models require protections against jailbreaking to help ensure safe, ethical use. This lightning talk covers best practices for protecting your generative AI application against threats that could make models behave undesirably. Explore approaches to mitigate risks from the start, helping you build responsibly.
Learn more about AWS re:Inforce at https://go.aws/reinforce.
Subscribe: More AWS videos: http://bit.ly/2O3zS75 More AWS events videos: http://bit.ly/316g9t4
ABOUT AWS Amazon Web Services (AWS) hosts events, both online and in-person, bringing the cloud computing community together to connect, collaborate, and learn from AWS experts.
AWS is the world's most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies—are using AWS to lower costs, become more agile, and innovate faster.
reInforce2024 #CloudSecurity #AWS #AmazonWebServices #CloudComputing
Generative AI–based applications have the most business impact when they have access to critical business data and are empowered to take actions on behalf of the user. However, these integrations raise important security questions outlined in the OWASP Top 10 for LLM vulnerabilities and NIST Adversarial Machine Learning frameworks. This lightning talk introduces high-level architectural patterns to effectively mitigate key OWASP Top 10 for LLM vulnerabilities through Zero Trust principles. Leave this talk with best practices for building generative AI applications accessing sensitive business data using Agents for Amazon Bedrock.
Learn more about AWS re:Inforce at https://go.aws/reinforce.
Subscribe: More AWS videos: http://bit.ly/2O3zS75 More AWS events videos: http://bit.ly/316g9t4
ABOUT AWS Amazon Web Services (AWS) hosts events, both online and in-person, bringing the cloud computing community together to connect, collaborate, and learn from AWS experts.
AWS is the world's most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies—are using AWS to lower costs, become more agile, and innovate faster.
reInforce2024 #CloudSecurity #AWS #AmazonWebServices #CloudComputing
The security and privacy of data during the training, fine-tuning, and inferencing phases of generative AI are paramount. This lightning talk introduces a reference architecture designed to use the security of AWS PrivateLink with generative AI applications. Explore the importance of protecting proprietary data in applications that leverage both AWS native LLMs and ISV-supplied external data stores. Learn about the secure movement and usage of data, particularly for RAG processes, across various data sources like Amazon S3, vector databases, and Snowflake. Learn how this reference architecture not only meets today’s security demands but also sets the stage for the future of secure generative AI development.
Learn more about AWS re:Inforce at https://go.aws/reinforce.
Subscribe: More AWS videos: http://bit.ly/2O3zS75 More AWS events videos: http://bit.ly/316g9t4
ABOUT AWS Amazon Web Services (AWS) hosts events, both online and in-person, bringing the cloud computing community together to connect, collaborate, and learn from AWS experts.
AWS is the world's most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies—are using AWS to lower costs, become more agile, and innovate faster.