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Aug 8 - AI, Machine Learning and Computer Vision Meetup
2024-08-08 · 17:00
When August 8, 2024 – 10:00 AM Pacific / 1:00 PM Eastern Where Virtual Register for the Zoom: https://voxel51.com/computer-vision-events/ai-machine-learning-computer-vision-meetup-aug-8-2024/ GenAI for Video: Diffusion-Based Editing and Generation Recently, diffusion-based generative AI models have gained popularity due to their wide applications in the image domain. Additionally, there is growing attention to the video domain because of its ubiquitous presence in real-world applications. In this talk, we will discuss the future of GenAI in the video domain, highlighting recent advancements and exploring its potential and impact on video editing and generation. We will also examine the challenges and opportunities these technologies present, offering insights into how they can revolutionize the video industry. About the Speaker Ozgur Kara is a PhD student in the Computer Science Department at the University of Illinois at Urbana-Champaign. He earned his Bachelor’s degree in Electrical and Electronics Engineering from Boğaziçi University. His research focuses on generative AI and computer vision, particularly on generative AI and its applications in video. Evaluating RAG Models for LLMs: Key Metrics and Frameworks Evaluating the model performance is the key for ensuring effectiveness and reliability of LLM models. In this talk, we will look into the intricate world of RAG evaluation metrics and frameworks, exploring the various approaches to assessing model performance. We will discuss key metrics such as relevance, diversity, coherence, and truthfulness and examine various evaluation frameworks, ranging from traditional benchmarks to domain-specific assessments, highlighting their strengths, limitations, and potential implications for real-world applications. About the Speaker Abi Aryan is the founder of Abide AI and a machine learning engineer with over eight years of experience in the ML industry building and deploying machine learning models in production for recommender systems, computer vision, and natural language processing—within a wide range of industries such as ecommerce, insurance, and media and entertainment. Previously, she was a visiting research scholar at the Cognitive Sciences Lab at UCLA where she worked on developing intelligent agents. Also, she has authored research papers on AutoML, multi agent systems, and LLM cost modeling and evaluations and is currently authoring LLMOps: Managing Large Language Models in Production for O'Reilly Publications. Why You Should Evaluate Your End-to-End LLM applications with In-House Data This task discusses end-to-end NLP evaluations, focusing on key areas, common pitfalls, and the workings of production evaluation systems. It also explores how to fine-tune in-house LLMs as judges using custom data for more accurate performance assessments. About the Speaker Mahesh Deshwal is a Data Scientist and AI researcher with over 5.5 years of experience in using ML and AI to solve business problems, particularly in Computer Vision, NLP, recommendation, and personalization. As the author of the paper PHUDGE and an active open source contributor, he excels in delivering end-to-end solutions, from user requirements to deploying scalable models using MLOps. |
Aug 8 - AI, Machine Learning and Computer Vision Meetup
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Aug 8 - AI, Machine Learning and Computer Vision Meetup
2024-08-08 · 17:00
When August 8, 2024 – 10:00 AM Pacific / 1:00 PM Eastern Where Virtual Register for the Zoom: https://voxel51.com/computer-vision-events/ai-machine-learning-computer-vision-meetup-aug-8-2024/ GenAI for Video: Diffusion-Based Editing and Generation Recently, diffusion-based generative AI models have gained popularity due to their wide applications in the image domain. Additionally, there is growing attention to the video domain because of its ubiquitous presence in real-world applications. In this talk, we will discuss the future of GenAI in the video domain, highlighting recent advancements and exploring its potential and impact on video editing and generation. We will also examine the challenges and opportunities these technologies present, offering insights into how they can revolutionize the video industry. About the Speaker Ozgur Kara is a PhD student in the Computer Science Department at the University of Illinois at Urbana-Champaign. He earned his Bachelor’s degree in Electrical and Electronics Engineering from Boğaziçi University. His research focuses on generative AI and computer vision, particularly on generative AI and its applications in video. Evaluating RAG Models for LLMs: Key Metrics and Frameworks Evaluating the model performance is the key for ensuring effectiveness and reliability of LLM models. In this talk, we will look into the intricate world of RAG evaluation metrics and frameworks, exploring the various approaches to assessing model performance. We will discuss key metrics such as relevance, diversity, coherence, and truthfulness and examine various evaluation frameworks, ranging from traditional benchmarks to domain-specific assessments, highlighting their strengths, limitations, and potential implications for real-world applications. About the Speaker Abi Aryan is the founder of Abide AI and a machine learning engineer with over eight years of experience in the ML industry building and deploying machine learning models in production for recommender systems, computer vision, and natural language processing—within a wide range of industries such as ecommerce, insurance, and media and entertainment. Previously, she was a visiting research scholar at the Cognitive Sciences Lab at UCLA where she worked on developing intelligent agents. Also, she has authored research papers on AutoML, multi agent systems, and LLM cost modeling and evaluations and is currently authoring LLMOps: Managing Large Language Models in Production for O'Reilly Publications. Why You Should Evaluate Your End-to-End LLM applications with In-House Data This task discusses end-to-end NLP evaluations, focusing on key areas, common pitfalls, and the workings of production evaluation systems. It also explores how to fine-tune in-house LLMs as judges using custom data for more accurate performance assessments. About the Speaker Mahesh Deshwal is a Data Scientist and AI researcher with over 5.5 years of experience in using ML and AI to solve business problems, particularly in Computer Vision, NLP, recommendation, and personalization. As the author of the paper PHUDGE and an active open source contributor, he excels in delivering end-to-end solutions, from user requirements to deploying scalable models using MLOps. |
Aug 8 - AI, Machine Learning and Computer Vision Meetup
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Aug 8 - AI, Machine Learning and Computer Vision Meetup
2024-08-08 · 17:00
When August 8, 2024 – 10:00 AM Pacific / 1:00 PM Eastern Where Virtual Register for the Zoom: https://voxel51.com/computer-vision-events/ai-machine-learning-computer-vision-meetup-aug-8-2024/ GenAI for Video: Diffusion-Based Editing and Generation Recently, diffusion-based generative AI models have gained popularity due to their wide applications in the image domain. Additionally, there is growing attention to the video domain because of its ubiquitous presence in real-world applications. In this talk, we will discuss the future of GenAI in the video domain, highlighting recent advancements and exploring its potential and impact on video editing and generation. We will also examine the challenges and opportunities these technologies present, offering insights into how they can revolutionize the video industry. About the Speaker Ozgur Kara is a PhD student in the Computer Science Department at the University of Illinois at Urbana-Champaign. He earned his Bachelor’s degree in Electrical and Electronics Engineering from Boğaziçi University. His research focuses on generative AI and computer vision, particularly on generative AI and its applications in video. Evaluating RAG Models for LLMs: Key Metrics and Frameworks Evaluating the model performance is the key for ensuring effectiveness and reliability of LLM models. In this talk, we will look into the intricate world of RAG evaluation metrics and frameworks, exploring the various approaches to assessing model performance. We will discuss key metrics such as relevance, diversity, coherence, and truthfulness and examine various evaluation frameworks, ranging from traditional benchmarks to domain-specific assessments, highlighting their strengths, limitations, and potential implications for real-world applications. About the Speaker Abi Aryan is the founder of Abide AI and a machine learning engineer with over eight years of experience in the ML industry building and deploying machine learning models in production for recommender systems, computer vision, and natural language processing—within a wide range of industries such as ecommerce, insurance, and media and entertainment. Previously, she was a visiting research scholar at the Cognitive Sciences Lab at UCLA where she worked on developing intelligent agents. Also, she has authored research papers on AutoML, multi agent systems, and LLM cost modeling and evaluations and is currently authoring LLMOps: Managing Large Language Models in Production for O'Reilly Publications. Why You Should Evaluate Your End-to-End LLM applications with In-House Data This task discusses end-to-end NLP evaluations, focusing on key areas, common pitfalls, and the workings of production evaluation systems. It also explores how to fine-tune in-house LLMs as judges using custom data for more accurate performance assessments. About the Speaker Mahesh Deshwal is a Data Scientist and AI researcher with over 5.5 years of experience in using ML and AI to solve business problems, particularly in Computer Vision, NLP, recommendation, and personalization. As the author of the paper PHUDGE and an active open source contributor, he excels in delivering end-to-end solutions, from user requirements to deploying scalable models using MLOps. |
Aug 8 - AI, Machine Learning and Computer Vision Meetup
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Aug 8 - AI, Machine Learning and Computer Vision Meetup
2024-08-08 · 17:00
When August 8, 2024 – 10:00 AM Pacific / 1:00 PM Eastern Where Virtual Register for the Zoom: https://voxel51.com/computer-vision-events/ai-machine-learning-computer-vision-meetup-aug-8-2024/ GenAI for Video: Diffusion-Based Editing and Generation Recently, diffusion-based generative AI models have gained popularity due to their wide applications in the image domain. Additionally, there is growing attention to the video domain because of its ubiquitous presence in real-world applications. In this talk, we will discuss the future of GenAI in the video domain, highlighting recent advancements and exploring its potential and impact on video editing and generation. We will also examine the challenges and opportunities these technologies present, offering insights into how they can revolutionize the video industry. About the Speaker Ozgur Kara is a PhD student in the Computer Science Department at the University of Illinois at Urbana-Champaign. He earned his Bachelor’s degree in Electrical and Electronics Engineering from Boğaziçi University. His research focuses on generative AI and computer vision, particularly on generative AI and its applications in video. Evaluating RAG Models for LLMs: Key Metrics and Frameworks Evaluating the model performance is the key for ensuring effectiveness and reliability of LLM models. In this talk, we will look into the intricate world of RAG evaluation metrics and frameworks, exploring the various approaches to assessing model performance. We will discuss key metrics such as relevance, diversity, coherence, and truthfulness and examine various evaluation frameworks, ranging from traditional benchmarks to domain-specific assessments, highlighting their strengths, limitations, and potential implications for real-world applications. About the Speaker Abi Aryan is the founder of Abide AI and a machine learning engineer with over eight years of experience in the ML industry building and deploying machine learning models in production for recommender systems, computer vision, and natural language processing—within a wide range of industries such as ecommerce, insurance, and media and entertainment. Previously, she was a visiting research scholar at the Cognitive Sciences Lab at UCLA where she worked on developing intelligent agents. Also, she has authored research papers on AutoML, multi agent systems, and LLM cost modeling and evaluations and is currently authoring LLMOps: Managing Large Language Models in Production for O'Reilly Publications. Why You Should Evaluate Your End-to-End LLM applications with In-House Data This task discusses end-to-end NLP evaluations, focusing on key areas, common pitfalls, and the workings of production evaluation systems. It also explores how to fine-tune in-house LLMs as judges using custom data for more accurate performance assessments. About the Speaker Mahesh Deshwal is a Data Scientist and AI researcher with over 5.5 years of experience in using ML and AI to solve business problems, particularly in Computer Vision, NLP, recommendation, and personalization. As the author of the paper PHUDGE and an active open source contributor, he excels in delivering end-to-end solutions, from user requirements to deploying scalable models using MLOps. |
Aug 8 - AI, Machine Learning and Computer Vision Meetup
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Reimagining Deep Learning Artefact Management
2024-08-07 · 17:00
Tanay Mehta
– Kaggle Grandmaster
In this session, I will talk about using Lance file format to manage deep learning artefacts. More specifically, saving, loading and versioning model weights. I will also be demonstrating a Proof-of-Concept on this topic. |
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Open discussion: What makes a good AI application?
2024-08-07 · 17:00
Mischa van Kesteren
– Moderator
@ Nexgen Cloud
In this session we will go over some of the key considerations for a new AI application/startup, what things are often overlooked and which may be given too much weight. Then we'll have a go at putting those thoughts into practice. |
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July is almost over and on 7 August we’d like to invite you to our meetup hosted by Artefact at their office in Utrecht, directly next to the Utrecht central train station! The meetup theme is centered around how to bring GenAI to production, but not just production, production to the next level. More specifically, the Artefact team will demonstrate how they use GenAI for the generation of customized, production-ready marketing images and the Phospho team will illustrate how to integrate robust ML best practices on scales of quality metrics for GenAI products. See you there! SCHEDULE
TALKS [Talk 1]: “GenAI Image Interaction: a next step beyond LLM text chatbots" by Arthur Lambert & Priya Sarkar We've all experienced the capabilities of GenAI chatbots for data interaction. Now, it's time to explore the new GenAI innovations that Artefact is developing. Discover how GenAI is transforming marketing by accelerating asset creation and reducing costs. In this talk, we'll demonstrate how we're using GenAI to generate customized, production-ready marketing images. You'll also gain insights into automating the processes, enhancing efficiency for creativity based applications and learn about the quality metrics essential for monitoring and enhancing model performance. [Talk 2]: “Emerging best practices in Analyzing Usage Patterns and Quantifying Quality Metrics for GenAI Products" by Paul-Louis Venard & Pierre-Louis Biojout Discover how to apply machine learning (ML) emerging best practices to Generative AI (GenAI) applications, specifically focusing on Large Language Models (LLMs) and diffusion models. This talk targets ML engineers and developers aiming to enhance their GenAI products through a quantified evaluation of model quality and user interaction analysis. Learn to implement rigorous, measurable standards to improve and understand GenAI applications. The rapid advancement in Generative AI technologies, including LLMs and diffusion models, has empowered ML engineers and developers to build new and powerful products. However, the integration of robust ML best practices into the development of these products is still nascent. This session aims to bridge that gap by introducing established methodologies from traditional ML to enhance the reliability and effectiveness of GenAI applications. DIRECTIONS Directly next to the Utrecht central train station, you’ll find the Artefact office in the Creative Valley building. The address is: Stationsplein 32, 3511 ED, Utrecht. |
Next level GenAI innovation to production: image interaction and quality metrics
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Exploring the Power of LLMs and Generative AI
2023-08-24 · 15:30
Welcome to another PyData Stockholm meetup! 🌟 We're thrilled to kick off our post-summer meetup with a special focus on Large Language Models (LLMs) hosted by Google Cloud. Large Language Models (LLMs) have created a significant buzz in the AI community, captivating researchers and industry professionals alike. LLMs have the ability to generate highly coherent and contextually relevant text in response to a prompt (or query), sparking immense excitement and exploration in various applications, ranging from content generation to virtual assistants. In this meetup, we will have two talks that will give insights to LLMs in general and how to personalize LLMs with a feature store. You'll also learn about Google's advancements in developing LLMs and how they can be harnessed by consumers and enterprises alike. Join us for an exciting event featuring two thought-provoking talks on Large Language Models (LLMs) and their applications! ❗Please note that you will need to register through the above link in order to confirm your seat at the event. Agenda 17:30 - 18:00: Doors open 18:00 - 18:10: Welcome 18:10 - 18:40: Personalized LLMs with a Feature Store 18:40 - 19:10: Pizza & Beers 19:10 - 19:40: Large Language models and Generative AI at Google 19:40 - 21:00: Networking --- Presentations Personalized LLMs with a Feature Store Jim Dowling - CEO & Co-Founder, Hopsworks Large Language Models (LLMs) provide a model of the world, through a model of language. In this talk, we will walk through how to personalize a LLM using prompt-engineering with a feature store. The feature store will provide personalized history and context information for LLMs. Speaker Bio: Jim Dowling is CEO of Hopsworks and an Associate Professor at KTH Royal Institute of Technology. He is lead architect of the open-source Hopsworks Feature Store platform. He is the organizer of the annual Feature Store Summit and the Feature Store for ML community at featurestore.org. Large Language models and Generative AI at Google Zoe Tang - Customer Engineer / GenAI Specialist, Google Cloud Sweden Zoe will talk about Google's journey in developing Large Language Models and what is offered to consumers and enterprises. How large language models can be used in multiple modalities and solve different types of problems. And how they can be used in Google Cloud. Speaker Bio: Zoe is an AI + Cloud enthusiast who believes by heart that AI and ML can fundamentally change the way we live. She has 10+ years experience in the IT industry and works at Google Cloud as GenAI Specialist, primarily focusing on GenAI engagements for Sweden and Nordics customers. In her daily work, she meets with organizations to discuss how GenAI can be implemented to help them accelerate their business. --- About the event Date: August 24th, 17:30 - 21:00 Location: Google’s Office - Kungsbron 2, 111 22 Stockholm Directions: 5-7 minutes walk from T-Centralen or Hötorget stations. Tickets: Sign up required. Anyone who is not on the list will not get in. Capacity: Space is limited to 90 participants. If you are signed up but unable to attend, please let us know. Food and drinks: Pizza and drinks will be provided Questions: Please contact the meetup organizers. --- Code of Conduct The NumFOCUS Code of Conduct applies to this event; please familiarize yourself with it before attending. If you have any questions or concerns regarding the Code of Conduct, please contact the organizers. |
Exploring the Power of LLMs and Generative AI
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Berlin AWS Group Meetup - August 2023
2023-08-15 · 16:30
Dear community, we are pleased to announce the next meetup on the August 15th hosted by Babbel GmbH. This time you will have an even bigger chance to connect with your peers as Babbel has provided a large space for us and we can have more participants, so don’t miss that chance! The evening 18:30 - Warming up and networking chat 18:45 - Welcome talk 19:00 - 19:40 - Olalekan Elesin // Zero to One with LLMs on AWS This talk explores the utilization of Large Language Models (LLMs) and Amazon Web Services (AWS) to unlock new possibilities in Generative AI. The session will cover the basics introduction to LLMs and their applications, introduces AWS's ML Services such as Amazon SageMaker JumpStart and the latest offering from AWS, Amazon Bedrock. We will finally walk through how to deploy LLMs Amazon SageMaker. Attendees will gain a working understanding to deploy LLMs on AWS, and how to get started immediately. About: Olalekan has a decade of experience building data and AI products across 2 continents and 5 markets. He created AI Platform 1.0 at Scout24 and leads data platform and product teams at HRS Group. Lekan is also an AWS Machine Learning Community Hero in Germany and maintains open source projects in his free time. Description follows. 19:40 - 20:00 - Short break with snacks and drinks 20:00 - 20:40 - Mahavir Teraiya // Deconstructing the Data Mesh The concept of a Data Mesh has gained significant attention in recent years as a paradigm shift in data architecture. This talk aims to deconstruct the Data Mesh, exploring its fundamental principles, benefits, and challenges. We will delve into the decentralized data ownership and domain-oriented architecture, discussing how these concepts enable scalability and flexibility in data management. Attendees will gain a comprehensive understanding of the Data Mesh and its implications for modern data-driven organizations. About: Mahavir is a Solutions Architect at AWS, specializing in collaborating with digital native businesses to help them continuously innovate using the power of the cloud. 20:40 - 21:20 - Kimberly Schmitt et al. // Collaborative Engineering Driven Data Product Development on AWS Delivering data as a product is an outcome that many companies work to realize. Kimberly and her team are working towards making this a reality through their creation of a new B2B-based data architecture. They will share the identified requirements and challenges, their incremental delivery process, and efforts to craft this fully programmable product based on AWS services. The team continues to develop the data and the product itself, but does so with greater confidence and oversight that comes from their assumption of increased responsibility and courage to take some risks along the way. About: Babbel professionals Kimberly Schmitt and Yaniv Hamo, along with Omar Moussa from Netlight, will give a presentation on the topic. 21:20 - 21:30 Closing Announcements ======================================================================== Additional Information Would you like to host AWS UG MeetUp at your company? Register here Would you like to speak at AWS UG MeetUp? Submit your talk here |
Berlin AWS Group Meetup - August 2023
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