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Go Beyond the Hype and Get Started with Generative AI
Generative AI is all the hype in the realm of data science and artificial intelligence right now. Tools like ChatGPT, Craiyon, DALL-E, Stable Diffusion, Whisper, and more are changing the modern landscape of AI, with even non-data science individuals becoming interested in the topic. During the ODSC West Generative AI conference track, you’ll gain core skills needed to become a part of this movement to both develop and implement generative AI into your organization or research.
What You'll Learn
Talks + Workshops + Special Events on these topics:
Topics
How to use generative AI in practice
The ethical use of generative AI
Generative adversarial models
Tools like Stable Diffusion, ChatGPT, DALL-E, and more
Deep learning models to develop these tools
Business models & use cases
and more…
Some of Our Confirmed Generative AI Speakers
Yaron Haviv
Yaron Haviv is a serial entrepreneur who has been applying his deep technological experience in AI, cloud, data and networking to leading startups and enterprises since the late 1990s. As the Co-Founder and CTO of Iguazio, Yaron drives the strategy for the company’s MLOps platform and led the shift towards the production-first approach to data science and catering to real-time AI use cases. He also initiated and built Nuclio, a leading open source serverless framework with over 4,000 Github stars and MLRun, a cutting-edge open source MLOps orchestration framework.
Prior to co-founding Iguazio in 2014, Yaron was the Vice President of Datacenter Solutions at Mellanox (now NVIDIA – NASDAQ: NVDA), where he led technology innovation, software development and solution integrations. He also served as the CTO and Vice President of R&D at Voltaire, a high-performance computing, IO and networking company which floated on the NYSE in 2007 and was later acquired by Mellanox (NASDAQ:MLNX).
Yaron is an active contributor to the CNCF Working Group and was one of the foundation’s first members. He sits on the Data Science Committee of the AI Infrastructure Alliance (AIIA), of which Iguazio is a founding member. He is co-authoring a book on Implementing MLOps in the Enterprise for O’Reilly. Yaron presents at major industry events worldwide and writes tech content for leading publications including TheNewStack, Hackernoon, DZone,Towards Data Science and more.
Implementing Gen AI in Practice(Track Keynote)
Alison Cossette
Alison Cossette is a dynamic Data Science Strategist, Educator, and Podcast Host. As a Developer Advocate at Neo4j specializing in Graph Data Science, she brings a wealth of expertise to the field. With her strong technical background and exceptional communication skills, Alison bridges the gap between complex data science concepts and practical applications.
Alison’s passion for responsible AI shines through in her work. She actively promotes ethical and transparent AI practices and believes in the transformative potential of responsible AI for industries and society. Through her engagements with industry professionals, policymakers, and the public, she advocates for the responsible development and deployment of AI technologies.
Alison’s academic journey includes pursuing her Master of Science in Data Science program, specializing in Artificial Intelligence, at Northwestern University and research with Stanford University Human-Computer Interaction Crowd Research Collective. Alison combines academic knowledge with real-world experience. She leverages this expertise to educate and empower individuals and organizations in the field of data science.
Overall, Alison Cossette’s multifaceted background, commitment to responsible AI, and expertise in data science make her a respected figure in the field. Through her role as a Developer Advocate at Neo4j and her podcast, she continues to drive innovation, education, and responsible practices in the exciting realm of data science and AI.
Bridging the Gap: Light Code Solutions to Uniting Social Science and Modern Knowledge Graphs(Workshop)
David Mertz, Ph.D.
David is founder of KDM Training, a partnership dedicated to educating developers and data scientists in machine learning and scientific computing. He created the data science training program for Anaconda Inc. and was a senior trainer for them. With the advent of deep neural networks he has turned to training our robot overlords as well.
He was honored to work for 8 years with D. E. Shaw Research, who have built the world’s fastest, highly-specialized (down to the ASICs and network layer), supercomputer for performing molecular dynamics.
David was a Director of the PSF for six years, and remains co-chair of its Trademarks Committee and of its Scientific Python Working Group. His columns, Charming Python and XML Matters, written in the 2000s, were the most widely read articles in the Python world. He has written previous books for Manning, Packt, O’Reilly and Addison-Wesley, and has given keynote addresses at numerous international programming conferences.
Amy Hodler
Amy Hodler is an evangelist for graph analytics and responsible AI. She’s the co-author of O’Reilly books on Graph Algorithms and Knowledge Graphs as well as a contributor to the Routledge book, Massive Graph Analytics and Bloomsbury book, AI on Trial. Amy has decades of experience in emerging tech at companies such as Microsoft, Hewlett-Packard (HP), Hitachi IoT, Neo4j, Cray, and RelationalAI. Amy is the founder of GraphGeeks.org promoting connections everywhere.
Jim Dowling
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 conference and featurestore.org community, as well as co-organizer of PyData Stockholm.
Personalizing LLMs with a Feature Store(Workshop)
Michael Auli
Michael Auli is a principal research scientist/director at FAIR in Menlo Park, California. His work focuses on speech and NLP and he helped create projects such as wav2vec/data2vec, the widely used fairseq toolkit, the first modern feed-forward seq2seq models outperforming RNNs for NLP, and several top ranked submissions at the WMT news translation task in 2018 and 2019. Before that Michael was at Microsoft Research, where he did early work on neural machine translation and using neural language models for conversational applications. During his PhD at the University of Edinburgh he worked on natural language processing and parsing. http://michaelauli.github.io
General and Efficient Self-supervised Learning with data2vec(Talk)
Lukas Biewald
Lukas Biewald is the CEO and co-founder of Weights & Biases, a developer-first MLOps platform. He also co-founded Figure Eight (formerly CrowdFlower), a pioneer in the ML data-labeling space. Figure Eight was acquired by Appen (APX) in 2019. Lukas has dedicated his career to optimizing ML workflows, teaching ML practitioners, making machine learning more accessible to all, and occasionally tinkering with robots.
Amber Roberts
Amber Roberts is a ML Growth Lead at Arize AI, a ML observability company built for maintaining models in production. Previously, Amber was a product manager of AI at Splunk and the Head of Artificial Intelligence at Insight Data Science. A Carnegie Fellow, Amber has an MS in Astrophysics from the Universidad de Chile.
Troubleshooting Large Language Models in Production with Embeddings and Evals(Talk)
Jerry Liu
Jerry is the co-founder/CEO of LlamaIndex, an open-source tool that provides a central data management/query interface for your LLM application. Before this, he has spent his career at the intersection of ML, research, and startups. He led the ML monitoring team at Robust Intelligence, did self-driving AI research at Uber ATG, and worked on recommendation systems at Quora. He graduated from Princeton in 2017 with a degree in CS.
Building LLM-powered Knowledge Workers over your Data with LlamaIndex(Workshop)
Rajiv Shah, PhD
Rajiv Shah is a machine learning engineer at Hugging Face who focuses on enabling enterprise teams to succeed with AI. Rajiv is a leading expert in the practical application of AI. Previously, he led data science enablement efforts across hundreds of data scientists at DataRobot. He was also a part of data science teams at Snorkel AI, Caterpillar, and State Farm. Rajiv is a widely recognized speaker on AI, published over 20 research papers, and received over 20 patents, including sports analytics, deep learning, and interpretability. Rajiv holds a PhD in Communications and a Juris Doctor from the University of Illinois at Urbana Champaign. While earning his degrees, he received a fellowship in Digital Government from the John F. Kennedy School of Government at Harvard University. He also has a large following on AI-related short videos on Tik Tok and Instagram at @rajistics.
Evaluation Techniques for Large Language Models(Tutorial)
Walid S. Saba
Walid Saba is a Senior Research Scientist at the Institute for Experiential AI at Northeastern University. Prior to joining the institute in 2023, he worked at two Silicon Valley startups, focusing on conversational AI. This work included high-level roles as the principal AI scientist for telecommunications company Astound and CTO of software company Klangoo, where he helped develop its state-of-the-art digital content semantic engine (Magnet).
Saba’s career to date has seen him hold various positions in both the private sector and academia. His resume includes entities such as the American Institutes for Research, AT&T Bell Labs, IBM and Cognos, while he has also spent a cumulative seven years teaching computer science at the University of Ottawa, the New Jersey Institute of Technology (NJIT), the University of Windsor (a public research university in Ontario, Canada), and the American University of Beirut (AUB).
Walid is frequent invited for interviews and as a keynote speaker on AI and NLP has published over 45 technical articles, including an award-winning paper that he presented at the German Artificial Intelligence Conference (KI-2008). Walid received his BSc and MSc in Computer Science from the University of Windsor, and a Ph.D in Computer Science from Carleton University in 1999.
Eli Chen
Eli is CTO and Co-Founder at Credo AI. He has led teams building secure and scalable software at companies like Netflix and Twitter. Eli has a passion for unraveling how things work and debugging hard problems. Whether it’s using cryptography to secure software systems or designing distributed system architecture, he is always excited to learn and tackle new challenges. Eli graduated with an Electrical Engineering and Computer Science degree from U.C. Berkeley.
Valentina Alto
Valentina is a Data Science MSc graduate and Cloud Specialist at Microsoft, focusing on Analytics and AI workloads within the manufacturing and pharmaceutical industry since 2022. She has been working on customers’ digital transformations, designing cloud architecture and modern data platforms, including IoT, real-time analytics, Machine Learning, and Generative AI. She is also a tech author, contributing articles on machine learning, AI, and statistics, and recently published a book on Generative AI and Large Language Models.
In her free time, she loves hiking and climbing around the beautiful Italian mountains, running, and enjoying a good book with a cup of coffee.
The AI Paradigm Shift: Under the Hood of a Large Language Models(Workshop)
Sinan Ozdemir
Sinan Ozdemir is a mathematician, data scientist, NLP expert, lecturer, and accomplished author. He is currently applying my extensive knowledge and experience in AI and Large Language Models (LLMs) as the founder and CTO of LoopGenius, transforming the way entrepreneurs and startups market their products and services.
Simultaneously, he is providing advisory services in AI and LLMs to Tola Capital, an innovative investment firm. He has also worked as an AI author for Addison Wesley and Pearson, crafting comprehensive resources that help professionals navigate the complex field of AI and LLMs.
Previously, he served as the Director of Data Science at Directly, where my work significantly influenced their strategic direction. As an official member of the Forbes Technology Council from 2017 to 2021, he shared his insights on AI, machine learning, NLP, and emerging technologies-related business processes.
He holds a B.A. and an M.A. in Pure Mathematics (Algebraic Geometry) from The Johns Hopkins University, and he is an alumnus of the Y Combinator program. Sinan actively contribute to society through various volunteering activities.
Sinan’s skill set is strongly endorsed by professionals from various sectors and includes data analysis, Python, statistics, AI, NLP, theoretical mathematics, data science, function analysis, data mining, algorithm development, machine learning, game-theoretic modeling, and various programming languages.
Aligning Open-source LLMs Using Reinforcement Learning from Feedback(Workshop)
Martin Musiol
Long before the buzz surrounding generative AI, Martin Musiol was already advocating for its significance in 2015. Since then, he has been a frequent speaker at conferences, podcasts, and panel discussions, addressing the technological advancements, practical applications, and ethical considerations of generative AI. Martin Musiol is a founder of generativeAI.net, a lecturer on AI to over 3000 students, and publisher of the newsletter ‘Generative AI: Short & Sweet’. As the lead for GenAI Projects in Europe at Infosys Consulting (previously at IBM), Martin Musiol helps companies globally harness the power of generative AI to gain a competitive advantage. -> https://www.linkedin.com/in/martinmusiol1/ and his webpage: https://generativeai.net/
Nirmal Budhathoki
Nirmal Budhathoki is a Senior Data Scientist, who is currently working at Microsoft in Cloud Security. Nirmal has over 12+ years of experience in the IT industry, including 5+ years in data science. Nirmal’s strong belief in continuous learning has led him to complete three master’s degrees with majors on: Information Systems, Business Administration, and Data Science. Nirmal loves to help the data science community and has completed over 600+ free mentoring sessions with aspiring data scientists to help them navigate their data science career. Nirmal also conducts mentored learning sessions for MiT’s Data Science and Machine Learning certification program in collaboration with Great Learning. Nirmal has experience working with the US government for the Department of Navy, and he is also a US army veteran. Nirmal yearns to solve data science problems that are aligned with product strategy and business outcomes. In his free time, Nirmal loves using this data science skills in sports analytics.
Mike Taylor
Mike is a data-driven, technical marketer who built a 50 person marketing agency (Ladder), and 300k people have taken his online courses (LinkedIn, Udemy, Vexpower). He now works freelance on generative AI projects, and is writing a book on Prompt Engineering for O’Reilly Media.
Sandeep Singh
Sandeep Singh is a leader in applied AI and computer vision in Silicon Valley’s mapping industry, and he is at the forefront of developing cutting-edge technology to capture, analyze and understand satellite imagery, visual and location data. With a deep expertise in computer vision algorithms, machine learning and image processing and applied ethics, Sandeep is responsible for creating innovative solutions that enable mapping and navigation software to accurately and efficiently identify and interpret features to remove inefficiencies of logistics and mapping solutions. His work includes developing sophisticated image recognition systems, building 3D mapping models, and optimizing visual data processing pipelines for use in logistics, telecommunications and autonomous vehicles and other mapping applications. With a keen eye for detail and a passion for pushing the boundaries of what’s possible with AI and computer vision, Sandeep’s leadership is driving the future of applied AI forward.
Stable Diffusion: A New Frontier for Text-to-Image Paradigm(Workshop)
Kabir Nagrecha
Kabir Nagrecha is a Ph.D. candidate at UC San Diego, working with Professors Arun Kumar & Hao Zhang. His work focuses on systems infrastructure to support deep learning at scale, aiming to democratize large models and amplify the impact of machine learning applications. He is the recipient of the Meta Research Fellowship, as well as fellowships from the Halicioglu Data Science Institute and Jacobs School of Engineering at UCSD.
Kabir is the youngest-ever Ph.D. student at UCSD, having started his doctorate at the age of 17. He’s previously worked with companies such as Apple, Meta, & Netflix to build the core infrastructure that supports widely-used services such as Siri & Netflix’s recommendation algorithms. Most recently, he’s been working on Saturn, a new system to support automatic parallelization, scheduling, and resource apportioning for training large neural networks.
Democratizing Fine-tuning of Open-Source Large Models with Joint Systems Optimization(Talk)
Suhas Pai
Suhas Pai is a NLP researcher and co-founder/CTO at Bedrock AI, a Toronto based startup. At Bedrock AI, he works on text ranking, representation learning, and productionizing LLMs. He is also currently writing a book on Designing Large Language Model Applications with O’Reilly Media. Suhas has been active in the ML community, being the Chair of the TMLS (Toronto Machine Learning Summit) conference since 2021 and also NLP lead at Aggregate Intellect (AISC). He was also co-lead of the Privacy working group at Big Science, as part of the BLOOM project.
Beyond Demos and Prototypes: How to Build Production-Ready Applications Using Open-Source LLMs(Workshop)
Why Attend
Immerse yourself in talks and workshops on Generative AI
With numerous introductory level workshops, get hands-on experience to quickly build up your skills
Post-conference, get access to recorded talks online and learn from over 100+ high-quality recording sessions that let you review content at your own pace
Take time out of your busy schedule to accelerate your knowledge of the latest advances in data science
Learn directly from world-class instructors who are the authors of and contributors to many of the tools and frameworks used in quant finance today
Meet hiring companies ranging from hot startups to Fortune 500s looking to hire professionals with data science skills at all levels
Get speaker insights and training in AI frameworks such as TensorFlow, MXNet, PyTorch, Spark, Storm, Drill, Keras, and other AI platforms
Get access to other focus area content, including ML/DL, Data Visualization Big Data, and Open Data Science
More Reasons To Attend?
Download the why attend guideWho should attend
Data scientists looking to use generative AI in their work
AI researchers who want to understand more about the field
Students who can benefit from getting a head start on an emerging topic
Decision makers who can implement generative AI into their business
Programmers who can use AI to supplement and improve their work
Professionals from all verticals to see how they can use generative AI to make their lives easier
Educators so they can prepare for a changing landscape
Anyone else interested in the latest trend in AI!
ODSC WEST 2023 - Oct 30th – Nov 2nd
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