June 25, 2024 The Hibernia San Francisco, CA
CONNECT + COLLABORATE ON EVOLVING AI QUALITY
What is AIQCON?
AIQCon is brought to you by MLOps Community, which brings together 75,000 ML engineers and data scientists and Kolena, provider of an end-to-end ML model testing platform. This is not your average AI conference—we’re not here to gatekeep or bore you with the same conversations you’ve already had.
Our goal is to harness the power of our community to develop new GOLD STANDARDS for AI quality, bringing together renowned leaders and professionals from across the industry toward reliable AI quality solutions and standards. With three tracks led by dozens of speakers who understand the problems you’re facing daily, space for authentic networking, and entertainment that you’ll actually enjoy, we guarantee this conference will be the most fun you’ve ever had while working.
Whether you’re leading teams or an individual contributor, we know you’ll walk away with a deeper knowledge of evolving AI and tools on the market, along with new friends and collaborators to add to your network.
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WHY ATTEND AIQCON
CONNECT
Everyone is welcome! The world of machine learning can be intimidating so we invite you to come as you are—hand over imposter syndrome to the computers. Come to make new friendships and build your professional network with folks who are as passionate as you are.
LEARN + INNOVATE
Create your journey through three comprehensive specialized tracks focused on quality, rigorous, and scalable AI. Come together with speakers and fellow attendees, feel inspired to approach old problems in new ways, and share hard-earned lessons. Bring your notebooks for in-person collaboration and problem-solving!
HAVE FUN
We’re serious about learning and business, but we aren’t serious people so we’ve built in real opportunities for fun in the agenda. Lighten up with a stand-up comedy set, grab a guitar to get your creative juices flowing, and mix and mingle with new connections.
VALUE
It’s our responsibility to host things in person that deliver value and aren't replicable online. For AIQCon, we’ve curated an agenda that’s comprehensive and goes deep on evolving AI quality in one jam-packed day. Meet and engage with speakers who understand the problems you’re facing daily and learn about products firsthand that can help you achieve your quality goals. You’ll even get access to recorded sessions after the conference.
“Amazing event! Thank you for all this ultra-high density of knowledge and passion on the topic!!!” - Isabela C.
JAM-PACKED AGENDA
INNOVATIVE TALKS + PANELS
- Main Hall
- Autonomous & Robotics
- Foundational/LLM/GenAI
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10:00 AM 10:30 AM
Keynote: The Future of AI Quality Standards
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10:30 AM 11:00 AM
Keynote: Trust in LLMs
Richard Socher
CEO & Founder, You.comRichard Socher, CEO and founder of You.com and AIX Ventures will share insights from his journey of a decade in AI and NLP: from the invention of prompt engineering to founding You.com, an AI Assistant that was the first to integrate an LLM with live web access for accurate, up-to-date answers with citations. Richard will discuss tackling the biggest challenges facing LLMs, from hallucinations to generic responses. Gain insight into the potential for these advancements to be adopted by other LLM-based platforms. -
11:00 AM 11:30 AM
To RAG or not to RAG?
Amr Awadallah
CEO & Founder, VectaraRetrieval-Augmented-Generations (RAG) is a powerful technique to reduce hallucinations from Large Language Models (LLMs) in GenAI applications. However, large context windows (e.g., 1M tokens for Gemini 1.5 pro) can be a potential alternative to the RAG approach. This talk contrasts both approaches and highlights when Large Context Window is a better option thank RAG, and vice-versa. -
12:00 PM 12:30 PM
Implementing Robust AI Testing Frameworks
Mohamed Elgendy
CEO & Co-Founder, Kolena -
1:30 PM 2:00 PM
Panel: A blueprint for scalable & reliable enterprise AI/ML systems
Moderator: Hira Dangol
Panelists:
VP, AI/ML & Automation, Bank of America
- Steven Eliuk, VP AI & Governance, IBM
- Rama Akkiraju, VP Enterprise AI/ML, NVIDIA
- Nitin Agrawal, Head of AI Services, Google
Enterprise AI leaders continue to explore the best productivity solutions that solve business problems, mitigate risks and increase efficiency. Building reliable and secure AI/ML systems requires following industry standards, an operating framework, and best practices that can accelerate and streamline the scalable architecture that can produce expected business outcomes.
This session, featuring veteran practitioners, focuses on building scalable, reliable and quality AI and ML systems for the enterprises.
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2:00 PM 2:30 PM
Setting the Standard: Safety and Quality Benchmarks for Autonomous Systems
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2:30 PM 3:00 PM
Avoiding Self-Driving Disasters: Lessons Learned
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3:00 PM 3:30 PM
The Future of Simulation: Building Virtual Worlds for AI Training and Testing
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3:30 PM 4:00 PM
Simple, Proven Methods for Improving AI Quality in Production
Shreya Rajpal
CEO, Guardrails AIIn this talk, Shreya will share a candid look back at a year dedicated to developing reliable AI tools in the open-source community. The talk will explore which tools and techniques have proven effective and which ones have not, providing valuable insights from real-world experiences. Additionally, Shreya will offer predictions on the future of AI tooling, identifying emerging trends and potential breakthroughs. This presentation is designed for anyone interested in the practical aspects of AI development and the evolving landscape of open-source technology, offering both reflections on past lessons and forward-looking perspectives. -
4:00 PM 4:30 PM
Workshop: Building a Robust Testing Framework for Your Autonomous System
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2:00 PM 2:30 PM
Beyond benchmarks: measuring success for your AI initiatives
Salma Mayorquin
CEO, Remyx AIIn this session, we move beyond benchmarks and explore a more nuanced take on model evaluation and its role in the process of specializing models. We'll discuss how to ensure that your AI model development aligns with your business objectives and results, while also avoiding common pitfalls that arise when training and deploying. We'll share tips on how to design tests and define quality metrics, and provide insights into the various tools available for evaluating your model at different stages in the development process. -
2:30 PM 3:00 PM
AIOps, MLOps, DevOps, Ops: Enduring Principles and Practices
Charles Frye
AI Engineer, Modal LabsIt may be hard to believe, but AI apps powered by big Transformers are not actually the first complex system that engineers have dared to try to tame. In this talk, I will review one thread in the history of these attempts, the "ops" movements, beginning in mid-20th-century Japanese factories and passing, through Lean startups and the leftward shift of deployment, to the recent past of MLOps and the present future of LLMOps/AIOps. I will map these principles, from genchi genbustu and poka yoke to observability and monitoring, onto emerging practices in the operationalization of and quality management for AI systems. -
3:00 PM 3:30 PM
Models making sentences: not gud at werds.
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3:30 PM 4:00 PM
From Predictive to Generative: Uber's Journey
Kai Wang
Lead PM, AI Platform, UberToday, Machine Learning (ML) plays a key role in Uber’s business, being used to make business-critical decisions like ETA, rider-driver matching, Eats homefeed ranking, and fraud detection. As Uber’s centralized ML platform, Michelangelo has been instrumental in driving Uber’s ML evolution since it was first introduced in 2016. It offers a set of comprehensive features that cover the end-to-end ML lifecycle, empowering Uber’s ML practitioners to develop and productize high-quality ML applications at scale. -
4:30 PM 5:00 PM
Building advanced question-answering agents over complex data
Jerry Liu
CEO, LlamaIndexLarge Language Models (LLMs) are revolutionizing how users can search for, interact with, and generate new content, leading to a huge wave of developer-led, context-augmented LLM applications. Some recent stacks and toolkits around Retrieval-Augmented Generation (RAG) have emerged, enabling developers to build applications such as chatbots using LLMs on their private data.
ENGAGE WITH AI/ML PROS FROM:
MEET THE ORGANIZERS:
MOHAMED ELGENDY, CEO & Co-Founder, Kolena
Mohamed Elgendy is a distinguished figure in the field of artificial intelligence (AI) and machine learning (ML), currently leading as the CEO and Co-founder of Kolena, an innovative platform aimed at enhancing ML testing and validation. With a career spanning notable companies such as Rakuten, Amazon, and Twilio Inc., Mohamed has demonstrated leadership in developing AI/ML platforms, managing engineering teams, and pioneering in computer vision technologies. He is also the acclaimed author of "Deep Learning for Vision Systems" a testament to his expertise in AI, with over 20,000 copies sold. Mohamed's vision extends to ensuring the quality, reliability, and security of ML models and applications, driving innovation and setting standards in the AI industry.
.jpeg?width=200&height=200&name=me%20(1).jpeg "Demetrios Brinkmann")
DEMETRIOS BRINKMANN, CEO & Co-Founder, MLOps.community
Demetrios is one of the main organizers of the MLOps community and currently resides in a small town outside Frankfurt, Germany. He is an avid traveler who taught English as a second language to see the world and learn about new cultures. Demetrios fell into the Machine Learning Operations world, and since, has interviewed the leading names around MLOps, Data Science, and ML.
Since diving into the nitty-gritty of Machine Learning Operations he felt a strong calling to explore the ethical issues surrounding ML. When he is not conducting interviews you can find him making stone stacking with his daughter in the woods or playing the ukulele by the campfire.
%20(1).png?width=200&height=203&name=Copywriting%20(1)%20(1).png "Adam Becker")
ADAM BECKER, COO, MLOps.community
Adam is a machine learning engineer and serial entrepreneur. He runs the global network of the IRL meetup with over 20,000 ML Engineers, organizing events in dozens of countries.
He previously founded and sold a startup that leveraged ML to help Democratic campaigns with their fundraising, as well as other startups in the machine learning infrastructure space.
He is also the host of the AutoML Podcast, and interviewed leading researchers in the space of machine learning automation.
PETER VASELKIV, Business Operations Lead, Kolena
Peter Vaselkiv is the Business Operations Lead at Kolena, and AIQCON’s Lead Project Manager. Peter served as a consultant for Kolena for over a year, and recently joined the team full-time. Peter has led the Operations Teams of rapidly growing companies across a variety of industries, including clean-tech, venture capital, logistics, and healthcare. He brings a unique blend of strategic vision and administrative expertise. Peter holds a BA from Northeastern University, where he concentrated in Entrepreneurship.
DAN BAKER, Co-Founder, MLOps.community
Bio coming soon!
GEVA PERRY, CMO, Kolena
Bio coming soon!
PAM ENNIS, Marketing, Kolena
Bio coming soon!
PHOEBE VAN BUREN, Business Operations & Growth Lead, Kolena
Bio coming soon!
