Fully Connected 2023
San Francisco Conference

Join us for a one-day event focused on the generative models and LLMs transforming the world today!

You’ll hear from the creators of the most exciting LLM tools like LangChain & OpenAI, people building your favorite platforms like AWS, NVIDIA, Lightning, HuggingFace, Kaggle, and companies having a positive impact on the world through machine learning.

Speakers

At weights & Biases FullyConnecteD, Spring 2023

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Bringing Together Builders of Large Language Models

At weights & Biases Fully ConnecteD ON June 7

Join us for a one-day event focused on the generative models and LLMs transforming the world today! You’ll hear from the creators of the most exciting ML tools like LangChain & OpenAI, people building your favorite platforms like AWS, NVIDIA, Lightning, HuggingFace, Kaggle, and companies having a positive impact on the world through machine learning.

We’ll also be launching an exciting new product at Fully Connected that will dramatically change how you train and deploy your models. We will be demoing it live and we can’t wait to hear what you think.

Join us on June 7 to hear how the future of ML is being built on Weights & Biases.

Venue

building 12 at Pier 70 in San Francisco

Building 12 is a thriving multi-use historic structure immediately adjacent to Pier 70’s parks and open space. The expansive, sun-soaked floors offer limitless opportunities to foster community and culture.

Fully Connected Sponsors

Fully Connected Community Partners

Agenda

1:00

Welcome and Opening Remarks

Lukas Biewald, CEO and Co-Founder at Weights & Biases

We’ll kick off Fully Connected 2023 with a keynote from W&B’s CEO and Co-founder Lukas Biewald. He’ll set the stage for the day and introduce a new product we think you’re going to love.

1:15

W&B Product Announcement

Shawn Lewis, CTO and Co-Founder at Weights & Biases

We’ve been hard at work building new features that will dramatically change how you train and productionize your models on Weights & Biases. Join us as our CTO Shawn Lewis demos two of our most requested–and most magical–features.

1:45

W&B for Model CI/CD

Carey Phelps, Founding PM at Weights & Biases

Join Carey Phelps as she showcases how our newest products and features fit into your current ML workflows. This will be a true end-to-end demo condensed into a brief 15 minutes.

2:00

Main Sessions

During our main sessions, you’ll hear from speakers from AWS, Langchain, NVIDIA, You.com, Nomic AI, and more, with a special keynote presentation by Tim Urban. Check the “Main Stage” tab for the full list of presentations.

5:10

Breakout Sessions

The second half of Fully Connected will be short, rapid-fire breakouts from some of the most innovative voices and companies in machine learning. We have speakers from Lightning AI, Run AI, Mosaic ML, Humane, AWS, Snowflake, Anyscale, Domino, fast.ai, and a whole lot more. Check the “Coatue Breakout Room” and “Felicis Breakout Room” tabs for the full list of presentations.

5:00

Afterparty and Networking

Our last few hours will be completely devoted to networking, mingling, and getting to know likeminded ML practitioners. Drinks on us.

2:00

Memory in LLM Applications

Harrison Chase, Co-Founder & CEO at Langchain

This talk will focus on how “memory” in the context of LLM applications. Memory is most often discussed in the context of chatbots so it will start with an overview of conversational memory. This can vary from simple (buffer of recent messages) to complex (extracting and dynamically generating a knowledge graph). It will then cover recent advances in memory, including the “Generative Agents” paper. It will finish will an overview of where the space is now and where it could go in the future (it is still early days!)

2:15

NLP is the future of AI

Richard Socher, Founder & CEO at You.com

This session delves into the immense potential of natural language processing and generative AI, in revolutionizing summarization, human productivity and online search. Led by Richard Socher, a top NLP research scientist and founder and CEO of You.com, the session showcases his transition from academic research to large-scale AI in industry. Richard will explore AI in search and demonstrate its most impactful use cases.

2:30

Building trustworthy, safe, and secure LLM conversational systems

Jonathan Cohen, VP of Applied Research at NVIDIA

Large language models (LLMs) are incredibly powerful and capable of answering complex questions, performing feats of creative writing, developing, debugging source code, and so much more. Yet, building these LLM applications in a safe and secure manner is challenging. Because safety in generative AI is an industry-wide concern, NVIDIA developed NeMo Guardrails as an open-source toolkit to help developers guide generative AI applications to create impressive text responses that stay on track and on topic.

2:45

Break Time

3:15

Custom Chatbots using LLMs, Streamlit, LangChain, and Snowflake - Why and How

Adrien Treuille, Head of Streamlit at Snowflake

Chatbots are not just a passing fad. Their ability to express successive task refinement with a Large Language Model (LLM) makes chatbots a fundamental UI paradigm of the LLM era. In this talk, we’ll preview a new chat UI in Streamlit, explain some of the design decisions that went into this design. Finally, we will build our own custom chatbot, live on stage, using Streamlit, LangChain, and Snowflake.

3:30

The Future of Generative AI

Ari Kalfayan, global head of early-stage Business Development for AI/ML startups & VC at AWS

Generative AI is one of the hottest topics in business and the AWS Gen AI Accelerator has picked the top 21 Gen AI companies in the world to accelerate their growth and technical development.

Join us for a panel with 4 of the top startups in our inaugural cohort as we talk through the Generative AI market as a whole. We’ll discuss the tooling needed to develop Gen AI applications and share helpful insights on how people can leverage these tools and applications.

Featuring:

Bernardo Aceituno, Co-Founder at Stack AI
Eiman Ebrahimi, CEO at Protopia AI
Mihail Eric, Co-CEO at Storia AI
Max Mergenthaler, CEO and Co-Founder at Nixtla

3:45

Leadership needs us to do gen AI, what do I do?

Chip Huyen, Founder & Ceo at Claypot AI

Everywhere we go, we see companies trying to figure out their generative AI strategy, but few seem to know what exactly to do. In this short talk, we’ll discuss key considerations when evaluating LLMs.

4:00

Why ‘no-code’ will power the long tail of AI applications

Howie Liu, Co-Founder & CEO at Airtable

Generative AI is capable of advanced reasoning and creativity that can be immediately applied to a broad range of knowledge work. Yet the bottleneck to broader adoption will be enabling the creation and experimentation of AI-enabled workflows on a large scale. The no-code approach to app-building is very well-suited to enabling the long tail AI applications. In this talk, we discuss the opportunity, and design patterns, for no-code LLM apps.

4:15

Large Models, AI, Human History and the Future

Tim Urban, Writer, Illustrator, and Co-Founder of Wait But Why

Back in 2014, long before Artificial Intelligence became the subject that everyone is talking about, Tim Urban began some serious research. It hit him pretty quickly that what’s happening in the world of AI is not just an important topic, but, by far THE most important topic for our future. After three years of diving deeply into the subject and all its future implications, Tim published “The AI Revolution and the Road to Superintelligence.” Vox dubbed this Tim’s “epic series on artificial intelligence,” taking readers on a deep exploration of what AI is, how it works, and why it will dramatically change our lives.

Instantly, Tim established himself as the ultimate explainer of AI to a wide range of audiences—including Silicon Valley thought leaders. Elon Musk shared “The AI Revolution” twice on Twitter, commenting, “Excellent and funny intro article about Artificial Superintelligence! Highly recommend reading.” Tim soon turned his fascinating exploration of AI into a gripping talk—one in which the head of Sweden’s Øredev conference called it “the best keynote in years.” After experiencing the same talk at Social Media Week in New York, conference founder Toby Daniels wrote that Urban “was brilliant, inspiring and terrifying at the same time, and left most of us speechless, breathless and in a mixed emotional state of wonder and awe at what the future holds.”

As AI has expanded into our world, so has Tim’s knowledge and insights. With today’s conversations on AI taking on multiple dimensions, Tim Urban remains the ultimate (and frequently entertaining) explainer of the most transformational shift in the way we live, work, and evolve as a society.

5:10

Why ML Engineers are still useful when using LLM APIs

Hamel Husain, Independent Consultant / Founder

It’s tempting to feel that ML Engineers are obsolete in the case where you are just using OpenAI’s APIs off the shelf. Even though you don’t need to train or serve a model, evaluation of LLMs are still critical. Thinking rigorously about evaluation metrics and building offline evaluation harnesses are key to enabling rapid development velocity and making progress on LLMs. In this lighting talk, Hamel will share his experiences on this subject.

5:20

Using modern NLP to build a knowledge graph

Anthony Goldbloom, Co-Founder & CEO at Sumble; Co-founder & Former CEO at Kaggle

We are building a knowledge graph that takes unstructured data, does entity extraction, entity normalization, text summarization and text classification. We’re using everything from regex through to LLMs, always starting with the simplest solution first and working our way up to something more complex only when it’s necessary. In this talk I’ll go over our NLP use cases and talk about what’s working best.

5:40

Best Practices of W&B and Amazon Sagemaker

James Yi, AI/ML Tech Lead at AWS + Matt Hoffman, ML Engineer at Weights & Biases

Learn best practices for setting up Amazon Sagemaker with Weights & Biases MLOps platform. Quick demo will show how to setup experiment jobs, model monitoring, check model performance, identify best models in dashboard, and launching training jobs in Sagemaker.

6:00

Break Time

6:10

Decrease PyTorch Model Load Times with CoreWeave’s Tensorizer

Rahul Talari, Sr. Machine Learning Platform Engineer at CoreWeave + Navarre Pratt, Machine Learning Engineer at CoreWeave

Large language models and machine learning models with billions of parameters can take a long time to load, severely impacting a company’s ability to quickly scale its inference stack to meet rising demand. To help reduce latency, improve throughput, and reduce resource usage, CoreWeave employs a range of open-source tools, including CoreWeave’s Tensorizer. Join Rahul Talari and Navarre Pratt, machine learning engineers at CoreWeave, as they walk through how CoreWeave’s Tensorizor makes it possible to load models extremely quickly from HTTP/HTTPS and S3 endpoints for better end-to-end latency and reduced resource utilization, and lower costs.

6:20

Responsible Generative AI

Josh Mineroff, Head of Technical Alliances at Domino Data Lab

Model explainability is one thing – increasingly, that’s not the hard part. It’s easy to get lost in the technical complexity of LLMs, as well as the abstract concepts surrounding responsible AI. But like any new technology, people and processes matter more than algorithms – and full tracking and reproducibility across the model lifecycle is foundational. Join this breakout session to learn how enterprises are adapting foundation models to meet their business and governance objectives – from tuning to deployment to monitoring.

6:30

Customer Trends for Azure OpenAI Engagements

Michael Lanzetta, Lead Technical Architect for Data and AI at Microsoft

As our enterprise partners go from ideation to production, we’re gaining a better understanding of what is resonating with them, their open concerns, and the blind spots we can help illuminate. In this short talk I’ll share what we’re learning, and which insights I believe are evergreen and which are rapidly evolving.

6:40

State of GPU Market for Deep Learning

Mitesh Agrawal, Head of Cloud at Lambda

This session provides a comprehensive overview of the current state of the Graphics Processing Unit (GPU) market, with a particular emphasis on their use in deep learning applications. The discussion will cover key topics including:

the current availability of GPUs
challenges in the supply chain, and
the implications of large-scale deployments.

With a rapidly evolving market, understanding these aspects is crucial for both practitioners and organizations aiming to leverage GPU power for their deep learning needs. Additionally, the session will explore the role of Lambda in addressing these challenges. Lambda’s solutions can provide effective strategies to navigate supply constraints, manage deployments, and ensure uninterrupted access to essential GPU resources, hence enabling organizations to sustain and enhance their deep learning capabilities. This session promises to bring valuable insights for anyone vested in deep learning, from researchers to industry professionals.

6:50

LLMs ❤️ Enterprise Data - Perils and Opportunities

Venkat Krishnamurthy, Head of ML Platform at Snowflake

LLMs and Generative AI are being talked about as equivalent to the Industrial Revolution, in terms of potential impact to society at large. The enterprise world is no exception. We’ll cover the promise of LLMs when applied to enterprise data, but also uncover some obvious, and some not so obvious perils along the way.

7:00

Responsible AI for Enterprise Adoption of Generative AI

Ali Arsanjani, Director of Cloud Partner Engineering at Google

Generative AI offers enterprises opportunities for creativity, innovation, and automation, but responsible AI practices are crucial for ethical and unbiased outcomes.
Understanding generative models and data requirements, including diversity and privacy concerns, is essential for successful enterprise adoption of generative AI.
A responsible AI framework for enterprise adoption involves ethical considerations, transparency and explainability, robustness and security measures, and ensuring legal and regulatory compliance.
Mitigating social impact and bias in generative AI outputs, along with addressing the impact on human labor and creativity, are crucial considerations for responsible enterprise adoption.
Addressing the adaptation of foundation models through AI safety, toxicity mitigation, misuse prevention, and robustness is paramount to ensure ethical and reliable outcomes in enterprise applications.

5:10

The Science Behind MPT-7B, Our Open Source LLM

Hanlin Tang, Co-Founder & CTO at MosaicML

Last month, we open sourced MPT-7B, the first commercially licensed model in the LLaMa style, and variants including a long context length Storywriter model. In this talk, you’ll learn about the science behind training these LLMs, from how we determined the data mixture to our algorithmic decisions and evaluation. Hear about some amazing community projects built on the MPT series as we continue to push the frontier of open source models.

5:20

Orchestrating and Tracking the Full AI Lifecycle: Training LLMs and Serving Inference

Robert Magno, Solutions Architect at Run:AI

Building a robust and secure AI infrastructure is crucial for enterprises aiming to leverage the power of artificial intelligence effectively. Run:ai, together with Weights and Biases, offer a comprehensive platform designed to address the unique challenges faced by IT, DevOps and Platform teams in building an end to end AI platform that ensures researchers have on-demand access to compute and the tools necessary to monitor their experiment progress.

5:30

What is GPT-4 good for?

Ted Sanders, Member of Technical Staff at OpenAI

As a research engineer at OpenAI, I advise companies, from startups to Fortune 100, trying to build GPT into their products.

This talk will share my perspective on:

GPT’s #1 superpower
GPT’s #1 weakness
The #1 misconception about GPT
The #1 mistake teams make when building products atop GPT
The markets and applications I’m most excited by

5:40

Accelerating AI Product Development with Lightning AI

William Falcon, Founder & CEO at Lightning.AI

Join us for an engaging community talk on Lightning AI, designed by the creators of PyTorch Lightning. Lightning AI is the platform to build foundation models, on your data, your cloud. Lightning expedites AI product development by providing a comprehensive suite of features to build, train, deploy, and ship AI products seamlessly.

During this talk, we will explore how Lightning AI simplifies and streamlines the entire AI development process. By enabling distributed training, hyperparameter tuning and autoscaling at the click of a button, the Lightning platform empowers developers to focus on their models and ideas rather than dealing with the underlying infrastructure.

Through real-world examples and use cases, we will demonstrate how the Lightning Platform significantly reduces the time and effort required to build and deploy AI products. Whether you are a researcher, data scientist, or AI enthusiast, this talk will equip you with the knowledge and tools necessary to accelerate your AI development workflow and maximize productivity.

Join us for an insightful session filled with valuable insights, practical tips, and a glimpse into the future of AI development.

5:50

PatentPT: Building an LLM-Powered Solution with Enterprise-Grade Memory Agents

Davit Buniatyan, CEO & Founder at Activeloop

Learn how we created PatentPT, an advanced language model solution that greatly enhances patent search and interaction capabilities. The presentation offers practical insights on fine-tuning and deploying large language models and leveraging enterprise-grade memory agents to autocomplete patents, generate abstracts and claims, and conduct advanced patent search functions using the rich patent corpus. We’ll walk you through how to develop a similar solution using cutting-edge Activeloop’s Deep Lake, the Database for AI, open-source LLM models, Habana Gaudi HPU hardware, and Amazon Sagemaker’s LLM inference APIs.

We will walk you architectural blueprints and all the steps we took to build the solution – from training our LLM model, and finetuning it, as well as creating custom featurizers and the deployment of search APIs.

Whether you’re an AI practitioner looking for practical guides on finetuning LLMs, a legal professional interested in leveraging AI for patent search, or simply curious about the future of AI-enhanced solutions, our talk provides a glimpse into the process and potential of using LLMs in a specialized field. Join us as we share our journey of building custom LLM-powered apps powered by Deep Lake, the Database for AI for companies big and small.

6:00

Break Time

6:10

How LLMs have redefined the way we do AI

Robert Nishihara, Co-Founder & CEO at Anyscale

Large Language Models are getting more attention as a way to address the data privacy, latency, flexibility, and cost challenges of using general purpose LLM services. But deploying LLMs in production means solving for performance, scale, infrastructure/cloud costs, and integration with other tools and frameworks. In this session, you’ll hear about what Anyscale has learned from powering the world’s most popular LLMs including OpenAI, and how Anyscale helps organizations productionize and scale LLMs.

6:30

Towards Explainable and Accessible AI

Brandon Duderstadt, Founder & CEO at Nomic AI

Nomic’s mission is to improve the explainability and accessibility of AI. In this talk, we will examine what it means for a model to be explainable and accessible, as well as strategies for finding and resolving model errors using the methods of information cartography. We will close by remarking on the short term risks posed by inaccessible AI models.

6:40

Building AI with open source and Hugging Face

Jeff Boudier, Product Director at Hugging Face

In this talk, Jeff Boudier will tell you about the latest and greatest releases in the beautiful world of open source machine learning, and walk you through how you can build AI into your apps using Hugging Face tools.

FAQ

frequently-asked questions

Registrations

I tried to register to the event with a code but the code is not working, what do I do?

Please make sure you enter the code in the correct space (you’ll see a section marked “X Promo code”) and click on Apply. If this isn’t working, your code might be expired or incorrect. If you keep experiencing issues, please contact us at events@wandb.com.

Can I transfer my ticket to someone else if I can’t attend?

Yes! You can transfer your ticket to another person by sending an email to events@wandb.com and we will update the ticket contact details for you.

I registered for the event, but I haven’t received a confirmation email. What should I do?

Please check your spam or junk folder to ensure the confirmation email didn’t end up there. If you still haven’t received it, contact our support team at events@wandb.com with your registration details and we’ll assist you.

Do I need to be over 21 to attend the event?

Yes, that’s correct. There will be alcohol served after 5. To ensure compliance with legal regulations and promote responsible drinking, the conference organizers have implemented an age restriction policy, allowing only individuals who are 21 years or older to attend and partake in these activities.

Entry and Check-in

What do I need to bring for check-in at the event?

Please show the QR that you’ll receive 24 hours before the event for smooth check-in. Additional requirements or instructions will be communicated prior to the event if necessary.

Logistics

Where is the event venue located and how do I get there?

The in person event is at Pier 70, Building 12, San Francisco, CA. You will find more details in the email going out 24 hour before the event. We recommend using navigation apps or public transportation options for ease of travel.

Is parking available at the event venue? If so, is there a fee?

Parking is available at the event venue but is limited! We will send an email with specifics for parking details.

Will food be provided at the event?

Yes there will be snacks & drinks provided between 1-5pm. At 5pm there will be more food, drinks, and time to network with the attendees and sponsors.

Sessions

Will the event be live-streamed and recorded?

This event is run entirely in person. We will record the main keynote sessions but the event will not be live streamed.

Are there any giveaways for attendees?

Attendees will receive a bag of goodies upon registration.

Additionally, you can participate in the W&B Treasure Trek by scanning QR Codes to unlock clues. Use the clues to guess the right answer to win a pair of Apple AirPods or Bose Speakers. Find the first clue in our Discord: http://wandb.me/discord

Fully Connected 2023San Francisco Conference

Speakers

Lukas Biewald

CEO & Co-founder, Weights & Biases

Harrison Chase

CEO & Co-Founder, Langchain

Shawn Lewis

CTO & Co-founder, Weights & Biases

anthony goldbloom

Former CEO & Co-founder, Kaggle

Chip huyen

CEO & Co-Founder, Claypot AI

Richard Socher

CEO, You.com

Ted Sanders

Technical Staff, OpenAI

Robert Nishihara

Co-founder & CEO, Anyscale

will falcon

CEO, lightning AI

hamel husain

Independent Consultant / Founder

Carey Phelps

Founding PM, Weights & Biases

Hanlin Tang

CTO & CO-founder, MosaicML

Adrien Treuille

CEO & CO-founder, Streamlit

Brandon Duderstadt

Founder, GPT4All

Howie Liu

CEO & CO-founder, Airtable

joe spisak

product director, google

Davit Buniatyan

CEO & Founder, Activeloop

James Yi

AI/ML Tech Lead, AWS

Jonathan Cohen

VP of Applied Research, NVIDIA

Jeff Boudier

Product + Growth, Hugging Face

Venkat Krishnamurthy

Head of ML Platform, Snowflake

Mitesh Agrawal

COO & Head of Cloud, Lambda

Ali Arsanjani

Director of Cloud Partner Engineering, Google

Robert Magno

Solutions Architect, Run:AI

Tim Urban

Writer/Illustrator and Co-Founder, Wait But Why

Rahul Talari

Sr. Machine Learning Platform Engineer, CoreWeave

Navarre Pratt

Machine Learning Engineer, CoreWeave

Michael Lanzetta

Lead Technical Architect for Data and AI, Microsoft

Josh Mineroff

Head of Technical Alliances, Domino Data Lab

Ari Kalfayan

Global Head of Early-Stage Business Development for AI/ML Startups & VC, AWS

Bringing Together Builders of Large Language Models

Venue

Fully Connected Sponsors

Fully Connected Community Partners

Agenda

1:00

Welcome and Opening Remarks

1:15

W&B Product Announcement

1:45

W&B for Model CI/CD

2:00

Main Sessions

5:10

Breakout Sessions

5:00

Afterparty and Networking

2:00

Fully Connected 2023
San Francisco Conference