12 Out-of-the-Box AI Solutions to Transform Your Company 12 Out-of-the-Box AI Solutions to Transform Your Company
At the AI Expo and Demo Hall as part of ODSC East in a few weeks, you’ll have the opportunity to... 12 Out-of-the-Box AI Solutions to Transform Your Company

At the AI Expo and Demo Hall as part of ODSC East in a few weeks, you’ll have the opportunity to meet one-on-one with representatives from industry-leading organizations like IBM, SAS, Nvidia, HP, HPCC Systems, and others. These organizations and others will be showcasing their latest products and services that can help you implement AI in your organization or improve your processes already in progress. Learn more about the sessions below.

In-Person and Virtual Conference

April 23rd to 25th, 2024

Join us for a deep dive into the latest data science and AI trends, tools, and techniques, from LLMs to data analytics and from machine learning to responsible AI.


Low-Code, High Impact: Kickstart Your Data Analytics Journey with KNIME

Roberto Cadili | Data Scientist on the Evangelism team | KNIME

In this talk, we’ll introduce you to KNIME Analytics Platform, the free and open-source data analytics software that relies on a low-code/no-code visual interface to enable professionals from any field to make sense of data. It features extensive data access & blending, wrangling, modeling, and visualization capabilities, making it comprehensive and versatile for all stages of the data science life cycle.

Visualizing the Evolution of ML Models: Insights and Tools for Enhanced Understanding

Rajat Arya | Co-founder | XetHub

The increasing size and complexity of machine learning (ML) models make understanding their evolution crucial. This talk will demonstrate how to track ML model changes using visualizations, from classical tree models to complex deep learning architectures. We will showcase XetHub (and other tools) for building these visualizations and reasoning about model changes. The talk will conclude by extending this framework for adding visual context at any stage of an ML project.

The Unreasonable Effectiveness of an Asset Graph

Sean Lopp | Sales Engineer at Dagster Labs | Dagsterlabs

From hobbyist ML developers to platform architects at Fortune 100 firms, most data professionals spend the majority of their time answering simple questions: “If I update x, what else needs to be updated?” or “If y breaks, what else will be broken?”.

In this demo, Sean Lopp, sales engineer at Dagster Labs will show how a global data lineage graph can answer all of these questions and become the highest leverage piece of a data platform. Best of all, he’ll show how organizations adopting Dagster as an orchestrator get this global lineage graph for free.


From Pilot to Scale: How Companies are Deploying Generative AI in 2024

Carlo Appugliese | Director, Generative AI, Machine Learning and AI Engineering | IBM

There’s a lot of interest and buzz around generative AI, however, over 90% of companies are still in the experimental phase. So how do you take those pilots to production and drive ROI for your business? Join Carlo Appugliese, Program Director, Client Engineering at IBM Watsonx as he shares top insights from IBM’s generative AI client engagements, including how to develop a model strategy to keep costs down and improve performance while using AI responsibly.

HPCC Systems – The Definitive Big Data Open-Source Platform

Bob Foreman | Senior Software Engineer | LexisNexis Risk Solutions

Hugo Watanuki | Senior Technical Support Engineer | LexisNexis Risk Solutions

Learn why the completely free and open-source HPCC Systems platform is better at big data and offers an end-to-end solution for developers and data scientists. Learn how ECL can empower you to build powerful data queries with ease. HPCC Systems, a comprehensive and dedicated data lake platform makes combining different types of data easier and faster than competing platforms — even data stored in massive, mixed schema data lakes — and it scales very quickly as your data needs grow.

Unblock Data Science Teams with Prefect: Self-serve Python Scripting to Deployment

Mike Grabbe | Principal Data Engineer | EF Educational Tours

Taylor Curran | Senior Sales Engineer | Prefect

See how Prefect helps data engineers unblock data science teams with a Python-first approach to deploying workflows, a repeatable framework for managing infrastructure, and custom metrics and alerting to ensure everything is running. You’ll hear from Taylor (Prefect) about how to take any ol’ Python script and deploy it on a container service, and then a deep dive into how Mike developed a cost-efficient workflow to query historical Snowflake data without creating bulk copies.

How to Level-Up Your Creativity and Projects with On-Demand Analytics

Joe Madden | Senior Product Manager | SAS

Often, data scientists build their models on an entirely different stack from ML engineers creating inefficiencies, silos and leading to frustration. In this demo, we will show how a streamlined handoff between a data scientist and their ML engineer counterpart helps to get the model into production faster. The scenario covers a data scientist or developer, using Python or SAS, creating a model that can easily be shared, published, and registered to their production system of choice.

In-Person Data Engineering Conference

April 23rd to 24th, 2024 – Boston, MA

At our second annual Data Engineering Summit, Ai+ and ODSC are partnering to bring together the leading experts in data engineering and thousands of practitioners to explore different strategies for making data actionable.


The Open Source ML Advantage

Kevin Musgrave | ML Developer Advocate | HPE/Hewlett Packard Enterprise

In this talk, you’ll hear about HPE’s approach to building an end-to-end ML stack, including Determined AI for model training and Pachyderm for data preparation among other open-source alternatives. You’ll also see a live demo of how to use Determined AI for a transfer learning use case in the biomedical image domain. We’ll also touch on some key collaborations, including our partnerships with the AI Infrastructure Alliance, NVIDIA, and Aleph Alpha.

Mastering Complexity: Optimize your Decision Making for 500% ROI

Jennifer Locke | Manager  – Technical Account Management, Americas | Gurobi

Businesses focus a lot on forecasts and predictions – trying to get a clearer picture of the future. But even if you had perfect information, the most sprawling and impactful business decisions are much too complex to guarantee optimal outcomes, with millions, billions, or even trillions of trade-offs to consider. See why leading companies use mathematical optimization to solve their most complex real-world business problems.

Dive into the Lightning AI Open Source Stack and Lightning Studios to Unlock Reproducible AI Development on the Cloud

Luca Antiga | CTO | Lightning AI 

PyTorch Lightning is a leading open-source framework that was used to train several of the best generative AI models. With over 100 million downloads, it is the framework of choice for researchers and companies worldwide to train and fine-tune AI models. PyTorch Lightning and the rest of the Lightning AI stack, which includes Fabric, TorchMetrics, litgpt, litdata, and Thunder, provide a cutting-edge open-source foundation for practitioners. Just as the Lightning AI open source stack is democratizing access to cutting-edge AI research and engineering, Lightning Studios democratizes access to cloud computing resources and solves the challenges of reproducibility and collaboration.

The Diagram-Based Deep Learning Framework that Brings Visibility to Model Architectures

David Winer | Co-founder | Сerbreс

No doubt that the transformer model architecture has revolutionized AI, but working with these models has an ever-expanding set of technical challenges and long learning curves.  In this case study, we will navigate the Llama-2 model architecture and steer fine-tuning for customized document summarization.  We will use Graphbook, the deep learning framework that brings visibility and intelligent guidance to researchers focusing on model architectures.

Say Goodbye to Time-Consuming Generative AI Proof of Concept

Rei Araki | CEO, GenerativeX | GenerativeX

The concept of time and money spent on proof of concept (POC) has dramatically changed with generative AI. Since POCs can now be conducted immediately and at a low cost due to generative AI, businessmen and companies wanting to utilize generative AI in their operations should get started right away.

How can I check these out?

Get our free Open Pass to join these, and all of our Showcase Talks, at ODSC East in the AI Expo & Demo Hall. Want to take a deeper dive into topics like LLMs, Generative AI, Machine Learning, NLP, and more? Get one of our paid passes for access to hands-on training sessions, workshops, and more.



ODSC gathers the attendees, presenters, and companies that are shaping the present and future of data science and AI. ODSC hosts one of the largest gatherings of professional data scientists with major conferences in USA, Europe, and Asia.