Day 2 - 6 June 2024

09:45AM

(PDT)

Brian Krug

Founder & CEO

AppFaktors

Associated Talks:

09:45AM - Day 2

View AI & MLOps for the Optimised Enterprise: Chairpersons Welcome

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Andy Smith

COO & CMO

AppFaktors

Associated Talks:

09:45AM - Day 2

View AI & MLOps for the Optimised Enterprise: Chairpersons Welcome

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AI & MLOps for the Optimised Enterprise: Chairpersons Welcome

Chairpersons welcome and opening remarks.

. Brian Krug, Founder & CEO, AppFaktors
. Andy Smith, COO & CMO, AppFaktors

10:00AM

(PDT)

Katie Sanders

Assistant Vice President - Tech

Union Pacific Railroad

Associated Talks:

10:00AM - Day 2

View Keynote Address: On Track for Tomorrow – GEN AI & MLOps Revolutionizing the Rail Industry

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Keynote Address: On Track for Tomorrow – GEN AI & MLOps Revolutionizing the Rail Industry

Explore the transformative potential of Gen AI and MLOps in the rail industry in this keynote presentation.

Discover how these cutting-edge technologies are reshaping operations by optimizing maintenance schedules, enhancing safety protocols, and improving overall efficiency.

Through real-world case studies and best practices, learn how Gen AI enables adaptive AI systems while MLOps streamlines the deployment and management of machine learning models.

Join us to uncover how embracing these innovations can drive tangible business outcomes and propel the rail sector into a smarter, more efficient future.

. Katie Sanders, Assistant Vice President - Tech, Union Pacific Railroad

10:35AM

(PDT)

Nataliya Polyakovska

Principal Data Scientist

SoftServe

Associated Talks:

12:45PM - Day 2

View Panel: MLOps Excellence – Best Practices for Managing Data, Models, and Integrations

10:35AM - Day 2

View Presentation: Revolutionizing Learning – Unleashing the Power of Generative AI in Education and Beyond

11:50AM - Day 2

View Panel: Navigating the Data & AI Landscape – Ensuring Safety, Security, and Responsibility in Big Data and AI Systems

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Presentation: Revolutionizing Learning – Unleashing the Power of Generative AI in Education and Beyond

In an era where the volume of information overwhelms human capacity to comprehend, the challenge of making knowledge accessible, personalized, and engaging is more pressing than ever. Generative AI and Large Language Models (LLMs) stand at the vanguard of this revolution, offering unprecedented opportunities to transform how we learn and interact with information across various sectors, including public education and EdTech. 

This presentation will spotlight the transformative impact of these technologies, beginning with a deep dive into the current state of Generative AI and LLMs, both open-source and proprietary. By exploring the intricate relationship between language and knowledge, we unravel the potential of unstructured data — from Wikipedia articles and scientific publications to web pages and private data sources — as a treasure trove for knowledge discovery and education. 

As we explore the mechanisms through which Generative AI leverages data, including training methodologies like fine-tuning and Retrieval Augmented Generation (RAG), we will pinpoint high-value, low-risk applications that promise to redefine the educational landscape. The journey from a nascent idea to a fully operational AI solution is fraught with challenges, including ethical considerations and risks inherent in deploying AI solutions. Through the lens of a success story at Mesquite ISD, where Generative AI was leveraged to help students uncover their passions and aptitudes enabling the delivery of personalized learning experiences, this presentation will illustrate the practical benefits and transformative potential of Generative AI in education. 

. Nataliya Polyakovska, Principal Data Scientist, SoftServe

11:10AM

(PDT)

Rohan Singh Rajput

Senior Machine Learning Engineer

Headspace Health

Associated Talks:

11:10AM - Day 2

View Presentation: A/B TESTING FOR PERSONALIZED MEDITATION RECOMMENDATIONS

03:20PM - Day 1

View Presentation: A/B Testing for Personalized Meditation Recommendations

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Presentation: A/B TESTING FOR PERSONALIZED MEDITATION RECOMMENDATIONS

This talk focuses on building and implementing an A/B testing ecosystem for personalized meditation recommendations in an online meditation company.

It will cover key metrics, strategies for testing, and best practices for deploying effective personalized recommendations to improve user experience and engagement.

. Rohan Singh Rajput, Senior Machine Learning Engineer, Headspace Health

11:40AM

Networking Break

12:10PM

(PDT)

Rodney Brooks

Professor Emeritus

MIT

Associated Talks:

12:10PM - Day 2

View Presentation: AI-based robots that complement human workers in warehouse and factory floors, radically increasing efficiency

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Presentation: AI-based robots that complement human workers in warehouse and factory floors, radically increasing efficiency

The US has labor shortages in warehouses and manufacturing.  For such indoor environments, even with seasonal human workers present, it is now possible to deploy AI-based robots for whom there is no long tail of unexpected situations. Not only are the fruits of ML directly useful, but the impact ML has had on silicon architectures gives us a double bounty for more traditional spatial perception, awareness, and reasoning.  All robots in a facility contribute to enabling robots to fully understand what is happening everywhere in a facility.

By making robots human-centric first, the robots can increase both productivity and job satisfaction among hard-to-retain workers. Such robots not only offload the grunt work of moving physical objects within the facility but through human-centred interaction design the robots can offload much of the cognitive load from people by giving them cues on both where to direct their attention and monitoring task completion, enabling them to be much more productive in their work.

  • Vision-based SLAM outperforms LIDAR-based positioning and lets the robots know at all times exactly where they are in a shared map.
  • Through mixed-initiative and cognitive support for workers our trials have shown productivity improvements of 30% to 40%.
  • By being just the right amount of deferential to human workers the robots are not seen as either a safety or employment threat, and instead become valuable tools.
. Rodney Brooks, Professor Emeritus, MIT

12:45PM

(PDT)

Abhijit Nikhade

Data Engineering / Science, Connected Vehicle & Global Data Insights & Analytics

Ford Motor Company

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Prasanth Nandanuru

SVP

Wells Fargo

Associated Talks:

12:45PM - Day 2

View Panel: MLOps Excellence – Best Practices for Managing Data, Models, and Integrations

02:25PM - Day 1

View Presentation: Revolutionizing Financial Forecasting

03:30PM - Day 1

View Panel: Talking Digitally with NLP

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Nataliya Polyakovska

Principal Data Scientist

SoftServe

Associated Talks:

12:45PM - Day 2

View Panel: MLOps Excellence – Best Practices for Managing Data, Models, and Integrations

10:35AM - Day 2

View Presentation: Revolutionizing Learning – Unleashing the Power of Generative AI in Education and Beyond

11:50AM - Day 2

View Panel: Navigating the Data & AI Landscape – Ensuring Safety, Security, and Responsibility in Big Data and AI Systems

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Christopher Stephens

Head of Applied AI

Appen

Associated Talks:

12:45PM - Day 2

View Panel: MLOps Excellence – Best Practices for Managing Data, Models, and Integrations

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David Matheson

Senior Engineering Manager

Klue

Associated Talks:

12:45PM - Day 2

View Panel: MLOps Excellence – Best Practices for Managing Data, Models, and Integrations

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Andrew Gibbs

National Sales Executive - Strategic Alliances

DataInFormation, Liberty Source

Associated Talks:

12:45PM - Day 2

View Panel: MLOps Excellence – Best Practices for Managing Data, Models, and Integrations

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Panel: MLOps Excellence – Best Practices for Managing Data, Models, and Integrations

Engage with MLOps experts in a panel discussion focused on best practices for managing the entire lifecycle of machine learning operations.

From data management to model deployment and integration, gain insights into creating a robust MLOps framework for sustained AI success.

Moderator: . Abhijit Nikhade, Data Engineering / Science, Connected Vehicle & Global Data Insights & Analytics, Ford Motor Company
. Prasanth Nandanuru, SVP, Wells Fargo
. Nataliya Polyakovska, Principal Data Scientist, SoftServe
. Christopher Stephens, Head of Applied AI, Appen
. David Matheson, Senior Engineering Manager, Klue
. Andrew Gibbs, National Sales Executive - Strategic Alliances, DataInFormation, Liberty Source

01:25PM

Networking Break & Lunch

02:25PM

(PDT)

Robert Gray lll

Principal Technical Delivery Manager

Blue Cross Blue Shield North Carolina

Associated Talks:

02:25PM - Day 2

View Presentation: Gen AI and Data Science in Healthcare – Precision Medicine, Diagnosis, and Beyond

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Presentation: Gen AI and Data Science in Healthcare – Precision Medicine, Diagnosis, and Beyond

This session focuses on the transformative impact of Gen AI and data science in the healthcare domain.

We delve into precision medicine, leveraging advanced analytics and AI-driven insights for personalized patient care.

Precision Medicine Advancements:

Examine how Gen AI and data science are driving precision medicine, enabling tailored and effective healthcare interventions.

Innovations in Medical Diagnosis:

Uncover the latest innovations in medical diagnosis powered by advanced data science techniques and Gen AI, revolutionizing disease detection and classification.

Treatment Optimization Through Insights:

Discuss real-world applications where AI-driven insights optimize treatment plans, contributing to enhanced patient outcomes and healthcare efficiency.

. Robert Gray lll, Principal Technical Delivery Manager , Blue Cross Blue Shield North Carolina

02:50PM

(PDT)

Jan Piotrowski

VP, Head of Search Business

Brave Software

Associated Talks:

02:50PM - Day 2

View Presentation: Finding High-Quality Training Data for Next-Gen AI

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Presentation: Finding High-Quality Training Data for Next-Gen AI

Great data underpins great models. But with so much data out there, how do you make sure that you’re using the right sources?

In this session, I’ll walk through some of the commonly used training data sets and some considerations for each.

I’ll introduce Brave and our Web search API, and talk about how our independence from Big Tech means data for AI and search apps that’s better quality, cheaper, and more current.

. Jan Piotrowski, VP, Head of Search Business , Brave Software

03:15PM

(PDT)

Paul Kleen

CEO

Pitchit

Associated Talks:

03:15PM - Day 2

View Presentation: An AI case study: Improving D2C multichannel customer experience

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Presentation: An AI case study: Improving D2C multichannel customer experience

In this session, we’ll cover a case study of how a Fortune 500 telecom provider implemented AI to open up new acquisition channels for customers that previously were too manual labor-intensive to support at scale. We’ll share the before and after results of the implementation and discuss in detail how they accomplished everything in 6 months.

. Paul Kleen, CEO, Pitchit

03:25PM

End of Day