Day 1 - 5 October 2022

09:45AM

(PDT)

Mohan Reddy

Chief Technology Officer/ Associate Director, Human Perception Lab

SkyHive/ Stanford University

Associated Talks:

09:45AM - Day 1

View Enterprise AI: Chairpersons Welcome

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Enterprise AI: Chairpersons Welcome

Chairpersons welcome and opening remarks. 

. Mohan Reddy, Chief Technology Officer/ Associate Director, Human Perception Lab, SkyHive/ Stanford University

10:00AM

(PDT)

Xingchu Liu

SVP Enterprise Data & Analytics

Macy's

Associated Talks:

10:00AM - Day 1

View Presentation: Building Enterprise AI Excellence

11:00AM - Day 1

View Panel: Responsible delivery – the ethics of AI

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Presentation: Building Enterprise AI Excellence

As investment in AI continues to grow rapidly, many businesses continue to face the challenge of effectively leveraging AI and maximizing business impact. Although AI has shown incredible power when solving certain problems and driving tremendous value, building enterprise AI excellence is a journey that requires vision, strategy plan, and execution. With the right framework and clear focus on key aspects to drive success including organization, data & analytics capability, technology, and value delivery, the power of AI can be fully unleashed and drive exponential impact across enterprises.

. Xingchu Liu, SVP Enterprise Data & Analytics, Macy's

10:30AM

(PDT)

Braden Hancock

Co-founder and Head of Technology

Snorkel AI

Associated Talks:

11:00AM - Day 1

View Panel: Keeping it Ethical in AI

10:30AM - Day 1

View Keynote: Automated Data Labeling – The Power of Going Programmatic

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Keynote: Automated Data Labeling – The Power of Going Programmatic

Labeling training data is exhausting—the de facto bottleneck most AI teams face today. Eager to alleviate this pain point of AI development, practitioners have long sought ways to automate this labor-intensive labeling process. Automate too little (e.g., with manual labeling optimizations such as active learning or model-assisted labeling) and the gains are marginal. Automate too much and your model becomes disconnected from the essential human-provided domain knowledge it needs to solve relevant problems. The key to truly transformative (e.g., 10x to 100x) efficiency improvements is to change the interface to labeling altogether, moving from manual labeling collecting individual labels one-by-one to programmatic labeling with labeling functions that capture labeling rationales. The result is a labeling process that is significantly more scalable, adaptable, and governable. In this talk, we review these techniques for automating parts of the labeling process, show how the Snorkel Flow platform integrates them in a unified framework, and share real-world experiences from Fortune 500 companies that have made the transition from manual to programmatic labeling.

. Braden Hancock, Co-founder and Head of Technology, Snorkel AI

11:00AM

(PDT)

Mohan Reddy

Chief Technology Officer/ Associate Director, Human Perception Lab

SkyHive/ Stanford University

Associated Talks:

09:45AM - Day 1

View Enterprise AI: Chairpersons Welcome

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Ruben Buell

Chief Technology Officer & Chief Operations Officer

Reflex Media

Associated Talks:

11:00AM - Day 1

View Panel: Keeping it Ethical in AI

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Braden Hancock

Co-founder and Head of Technology

Snorkel AI

Associated Talks:

11:00AM - Day 1

View Panel: Keeping it Ethical in AI

10:30AM - Day 1

View Keynote: Automated Data Labeling – The Power of Going Programmatic

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Arjuna Flenner

Senior Technical Leader, Machine Learning and Autonomy

GE Aviation Systems

Associated Talks:

11:00AM - Day 1

View Panel: Keeping it Ethical in AI

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Forrest Pascal

Principal, AI/ML Model Governance, Data & AI Platform Engineering

Kaiser Permanente

Associated Talks:

11:00AM - Day 1

View Panel: Keeping it Ethical in AI

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Karthik Shanmugasundaram

Senior Engineering Manager, Linkedin Learning Discovery & Search

Linkedin

Associated Talks:

11:00AM - Day 1

View Panel: Keeping it Ethical in AI

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Panel: Keeping it Ethical in AI

  • Human-in-the-loop review processes – how can we decide where the buck stops in decision making?  
  • Reconfiguring data input to tackle non-ethical AI bias. 
  • The potential of labour replacement and corporate practice that can be done to mitigate the risk of job-loss. 
Moderator: . Mohan Reddy, Chief Technology Officer/ Associate Director, Human Perception Lab, SkyHive/ Stanford University
. Ruben Buell, Chief Technology Officer & Chief Operations Officer, Reflex Media
. Braden Hancock, Co-founder and Head of Technology, Snorkel AI
. Arjuna Flenner, Senior Technical Leader, Machine Learning and Autonomy, GE Aviation Systems
. Forrest Pascal, Principal, AI/ML Model Governance, Data & AI Platform Engineering, Kaiser Permanente
. Karthik Shanmugasundaram, Senior Engineering Manager, Linkedin Learning Discovery & Search, Linkedin

11:40AM

(PDT)

Bjorn Austraat

Head of AI Acceleration

Truist

Associated Talks:

11:40AM - Day 1

View Presentation: Enough Science Experiments! Pragmatic Tips from the Real World for Turning AI Ideas into Enterprise Value

02:30PM - Day 1

View Is Agile AI a Myth? Three ways to pull off design and agile thinking in your AI project

09:30AM - Day 1

View Panel: Built to scale – Ramping up AI projects

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Presentation: Enough Science Experiments! Pragmatic Tips from the Real World for Turning AI Ideas into Enterprise Value

  • 5% model, 95% everything else: Three truly comprehensive pillars to evaluate AI ideas for enterprise “viability”
  • Tips on building AI teams that get things done
  • Agile AI? Waterfall agile AI? Examples of bringing agile principles to AI and machine learning
. Bjorn Austraat, Head of AI Acceleration, Truist

12:10PM

Lunch & Networking in the Exhibition Area

12:40PM

(PDT)

Senior Representative, Snowplow Analytics

Associated Talks:

12:40PM - Day 1

View VIRTUAL PRESENTATION: Powering AI with the Right Data

12:40PM - Day 1

View Presentation: Powering AI with the Right Data

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Presentation: Powering AI with the Right Data

AI is becoming increasingly important but is only effective with good quality data. Companies often dismiss the importance of this, but what does good data for AI look like? In this session we will discuss how AI powered by the right data is highly effective, and what tools you can use to confidently collect the best quality data from your platforms.

. Senior Representative, Snowplow Analytics, ,

01:00PM

(PDT)

Dr. Satyam Priyadarshy

Managing Director-India Centre & Technology Fellow and Chief Data Scientist

Halliburton

Associated Talks:

01:00PM - Day 1

View Presentation: Digital Disruption in a Complex Industry

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Presentation: Digital Disruption in a Complex Industry

Session focusing on utilizing Cloud and AI in the energy sector. 

. Dr. Satyam Priyadarshy, Managing Director-India Centre & Technology Fellow and Chief Data Scientist, Halliburton

01:30PM

(PDT)

Senior Representative, Altada Technology Solutions

Associated Talks:

01:30PM - Day 1

View Presentation: AI Enterprise Solution

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Presentation: AI Enterprise Solution

To follow soon …

. Senior Representative, Altada Technology Solutions, ,

01:50PM

(PDT)

Dan Mallin

CEO and Founder

Lucy AI

Associated Talks:

01:50PM - Day 1

View VIRTUAL PRESENTATION: How your Digital Transformation has Created your Ultimate Employee

01:50PM - Day 1

View Presentation: Bringing Internal Data Resources to Life with AI

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Presentation: Bringing Internal Data Resources to Life with AI

Internal intelligence is one of your companies’ biggest competitive assets. A tremendous amount of information lives in PowerPoints, PDFs, videos, Word Documents and more. This data is the most difficult to extract from, yet the most valuable, as time, money and insight was spent converting data into knowledge. It’s a constant challenge to find the information when needed, especially when information is spread across repositories and geographies. Recent advances in AI-knowledge management platforms are now providing teams the capability to instantly access answers across all sources of internal knowledge and delivering businesses huge advantages from freeing up thousands of hours per year spent on searching for existing information to saving millions of dollars in redundant work.

. Dan Mallin, CEO and Founder, Lucy AI

02:00PM

(PDT)

Laura Patel

Principal Data Scientist

UPS

Associated Talks:

02:00PM - Day 1

View Applying AI in the Enterprise to Drive Value

01:10PM - Day 2

View Panel: Making sense of your data

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Applying AI in the Enterprise to Drive Value

. Laura Patel, Principal Data Scientist, UPS

02:20PM

(PDT)

David Keene

Chief Strategy Officer

Speechmatics

Associated Talks:

02:20PM - Day 1

View Presentation: AI Bias, Inclusion, and Diversity in Speech Recognition

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Presentation: AI Bias, Inclusion, and Diversity in Speech Recognition

The global pandemic has changed life – the reduction in face-to-face contact and the pivot to audio has been great for many, but also raises questions around inclusion and diversity. Does today’s technology really understand everyone regardless of age, gender, accent, or location? This talk explores:

  • Self-supervised learning with Autonomous Speech Recognition.
  • How we can use Autonomous Speech Recognition to tackle inequality and bias in AI.
  • The move beyond language accuracy towards voice cohort accuracy will deliver inclusive and diverse speech recognition that makes AI work better anytime, anyplace, anywhere.
. David Keene, Chief Strategy Officer, Speechmatics

02:40PM

Coffee & Networking in the Exhibition Area

03:00PM

(PDT)

Cal Al-Dhubaib

CEO, AI Strategist

Pandata

Associated Talks:

03:00PM - Day 1

View Presentation: Operational Al and ML Building Business Capabilities

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Presentation: Operational Al and ML Building Business Capabilities

To follow soon …

. Cal Al-Dhubaib, CEO, AI Strategist, Pandata

03:20PM

(PDT)

Andy Rossmeissl

CEO & Co-founder

Faraday

Associated Talks:

03:20PM - Day 1

View VIRTUAL PRESENTATION: Build vs. Build Faster — Empower your Marketing Team with Consumer Predictions at Scale

03:20PM - Day 1

View Presentation: Build vs. Build Faster — Empower your Marketing Team with Consumer Predictions at Scale

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Presentation: Build vs. Build Faster — Empower your Marketing Team with Consumer Predictions at Scale

To follow soon …

. Andy Rossmeissl, CEO & Co-founder, Faraday

03:30PM

(PDT)

Senior Representative

Associated Talks:

03:30PM - Day 1

View Panel: Evolving the Enterprise with Language Modelling

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Rahul Singhal

CPO

Innodata Inc.

Associated Talks:

03:30PM - Day 1

View Panel: Evolving the Enterprise with Language Modelling

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Panel: Evolving the Enterprise with Language Modelling

  • NLP (Natural Language Processing) progressions like OpenAI for enhanced user experiences and automated responses.  
  • How these advancements are enhancing workforce and service capabilities, as well as increased data literacy.  
  • What are the challenges that need to be considered here?  
  • Accelerating processes with deep learning and neural networks – looking at the expansion of deep learning at scale across complex tasks.
. Senior Representative, ,
. Rahul Singhal, CPO, Innodata Inc.

04:10PM

(PDT)

Chanchal Chatterjee

Artificial Intelligence Leader, Google Cloud

Google

Associated Talks:

04:10PM - Day 1

View Presentation: From Concept to Production – MLOps for Your Entire ML Journey

01:50PM - Day 2

View Panel: Data led Intelligent Decision Making

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Presentation: From Concept to Production – MLOps for Your Entire ML Journey

  • End-to-end MLOps platform for 6 different ML frameworks and custom accelerators to transform your ML use cases from concept to production.
  • The platform offers 3 steps of MLOps starting with the “Dev” stage where we unit test the ML modules required in your use case.
  • This is followed by the “Test” stage where we build ML pipelines with Kubeflow and Airflow.
  • Finally the “Prod” stage deploys the ML components into production with model monitoring and CI/CD.
  • The platform is supported by code in GitHub with examples.
. Chanchal Chatterjee, Artificial Intelligence Leader, Google Cloud, Google

04:40PM

(PDT)

Chair’s Closing Remarks

04:40PM

(PDT)

End of Day 1

View day 2 content here:

Applied Data & Analytics

Data Optimisation | Big Data | Intelligent Decision Making | Data Storage | Industry Use-cases 

 

Transformational AI

Personalisation | Edge AI | Digital Transformation | Future Progressions | Industry Use-case