Day 1 - 5 October 2022
09:45AM
(PDT)
Mohan Reddy
Chief Technology Officer/ Associate Director, Human Perception Lab
SkyHive/ Stanford University
09:45AM - Day 1
View Enterprise AI: Chairpersons Welcome
Enterprise AI: Chairpersons Welcome
Chairpersons welcome and opening remarks.
10:00AM
(PDT)
Xingchu Liu
SVP Enterprise Data & Analytics
Macy's
10:00AM - Day 1
View Presentation: Building Enterprise AI Excellence
11:00AM - Day 1
View Panel: Responsible delivery – the ethics of AI
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.
10:30AM
(PDT)
Braden Hancock
Co-founder and Head of Technology
Snorkel AI
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
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.
11:00AM
(PDT)
Mohan Reddy
Chief Technology Officer/ Associate Director, Human Perception Lab
SkyHive/ Stanford University
09:45AM - Day 1
View Enterprise AI: Chairpersons Welcome
Ruben Buell
Chief Technology Officer & Chief Operations Officer
Reflex Media
11:00AM - Day 1
View Panel: Keeping it Ethical in AI
Braden Hancock
Co-founder and Head of Technology
Snorkel AI
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
Arjuna Flenner
Senior Technical Leader, Machine Learning and Autonomy
GE Aviation Systems
11:00AM - Day 1
View Panel: Keeping it Ethical in AI
Forrest Pascal
Principal, AI/ML Model Governance, Data & AI Platform Engineering
Kaiser Permanente
11:00AM - Day 1
View Panel: Keeping it Ethical in AI
Karthik Shanmugasundaram
Senior Engineering Manager, Linkedin Learning Discovery & Search
11:00AM - Day 1
View Panel: Keeping it Ethical in AI
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.
11:40AM
(PDT)
Bjorn Austraat
Head of AI Acceleration
Truist
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
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
12:10PM
Lunch & Networking in the Exhibition Area
12:40PM
(PDT)
Senior Representative, Snowplow Analytics
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
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.
01:00PM
(PDT)
Dr. Satyam Priyadarshy
Managing Director-India Centre & Technology Fellow and Chief Data Scientist
Halliburton
01:00PM - Day 1
View Presentation: Digital Disruption in a Complex Industry
Presentation: Digital Disruption in a Complex Industry
Session focusing on utilizing Cloud and AI in the energy sector.
01:30PM
(PDT)
Senior Representative, Altada Technology Solutions
01:30PM - Day 1
View Presentation: AI Enterprise Solution
Presentation: AI Enterprise Solution
To follow soon …
01:50PM
(PDT)
Dan Mallin
CEO and Founder
Lucy AI
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
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.
02:00PM
(PDT)
Laura Patel
Principal Data Scientist
UPS
02:00PM - Day 1
View Applying AI in the Enterprise to Drive Value
01:10PM - Day 2
View Panel: Making sense of your data
Applying AI in the Enterprise to Drive Value
02:20PM
(PDT)
David Keene
Chief Strategy Officer
Speechmatics
02:20PM - Day 1
View Presentation: AI Bias, Inclusion, and Diversity in Speech Recognition
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.
02:40PM
Coffee & Networking in the Exhibition Area
03:00PM
(PDT)
Cal Al-Dhubaib
CEO, AI Strategist
Pandata
03:00PM - Day 1
View Presentation: Operational Al and ML Building Business Capabilities
Presentation: Operational Al and ML Building Business Capabilities
To follow soon …
03:20PM
(PDT)
Andy Rossmeissl
CEO & Co-founder
Faraday
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
Presentation: Build vs. Build Faster — Empower your Marketing Team with Consumer Predictions at Scale
To follow soon …
03:30PM
(PDT)
Senior Representative
03:30PM - Day 1
View Panel: Evolving the Enterprise with Language Modelling
Rahul Singhal
CPO
Innodata Inc.
03:30PM - Day 1
View Panel: Evolving the Enterprise with Language Modelling
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.
04:10PM
(PDT)
Chanchal Chatterjee
Artificial Intelligence Leader, Google Cloud
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
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.
04:40PM
(PDT)
Chair’s Closing Remarks
04:40PM
(PDT)
End of Day 1
View day 2 content here:
Data Optimisation | Big Data | Intelligent Decision Making | Data Storage | Industry Use-cases
Personalisation | Edge AI | Digital Transformation | Future Progressions | Industry Use-case