*AI OPEN TALKS

Wednesday, October 28, 2020

- PDT
OPEN TALK (AI): Leveraging AI to Recognize and Address Bias in Hiring
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Ashutosh Garg
Ashutosh Garg
Eightfold.ai., CEO & Co-Founder

Strategically using AI in business operations comes with an inherent ethical responsibility. This means a multifaceted approach is needed to address it. Ashutosh can explain how using career data from a large enough data set, equal parity algorithms, and audit and monitoring processes creates a transparent system that is independent from bias due to race, gender, ethnicity, age, and other characteristics. Breaking down each of these steps, Ashu can share how combining all of these levers allows candidates to move through the hiring process efficiently, accurately and while significantly reducing the potential for bias. Lastly, Ashu will share how an AI-based hiring process can help enterprises hire for potential, increase diversity, and even contribute to flattening the unemployment curve at scale today and in the future.

- PDT
OPEN TALK (AI): The 7 Habits of Highly Effective Automators
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Reza Shafii
Reza Shafii
Kong, VP of Product

Building a tech stack in today’s world means constantly making decisions about whether to automate or abstract challenges, but the goals are always the same – simplicity, security and speed. As organizations embrace myriad technologies, such as Kubernetes, to abstract away DevOps challenges, they also increase the need for automation to help them manage increasingly complex processes across platforms. In this session, Kong’s VP of Product Reza Shafii will explore how organizations can use automation to reduce friction in adopting new platforms, eliminate repetitive, error-prone tasks and increase the overall effectiveness of their development teams.

- PDT
OPEN TALK (AI): Building Scalable End-to-End Deep Learning Pipeline in the Cloud
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Rustem Feyzkhanov
Rustem Feyzkhanov
Instrumental, Machine Learning Engineer

Machine and deep learning become essential for a lot of companies for internal and external use. One of the main issues with its deployment is finding the right way to train and operationalize the model within the company. Serverless approach for deep learning provides simple, scalable, affordable and reliable architecture for it. My presentation will show how to do so within AWS infrastructure.

Serverless architecture changes the rules of the game - instead of thinking about cluster management, scalability, and queue processing, you can now focus entirely on training the model. The downside within this approach is that you have to keep in mind certain limitations and how to organize training and deployment of your model in a right fashion.

I will show how to deploy train and inference pipelines for Tensorflow models on serverless AWS infrastructure.

My talk will be beneficial for machine learning engineers and data scientists.

- PDT
OPEN TALK (AI): How Machine Learning Is Shaping Your Next Car Purchase?
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David Mortaz
David Mortaz
Binge.Ai Corp, Founder, CEO

Come and see how Machine Learning is shaping customer expectations and helping dealers respond to shopper questions.

- PDT
OPEN TALK (AI): The Rise of Enterprise Chatbot
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Gaurav Nigam
Gaurav Nigam
WorkBoard, Director Application Development

The chatbots have evolved a long way in the last few years, from the remote process automation, server orchestrations, account provisioning, customer agents to managing your schedule. One key area, where the chatbots are slowly penetrating and will be the key components, is enterprise. There're various challenges when it comes to building an enterprise chatbot and in this talk, the speaker would share a journey of enterprise chatbot, along with how to build a one that actually works.

Thursday, October 29, 2020

- PDT
OPEN TALK (AI): AI-Enabled Analytics Drive Better Agent Emotional Connection
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Tony Hung
Tony Hung
Vonage, Senior software engineer

Breakthroughs in artificial intelligence (AI), machine learning (ML) and natural language processing (NLP) have helped customers and call agents alike, to get more done in less time. It draws on multiple data sources to anticipate customer and company needs, handles interactions on its own where possible, and provides in-call support where needed.

The future of AI in the contact center is one where software tools make humans more efficient and allow the customers to have natural conversations with a bot via voice, webchat, social messaging app or other channels, handling requests, retrieving information and delivering answers to frequently asked questions. In short, creating the ultimate customer experience.

During this session, Tony Hung, senior software engineer at Vonage will discuss how enterprises with limited machine learning expertise can leverage communications APIs to unlock simple, secure and flexible solutions to deploy AI in their contact centers, elevating issues to experienced agents when needed to ensure personalized, emotive CX. He will draw on his experience to explain how enterprises can automate their agent-based live chats and streamline their support channels and operations, while offering a personalized human-like interaction. Most importantly, he will discuss how to find the right balance between seamless, intelligent self-service and efficient human intervention using integrated AI-driven communications - applications, APIs and the best of both.

- PDT
OPEN TALK (AI): Abusing Your CI/CD: Running Abstract Machine Learning Frameworks Inside Github Actions
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Jon Peck
Jon Peck
GitHub, Technical Advocate & Software Developer

We all love the conventional uses of CI/CD platforms, from automating unit tests to multi-cloud service deployment. But most CI/CD tools are abstract code execution engines, meaning that we can also leverage them to do non-deployment-related tasks. In this session, we'll explore how GitHub Actions can be used to train a machine learning model, then run predictions in response to file commits, enabling an untrained end-user to predict the value of their home by simply editing a text file. As a bonus, we'll leverage Apple's CoreML framework, which normally only runs in an OSX or iOS environment, without ever requiring the developer to lay their hands on an Apple device.

- PDT
OPEN TALK (AI): Harnessing the Power of AI for Personalization
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Gautam Gupta
Gautam Gupta
Intuit, Technology leader with AI / ML / Cloud focus

Personalization is a game changing goal for an organization. It can bring a boost to revenue as well as increase customer satisfaction. In this talk, I’ll show you the real life technology use cases of AI for implementing Personalization. I’ll share the tips and tricks of effectively using AI in the context of personalization. Join this session to learn the core AI models that can help in building awesome Personalized experiences for your customer.

- PDT
OPEN TALK (AI): A Framework for Running and Comparing Machine Learning Models
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Mariella Di Giacomo
Mariella Di Giacomo
Viasat, Database Engineer

Determining the best and most suitable Machine Learning model for a given
data science problem isn't an easy task and it can be rather challenging at times.
It is like benchmarking sports cars created by different racing teams!

This presentation will show an easily extensible framework
that implements several Machine Learning models for supervised,
unsupervised and semi supervised learning to execute and/or compare models. Additionally, the talk will introduce the open source python scikit learn toolkit through several Machine Learning Models and the open source python Hydra package from Facebook and how they have been used in the framework.
The framework is extensible, generic, portable and easy to use.

- PDT
OPEN TALK (AI): Future of Software Testing: Artificial Intelligence Assistance
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Mesut Durukal
Mesut Durukal
Siemens, Test Automation Lead

In this talk, we will discuss Machine Learning practices in Software Testing stages in detail with a case study. This is an important study since nowadays, researches are looking for adaptation of Machine Learning algorithms to testing processes to reduce the manual effort and improve quality.

We start with a quick view of the machine learning types. Then, we list AI applications in testing these perspectives: test definition, implementation, execution, maintenance and grouping, and bug handling. What’s more, we do not only present existing AI applications but also what can be done in the future. Finally, we summarize the application areas with algorithms and discuss the advantages and potential risks of AI applications in software testing.

- PDT
OPEN TALK (AI): AI and API Driven Omni Channel Servicing Strategy
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Savitha Ajitraj
Savitha Ajitraj
PayPal, Senior Product Manager, Enterprise Solutions

Customer servicing is evolving from reactive to proactive approach to retain your customer and build loyalty. I would like to share how to build AI driven Customer Service Platform with my experience at PayPal.

I will share a framework to assess your current landscape and provide a step by step journey to reach highest level of transformational impact for your customers at scale using AI.