Applied AI Innovation

Wednesday, October 26, 2022

- PDT
PRO TALK (AI): Data Ecosystem a Stepping Stone for Decarbonization of Operation Industry

Climate change is possibly one of the most complex and challenging issues on earth. On the other hand, manufacturing companies often find themselves in the crosswind of it. Oil and gas, mining, chemical, cement, energy, and utility sectors are responsible for more than 50% of the industrial GHG emissions. The changes they are bringing into their operations are not enough to address the issue. New initiatives for carbon abetment are not showing any visible improvement in reducing GHG levels in the environment.

In this session, we will analyze how data ecosystems such as LiDAR, remote-sensing data, IT, and OT data pertinent to these manufacturing companies can help them to track/measure, trace and mitigate excess emission issues for their operations. We will also explore how advanced AI techniques such as deep learning, and reinforcement learning techniques can be used effectively to find an optimal solution for the above-mentioned problem/s with real-life examples. 

- PDT
OPEN TALK (AI): How To Build An AI Based Knowledge Graph for Customers in Fintech
Gautam Gupta
Gautam Gupta
Intuit, Technology leader

In this session, we’d go through our journey to build an AI based Customer Knowledge graph. We’d share the insights & knowhow required to create this scalable & polyglot data platform. Join us to learn the design patterns & best practices that we have developed over time to create an intelligent solution based on AI & Graph technologies for an ever increasing list of product lines and customers. 

- PDT
OPEN TALK (AI): Patenting Artificial Intelligence– How AI Companies Can Identify and Protect AI Inventions
Steve Bachmann
Steve Bachmann
Bachmann Law Group PC, President, Silicon Valley Patent Attorney

Artificial intelligence is becoming one of the most widespread and useful technologies in use today. From data collection to model training, language processing to predictive models, deep networks to AI frameworks, there are many categories and implementations of AI, all with protectable features and important business applications. Protecting cutting edge AI technology helps companies achieve business goals and support their AI innovation.
This presentation will identify key strategies to identify which aspects of AI are patentable and which aspects are not. The discussed strategies will be supplemented with practical real-world examples of patenting different areas of the AI process, from data collection to model training and model implementation to output applications, as well as distinct types of AI systems.
Attendees will also learn about AI patent trends and the most common use cases in which different AI companies build valuable patent portfolios around their AI technology. 

- PDT
OPEN TALK (AI): Scalable, Explainable and Unsupervised Anomaly Detection for Telecom
Ivan Caramello de Andrade
Ivan Caramello de Andrade
Encora Brazil Division, Innovation Leader and Tech Lead

In developing and implementing a telecommunications network, one of the most oppressive challenges that these companies deal with are anomalies that occur within the network showing that something strange (usually an attack, a fraud or an error) is happening. Detecting these anomalies is a challenge because they may appear in different places and formats and require the observation of multiple metrics over hundreds of thousands of events to tell regular behaviors from anomalous ones. Ivan Carmello De Andrade, would like to explain how detecting these anomalies with higher accuracy may be possible with the technology and machine learning capabilities of today.

In his technical session, Ivan will explain how he and his team were able to customize and adapt a Robust Random Cut Forest model to identify and explain anomalies in an unsupervised and scalable way. He and his team will explain the process behind creating this solution as well as the challenges they overcame in development, such as extracting behaviors from individual events. He will also explain the benefit of this model to the user which include:

• The user does not need to understand which behaviors are regular or anomalous nor which features are relevant to describe and identify them
• The model provides accountability, because the user can identify and understand which factors lead to an event being identified as an anomaly
• Scalability in general, the model can be implemented on many different scales with a highly distributable structure and configurable levels of detail 

- PDT
OPEN TALK (AI): Pushing Deepfakes to the Limit - Fake Video Calls with AI
Martin Förtsch
Martin Förtsch
TNG Technology Consulting GmbH, Principal Consultant
Thomas Endres
Thomas Endres
TNG Technology Consulting GmbH, Partner
Jonas Mayer
Jonas Mayer
TNG Technology Consulting GmbH, Senior Consultant

Today's real-time Deepfake technology makes it possible to create indistinguishable doppelgängers of a person and let them participate in video calls. Since 2019, the TNG Innovation Hacking Team has intensively researched and continuously developed the AI around real-time Deepfakes. The final result and the individual steps towards photorealism will be presented in this talk.

Since its first appearance in 2017, Deepfakes have evolved enormously from an AI gimmick to a powerful tool. Meanwhile different media outlets such as "Leschs Kosmos", Galileo and other television formats have been using TNG Deepfakes.

In this talk we will show the different evolutionary steps of the Deepfake technology, starting with the first Deepfakes and ending with real-time Deepfakes of the entire head in high resolution. Several live demos will shed light on individual components of the software. In particular, we focus on various new technologies to improve Deepfake generation, such as Tensorflow 2 and MediaPipe, and the differences in comparison to our previous implementations. 

- PDT
OPEN TALK (AI): Democratizing Deep Learning with Vector Similarity Search
Nava Levy
Nava Levy
Redis, AI/ML Developer Advocate

Deep learning is responsible for most of the breakthroughs we have seen in AI/ML in recent years, yet most companies' models in production use classic or traditional ML. In this talk we will explore how deep learning is being democratized today, thanks to the rising use and availability of vector embeddings from giant pre-trained neural networks. We will see how these embeddings can be combined together with vector similarity search to address different use cases covering any modality and applied to any type of object. Finally, we will discuss the many opportunities this presents as well as the tools that are required to successfully deploy these applications into production. 

Thursday, October 27, 2022

- PDT
OPEN TALK (AI): Scaling AIaaS: from DALL-E to Uber
Daniel Siryakov
Daniel Siryakov
Comet, Senior Product Manager

As companies begin to embrace AI in key parts of their businesses, they want to explore and scale AI at minimal costs. However developing in-house AI-based solutions for every problem is a complex process and requires huge capital investment. The industry is now embracing AI as a service wherein third party tools can fill in the gaps. In this talk, Daniel will walk through the current landscape, trends, and technical challenges. He will also feature a few customer stories and a proposed modular solution to help your team jumpstart on this journey. 

Wednesday, November 2, 2022

- PDT
[#VIRTUAL] PRO TALK (AI): Data Ecosystem a Stepping Stone for Decarbonization of Operation Industry

Climate change is possibly one of the most complex and challenging issues on earth. On the other hand, manufacturing companies often find themselves in the crosswind of it. Oil and gas, mining, chemical, cement, energy, and utility sectors are responsible for more than 50% of the industrial GHG emissions. The changes they are bringing into their operations are not enough to address the issue. New initiatives for carbon abetment are not showing any visible improvement in reducing GHG levels in the environment.

In this session, we will analyze how data ecosystems such as LiDAR, remote-sensing data, IT, and OT data pertinent to these manufacturing companies can help them to track/measure, trace and mitigate excess emission issues for their operations. We will also explore how advanced AI techniques such as deep learning, and reinforcement learning techniques can be used effectively to find an optimal solution for the above-mentioned problem/s with real-life examples. 

- PDT
[#VIRTUAL] OPEN TALK (AI): How To Build An AI Based Knowledge Graph for Customers in Fintech
Gautam Gupta
Gautam Gupta
Intuit, Technology leader

In this session, we’d go through our journey to build an AI based Customer Knowledge graph. We’d share the insights & knowhow required to create this scalable & polyglot data platform. Join us to learn the design patterns & best practices that we have developed over time to create an intelligent solution based on AI & Graph technologies for an ever increasing list of product lines and customers. 

- PDT
[#VIRTUAL] OPEN TALK (AI): Patenting Artificial Intelligence– How AI Companies Can Identify and Protect AI Inventions
Steve Bachmann
Steve Bachmann
Bachmann Law Group PC, President, Silicon Valley Patent Attorney

Artificial intelligence is becoming one of the most widespread and useful technologies in use today. From data collection to model training, language processing to predictive models, deep networks to AI frameworks, there are many categories and implementations of AI, all with protectable features and important business applications. Protecting cutting edge AI technology helps companies achieve business goals and support their AI innovation.
This presentation will identify key strategies to identify which aspects of AI are patentable and which aspects are not. The discussed strategies will be supplemented with practical real-world examples of patenting different areas of the AI process, from data collection to model training and model implementation to output applications, as well as distinct types of AI systems.
Attendees will also learn about AI patent trends and the most common use cases in which different AI companies build valuable patent portfolios around their AI technology. 

- PDT
[#VIRTUAL] OPEN TALK (AI): Scalable, Explainable and Unsupervised Anomaly Detection for Telecom
Ivan Caramello de Andrade
Ivan Caramello de Andrade
Encora Brazil Division, Innovation Leader and Tech Lead

In developing and implementing a telecommunications network, one of the most oppressive challenges that these companies deal with are anomalies that occur within the network showing that something strange (usually an attack, a fraud or an error) is happening. Detecting these anomalies is a challenge because they may appear in different places and formats and require the observation of multiple metrics over hundreds of thousands of events to tell regular behaviors from anomalous ones. Ivan Carmello De Andrade, would like to explain how detecting these anomalies with higher accuracy may be possible with the technology and machine learning capabilities of today.

In his technical session, Ivan will explain how he and his team were able to customize and adapt a Robust Random Cut Forest model to identify and explain anomalies in an unsupervised and scalable way. He and his team will explain the process behind creating this solution as well as the challenges they overcame in development, such as extracting behaviors from individual events. He will also explain the benefit of this model to the user which include:

• The user does not need to understand which behaviors are regular or anomalous nor which features are relevant to describe and identify them
• The model provides accountability, because the user can identify and understand which factors lead to an event being identified as an anomaly
• Scalability in general, the model can be implemented on many different scales with a highly distributable structure and configurable levels of detail 

- PDT
[#VIRTUAL] OPEN TALK (AI): Pushing Deepfakes to the Limit - Fake Video Calls with AI
Thomas Endres
Thomas Endres
TNG Technology Consulting GmbH, Partner
Martin Förtsch
Martin Förtsch
TNG Technology Consulting GmbH, Principal Consultant
Jonas Mayer
Jonas Mayer
TNG Technology Consulting GmbH, Senior Consultant

Today's real-time Deepfake technology makes it possible to create indistinguishable doppelgängers of a person and let them participate in video calls. Since 2019, the TNG Innovation Hacking Team has intensively researched and continuously developed the AI around real-time Deepfakes. The final result and the individual steps towards photorealism will be presented in this talk.

Since its first appearance in 2017, Deepfakes have evolved enormously from an AI gimmick to a powerful tool. Meanwhile different media outlets such as "Leschs Kosmos", Galileo and other television formats have been using TNG Deepfakes.

In this talk we will show the different evolutionary steps of the Deepfake technology, starting with the first Deepfakes and ending with real-time Deepfakes of the entire head in high resolution. Several live demos will shed light on individual components of the software. In particular, we focus on various new technologies to improve Deepfake generation, such as Tensorflow 2 and MediaPipe, and the differences in comparison to our previous implementations. 

- PDT
[#VIRTUAL] OPEN TALK (AI): Democratizing Deep Learning with Vector Similarity Search
Nava Levy
Nava Levy
Redis, AI/ML Developer Advocate

Deep learning is responsible for most of the breakthroughs we have seen in AI/ML in recent years, yet most companies' models in production use classic or traditional ML. In this talk we will explore how deep learning is being democratized today, thanks to the rising use and availability of vector embeddings from giant pre-trained neural networks. We will see how these embeddings can be combined together with vector similarity search to address different use cases covering any modality and applied to any type of object. Finally, we will discuss the many opportunities this presents as well as the tools that are required to successfully deploy these applications into production. 

Thursday, November 3, 2022

- PDT
[#VIRTUAL] KEYNOTE (AI): Indico Data - Unstructured Data: Challenge and Opportunity for the AI Developer
Christopher M. Wells, Ph. D.
Christopher M. Wells, Ph. D.
Indico Data, VP of Research and Development

Unstructured Data represents a massive and little explored frontier for both the enterprise and the enterprise technology professional. The dizzying proliferation of tools for programatically working with documents, audio, images and video (as well as the corresponding hype) can be overwhelming. This session will provide a practical framework for breaking down the analysis and automation of unstructured data stores and flows, as well as a survey of success stories. 

- PDT
[#VIRTUAL] PRO TALK (AI): Enabling AI for Developers
Orly Amsalem
Orly Amsalem
cnvrg.io, VP of AI Innovation

Gartner TalentNeuron reveals that, in the U.S. employment market, there are roughly 140,000 people who describe themselves as data scientists. The supply of data science talent falls short compared to the demand for AI in everyday applications. Meanwhile, there are about 30M software developers that are looking for ways to enhance their applications with AI capabilities. The use of AI solutions is growing every day, with recommendation engines, text detection, virtual agents and more. As demand for AI grows, the fate of AI’s maturity relies on making AI accessible to developers, engineers, and business users, and offering the tools to apply machine learning in minutes.
In this session we will talk about how developers can become the main drivers of AI transformation and give an overview of cnvrg.io AI Blueprints, a new capability designed for data scientists, and software developers to build and create AI and integrate it to their applications. In minutes, any software developer or engineer can apply object detection, text-detection, pose-detection, scene detection and more into any application or solution they are building. Developers can use their own data to train and deploy their models using customizable and open source ML pipelines for any use case or industry. We will end with a real-life example of how to build and deploy a production-quality AI Blueprint in minutes. 

- PDT
[#VIRTUAL] OPEN TALK (AI): Scaling AIaaS: from DALL-E to Uber
Daniel Siryakov
Daniel Siryakov
Comet, Senior Product Manager

As companies begin to embrace AI in key parts of their businesses, they want to explore and scale AI at minimal costs. However developing in-house AI-based solutions for every problem is a complex process and requires huge capital investment. The industry is now embracing AI as a service wherein third party tools can fill in the gaps. In this talk, Daniel will walk through the current landscape, trends, and technical challenges. He will also feature a few customer stories and a proposed modular solution to help your team jumpstart on this journey.