#TheDevConf 2021 | FUTURE : ARTIFICIAL INTELLIGENCE TRACK INTERNATIONAL

ARTIFICIAL INTELLIGENCE TRACK INTERNATIONAL

A developer friendly track covering the new trends in AI and the opportunity to learn more about its various subfields, such as machine learning, deep learning, natural language processing (NLP) and robotics.

Artificial Intelligence (AI) has been a hot topic for several years now, constantly finding its way into a growing number of everyday applications.

In this second edition of the track, you'll have access to the new trends in AI and the opportunity to learn more about its various subfields, such as machine learning, deep learning, natural language processing (NLP) and robotics, not limited to just python developers but also inclusive to Java/JVM developers alike."

Date and Place

Wednesday, December 1, 2021

09h às 19h GMT-3

REMOTE ACCESS WITH ONLINE BROADCAST

Investment

For Brazilians, in BRL:
1 track: R$ ~~145~~ for R$ 110
2 tracks: R$ ~~290~~ for R$ 198
3 tracks: R$ ~~435~~ for R$ 285
* price valid until OCT/11, see full table

For Brazilians, in BRL:
1 track: R$ ~~145~~ for R$ 130
2 tracks: R$ ~~290~~ for R$ 230
3 tracks: R$ ~~435~~ for R$ 330
* price valid until NOV/12, see full table

For Brazilians, in BRL:
1 track: R$ 145
2 tracks: R$ ~~290~~ for R$ 260
3 tracks: R$ ~~435~~ for R$ 370
* price valid until DEC/02, see full table

For Foreigners, in USD:
1 track: ~~$30~~ for $20 USD
Connect Pass: ~~$80~~ for $60 USD
* price valid until OCT/11

For Foreigners, in USD:
1 track: ~~$30~~ for $25 USD
Connect Pass: ~~$80~~ for $70 USD
* price valid until NOV/12

For Foreigners, in USD:
1 track: $30 USD
Connect Pass: $60 USD
* price valid until DEC/02

How to register

ALL TRACKS

Schedule / Talks Time Zone: GMT-3 ALL TRACKS

Time	Content
10:15 to 10:45 (GMT-3) 13:15 to 13:45 (GMT)	TDC Opening Welcome Session - International Edition
10:50 to 11:25 (GMT-3) 13:50 to 14:25 (GMT)	When should I Retrain My Model ? Horst Erdmann / André Oliveira da Silva Once a Machine Learning model is deployed and working, when is the best time to retrain it ? How to evaluate automatically if the prediction dataset has changed over time ? We intend to present a methodology where we answer these questions. After showing our method, we present a use-case for car damage detection using Deep Learning. Finally, we show the concepts of data drift detection over the presented use-case model and simulate different situations The presentation will be in the form of slides, and the code to the experiments and data will be shared on a GitHub repo after the presentation (To prevent spoilers).
11:30 to 12:05 (GMT-3) 14:30 to 15:05 (GMT)	MLOps: DevOps for Machines Tarcisio Oliveira Artificial Intelligence / Machine Learning is quickly becoming essential for companies and organizations around the world, generating emerging demands for IT resources. MLOps applies DevOps to AI/ML, combining cultural philosophies, practices, and tools to the development cycle of ML models and infrastructure, whether public cloud, on-premise or hybrid, in order to deliver systems and services with greater speed, reliably , scalable, resilient and secure. In this presentation, we will pass some concepts of artificial intelligence / machine learning, MLOps, and a technical overview of some tools that help implement this model.
12:10 to 12:45 (GMT-3) 15:10 to 15:45 (GMT)	Autonomous Robots with Deep Learning, Natural Language and Logic Hobbert Evergreen Autonomous robots have arrived in an increasing amount of areas and usages. They need to interact with human beings, solve tasks, and this makes them need a lot of skills such as natural language, logic, people detection, and recognition. Deep learning techniques, speech recognition, planning and navigation through environments, real-time people interaction are helpful in these scenarios. We have worked for some years delivering more robust and efficient computer vision algorithms. They can interact with lots of complex scenarios, taking Artificial Intelligence to its most diverse limits.
12:50 to 13:50 (GMT-3) 15:50 to 16:50 (GMT)	Networking and Visiting Stands Break to network and get to know the booths of the event.
14:00 to 14:05 (GMT-3) 17:00 to 17:05 (GMT)	Track opening by coordination Here the coordinators introduce themselves and make an introduction to the track.
14:10 to 14:45 (GMT-3) 17:10 to 17:45 (GMT)	Opening a business in Brazil with the help of Artificial Intelligence Ingrid Knochenhauer de Souza / Nickolas Mendes Suppose you want to open your own business. A lot of questions can come over your head: Where should I open my business? In my core business, what are the main activities exercised in my region? Based on the existing company data, how has been their profile to be successful? Are they specialists or diversifying ones? In Brazil, we have open data of companies from all over the country. This data is a rich soil to artificial intelligence to be used as an instrument for decision-makers.
14:50 to 16:05 (GMT-3) 17:50 to 19:05 (GMT)	Panel discussion: Would advancements in NLP and other AI advancements affect privacy and fairness? Eyal Wirsansky / Mani Sarkar / Pablo Garateguy / Alessandra Monteiro Martins / Patricia Nunes Goncalves / Leonardo Moraes / Gerald Venzl It's an organic conversation with no specific structure. We build up as we go talking about how modern day advancements in NLP and other AI advancements maybe affecting privacy and fairness for everyone. This differs for everyone and every group and the corporate and academic worlds. Our speakers would be exploring this from different perspectives. We also welcome our guests and audience to add to the discussion with questions and comments.
16:10 to 16:25 (GMT-3) 19:10 to 19:25 (GMT)	Networking and Visiting Stands Break to network and get to know the booths of the event.
16:25 to 17:00 (GMT-3) 19:25 to 20:00 (GMT)	Automated Machine Learning for Image Processing Daniel Carvalho Photos are everywhere! With the popularity of smartphones, we need to get information from images and add value to the business. It can be made with automated machine learning, on the cloud productively. Let's see practical code application of machine learning in images at the cloud, how it can be made easily with short and sophisticated code. Identify image content, classify image content, get face features and recognition, create and deploy it as an API at the cloud and integrate with your current legacy system, app, or site. Developers do not need to master ML to have the advantage of it, they can quickly test, prototype, and put it in production, get information from data.
17:05 to 17:40 (GMT-3) 20:05 to 20:40 (GMT)	What is Text Summarization and how can we use it? Leonardo Moraes Have you ever heard about Text Summarization? Basically, Text Summarization refers to techniques of shortening long pieces of texts. In this presentation, we will see how this Natural Language Processing (NLP) technique works and some business applications, as well as some real cases of article summaries (in German) and chat conversations (in Portuguese). Note that the presentation will be a theoretical abstraction, therefore no code.
17:45 to 18:20 (GMT-3) 20:45 to 21:20 (GMT)	Explaining machine learning to kids Dale Lane Children are growing up in a world where machine learning is fast becoming ubiquitous and will affect many aspects of their lives. So we should be helping them to understand what machine learning is and what it can do, and how it impacts the world around them. This session will demonstrate free tools from IBM, MIT, Mozilla, and Google that can be used by children to learn about machine learning through hands-on creative activities. Children in schools and code clubs around the world are using these to make their own games and interactive ML projects, and learning about the way these technologies behave and are applied.
18:25 to 18:45 (GMT-3) 21:25 to 21:45 (GMT)	Closing session After the presentation of the results of the day, on the Stadium stage, many sweepstakes will close the day.