Khipu, or talking knots, were ancient data systems fashioned from knotted strings historically used by a number of cultures in the region of Andean South America. Khipus were used to store (mostly numerical) information and had multiple practical uses in the local communities.

Besides, one of the main goals of the event is to knit a network of Latin American talent in AI!

Khipu will be an annual regional Artificial Intelligence (AI) gathering and summer school in Latin America. The event is organized by a group of Latin American researchers working both inside and outside the region. Our primary goal is to facilitate a wide and diverse participation: there will be no registration fees for accepted students*, and we will provide financial assistance for travel expenses to selected applicants.

The inspiration for Khipu comes in large part from the success of the Deep Learning Indaba in Africa and the Eastern European Machine Learning Summer School.

Khipu aims to strengthen the AI ecosystem in Latin America via the following specific goals:

· Unlock talent through advanced trainings
· Foster research by building community
· Drive adoption by increasing awareness

* Students should be advanced undergrads, MSc, PhD, or postdoc level.

The inaugural conference will take place November 11-15, 2019 at the Universidad de la República Engineering School in Montevideo, Uruguay.

Everyone is welcome to apply, regardless of location or whether you are a student or not. We strive to have participants with diverse backgrounds to encourage networking between academic and industry communities from all over the world. The location of the summer school is tied to Latin America to raise visibility of the local Machine Learning community. But we are looking for participants coming from any region of the world.

Registration is FREE for full time students*. For general attendees there is a fee (please see below for details). Registration covers participation in lectures and practical sessions, lunch, coffee breaks and evening events. All other costs, including travel and accommodation, are the responsibility of the attendees. Attendees may apply for financial support for travel and accommodation.

* Students should be advanced undergrads, MSc, PhD, or postdoc level.

If you are interested in the topics of the summer school but the fees might prevent you from attending, you can apply for a scholarship. These are open to everyone, not only students. When filling in the Application form, please give a short justification for your request (this will not affect your chances of being accepted to attend Khipu). The funding will vary on a case-by-case basis and will cover fully or partially the costs of attending the school (registration, accommodation, travel).

· Unparalleled networking opportunities: Khipu will be the most important gathering of the fast-growing Latin American AI community.

· Learn from and interact with elite AI researchers: Khipu invited speakers are some of the very best AI talent in Latin America and the world!

· Take the time to focus on learning: The week long summer school has an intense programme designed to both teach and reinforce through tutorials, practical sessions and discussion with peers.

Applications for Khipu 2019 open on March 29. and will close on June 28.

Participants are expected to:

· Have experience in programming (preferably Python); knowledge of any modern framework for neural networks (TensorFlow, Keras, Theano, PyTorch, etc.) will come in handy though is not strictly necessary;

· Be familiar with notions of Linear Algebra, Probability Theory, general Machine Learning;

· Be very interested in learning about Deep Learning and Reinforcement Learning.

Any project related to the theme of the school (Machine Learning, Deep Learning or Reinforcement Learning) would be relevant. The project itself does not necessarily need to rely heavily on these techniques, but should connect to them (e.g. point out where they could have been used). It does not need to be novel either. For example, you can present your experience of reproducing published work, but be original and add a personal twist. If in doubt whether your project is suitable for presentation, you can send us an email at [email protected] and ask for advice as soon as possible.

Submissions are non-archival, so you can submit the same work to another conference/workshop.

Yes, you can submit the abstract of an already published paper if it is related to the theme of the summer school. Please specify in the abstract the venue where the paper was published.

Yes, during the application period, from March 29to June 28 you can update or edit the form. After the deadline this will not be possible anymore. We do recommend you to submit a partially completed form as early as possible and update it in due time. This will reduce the pressure as the deadline comes close and ensures you are familiar with the form, in particular how to upload files. Please make sure to keep the confirmation email received when submitting for the first time, as it contains the link to edit your form. Without this link, you will need to start the application all over again.

Yes, you can re-upload as many times as necessary. Please ensure the file is named properly every time you upload, otherwise it might not be correctly linked to your application. You do not need to update the form after re-uploading.

You can find details of the poster sessions and sizes here, and details of the industry exhibitions here.

Programming language: Python; Deep Learning library: TensorFlow and/or Pytorch.

We encourage people to apply even if they don’t have experience with TensorFlow or PyTorch. There will be a list of exercises posted prior to the summer school that participants can work on to get familiar with the environment used during the school.

The experiments will run in Colab - a framework provided by Google where you can access for free the Google cloud (CPU or GPU) to run ML experiments. You can use Colab on your own as well, independent from the school. All you need is a gmail account.

The experiments will run in Colab - a framework provided by Google where you can access for free the Google cloud (CPU or GPU) to run ML experiments. You can use Colab on your own as well, independent from the school. All you need is a gmail account.

Yes, you are encouraged to use your own laptop during labs. There are no specific hardware requirements. Only make sure you have Google Chrome installed, which is used to access the lab environment, Colab.

Yes, participants will receive a certificate at the end of the school, confirming their participation at the activities of the school.

Citizens from most* of Latin American countries, of the United States, Australia, Canada, Japan, New Zealand, Israel, South Africa, most of Europe and Scandinavia DO NOT require a tourist visa to enter Uruguay.

See here for a map and here for the full list of visa exemption.

If you get accepted to the school and you need a visa, contact us and we will send you an invitation letter.

The fee for non students is $400 US dollars.

Members of nonprofits do not have to pay to attend.

Please write to us at [email protected]

11-15TH. of November 2019

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