Video Presentation

Introduction

You have a chance of earning bonus points in the AI course by recording a presentation on an AI-related topic. This activity gives you the chance to freely explore and present concepts of AI you are passionate about that are not covered in the course including state-of-the-art advancements. The presentations are short and the slide number is limited. So, you need be concise and to-the-point.

Compose something you will be proud of!

General Guidelines

Please read carefully the following guidelines and adhere to them:

  1. Points: Maximum bonus points that can be earned from this activity is 10% of total course points: Maximum 5% from the verbal presentation and another 5% on the quality, organization, and coherence of the slides.

  2. Limits: Aim for a 7-minute presentation. It may not be less than 5 or more than 9 minutes. You can include short external videos in your presentation, but the presentation duration without them should be above the minimum, and with them below the maximum. Going over/under these limits will cost you points. Aim at 10 slides – keep the number above 7 and below 13 slides. Anything other than the main body of the presentation (e.g., title and references, etc.) are excluded from the slide limit count.

  3. Topic: We have provided a list of suggested topics from which you could choose one (see below) or you can also pick a topic that you are interested in that is not in the list. Appropriateness and significance of the topic will be evaluated in peer-review.

  4. Structure: Presentation and slides need to be to-the-point and, at the same time, self-sufficient. Address all points agreed on for the chosen topic (More details below).

  5. Format: Record your presentation as a video showing the slides and the audio of you presenting as a minimum (you can record yourself as well). You can use Panopto video recording software to create your presentation video (For instructions on installing Panopto software and recording with it, see: https://intra.tuni.fi/en/handbook/2677/2743/10802?page=9687). Whichever software (Panopto, PowerPoint, …) you choose to use, submit a link to where your video is uploaded in the text field on the submission page. Make sure also that the destination folder is Courses > Courses 2019- > DATA.ML.310-2021-2022-1 Artificial Intelligence (Lectures) [assignments]. Uploaded videos will not be visible to other students except for your peers doing its review.

    Note

    More detailed instructions on how to submit link to your video can be found here

  6. Referencing: Plagiarism is strictly prohibited! Read source material to gain information on the chosen topic. Digest what you have read and write down the things in your own words. When you want to make a direct citation acknowledge the original publication. Proper referencing is important and is thus also graded.

  7. Grading: This activity is peer-graded, which means that after you submit your video and slides, you get assigned 3 of your peers’ slides and presentations to grade based on the following criteria. Keep in mind that in order to receive points you have to complete the grading part as well. Grading Criteria is generally as follows:

    1. Appropriateness of the topic: 1 point slides/presentation.
    2. Demandingness of the topic: 1 point slides/presentation.
    3. Adhering to limits + proper referencing: 1 point slides/presentation.
    4. Structure: The following points are graded as 0.5 points in the slides/presentation:
      1. Describe the technique or application clearly and concisely.
      2. Report the advantages that have been gained.
      3. Discuss how you see the future on this application / technique.
      4. Provide examples wherever relevant.

Possible Topics

The same topic can be chosen by several students. However, each needs to compose her/his own slides and give an individual presentation. Suitable topic candidates include (feel free to modify):

Exploring / deepening the techniques covered in the textbook (but not in the course), such as:

  • Knowledge representations and knowledge bases
  • Planning (algorithms)
  • Probabilistic Reasoning over time (e.g., Kalman and Particle Filters)
  • Computer vision
    • Object tracking algorithms
    • Face recognition
    • Gesture identification
  • Robotics
  • Security in AI
  • Application of AI techniques to real-world problems, e.g., at your work.
  • Recent algorithmic development within AI
  • New AI techniques / approaches which are making a major impact
  • Autonomous Vehicles
  • Commonsense reasoning
  • AI in Game Playing
  • Social Intelligence
  • Societal impact of AI in a particular application area, for example:
    • other fields of science
    • medicine and healthcare
    • business
    • popular culture, entertainment, recreation
  • Particular machine learning algorithms
  • Attacks against machine learning/AI algorithms
  • Negative application and impact of AI
  • Philosophical Foundations of AI
  • Future of AI
Posting submission...