AInspire’s 2020 Synapshot Competition

Head to this Google form to register!


Project Details

Synapshot: A short (3-4 minute long) video that sheds light on a specific concept in AI! For reference, check out our current Synapshot here as well as past ones on our YouTube channel.

Your task (it’s simple!): Choose a topic in AI of interest (that you can tie in with biology!) and create a video to teach others about it using concise language and attractive graphics.

Videos will be judged on:

  • Demonstrated understanding of the material in the video

  • A concise yet accurate description of the concept

  • Attractive graphics

  • Complexity of the topic selected

No AI experience? No problem! To find a topic & learn about it you can:

  • Attend one of our workshops

    • View the workshops we offer here and pick one that interests you

    • If a workshop that you are interested in attending is not on the schedule, please email contact@ainspire.org to request a date!

  • Watch one of our Synapshots

    • This is a great way to prepare since you’ll have examples of how Synapshots look & you can get topic ideas!

  • We’ll also be releasing a topic ideas sheet in the next couple of weeks

    • Sign up for our mailing list, follow our instagram, or keep checking our website to find out when we release that sheet!

Two important documents!

  • Here's the link to the Google document where you’ll find the judging criteria and rubric. The rubric has been updated, so make sure you’re caught up!

  • This document contains important information regarding rules, submission guidelines, and more.


Important Dates

September 1st, 2020: Registration opens; resources & judging criteria will be released

September 26th, 2020: Submission portal will open

October 3rd, 2020: Submission deadline

October 17th: Competition decisions are released


Prizes

Grand Prize Winners (1): $100 gift card to store of choice

2nd Place (2): $50 gift card to store of choice

3rd place (3): $15 gift card to store of choice

Honorable mention (4): $10 gift card to store of choice

All competition participants will get free swag (think stickers). The top four winners listed above will also receive a t-shirt and have their videos featured on our social media channels and website!


Judges

Introducing our amazing team of judges! The AInspire Team thanks you so much for your help in making this possible!

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Addison

Leong

Addison builds things. He is the Director of Engineering at Pear Ventures, where he crafts portfolio-driving software and advises aspiring entrepreneurs. Before joining Pear, Addison was a product manager at Solvvy, after graduating from Stanford University with a degree in Symbolic Systems. He spends most of his free time producing music, baking, and wandering off to various art museums in search of new inspiration.

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John Melloni

Born and raised just north of Boston, MA, John graduated from the University of Massachusetts, Amherst, with a BS in Computer Engineering in 2018, and from Stanford University with a Master’s in Computer Science this past June. While at Stanford, he concentrated in Artificial Intelligence and Robotics. After graduating, John recently started working at Amazon Robotics as a Software Engineer. 

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Sailesh Patnala

Sailesh graduated from UC Davis in 2018 with a Bachelor of Science in Computer Science. He went on to work as a software engineer in finance for 2 years and he’s currently pursuing his Master in Engineering in Computer Science at Cornell Tech specializing in Machine Learning. 

Divya Saini

Divya spent her early career working in finance after completing her BA in Computer Science and MS in Management Science from Stanford University. She's currently exploring applications of technology in health and medicine.

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Lucy Li

Lucy is a PhD student who taught at Stanford AI4ALL, a program for high school students, at Berkeley and Stanford. Her research at UC Berkeley uses natural language processing and data mining to shed light on social behavior and interactions.

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Magdy Saleh

Magdy is a Machine Learning Engineer at Gridspace where he works on large scale natural language processing systems. Previously he was a masters student at Stanford studying Computer Science with a specialization in Artificial Intelligence.