Designing for TinyML Survey
If your company is building AI functionality for TinyML, we're very interested in your feedback!

To help support the TinyML community, Latent AI is conducting a short survey to find out how engineers and developers make design choices for their TinyML systems. All answers will be confidential (please see our Privacy Policy at https://latentai.com/privacy-policy). We intend to share only the key results (not personal information) of this survey with the TinyML community.

Please feel free to contact us at info@latentai.com for any inquiries or additional information.

We hope you are staying safe and healthy during these unprecedented times.

Thank you so much for your time and feedback!

The Latent AI Team


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1. Which of the following best describes your company’s focus? (Select all that apply) *
2. What is your role? *
3. Thinking about current products or design projects, what TinyML hardware do you have inside your design or for your app? *
4. What were the reasons you chose that particular hardware approach for AI/ML? *
Cost Considerations
Design Flexibility
Programming Environment
Power Efficiency
Performance
1st Choice
2nd Choice
3rd Choice
4th Choice
5th Choice
5. Which neural network frameworks are you using for inference? (Select all that apply) *
Required
6. How do you compress neural networks for TinyML inference? *
7. In your opinion, what TinyML use cases are most important? (Select all that apply) *
Required
8. Where do you get your ML algorithms/models? *
9. What data types are present in your ML models? (Select all that apply) *
Required
10. How would you rate the current state of TinyML tools? *
11. How can TinyML applications save lives and support COVID-19 pandemic recovery?
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