Comparing edge AI deployment platforms (Cloudflare, Fastly, Vercel)

End-of-lesson check

15 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-tools-AI-edge-deployment-platforms-creators

1. What is the core idea behind "Comparing edge AI deployment platforms (Cloudflare, Fastly, Vercel)"?

   1. Pick the right edge runtime for inference close to your users.
   2. Reels feed picks what to show you: AI based on what you watch.
   3. Scale instantly to spikes
   4. Surface action items from a verbal recap.

2. Which term best describes a foundational idea in "Comparing edge AI deployment platforms (Cloudflare, Fastly, Vercel)"?

   1. platforms
   2. edge inference
   3. latency
   4. Reels feed picks what to show you: AI based on what you watch.

3. A learner studying Comparing edge AI deployment platforms (Cloudflare, Fastly, Vercel) would need to understand which concept?

   1. edge inference
   2. latency
   3. platforms
   4. Reels feed picks what to show you: AI based on what you watch.

4. Which of these is directly relevant to Comparing edge AI deployment platforms (Cloudflare, Fastly, Vercel)?

   1. edge inference
   2. platforms
   3. Reels feed picks what to show you: AI based on what you watch.
   4. latency

5. Which of the following is a key point about Comparing edge AI deployment platforms (Cloudflare, Fastly, Vercel)?

   1. List supported model sizes and runtimes per platform
   2. Compare cold-start latency and per-region availability
   3. Reels feed picks what to show you: AI based on what you watch.
   4. Scale instantly to spikes

6. What is one important takeaway from studying Comparing edge AI deployment platforms (Cloudflare, Fastly, Vercel)?

   1. Replace your central inference for heavy workloads
   2. Run a 70B model at the edge
   3. Reels feed picks what to show you: AI based on what you watch.
   4. Scale instantly to spikes

7. What is the key insight about "Edge fit-check" in the context of Comparing edge AI deployment platforms (Cloudflare, Fastly, Vercel)?

   1. Reels feed picks what to show you: AI based on what you watch.
   2. Scale instantly to spikes
   3. Edge is a fit when: model <2GB, latency budget <100ms, request rate is bursty, and you do not need GPU.
   4. Surface action items from a verbal recap.

8. What is the key insight about "Edge memory is tight" in the context of Comparing edge AI deployment platforms (Cloudflare, Fastly, Vercel)?

   1. Reels feed picks what to show you: AI based on what you watch.
   2. Scale instantly to spikes
   3. Surface action items from a verbal recap.
   4. Many edge platforms cap RAM at 128MB-1GB — your model plus runtime plus tokens must fit, or you will OOM under load.

9. Which statement accurately describes an aspect of Comparing edge AI deployment platforms (Cloudflare, Fastly, Vercel)?

   1. Edge inference is great for small models and routing — and a trap for large ones.
   2. Reels feed picks what to show you: AI based on what you watch.
   3. Scale instantly to spikes
   4. Surface action items from a verbal recap.

10. Which best describes the scope of "Comparing edge AI deployment platforms (Cloudflare, Fastly, Vercel)"?

    1. It is unrelated to tools workflows
    2. It focuses on Pick the right edge runtime for inference close to your users.
    3. It applies only to the opposite beginner tier
    4. It was deprecated in 2024 and no longer relevant

11. Which section heading best belongs in a lesson about Comparing edge AI deployment platforms (Cloudflare, Fastly, Vercel)?

    1. Reels feed picks what to show you: AI based on what you watch.
    2. Scale instantly to spikes
    3. What AI does well here
    4. Surface action items from a verbal recap.

12. Which section heading best belongs in a lesson about Comparing edge AI deployment platforms (Cloudflare, Fastly, Vercel)?

    1. Reels feed picks what to show you: AI based on what you watch.
    2. Scale instantly to spikes
    3. Surface action items from a verbal recap.
    4. What AI cannot do

13. Which of the following is a concept covered in Comparing edge AI deployment platforms (Cloudflare, Fastly, Vercel)?

    1. edge inference
    2. platforms
    3. latency
    4. Reels feed picks what to show you: AI based on what you watch.

14. Which of the following is a concept covered in Comparing edge AI deployment platforms (Cloudflare, Fastly, Vercel)?

    1. edge inference
    2. platforms
    3. latency
    4. Reels feed picks what to show you: AI based on what you watch.

15. Which of the following is a concept covered in Comparing edge AI deployment platforms (Cloudflare, Fastly, Vercel)?

    1. edge inference
    2. platforms
    3. latency
    4. Reels feed picks what to show you: AI based on what you watch.