Top videos

The most-watched talks, lectures and explainers in Awesome Similarity Search.

Recent and gaining

Published in the last year, ranked by views per day.

  1. 6:11
  2. 10:44

    Rank 2: Vector Databases Explained — How They Actually Work

    Devsplainers

    Views
    743
    Likes
    37
    Published
    Apr 2026
  3. 2:41:08
  4. 6:28

    Rank 4: Day 27 : Locality-Sensitive Hashing (LSH) Explained: Fast Vector Search in High-Dimensional Data

    Cloud and Coffee with Navnit

    Views
    605
    Likes
    10
    Published
    Jan 2026

All-time

Ranked by reach and engagement, not recency.

  1. 4:23

    Rank 1: Vector Databases simply explained! (Embeddings & Indexes)

    AssemblyAI

    Views
    674K
    Likes
    14K
    Published
    May 2023
  2. 31:37

    Rank 2: Faiss - Introduction to Similarity Search

    James Briggs

    Views
    93K
    Likes
    1.6K
    Published
    Jul 2021
  3. 8:03

    Rank 3: Vector Database Search - Hierarchical Navigable Small Worlds (HNSW) Explained

    DataMListic

    Views
    52K
    Likes
    1.8K
    Published
    May 2024
  4. 34:35

    Rank 4: HNSW for Vector Search Explained and Implemented with Faiss (Python)

    James Briggs

    Views
    55K
    Likes
    982
    Published
    Oct 2021
  5. 1:02:12

    Rank 5: Semantic Search: A Deep Dive Into Vector Databases (with Zain Hasan)

    Developer Voices

    Views
    32K
    Likes
    1.2K
    Published
    Oct 2023
  6. 47:36

    Rank 6: [CVPR20 Tutorial] Billion-scale Approximate Nearest Neighbor Search

    Yusuke Matsui

    Views
    19K
    Likes
    498
    Published
    Jun 2020
  7. 13:05

    Rank 7: Vector Database Search: HNSW Algorithm Explained

    Redis

    Views
    11K
    Likes
    240
    Published
    Jul 2025
  8. 21:02

    Rank 8: Webinar replay: Vector Similarity Search & Indexing Methods

    Zilliz

    Views
    2.3K
    Likes
    39
    Published
    Apr 2021
  9. 6:11
  10. 1:29:36
  11. 10:44

    Rank 11: Vector Databases Explained — How They Actually Work

    Devsplainers

    Views
    743
    Likes
    37
    Published
    Apr 2026
  12. 2:41:08
  13. 6:28

    Rank 13: Day 27 : Locality-Sensitive Hashing (LSH) Explained: Fast Vector Search in High-Dimensional Data

    Cloud and Coffee with Navnit

    Views
    605
    Likes
    10
    Published
    Jan 2026

Counts from the YouTube Data API, refreshed weekly; last checked on or after 10 Aug 2026. How ranking works.