1. Pinecone 2.0: www.pinecone.io/learn/pinecone-v2/
It is GA and free:  https://www.pinecone.io/learn/v2-pricing/

2. Get your “Love Thy Nearest Neighbour” t-shirt :) shoot an email to greg@pinecone.io

3. Billion-Scale Approximate Nearest Neighbour Search Challenge: big-ann-benchmarks.com/index.html

4. ANNOY: github.com/spotify/annoy

5. FAISS: github.com/facebookresearch/faiss/

6. HNSW: https://github.com/nmslib/hnswlib

7. “How Zero Results Are Killing Ecommerce Conversions” https://lucidworks.com/post/how-zero-results-are-killing-ecommerce-conversions/

8. Try out Pinecone vector DB: www.pinecone.io/start/

9. Twitter: @pinecone_io

10. LinkedIn: www.linkedin.com/company/pinecone-io/

11. Greg’s Twitter: twitter.com/grigoriy_kogan

12. Dmitry's Twitter: https://twitter.com/DmitryKan

Greg Kogan - Pinecone - Vector Podcast with Dmitry Kan

1. Layering problem: https://www.edge.org/conversation/sean_carroll-layers-of-reality

2. Podcast with Etienne Dilocker (SeMI Technologies Co-Founder & CTO): https://www.youtube.com/watch?v=6lkanzOqhDs

3. SOC2: https://linfordco.com/blog/soc-1-vs-soc-2-audit-reports/

4. Dmitry's post on 7 Vector Databases: https://towardsdatascience.com/milvus-pinecone-vespa-weaviate-vald-gsi-what-unites-these-buzz-words-and-what-makes-each-9c65a3bd0696

5. Billion-Scale ANN Challenge: https://big-ann-benchmarks.com/index.html

6. Weaviate Introduction: https://www.semi.technology/developers/weaviate/current/
Newsletter: https://www.semi.technology/newsletter/

7. Use case: Scalable Knowledge Graph Search for 60+ million academic papers with Weaviate: https://medium.com/keenious/knowledge-graph-search-of-60-million-vectors-with-weaviate-7964657ec911

8. Bob's Twitter: https://twitter.com/bobvanluijt

9. Dmitry's Twitter: https://twitter.com/DmitryKan 

10. Dmitry's tech blog: https://dmitry-kan.medium.com/

Bob van Luijt (CEO, Semi) on the Weaviate vector search engine

Topics:
00:00 - Intro
00:10 - Connor's background and research interests

Show notes:
- On the Measure of Intelligence by François Chollet - Part 1: Foundations (Paper Explained)  [YouTube](https://www.youtube.com/watch?v=3_qGrmD6iQY)

- [2108.07258 On the Opportunities and Risks of Foundation Models](https://arxiv.org/abs/2108.07258)

- [2005.11401 Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks](https://arxiv.org/abs/2005.11401)

- Negative Data Augmentation: https://arxiv.org/abs/2102.05113

- Beyond Accuracy: Behavioral Testing of NLP models with CheckList: [2005.04118 Beyond Accuracy: Behavioral Testing of NLP models with CheckList](https://arxiv.org/abs/2005.04118)

- [2004.04906 Dense Passage Retrieval for Open-Domain Question Answering](https://arxiv.org/abs/2004.04906)

- [2111.05328 Data Augmentation Can Improve Robustness](https://arxiv.org/abs/2111.05328#:~:text=Adversarial%20training%20suffers%20from%20robust,using%20common%20data%20augmentation%20schemes.)

- Contrastive loss: [Contrastive Loss Explained. Contrastive loss has been used recently… | by Brian Williams | Towards Data Science](https://towardsdatascience.com/contrastive-loss-explaned-159f2d4a87ec)

- Keras Code examples: [Code examples](https://keras.io/examples/)

- you.com 

- [The Book of Why: The New Science of Cause and Effect: Pearl, Judea, Mackenzie, Dana: 9780465097609: Amazon.com: Books](https://www.amazon.com/Book-Why-Science-Cause-Effect/dp/046509760X)

Connor Shorten - Florida Atlantic University & Founder at Henry AI Labs on Deep Learning

Vector Podcast is here to bring you the depth and breadth of Search Engine Technology, Product, Marketing, Business. In the podcast we talk with engineers, entrepreneurs, thinkers and tinkerers, who put their soul into search.

Depending on your interest, you should find a matching topic for you -- whether it is deep algorithmic aspect of search engines and information retrieval field, or examples of products offering deep tech to its users.

"Vector" -- because it aims to cover an emerging field of vector similarity search, giving you the ability to search content beyond text: audio, video, images and more. 

"Vector" also because it is all about vector in your profession, product, marketing and business.

NOTE: We moved the podcast entirely to YouTube, Spotify and Apple Podcasts, due to limitation in upload on SoundCloud and no support for RSS-based distribution. See you on these respective platforms!