Topics:

00:00 Introduction

01:12 Malte’s background

07:58 NLP crossing paths with Search

11:20 Product discovery: early stage repetitive use cases pre-dating Haystack

16:25 Acyclic directed graph for modeling a complex search pipeline

18:22 Early integrations with Vector Databases

20:09 Aha!-use case in Haystack

23:23 Capabilities of Haystack today

30:11 Deepset Cloud: end-to-end deployment, experiment tracking, observability, evaluation, debugging and communicating with stakeholders

39:00 Examples of value for the end-users of Deepset Cloud

46:00 Success metrics

50:35 Where Haystack is taking us beyond MLOps for search experimentation

57:13 Haystack as a smart assistant to guide experiments

1:02:49 Multimodality

1:05:53 Future of the Vector Search / NLP field: large language models

1:15:13 Incorporating knowledge into Language Models & an Open NLP Meetup on this topic

1:16:25 The magical question of WHY

1:23:47 Announcements from Malte

Show notes:

- Open NLP Meetup on Sep 29th (Nils Reimers talking about “Incorporating New Knowledge Into LMs”): https://www.meetup.com/open-nlp-meetup/events/287159377/

- Atlas Paper (Few shot learning with retrieval augmented large language models): https://arxiv.org/abs/2208.03299

Very large LMs:

- 20B AlexaTM by Amazon: https://lnkd.in/eyBaZDTy

- Tutorials and papers around incorporating Knowledge into Language Models: https://cs.stanford.edu/people/cgzhu/

Riferimenti culturali e American Graffiti

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