Why Multi-Modality is the Future of Machine Learning w/ Letitia Parcalabescu (University of Heidelberg, AI Coffee Break)

Letitia Parcalabescu is a PhD candidate at the University of Heidelberg focused on multi-modal machine learning, specifically with vision and language.

Learn more about Letitia:

https://www.cl.uni-heidelberg.de/~parcalabescu/

https://www.youtube.com/channel/UCobqgqE4i5Kf7wrxRxhToQA

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Timestamps:

01:30 Follow Charlie on Twitter (https://twitter.com/CharlieYouAI)

02:40 Letitia Parcalabescu

03:55 How she got started in CS and ML

07:20 What is multi-modal machine learning? (https://www.youtube.com/playlist?list=PLpZBeKTZRGPNKxoNaeMD9GViU_aH_HJab)

16:55 Most exciting use-cases for ML

20:45 The 5 stages of machine understanding (https://www.youtube.com/watch?v=-niprVHNrgI)

23:15 The future of multi-modal ML (GPT-50?)

27:00 The importance of communicating AI breakthroughs to the general public

37:40 Positive applications of the future “GPT-50”

43:35 Letitia’s CVPR paper on phrase grounding (https://openaccess.thecvf.com/content_CVPRW_2020/papers/w56/Parcalabescu_Exploring_Phrase_Grounding_Without_Training_Contextualisation_and_Extension_to_Text-Based_CVPRW_2020_paper.pdf)

53:15 ViLBERT: is attention all you need in multi-modal ML? (https://arxiv.org/abs/1908.02265)

57:00 Preventing “modality dominance”

01:03:25 How she keeps up in such a fast-moving field

01:10:50 Why she started her AI Coffee Break YouTube Channel (https://www.youtube.com/c/AICoffeeBreakwithLetitiaParcalabescu/)

01:18:10 Rapid fire questions

Links:

AI Coffee Break Youtube Channel

Exploring Phrase Grounding without Training

AI Coffee Break series on Multi-Modal learning

What does it take for an AI to understand language?

ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations