Biggest challenge in making ML work in the real world with Richard Socher

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Richard Socher, ex-Chief Scientist at Salesforce, joins us to talk about The AI Economist, NLP protein generation and biggest challenge in making ML work in the real world.
Richard Socher was the Chief scientist (EVP) at Salesforce where he lead teams working on fundamental research ( https://einstein.ai/ ), applied research, product incubation, CRM search, customer service automation and a cross-product AI platform for unstructured and structured data. Previously, he was an adjunct professor at Stanford’s computer science department and the founder and CEO/CTO of MetaMind which was acquired by Salesforce in 2016. In 2014, he got my PhD in the CS Department at Stanford. He likes paramotoring and water adventures, traveling and photography.

More info:
– Forbes article with more info about Richard’s bio https://www.forbes.com/sites/gilpress/2017/05/01/emerging-artificial-intelligence-ai-leaders-richard-socher-salesforce/
– CS224n – NLP with Deep Learning the class Richard used to teach. http://web.stanford.edu/class/cs224n/
– TEDx talk: where AI is today and where it’s going: https://youtu.be/8cmx7V4oIR8

Research:
Google Scholar Link: https://scholar.google.com/citations?user=FaOcyfMAAAAJ&hl=en

The AI Economist: Improving Equality and Productivity with AI-Driven Tax Policies
Arxiv link: https://arxiv.org/abs/2004.13332
blog: https://blog.einstein.ai/the-ai-economist/
short video: https://youtu.be/4iQUcGyQhdA

ProGen: Language Modeling for Protein Generation:
bioRxiv link: https://www.biorxiv.org/content/10.1101/2020.03.07.982272v2
blog: https://blog.einstein.ai/progen/

Dye-sensitized solar cells under ambient light powering machine learning: towards autonomous smart sensors for the internet of things. Issue11, (**Chemical Science 2020**).
https://pubs.rsc.org/en/content/articlelanding/2020/sc/c9sc06145b#!divAbstract

CTRL: A Conditional Transformer Language Model for Controllable Generation:
Arxiv link: https://arxiv.org/abs/1909.05858
code pre-trained and fine-tuning: https://github.com/salesforce/ctrl
blog: https://blog.einstein.ai/introducing-a-conditional-transformer-language-model-for-controllable-generation/

Genie: a generator of natural language semantic parsers for virtual assistant commands:
https://almond-static.stanford.edu/papers/genie-pldi19.pdf

Topics Covered:
0:00 intro
0:42 the AI economist
7:08 the objective function and Gini Coefficient
12:13 on growing up in Eastern Germany and cultural differences
15:02 Language models for protein generation (ProGen)
27:53 CTRL: conditional transformer language model for controllable generation
37:52 Businesses vs Academia
40:00 What ML applications are important to salesforce
44:57 an underrated aspect of machine learning
48:13 Biggest challenge in making ML work in the real world

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Comments

Eldaniz Babayev says:

You deserve more subs and views with videos like that 🙂

Henry AI Labs says:

Great interview!

Max Scheijen says:

Great interview!

S Simon says:

Thank you for helpful interview! I learn a lot about what to expect from the business side by this video as a job seeker.

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