Richard Socher — The Challenges of Making ML Work in the Real World

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(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(www.metamind.io/) which was acquired by Salesforce in 2016. In 2014, he got my PhD in the [CS Department](www.cs.stanford.edu/) at Stanford. He likes paramotoring and water adventures, traveling and photography. More info:- Forbes article:https://www.forbes.com/sites/gilpress/2017/05/01/emerging-artificial-intelligence-ai-leaders-richard-socher-salesforce/) with more info about Richard's bio.- CS224n - NLP with Deep Learning(http://cs224n.stanford.edu/) the class Richard used to teach.- TEDx talk(https://www.youtube.com/watch?v=8cmx7V4oIR8) about where AI is today and where it's going.Research:Google Scholar Link(https://scholar.google.com/citations?user=FaOcyfMAAAAJ&hl=en)The AI Economist: Improving Equality and Productivity with AI-Driven Tax PoliciesArxiv link(https://arxiv.org/abs/2004.13332), blog(https://blog.einstein.ai/the-ai-economist/), short video(https://www.youtube.com/watch?v=4iQUcGyQhdA), Q&A(https://salesforce.com/company/news-press/stories/2020/4/salesforce-ai-economist/), Press: VentureBeat(https://venturebeat.com/2020/04/29/salesforces-ai-economist-taps-reinforcement-learning-to-generate-optimal-tax-policies/), TechCrunch(https://techcrunch.com/2020/04/29/salesforce-researchers-are-working-on-an-ai-economist-for-more-equitable-tax-policy/) 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 thingsIssue11, (**Chemical Science 2020**). paper link(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:PLDI 2019 pdf link(https://almond-static.stanford.edu/papers/genie-pldi19.pdf), https://almond.stanford.eduTopics Covered:0:00 intro0:42 the AI economist7:08 the objective function and Gini Coefficient12:13 on growing up in Eastern Germany and cultural differences15:02 Language models for protein generation (ProGen)27:53 CTRL: conditional transformer language model for controllable generation37:52 Businesses vs Academia40:00 What ML applications are important to salesforce44:57 an underrated aspect of machine learning48:13 Biggest challenge in making ML work in the real worldVisit our podcasts homepage for transcripts and more episodes!www.wandb.com/podcastGet our podcast on Soundcloud, Apple, Spotify, and Google!Soundcloud: https://bit.ly/2YnGjIqApple Podcasts: https://bit.ly/2WdrUvISpotify: https://bit.ly/2SqtadFGoogle: http://tiny.cc/GD_GoogleWeights and Biases makes developer tools for deep learning.Join our bi-weekly virtual salon and listen to industry leaders and researchers in machine learning share their research:http://tiny.cc/wb-salonJoin our community of ML practitioners:http://bit.ly/wb-slackOur gallery features curated machine learning reports by ML researchers.https://app.wandb.ai/gallery