A Language Detector for Identifying Machine-Generated Text

Yoav Schlesinger ·

In recent years, the natural language processing (NLP) community has seen the development of increasingly powerful language models [1, 2], capable of generating textual output that is indistinguishable from human-written text. This includes our own model called CTRL [3] (Conditional Transformer Language Model) for controllable generation. To prevent misuse or

The First Simulation Card for Ethical AI Simulations

Stephan Zheng ·

We recently released Foundation, an open-source framework to build economic simulations. Foundation has been designed with flexibility and AI research in mind, and can be modified by anyone. AI simulations offer researchers the power to generate data and evaluate outcomes of virtual economies that capture a part of the real

Model Cards for AI Model Transparency

Yoav Schlesinger · #ethics

At Salesforce, we take seriously our mission to create and deliver AI technology that is responsible, accountable, transparent, empowering, and inclusive. These principles ensure that our AI is safe, ethical, and engenders trust.

Theory-Inspired Network Architecture Search

Pan Zhou ·

TL;DR: We theoretically analyze the differential architecture search (DARTS) for understanding the role and impact of skip connections, which inspires a new method for Neural Architecture Search (NAS) using group-structured sparse gates and path-depth-wise regularization to overcome the limitation of existing NAS methods for AutoML. In our work [1]

How Salesforce Infuses Ethics into its AI

Katherine Siu · #artificial intelligence

For all the good that AI can bring, responsible tech companies understand they must recognize, prepare for, and mitigate the potential unintended, harmful effects. That’s why Salesforce sees ethics as foundational to AI — and why we’re sharing a closer look at how we infuse an ethical process into

The AI Economist: Join the Moonshot

Stephan Zheng ·

We are launching an open source collaborative project to build an AI Economist that can be used to guide policy making in the real world. We invite you to join us in our mission to help improve the world with AI and economics.

Salesforce Research at ACL 2020

Audrey Cook ·

The 58th Association for Computational Linguistics (ACL) Conference kicked off this week and runs from Sunday, Jul 5 to Friday, Jul 10 in a fully virtual format. ACL is the premier conference of the field of computational linguistics, covering a broad spectrum of diverse research areas that are concerned with

ERASER: A Benchmark to Evaluate Rationalized NLP Models

Nazneen Rajani · #research

Many NLP applications today deploy state-of-the-art deep neural networks that are essentially black-boxes. One of the goals of Explainable AI (XAI) is to have AI models reveal why and how they make their predictions so that these predictions are interpretable by a human. But work in this direction has been

Salesforce Research at ICLR 2019

Alexandria Murray · #news

May 6th - May 9th @ Ernest N. Morial Convention Center, New Orleans ABOUT:Salesforce is excited to be a diamond sponsor of the Seventh International Conference on Learning Representations happening Monday, May 6th through Thursday, May 9th in New Orleans, Louisiana. We encourage you to stop by our Salesforce Booth

Q&A with Salesforce Research Intern Akhilesh Gotmare on how "Optimization and Machine Learning" led him to ICLR.

Alexandria Murray · #news

In the research paper, “A Closer Look at Deep Learning Heuristics: Learning rate restarts, Warmup and Distillation” Futureforce PhD Intern Akhilesh Gotmare, worked with Research Scientist Nitish Shirish Keskar, Director of Research Caiming Xiong, and Salesforce Chief Scientist Richard Socher, to leverage recent tools built specifically for analyzing deep networks,

Ethics in AI research papers and articles

Kathy Baxter · #ethics

This is my obsessively curated list of research papers and articles on ethics in AI that I have been collecting over the years. Ones in bold are those that I refer back to and found particularly useful. Let me know if I am missing your favorites.

The Natural Language Decathlon

Bryan McCann · #research

Deep learning has significantly improved state-of-the-art performance for natural language processing tasks like machine translation, summarization, question answering, and text classification.