Generative Pretraining from Pixels - OpenAI

Language Models are Unsupervised Multitask Learners

Language Models are Unsupervised Multitask Learners Alec Radford * 1Jeffrey Wu Rewon Child David Luan 1Dario Amodei ** Ilya Sutskever ** 1 Abstract Natural language processing tasks, such as ques-tion answering, machine translation, reading com-

Benchmarking Safe Exploration in Deep Reinforcement …

range of prior work on safe reinforcement learning, we propose to standardize constrained RL as the main formalism for safe exploration. Second, we present the Safety Gym benchmark suite, a new slate of high-dimensional continuous control environments for measuring research progress on constrained RL. Finally, we

  Control, Learning, Reinforcement, Reinforcement learning

WebGPT: Browser-assisted question-answering with human ...

human feedback. To make human evaluation of factual accuracy easier, models ... or negative ways of talking about people’s religion, skin color, ability, or gender [3]. Often, people say bad words when they are experiencing strong emotions, …

  Feedback, Negative

Jukebox: A Generative Model for Music - OpenAI

frequencies perceptible to humans. As an example, a four-minute-long audio segment will have an input length of ˘10 million, where each position can have 16 bits of information. In comparison, a high-resolution RGB image with 1024 1024 pixels has an input length of ˘3 million, and each position has 24 bits of information. This makes learning

  Frequencies, Jukebox

Improving Language Understanding by Generative Pre …

Improving Language Understanding by Generative Pre-Training Alec Radford OpenAI alec@openai.com Karthik Narasimhan OpenAI karthikn@openai.com Tim Salimans OpenAI tim@openai.com Ilya Sutskever OpenAI ilyasu@openai.com Abstract Natural language understanding comprises a wide range of diverse tasks such

  Language, Understanding, Improving, Generative, Improving language understanding by generative pre, Language understanding

Dota 2 with Large Scale Deep Reinforcement Learning

Dota 2 with Large Scale Deep Reinforcement Learning OpenAI, ChristopherBerner,GregBrockman,BrookeChan,VickiCheung, Przemysław“Psyho"Dębiak,ChristyDennison ...

  Learning, Deep, Reinforcement, Otda, Deep reinforcement learning

Formal Mathematics Statement Curriculum Learning

more automation (such as more domain-specific statements generator or even informal to formal machine translation). 1.1. miniF2F benchmark In this work, we target the miniF2F (Zheng et al.,2021) benchmark, which consists of 244 validation and 244 test formalized statements of mathematical problems from var-ious competitions.

  Automation

Training language models to follow instructions with human ...

language models with human intent. 1 Introduction Large language models (LMs) can be “prompted” to perform a range of natural language process-ing (NLP) tasks, given some examples of the task as input. However, these models often express unintended behaviors such as making up facts, generating biased or toxic text, or simply not following

  Language, Model, Language model

Learning Transferable Visual Models From Natural …

of learning from natural language supervision. We study the scalability of CLIP by training a series of eight models spanning almost 2 orders of magnitude of compute and ob-serve that transfer performance is a smoothly predictable function of …

  Form, Language, Model, Learning, Visual, Natural, Transferable, Learning transferable visual models from natural

written by Todd Phillips & Scott Silver

Let's call it 1981. It's a troubled time. The crime rate in Gotham is at record highs. A garbage strike has crippled the city for the past six weeks. And the divide between the "haves" and the "have-nots" is palpable. Dreams are beyond reach, slipping into delusions. TP/SS ii

  Call

EU Experts Call for Expression of Interest

EU Experts: Call for expression of interest: V1.1 – 01.01.2022 4 1. Background, objectives and scope This call is a call for expression of interest for the Portal Expert Database for the period 2021-2027. It seeks individuals to assist the EU services in …

  Call, Interest, Expression, Call for expression of interest

“WORKING” REMOTELY - Harvard University

possibilities in the call-centers of a Fortune 500 online retailer. We find that working remotely in-creased call-center workers’ productivity. When previously on-site workers took up opportunities to go remote in 2018, their hourly calls rose by 7.5%. Similarly, when COVID-19 …

  Call, 2018, Remotely

Tax Compliance and Enforcement - NBER

July 2018 I am grateful to Garrett Anstreicher and Tejaswi Velayudhan for excellent research assistance and ... NBER working papers are circulated for discussion and comment purposes. They have not been ... liability and when, which we might call remittance rules. For example, under most income tax systems, it is the employer that remits ...

  Call, Enforcement, Compliance, Paper, 2018, Tax compliance and enforcement

Organizational Culture Drives Ethical Behaviour: Evidence ...

This paper was submitted as part of a competitive call for papers on integrity, anti-corruption and inclusive growth in the context of the 2018 OECD Global Anti-Corruption & Integrity Forum. 4 1. Introduction Regulators in the United States and the United Kingdom are increasingly focusing on corporate culture as a mechanism through which ...

  Code, Call, Paper, 2018, Call for papers, Oecd 2018