Researchers propose bias fix for GPT-3 and other language models

Few-shot learning, or the ability to learn tasks from a few examples, is a key aspect of human intelligence. Large AI natural language models like OpenAI’s GPT-3 can perform few-shot learning without fine-tuning. But despite the promise of few-shot learning, new research finds that the accuracy of language models — particularly GPT-3 — can be […]

Facebook researchers propose ‘pre-fine-tuning’ to improve language model performance

Machine learning researchers have achieved remarkable success with language model pretraining, which uses self-supervision, a training technique that doesn’t require labeled data. Pretraining refers to training a model with one task to help it recognize patterns that can be applied to a range of other tasks. In this way, pretraining imitates the way human beings […]

Researchers propose LEAF, a frontend for developing AI classification algorithms

In machine learning, mel-filterbanks — fixed, hand-engineered representations of sound — are often used to train algorithms that classify sound. Decades after the design of mel-filterbanks, research shows that they exhibit desirable mathematical properties for representation learning; in other words, they represent strong audio feature. But the design of mel-filterbanks is also flawed by biases, […]

Uber researchers propose AI language model that emphasizes positive and polite responses

AI-powered assistants like Siri, Cortana, Alexa, and Google Assistant are pervasive. But for these assistants to engage users and help them to achieve their goals, they need to exhibit appropriate social behavior and provide informative replies. Studies show that users respond better to social language in the sense that they’re more responsive and likelier to […]

Researchers propose ‘safe’ reinforcement learning algorithm for dangerous scenarios

Researchers have proposed a method for allowing reinforcement learning algorithms to accumulate knowledge while erring on the side of caution. The team, which hails from the University of Toronto, the Vector Institute, and the University of California, Berkeley,  claims this approach can achieve competitive performance while incurring lower catastrophic failure rates during training compared to […]

Nvidia researchers propose technique to transfer AI trained in simulation to the real world

In a preprint paper published this week on Arxiv.org, Nvidia and Stanford University researchers propose a novel approach to transferring AI models trained in simulation to real-world autonomous machines. It uses segmentation as the interface between perception and control, leading to what the coauthors characterize as “high success” in workloads like robot grasping. Simulators have […]

AI researchers propose ‘bias bounties’ to put ethics principles into practice

Researchers from Google Brain, Intel, OpenAI, and top research labs in the U.S. and Europe joined forces this week to release what the group calls a toolbox for turning AI ethics principles into practice. The kit for organizations creating AI models includes the idea of paying developers for finding bias in AI, akin to the […]