Animated video showing a system to interpret electrical impulses from the brain as words
Language

Listening to the Brain: NLP System Translates a Man's Brain Activity Into Words

Neural networks translated a paralyzed man’s brainwaves into conversational phrases. Researchers trained a system to interpret electrical impulses from the brain of a man who had lost the ability to speak 15 years ago, and displayed them as words on a video screen.
Screen captures of a job interviews automation system
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Danke for the Interview

An independent test found flaws in AI systems designed to evaluate job applicants. MyInterview and Curious Thing, which automate job interviews, gave a candidate who spoke only in German high marks on English proficiency, according to MIT Technology Review.
Series of AI generated imagery
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CLIP Art

Creative engineers are combining deep learning systems to produce a groundswell of generated imagery. Researchers, hackers, and artists are producing new works by pairing CLIP, a pretrained image classifier, with a generative adversarial network (GAN).
Image showing how object detectors work
Language

I Know It When I See It

Object detectors typically detect only items that were labeled in their training data. A new method liberates them to locate and recognize a much wider variety of objects.
New approach to automated real-estate assessment
Language

Home Sweet AI-Appraised Home

Real estate websites helped turn automated real-estate assessment into a classic AI problem. The latest approach by a leader in the field gets a boost from deep learning.
Architecture of vision-language tasks
Language

One Model for Vision-Language

Researchers have proposed task-agnostic architectures for image classification tasks and language tasks. New work proposes a single architecture for vision-language tasks.
Walking through a narrow hallway in a library
Language

Bias By the Book

Researchers found serious flaws in an influential language dataset, highlighting the need for better documentation of data used in machine learning.
Libel-detection system from CaliberAI.
Language

Double Check for Defamation: NLP System Scans Text for Libel

A libel-detection system could help news outlets and social media companies stay out of legal hot water. CaliberAI, an Irish startup, scans text for statements that could be considered defamatory, Wired reported.
Graph showing types of phishing attacks
Language

24/7 Phish Fry

Foiling attackers who try to lure email users into clicking on a malicious link is a cat-and-mouse game, as phishing tactics evolve to evade detection. But machine learning models designed to recognize phishing attempts can evolve, too, through automatic retraining and checks to maintain accuracy.
Animation of SourceAI working
Language

Robocoders

Language models are starting to take on programming work. SourceAI uses GPT-3 to translate plain-English requests into computer code in 40 programming languages. The French startup is one of several companies that use AI to ease coding.
Diagram showing how Project Debater works
Language

Up for Debate

IBM’s Watson question-answering system stunned the world in 2011 when it bested human champions of the TV trivia game show Jeopardy! Although the Watson brand has fallen on hard times, the company’s language-processing prowess continues to develop.
Voice recognition tool "Bleep" working
Language

Haters Gonna [Mute]: Intel NLP Allows Voice Chatters to Silence Hate Speech

A new tool aims to let video gamers control how much vitriol they receive from fellow players. Intel announced a voice recognition tool called Bleep that the company claims can moderate voice chat automatically, allowing users to silence offensive language.
CogView home website
Language

Large Language Models for Chinese

Researchers unveiled competition for the reigning large language model GPT-3. Four models collectively called Wu Dao were described by Beijing Academy of Artificial Intelligence, a research collective funded by the Chinese government, according to Synced Review.
Model identifying erroneous labels in popular datasets
Language

Labeling Errors Everywhere

Key machine learning datasets are riddled with mistakes. Several benchmark datasets are shot through with incorrect labels. On average, 3.4 percent of examples in 10 commonly used datasets are mislabeled and the detrimental impact of such errors rises with model size.
Data related to SElf-supERvised (SEER), an image classifier pretrained on uncurated, unlabeled images
Language

Pretraining on Uncurated Data

It’s well established that pretraining a model on a large dataset improves performance on fine-tuned tasks. In sufficient quantity and paired with a big model, even data scraped from the internet at random can contribute to the performance boost.

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