Online marketplace eBay incorporated additional buying signals such as "Add to Watchlist," "Make Offer," and "Add to Cart" into its machine learning model to improve the relevance of recommended ad listings, based on the initial items searched for. Chen Xue goes into great detail in this recent article. EBay's Promoted Listings Standard (PLS) is a paid option for sellers. With one option, PLSIM, eBay's recommendation engines suggest sponsored items similar to something a potential buyer just clicked on. The PLSIM is paid on a CPA model (the seller pays eBay only when a sale is made) so that can be very motivating in terms of creating the most effective model to promote the best listings.

Sinequa said its neural search function can answer natural language questions, thanks to four deep learning models it developed with Microsoft Azure and Nvidia teams. Enterprise search company Sinequa is adding a neural search option to its platform with the aim of giving improved accuracy and relevance to customers. Sinequa said the new AI function is the first commercially available system to use four deep learning language models. Combined with the platform's natural language processing and semantic search abilities, Sinequa said this will lead to improved question-answering and search relevance. The Sinequa Search Cloud platform is designed to help employees find relevant information and insights from all enterprise sources in any language in the context of their work.

Data-centric AI, on the other hand, began in earnest in the 1970s with the invention of methods for automatically constructing "decision trees" and has exploded in popularity over the last decade with the resounding success of neural networks (now dubbed "deep learning"). Data-centric artificial intelligence has also been called "narrow AI" or "weak AI," but the rapid progress over the last decade or so has demonstrated its power. Deep-learning methods, coupled with massive training data sets plus unprecedented computational power, have delivered success on a broad range of narrow tasks from speech recognition to game playing and more. The artificial-intelligence methods build predictive models that grow increasingly accurate through a compute-intensive iterative process. In previous years, the need for human-labeled data to train the AI models has been a major bottleneck in achieving success.

Rodney Brooks knows a fair bit about robots. Besides being a pioneer of academic robotics research, he has founded companies that have given the world the robot vacuum cleaner, the bomb disposal bot, and a factory robot anyone can program. Now Brooks wants to introduce another revolutionary type of robot helper--a mobile warehouse robot with the ability to read human body language to tell what workers around it are doing. Robots are increasingly working in close proximity to humans, and finding ways to maximize human-machine teamwork could help companies boost productivity and perhaps lead to new kinds of jobs rather than robots replacing people. But giving robots the ability to read human cues is far from easy.

Australia's second-biggest appliances chain says it is pausing a trial of facial recognition technology in stores after a consumer group referred it to the privacy regulator for possible enforcement action. In an email on Tuesday, a spokesperson for JB Hi-Fi Ltd said The Good Guys, which JB Hi-Fi owns, would stop trialling a security system with optional facial recognition in two Melbourne outlets. Use of the technology by The Good Guys, owned by JB Hi-Fi Ltd, was "unreasonably intrusive" and potentially in breach of privacy laws, the group, CHOICE, told the Office of the Australian Information Commissioner (OAIC). While the company took confidentiality of personal information seriously and is confident it complied with relevant laws, it decided "to pause the trial … pending any clarification from the OAIC regarding the use of this technology", JB Hi-Fi's spokesperson added. The Good Guys was named in a complaint alongside Bunnings, Australia's biggest home improvement chain, and big box retailer Kmart, both owned by Wesfarmers Ltd, with total annual sales of about 25 billion Australian dollars ($19.47m) across 800 stores.

A robot running an artificial intelligence (AI) model carries out actions that perpetuate racist and sexist stereotypes, highlighting the issues that exist when tech learns from data sets with inherent biases.

A robot has learned how to mould modelling clay into letters that it has never seen before. Creating complex shapes out of doughy materials is a skill that could be put to use in the future in the form of a dumpling-making robot chef. "Deformable objects are ubiquitous in our daily life," says Yunzhu Li at the Massachusetts Institute of Technology. Robots capable of gently handling such objects could one day cook, do housework or even help care for elderly people, he says.

Small robots that have two flapping arms and can't move around on their own can spontaneously link up and glide together instead. This self-organisation may be related to how complex structures arise from simple building blocks in nature. Daniel Goldman at the Georgia Institute of Technology in Atlanta and his colleagues used small robots called smarticles – short for "smart active particles" – to observe self-organisation in the lab.

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A transformer has strong language representation ability; a very large corpus contains rich language expressions (such unlabeled data can be easily obtained) and training large-scale deep learning models has become more efficient. Therefore, pre-trained language models can effectively represent a language's lexical, syntactic, and semantic features. Pre-trained language models, such as BERT and GPTs (GPT-1, GPT-2, and GPT-3), have become the core technologies of current NLP. Pre-trained language model applications have brought great success to NLP. "Fine-tuned" BERT has outperformed humans in terms of accuracy in language-understanding tasks, such as reading comprehension.8,17 "Fine-tuned" GPT-3 has also reached an astonishing level of fluency in text-generation tasks.3