Educational assessment might need a rethink in the wake of ChatGPT.Credit: Thomas Trutschel/Photothek/Getty Between overwork, underpayment and the pressure to publish, academics have plenty to worry about. Now there's a fresh concern: ChatGPT, an artificial intelligence (AI) powered chatbot that creates surprisingly intelligent-sounding text in response to user prompts, including homework assignments and exam-style questions. The replies are so lucid, well-researched and decently referenced that some academics are calling the bot the death knell for conventional forms of educational assessment. How worried should professors and lecturers be? "At the moment, it's looking a lot like the end of essays as an assignment for education," says Lilian Edwards, who studies law, innovation and society at Newcastle University, UK. Dan Gillmor, a journalism scholar at Arizona State University in Tempe, told newspaper The Guardian that he had fed ChatGPT a homework question that he often assigns his students -- and the article it produced in response would have earned a student a good grade. ChatGPT is the brainchild of AI firm OpenAI, based in San Francisco, California.

The topic of how artificial intelligence can transform banking continues to get a massive amount of attention. With data in abundance, and the need to improve efficiency and create better customer experiences, every new evolution of AI creates opportunities, while also raising questions around privacy, biases, the impact on the human workforce, and changes in existing business models. One of the most talked about advances in the deployment of AI occurred on November 30, when OpenAI released ChatGPT, deemed "the most advanced, user-friendly chatbot to enter the public domain." ChatGPT can create high-level content, respond to customer inquiries, assist with research, and provide perspectives on current trends. OpenAI, a nonprofit company, was founded in 2015 by Sam Altman, Elon Musk and other Silicon Valley investors.

Abstract: This work explores an efficient approach to establish a foundational video-text model for tasks including open-vocabulary video classification, text-to-video retrieval, video captioning and video question-answering. We present VideoCoCa that reuses a pretrained image-text contrastive captioner (CoCa) model and adapt it to video-text tasks with minimal extra training. While previous works adapt image-text models with various cross-frame fusion modules (for example, cross-frame attention layer or perceiver resampler) and finetune the modified architecture on video-text data, we surprisingly find that the generative attentional pooling and contrastive attentional pooling layers in the image-text CoCa design are instantly adaptable to flattened frame embeddings'', yielding a strong zero-shot transfer baseline for many video-text tasks. Specifically, the frozen image encoder of a pretrained image-text CoCa takes each video frame as inputs and generates N token embeddings per frame for totally T video frames. We flatten N T token embeddings as a long sequence of frozen video representation and apply CoCa's generative attentional pooling and contrastive attentional pooling on top. All model weights including pooling layers are directly loaded from an image-text CoCa pretrained model.

Abstract: Zero-shot cross-lingual named entity recognition (NER) aims at transferring knowledge from annotated and rich-resource data in source languages to unlabeled and lean-resource data in target languages. Existing mainstream methods based on the teacher-student distillation framework ignore the rich and complementary information lying in the intermediate layers of pre-trained language models, and domain-invariant information is easily lost during transfer. In this study, a mixture of short-channel distillers (MSD) method is proposed to fully interact the rich hierarchical information in the teacher model and to transfer knowledge to the student model sufficiently and efficiently. Concretely, a multi-channel distillation framework is designed for sufficient information transfer by aggregating multiple distillers as a mixture. Besides, an unsupervised method adopting parallel domain adaptation is proposed to shorten the channels between the teacher and student models to preserve domain-invariant features.

Asking the technology to describe itself, ChatGPT says it is: "a chatbot trained using GPT-3, which is a state-of-the-art language model developed by OpenAI. It is capable of generating human-like text in response to user input. It can be used to create chatbots that can engage in natural conversations with users on a variety of topics."

ChatGPT and GPT-3 are two of the most powerful language models available today.

As 2022 starts to draw to a close, we thought it was high time to take a look back over the most popular stories we've published in the past 12 months. From a biotech scoop to a thoughtful interrogation of whether digital replicas of our deceased loved ones can really help to ease the grieving process, our readers have enjoyed the full gamut of our technology coverage. If you missed them the first time round, here's our top five most-read stories of the year. We hope you keep reading into the new year, and beyond. The pig heart transplanted into an American patient earlier this year in a landmark operation carried a porcine virus that may have derailed the experiment and contributed to his death two months later.

The topic of how artificial intelligence can transform banking continues to get a massive amount of attention. With data in abundance, and the need to improve efficiency and create better customer experiences, every new evolution of AI creates opportunities, while also raising questions around privacy, biases, the impact on the human workforce, and changes in existing business models. One of the most talked about advances in the deployment of AI occurred on November 30, when OpenAI released ChatGPT, deemed "the most advanced, user-friendly chatbot to enter the public domain." ChatGPT can create high-level content, respond to customer inquiries, assist with research, and provide perspectives on current trends. OpenAI, a nonprofit company, was founded in 2015 by Sam Altman, Elon Musk and other Silicon Valley investors.

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Something happened on November 30 that many experts believe could rank among the seminal moments in modern technology. At first, it sounds underwhelming: a company in California released a chatbot. Not a primitive "how can I help you" chatbot that appears on websites, leaving you yearning for human interaction. This is the most sophisticated chatbot yet, and it has left even the most cynical and knowledgeable observers slack-jawed at its capabilities. More than two million people have been playing with ChatGPT, discovering that it can write scripts, essays, contracts, computer code, jokes, poems and marketing pitches to a high level. It synthesises long pieces of text, does business analysis, translates languages, gives creative suggestions and can answer hypotheticals.