Artificial-intelligence systems that can churn out fluent text, such as OpenAI's ChatGPT, are the newest darlings of the technology industry. But when faced with mathematical queries that require reasoning to answer, these large language models (LLMs) often stumble. A line parallel to y 4x 6 passes through (5, 10). What is the y-coordinate of the point where this line crosses the y-axis? Although LLMs can sometimes answer these types of question correctly, they more often get them wrong. In one early test of its reasoning abilities, ChatGPT scored just 26% when faced with a sample of questions from the'MATH' data set of secondary-school-level mathematical problems1. This is to be expected: given input text, an LLM simply generates new text in accordance with statistical regularities in the words, symbols and sentences that make up the model's training data.

Generative AI has hit the public imagination in full force during 2022. Perhaps the biggest splash was made by OpenAI's launch of the text-to-image generator DALL-E 2 with its stunning illustrations. Under the guise of generative AI art, code-completion programs are boosting developer productivity by automating repetitive and mundane programming tasks. The world's largest source code host GitHub released its code-completion tool called Copilot in June 2022. It is trained on 45 terabytes of coding data from the GitHub code repository and runs on OpenAI's Codex model.

Even if you haven't tried artificial intelligence tools that can writing essays and poems or conjure new images on command, chances are the companies that make your household products are already starting to do so. Mattel has put the AI image generator DALL-E to work by having it come up with ideas for new Hot Wheels toy cars. Used vehicle seller CarMax is summarizing thousands of customer reviews with the same "generative" AI technology that powers the popular chatbot, ChatGPT. Meanwhile, Snapchat is bringing a chatbot to its messaging service. And the grocery delivery company Instacart is integrating ChatGPT to answer customers' food questions.

Following the hype around OpenAI's ChatGPT conversational agent, the last straw in the recent development of Large Language Models (LLMs) that demonstrate emergent unprecedented zero-shot capabilities, we audit the latest OpenAI's GPT-3.5 model, `gpt-3.5-turbo', the first available ChatGPT model, in the LexGLUE benchmark in a zero-shot fashion providing examples in a templated instruction-following format. The results indicate that ChatGPT achieves an average micro-F1 score of 47.6% across LexGLUE tasks, surpassing the baseline guessing rates. Notably, the model performs exceptionally well in some datasets, achieving micro-F1 scores of 62.8% and 70.2% in the ECtHR B and LEDGAR datasets, respectively. The code base and model predictions are available for review on https://github.com/coastalcph/zeroshot_lexglue.

We introduce ViLPAct, a novel vision-language benchmark for human activity planning. It is designed for a task where embodied AI agents can reason and forecast future actions of humans based on video clips about their initial activities and intents in text. The dataset consists of 2.9k videos from \charades extended with intents via crowdsourcing, a multi-choice question test set, and four strong baselines. One of the baselines implements a neurosymbolic approach based on a multi-modal knowledge base (MKB), while the other ones are deep generative models adapted from recent state-of-the-art (SOTA) methods. According to our extensive experiments, the key challenges are compositional generalization and effective use of information from both modalities.

Despite recent advancements, the field of text-to-image synthesis still suffers from lack of fine-grained control. Using only text, it remains challenging to deal with issues such as concept coherence and concept contamination. We propose a method to enhance control by generating specific concepts that can be reused throughout multiple images, effectively expanding natural language with new words that can be combined much like a painter's palette. Unlike previous contributions, our method does not copy visuals from input data and can generate concepts through text alone. We perform a set of comparisons that finds our method to be a significant improvement over text-only prompts.

Even if you haven't tried artificial intelligence tools that can write essays and poems or conjure new images on command, chances are the companies that make your household products are already starting to do so. Mattel has put the AI image generator DALL-E to work by having it come up with ideas for new Hot Wheels toy cars. Used vehicle seller CarMax is summarizing thousands of customer reviews with the same "generative" AI technology that powers the popular chatbot ChatGPT. Meanwhile, Snapchat is bringing a chatbot to its messaging service. And the grocery delivery company Instacart is integrating ChatGPT to answer customers' food questions. Coca-Cola plans to use generative AI to help create new marketing content.

Suppose that Elon Musk opts to develop a generative AI ChatGPT knockoff, what does this foretell and ... [ ] is a presumed "TruthGPT" even possible to build? There is a knock at the cabin door. Should we open the door? Movies usually suggest that we ought to not let our curiosity get the better of us, namely we should absolutely positively never open the door. Well, that being said, opting to leave the door closed wouldn't seem to make for much of a worthy tale. Seems like we are drawn toward excitement and the unknown. So, let's go ahead and open the door. In this particular case, I am referring to some emerging scuttlebutt within the field of Artificial Intelligence (AI) that either portends good times ahead or the worst of times for all of us. The situation potentially entails the future of AI. And one might solemnly speculate ergo that the future of AI encompasses quite dramatic repercussions all told, including ostensibly shaping the future of society and the fate of humankind. According to recent news reports, Elon Musk, the at-times richest person in the world, has been fishing around for top-notch AI researchers to come on board with a new AI venture that he has in mind. Various AI developers and AI scientists are quietly being approached. The knock on their door apparently provides great promise and potentially lucrative tidings.

A real-time special effect has flooded TikTok in recent weeks, chiseling chins, plumping lips and serving Kardashian-style makeup contours for anyone with a smartphone. While it's being touted as a remarkably convincing beauty filter, AI researchers say the effect leaves no clues to its presence, giving it unprecedented capacity to manipulate people in and outside an app that has elicited scrutiny from governments around the world.

We may chip our pets, but can humans be chipped safely? Kurt "The CyberGuy" Knutsson explains. It is no secret that prices for pharmaceutical drugs are expensive, especially if you do not have great insurance or no insurance at all. Add to that the fact that according to the Centers for Disease Control and Prevention, about 50% of Americans take at least one prescription medication, with nearly 13% taking five or more medications. CLICK TO GET KURT'S CYBERGUY NEWSLETTER WITH QUICK TIPS, TECH REVIEWS, SECURITY ALERTS AND EASY HOW-TO'S TO MAKE YOU SMARTER Now, one company is hoping to significantly lower those drug costs and develop new cancer drugs with AI technology.