The modular and repairable PC maker Framework's latest machine moves into the notoriously difficult to fix 2-in-1 category with a fun 12in laptop with a touchscreen and a 360-degree hinge. The new machine still supports the company's innovative expansion cards for swapping the different ports in the side, which are cross-compatible with the Framework 13 and 16 among others. And you can still open it up to replace the memory, storage and internal components with a few simple screws. The Framework 12 is available in either DIY form, starting at 499 ( 569/ 549/A 909), or more conventional prebuilt models starting at 749. It sits under the 799-and-up Laptop 13 and 1,399 Laptop 16 as the company's most compact and affordable model.

Fox News chief political anchor Bret Baier has the latest on regulatory uncertainty amid AI development on'Special Report.' An increasing number of companies are using artificial intelligence (AI) for everyday tasks. Much of the technology is helping with productivity and keeping the public safer. However, some industries are pushing back against certain aspects of AI. And some industry leaders are working to balance the good and the bad.

Open AI is reportedly preparing the launch of a new AI agent, codenamed'Operator', which can perform tasks for users, such as writing code or booking travel. According to sources familiar with the project, the tool is planned to be released in January as a research version and via the company's API for developers. The launch is part of a larger trend in the AI industry towards developing agents, AI tools that can perform multi-step tasks with minimal supervision, Bloomberg reports. Competitor Anthropic has recently launched a similar agent that can handle real-time tasks on the user's computer. Microsoft, which also supports Open AI, has recently launched AI tools to automate tasks like sending emails and managing documents.

We provide the mechanical and dynamical requirements for a robotic finger capable of performing thirty diverse everyday tasks. To match these requirements, we present a finger design based on series-elastic actuation that we call the everyday finger. Our focus is to make the fingers as compact as possible while achieving the desired performance. We evaluated everyday fingers by constructing a two-finger robotic hand that was tested on various performance parameters and tasks like picking and placing dishes in a rack, picking thin and flat objects like paper and delicate objects such as strawberries. Videos are available at the project website: https://sites.google.com/view/everydayfinger.

We present R+X, a framework which enables robots to learn skills from long, unlabelled, first-person videos of humans performing everyday tasks. Given a language command from a human, R+X first retrieves short video clips containing relevant behaviour, and then executes the skill by conditioning an in-context imitation learning method on this behaviour. By leveraging a Vision Language Model (VLM) for retrieval, R+X does not require any manual annotation of the videos, and by leveraging in-context learning for execution, robots can perform commanded skills immediately, without requiring a period of training on the retrieved videos. Experiments studying a range of everyday household tasks show that R+X succeeds at translating unlabelled human videos into robust robot skills, and that R+X outperforms several recent alternative methods. Videos are available at https://www.robot-learning.uk/r-plus-x.

This paper examines the question of how generative AI can improve the well-being of blind or visually impaired people. It refers to a current example, the Be My Eyes app, in which the Be My AI feature was integrated in 2023, which is based on GPT-4 from OpenAI. The author's tests are described and evaluated. There is also an ethical and social discussion. The power of the tool, which can analyze still images in an amazing way, is demonstrated. Those affected gain a new independence and a new perception of their environment. At the same time, they are dependent on the world view and morality of the provider or developer, who prescribe or deny them certain descriptions. An outlook makes it clear that the analysis of moving images will mean a further leap forward. It is fair to say that generative AI can fundamentally improve the well-being of blind and visually impaired people and will change it in various ways.

Automatically generating scripts (i.e. sequences of key steps described in text) from video demonstrations and reasoning about the subsequent steps are crucial to the modern AI virtual assistants to guide humans to complete everyday tasks, especially unfamiliar ones. However, current methods for generative script learning rely heavily on well-structured preceding steps described in text and/or images or are limited to a certain domain, resulting in a disparity with real-world user scenarios. To address these limitations, we present a new benchmark challenge -- MultiScript, with two new tasks on task-oriented multimodal script learning: (1) multimodal script generation, and (2) subsequent step prediction. For both tasks, the input consists of a target task name and a video illustrating what has been done to complete the target task, and the expected output is (1) a sequence of structured step descriptions in text based on the demonstration video, and (2) a single text description for the subsequent step, respectively. Built from WikiHow, MultiScript covers multimodal scripts in videos and text descriptions for over 6,655 human everyday tasks across 19 diverse domains. To establish baseline performance on MultiScript, we propose two knowledge-guided multimodal generative frameworks that incorporate the task-related knowledge prompted from large language models such as Vicuna. Experimental results show that our proposed approaches significantly improve over the competitive baselines.

Can language models reason in a real-world setting? USC researchers explored this question in a recent paper published at AAAI. Your coffee has gone cold. You pick up your cup, place it in the microwave, and zap it. For a robot, however, the task is not easy – even if it has been "taught" by language models (LMs) where the water, cup and microwave are.

Artificial intelligence (AI) refers to smart computer programs that may one day become as smart as humans – though not as creative. Even their current development was unexpected - no one foresaw machines becoming as smart as they are today. Technology has made many'impossible' things possible. Before the beginning of AI, there were already many tools and management systems that streamlined all processes of every business - but they all required a human to operate them. They worked perfectly as software, but they didn't have AI. Today, there are tools that help businesses grow their sales and even provide customer service without the help of an operator.

The email that we take for granted is one of the biggest users of AI. The first of this list is the Spam filter. Rule-based filters that traditionally work aren't useful against spam, as they are constantly updated to work around things like that. The AI employed to work to filter out the spam mail needs to constantly learn from a variety of flags that range from the number of words in a message to the metadata, The algorithms also need to be smart in terms of personalizing the spam messages. One person's spam could be another person's gold.