Personalized news headline generation aims to provide users with attention-grabbing headlines that are tailored to their preferences. Prevailing methods focus on user-oriented content preferences, but most of them overlook the fact that diverse stylistic preferences are integral to users' panoramic interests, leading to suboptimal personalization. In view of this, we propose a novel Stylistic-Content Aware Personalized Headline Generation (SCAPE) framework. SCAPE extracts both content and stylistic features from headlines with the aid of large language model (LLM) collaboration. It further adaptively integrates users' long- and short-term interests through a contrastive learning-based hierarchical fusion network. By incorporating the panoramic interests into the headline generator, SCAPE reflects users' stylistic-content preferences during the generation process. Extensive experiments on the real-world dataset PENS demonstrate the superiority of SCAPE over baselines.

Conceptual architecture involves a highly creative exploration of novel ideas, often taken from other disciplines as architects consider radical new forms, materials, textures and colors for buildings. While today's generative AI systems can produce remarkable results, they lack the creativity demonstrated for decades by evolutionary algorithms. SCAPE, our proposed tool, combines evolutionary search with generative AI, enabling users to explore creative and good quality designs inspired by their initial input through a simple point and click interface. SCAPE injects randomness into generative AI, and enables memory, making use of the built-in language skills of GPT-4 to vary prompts via text-based mutation and crossover. We demonstrate that compared to DALL-E 3, SCAPE enables a 67% improvement in image novelty, plus improvements in quality and effectiveness of use; we show that in just 3 iterations SCAPE has a 24% image novelty increase enabling effective exploration, plus optimization of images by users. We use more than 20 independent architects to assess SCAPE, who provide markedly positive feedback.

Credit the pursuits of biomedical engineers for developing a microscope called'SCAPE' (Swept Confocally Aligned Planar Excitation) that can not only view groups of neurons in a living brain; it can do so while the person is busy engaged in an activity. With this innovation, scientists hope to get a deeper understanding into what fuels the brain of a human. We can also hope that SCAPE will help scientist come closer to understanding human'thought' and decision-making. I find it fitting that this kind of scientific achievement is happening in tandem with the development of machine learning. That's why I was surprised by the latest scourge of'fake news' on the Internet, which is largely going undetected.

Earlier this year, UK-based startup Scape Technologies previewed a potentially exciting new augmented reality technology for smartphones, promising to use a device's camera to automatically determine its location. Now the company's larger plan is coming into focus, and it's exciting -- using vast, accurate 3D maps to enable city-scale augmented reality applications. Scape's pitch is as simple as the enabling technology is complex. While some companies have mapped individual landmarks, buildings, or roads for narrow AR applications, Scape is now mapping entire cities. Already live in London and San Francisco, its 3D maps are underway for 100 cities, it told PCMag, thanks to data gathered by cameras with computer vision.

If you believe tech optimists, 10 years from now self-driving cars will be ubiquitous, drones will deliver our parcels, and robots will bring us our groceries. And one day soon, our cities will be painted with augmented reality that feels as if it belongs to the street corner where it was placed. Whether or not any of that comes to pass, one piece of the puzzle will be crucial to this future: ultra-precise location technology. GPS and the wandering blue dot on smartphone mapping apps are useful for a human navigating an unfamiliar city, but that just won't cut it for machines. They will need to know where things are down to the centimeter. London-based startup Scape reckons that's what it can provide.

Scape Technologies, a London-based computer vision startup, is de-cloaking today to announce that it has raised $8 million in seed funding and is launching the first iteration of its "Visual Positioning Service," which lets developers build apps that require location accuracy far beyond the capabilities of GPS alone. The technology will initially target augmented reality apps, but also can be used to power applications in mobility, logistics and robotics. More broadly, Scape wants to enable any machine equipped with a camera to understand its surroundings. Backing the round is LocalGlobe, Mosaic Ventures, Fly Ventures and company builder Entrepreneur First. Scape Technologies was a member of EF cohort 7, which pitched at EF's London demo day almost two years ago.