Case Studies in Community-Centered Living: Innovative Residential DesignSave this picture!Residential Park Lozen / IPA - Architecture and more. Image Dian StanchevArchitecture evolves, particularly in how it reflects the relationships between people, their behavior, and the environment. Even subtle variations in these dynamics can influence how we think and live in our communities. According to the World Bank, 56% of the population currently lives in urban environments, and it is estimated that by 2050 this number will reach 70%. This projection echoes the speed and magnitude of urban growth, posing challenges for architects and design firms, from the viability of buildings to the sustainability of the built environment, encompassing residential architecture and other typologies that influence daily life.Transforming the environment to adapt to these changes depends significantly on architecture. Through collaboration between designers and engineers, spaces are created that are not only aesthetically pleasing but also functional and sustainable. Since 2005, a focus on innovation and a multidisciplinary approach has guided IPA Architecture and more, a studio that has evolved alongside the dynamic landscape of architecture. Over time, its team has grown to over 150 people from diverse backgrounds, with a core belief that the most powerful ideas emerge when diverse minds collaborate.Save this picture! Our strength lies in our multidisciplinary team of architects and engineers, each contributing a unique perspective yet all working towards a shared vision. IPA Architecture and more The architectural office adopts an approach that integrates design, engineering, urban planning, and sustainability to create functional, meaningful, and durable environments. Its work encompasses diverse typologies, with a special focus on residential spaces, interiors, and hospitality projects, always with a comprehensive and forward-looking vision.Adaptive Residential Environments: Case Studies in Community-Centered LivingThe transformation of housing dynamics is one of the most significant changes in the built environment. For a long time, the dominant model consisted of single-family houses, either isolated or grouped in small communities, depending on land availability. However, demographic expansion, economic shifts, and evolving needs have driven the emergence of new forms of living. Examples such as Residential Park Lozen and River Park Residential Complex show how housing has evolved towards schemes that balance the independence of domestic units with an environment designed to strengthen the sense of community and encourage coexistence. In these projects, flexibility is key, with diverse housing typologies integrated into a planned environment that considers location, landscape, light, views, forms, and the preferences of the modern inhabitant.Save this picture!Save this picture!Both projects demonstrate a sensitivity to the natural environment. In Lozen, solid colors inspired by nature's chromatic range are used, while in the Simeonovo project, the design features materials such as wood and corrugated sheet metal used on the facade and roof. This strategy creates a visual unity, softening in the building's presence within the landscape.In more urban settings, a sensitive design has been adopted to balance the urban environment with the need for privacy and comfort in dynamic cities like Sofia, Bulgaria. The architects designed two structures parallel to the streets, connected by an inner patio that reduces the sense of urban density and creates an integrative space for users. The volumes lose their sense of massiveness through a facade that integrates diverse materials, avoiding visual conflict with surrounding buildings and enhancing the contemporary character of the complex. This approach is similarly reflected in low-density residential buildings, where balconies and panoramic terraces, arranged on all sides, strengthen the connection to the terrain.Save this picture!Residential Park Sofia, on the other hand, incorporates various housing typologies and offices and commercial areas distributed in low-rise volumes within a scheme that refers to a city within the city. This configuration seeks to balance density with a more human scale, promoting environments where daily life, work, and commerce coexist in an integrated way, reducing commuting and encouraging walking. Save this picture! As we evolve, so does our commitment to sustainability and community-driven architecture. We believe that great design should not only be innovative but also responsible. IPA Architecture and more Whether horizontal buildings or low-rise complexes, each project designed by the studio or currently in progress reflects a unique understanding of the natural environment and program needs. With a holistic approach that merges design, engineering, urban planning, and sustainability, these projects address current needs while considering long-term interactions.Save this picture!Save this picture!Exploring New Narratives in Hospitality and Interior SpacesHousing is one of the most representative typologies in the evolution of the built environment. Yet hospitality design has nourished IPA Architecture and more with an equally valuable perspective on how environments shape the human experience. In this context, hospitality goes beyond functionality, focusing on crafting atmospheres that transform our perception of space. This approach also embraces new dynamics, such as building renovations, which offer opportunities to rethink space use and interaction.An example is a hotel project where the architecture studio based in Bulgaria and Berlin chose a renovation strategy known for its lower environmental impact than new construction. In this case, efforts focused on remodeling the volumes and enhancing the connection to the green areas surrounding the building. The project included three extensions: an expanded restaurant and lobby bar, a new first-floor conference room and ballroom, and the integration of a 550 m vertical garden. This green space is a connective element, establishing continuity between the existing vegetation and the building. It softens the scale of the ensemble and visually guides visitors toward the lobby, gradually accentuating its presence.Save this picture!Other notable explorations have focused on office interiors and multifunctional spaces, emphasizing consistency in the arrangement of environments. The challenge has been to create a flexible design that adapts to various configurations and uses in work settings. These spaces must respond to the daily needs of collaboration and offer dynamic solutions that promote well-being and efficiency, favoring cooperation in different contexts.Save this picture!Save this picture!Beyond solving the layout of residential, office, or hotel atmospheres, the real challenge in conceiving space lies in understanding the dynamics of people and their interaction with the environment. This approach is reflected in the studio's vision, which emphasizes, "For us, architecture is more than just design it's about shaping environments that serve, inspire, and endure". Thus, the value behind the built environment lies not only in its functionality but in its ability to transform itself and continue to enrich the experience of those who inhabit and design it, continually adapting to new needs and perspectives.To learn more about IPA Architecture and More, visit their website.Image gallerySee allShow lessAbout this authorEnrique TovarAuthorCite: Enrique Tovar. "Case Studies in Community-Centered Living: Innovative Residential Design" 18 Mar 2025. ArchDaily. Accessed . <https://www.archdaily.com/1027788/case-studies-in-community-centered-living-innovative-residential-design&gt ISSN 0719-8884Save!ArchDaily?You've started following your first account!Did you know?You'll now receive updates based on what you follow! Personalize your stream and start following your favorite authors, offices and users.Go to my stream

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Large language models (LLMs) have demonstrated remarkable capabilities in reasoning, language understanding, and even creative tasks. Yet, a key challenge persists: how to efficiently integrate external knowledge.Traditional methods such as fine-tuning and Retrieval-Augmented Generation (RAG) come with trade-offsfine-tuning demands costly retraining, while RAG introduces separate retrieval modules that increase complexity and prevent seamless, end-to-end training. In-context learning, on the other hand, becomes increasingly inefficient as knowledge bases grow, facing quadratic computational scaling that hinders its ability to handle large repositories. A comparison of these approaches can be seen in Figure 1.A new way to integrate knowledgeTo address these challenges, we introduce the Knowledge Base-Augmented Language Model (KBLaM) a novel approach that integrates structured knowledge bases into pre-trained LLMs. Instead of relying on external retrieval modules or costly fine-tuning, KBLaM encodes knowledge into continuous key-value vector pairs, efficiently embedding them within the models attention layers using a specialized rectangular attention mechanism, which implicitly performs retrieval in an integrated manner.We use structured knowledge bases to represent the data, allowing us to consolidate knowledge and leverage structure. This design allows it to scale linearly with the size of the knowledge base while maintaining dynamic updates without retraining, making it far more efficient than existing methods.on-demand eventMicrosoft Research Forum Episode 4Learn about the latest multimodal AI models, advanced benchmarks for AI evaluation and model self-improvement, and an entirely new kind of computer for AI inference and hard optimization. Watch on-demandOpens in a new tab Scalable, efficient, and future-readyAt its core, KBLaM is designed to integrate structured knowledge into LLMs, making them more efficient and scalable. It achieves this by converting external knowledge basescollections of facts structured as triples consisting of an entity, a property, and a valueinto a format that LLMs can process naturally. Such knowledge bases allow for consolidated, reliable sources of knowledge.To create these knowledge bases, we first extract structured data in JSON format using small language models. We then apply Project Alexandrias probabilistic clustering. Once we have this structured knowledge base, KBLaM follows a three-step pipeline:Knowledge Encoding: Each knowledge triple is mapped into a key-value vector pair using a pre-trained sentence encoder with lightweight linear adapters. The key vector, derived from the entity name and property, encodes index information, while the value vector captures the corresponding property value. This allows us to create continuous, learnable key-value representations.Integration with LLMs: These key-value pairs, or knowledge tokens, are augmented into the models attention layers using a specialized rectangular attention structure. Unlike traditional transformer models that process all tokens equally and come with quadratic costsuch as GPT-4, Phi, and Llamarectangular attention enables the model to attend over knowledge with linear cost, as illustrated in Figure 2. Compared to standard attention mechanisms in generative language models, where each token attends to all preceding tokens, our approach introduces a more efficient structure. In this setup, language tokens (such as those from a users question) attend to all knowledge tokens. However, knowledge tokens do not attend to one another, nor do they attend back to the language tokens. This selective attention pattern significantly reduces computational cost while preserving the models ability to incorporate external knowledge effectively.This linear cost, which is crucial for the efficiency of KBLaM, effectively amounts to treating each fact independentlyan assumption that holds for most facts.For example, the models name, KBLaM, and the fact that the research was conducted at Microsoft Research are very weakly correlated. This rectangular attention is implemented as an extension of standard attention. During training, we keep the base models weights frozen, ensuring that when no knowledge tokens are provided, the model functions exactly as it did originally.Efficient Knowledge Retrieval: Through this rectangular attention, the model learns to dynamically retrieve relevant knowledge tokens during inference, eliminating the need for separate retrieval steps.Figure 1: KBLaM allows for attention over the entire knowledge base instead of having an external retriever.Figure 2: By having the users question attend to the knowledge base, while treating facts in the knowledge base independently, KBLaM scales efficiently and linearly with the size of the knowledge base.Unlike RAG, which appends retrieved document chunks to prompts, KBLaM allows for direct integration of knowledge into the model. Compared to in-context learning, KBLaMs rectangular attention maintains a linear memory footprint, making it vastly more scalable for large knowledge bases.Its efficiency is a game-changer. While traditional in-context learning methods struggle with quadratic memory growth due to self-attention overhead, KBLaMs linear overhead means we can store much more knowledge in the context. In practice, this means KBLaM can store and process over 10,000 knowledge triples, the equivalent of approximately 200,000 text tokens on a single GPUa feat that would be computationally prohibitive with conventional in-context learning. The results across a wide range of triples andcan be seen in Figure 3. Remarkably, it achieves this while extending a base model that has a context length of only 8K tokens. Additionally, KBLaM enables dynamic updates: modifying a single knowledge triple does not require retraining or re-computation of the entire knowledge base.Figure 3: KBLaM is much faster and uses much less memory than adding the equivalent number of triples in the context using conventional RAG-like approaches. In particular, we have lower time to first token with 4,096 tripes in the context with KBLaM than we would with 5 triples in the context.Enhancing interpretability and reliabilityAnother major benefit of KBLaM is its interpretability. Unlike in-context learning, where knowledge injection is opaque, KBLAMs attention weights provide clear insights into how the model utilizes knowledge tokens. Experiments show that KBLaM assigns high attention scores to relevant knowledge triples, effectively mimicking a soft retrieval process.Furthermore, KBLaM enhances model reliability by learning through its training examples when not to answer a question if the necessary information is missing from the knowledge base. In particular, with knowledge bases larger than approximately 200 triples, we found that the model refuses to answer questions it has no knowledge about more precisely than a model given the information as text in context. This feature helps reduce hallucinations, a common problem in LLMs that rely on internal knowledge alone, making responses more accurate and trustworthy.The future of knowledge-augmented AIKBLaM represents a major step forward in integrating structured knowledge into LLMs. By offering a scalable, efficient, and interpretable alternative to existing techniques, it paves the way for AI systems that can stay up to date and provide reliable, knowledge-driven responses. In fields where accuracy and trust are criticalsuch as medicine, finance, and scientific researchthis approach has the potential to transform how language models interact with real-world information.As AI systems increasingly rely on dynamic knowledge rather than static model parameters, we hope KBLaM will serve as a bridge between raw computational power and real-world understanding.However, there is still work to be done before it can be deployed at scale. Our current model has been trained primarily on factual question-answer pairs, and further research is needed to expand its capabilities across more complex reasoning tasks and diverse knowledge domains.To accelerate progress, we are releasing KBLaMs code and datasets (opens in new tab) to the research community, and we are planning integrations with the Hugging Face transformers library. By making these resources available, we hope to inspire further research and adoption of scalable, efficient knowledge augmentation for LLMs. The future of AI isnt just about generating textits about generating knowledge that is accurate, adaptable, and deeply integrated with the evolving world. KBLaM is a step in that direction.Opens in a new tab

Springtime is all about renewal and rebirth. New flowers are popping up. Baseball is getting underway. The re-emerging sun is allowing us to experience at least some small amount of joy after a winter full of oppressive cold and darkness. Its also a great time to get a new phone (like the new Galaxy S25 Ultra) or pretty much any other personal gadget. Right now, Samsung is offering solid trade-in deals toward new devices. You can get up to $1,000, but its more likely youll get a couple hundred bucks, even if youre trading in a older broken phone. If you have old electronics sitting around, now is the time to swap them for something good.Galaxy S25 Ultra (Up to $900 off with trade-in)Samsung This is Samsungs latest and greatest device. It offers a massive 6.9-inch screen, an advanced three-camera array, and all the built-in AI features you could possibly want. You can opt for 256 GB, 512 GB, or 1 TB of storage, depending on how much onboard space you really need.Samsung will give you up to $1,000 for a traded-in device, but typical savings look to be more like a few hundred, which is still a solid deal. For instance, the deal offers $180 for a used iPhone 12, which is about the same as youd get if you sold it on eBay, and you dont have to worry about definitely getting ripped off.This trade-in program does make me wonder what Samsung is doing with all those phones that get traded in. Maybe they take turns sitting on top of a giant pile of phones like a mythical dragon sitting atop a mountain of treasure. They actually probably recycle them, but the dragon thing would be fun.More Samsung devices eligible for enhanced trade-in ratesGalaxy Z Fold6 (Up to $1,000 off with trade-in plus $200 instant savings)Galaxy Z Flip6 (Upt to $700 with trade-in)Galaxy Book4 Ultra (Up to $600 off with trade-in)Galaxy Book5 Pro 360 (Up to $500 off with trade-in)Galaxy Watch Ultra (Up to $325 off with trade-in)Galaxy Watch7 (Up to $200 off with trade-in)Galaxy Buds3 Pro (Up to $150 with trade-in)

Team members Erika Blecha, Haley Bjorklund, Justin Garnett and Bryon Schroeder wrap the tusk with strips of plaster-covered burlap that will harden into a cast to protect it during transport. Credit: Devin Pettigrew / CBBSShareA local visitor to the O2 Ranch believed he came across something special while hunting on the property in West Texas. But ranch manager Will Juett took some convincing. After researchers from Sul Ross State University (SRSU) descended on the historic property, Juett realized the discovery was indeed something special: It was an extremely rare mammoth tusk.I was skeptical when a deer hunter showed me a picture of what he thought was a fossil, Juett said in a university announcement. I figured it was likely just an old stump.Columbian mammoths went extinct around 12,000 years ago. Credit: Benji Paysnoe / NPS The investigation began soon after Juett contacted Bryon Schroeder, a longtime acquaintance and director of SRSUs Center for Big Bend Studies (CBBS). Along with CBBS archeologist Erika Blecha and a few other colleagues, Schroeders team traveled to O2 Ranch to examine the object found sticking out the ground in a creekbeds drainage area.We realized pretty quickly there was not more to the skeleton, just an isolated tusk that had been separated from the rest of the remains, Schroeder explained.Researchers worked over two days to create a protective cast around the tusk for transport. After covering the fossil in plaster-soaked burlap strips, Schroeders group then constructed a frame around the ranch discovery before hauling it to SRSU for further analysis.Although multiple mammoth and mastodon species existed across modern North America until roughly 12,000 years ago, few of the elephant relatives ever migrated into West Texas. According to Schroeder, only a single mammoth tusk excavated from the Trans-Pecos region has ever been carbon-datedand that happened over 60 years ago. Even then, the process at the time was far less accurate than dating methods used today that can narrow down an age range to within 500 years. Schroeder believes a more precise estimate for the O2 Ranch tusk should be completed within the next few months. Get the Popular Science newsletter Breakthroughs, discoveries, and DIY tips sent every weekday. By signing up you agree to our Terms of Service and Privacy Policy.Its too early to determine the exact mammoth species just yet. But as Gizmodo noted, the tusk possibly belonged to a Columbian mammoth (Mammuthus columbi), one of the only species documented in Texas. The Columbian mammoth was a distant cousin of the more recognizable woolly mammoth, but could still grow to around 13 feet tall while weighing around 10 tons. The reasons behind their eventual extinction remain debatable, but they likely died out due to a combination of factors including climate change and human hunting. Its a bit poetic, then, that hunting is what led humans back to one of these megafauna in 2025.

NewsCosmologyNew baby pictures of the universe deepen a cosmic mysteryCosmic expansion rate questions persist, but the standard cosmology model holds The Atacama Cosmology Telescope (pictured) in Chile is designed to gather intel on the cosmic microwave background, the thermal afterglow of the Big Bang.Princeton UniversityBy Lisa Grossman44 seconds agoThe clearest pictures yet of the newborn cosmos strengthen the prevailing model of the universe but deepen a mystery about its expansion rate.Measurements of this rate, known as the Hubble constant, have produced conflicting results. Cosmologists hoped that new data from the Atacama Cosmology Telescope in Chile, which examines the oldest light in the universe, would clear things up and possibly reveal physics that diverges from the standard model of cosmology. But those results, announced March 18 in a webinar, only affirmed that model.

Nature, Published online: 18 March 2025; doi:10.1038/d41586-025-00822-9Global cooperation is crucial for DeepSeek and broader AI research

Nature, Published online: 18 March 2025; doi:10.1038/d41586-025-00824-7US disruptions to science could transform global research landscape

Mount Spurr near Anchorage has been showing signs of unrest for a year. Now scientists think it's creeping closer to an eruption.

Download: https://www.blender.org/download/ Release Page: https://www.blender.org/download/releases/4-4/ Showcase Reel: https://www.youtube.com/watch?v=TQElJP1AaS0 Feature Overview: https://www.youtube.com/watch?v=-eqPs-boihU Release Notes: https://developer.blender.org/docs/release_notes/4.4/ Help fund Blender's continued development: https://fund.blender.org/ submitted by /u/Avereniect [link] [comments]