Architects: Want to have your project featured? Showcase your work by uploading projects to Architizer and sign up for our inspirational newsletters. When we think about homes, we tend to picture familiar ideas: comfort, privacy, function — spaces designed to suit many people at once (and, if all goes well, let at least two household members agree on where the sofa and TV should go). But sometimes, architects are asked to design something more specific: a place shaped not by broad assumptions, but by one particular life, habit or need. Across settings and scales, the homes in this collection respond to unusual briefs with equal parts function and imagination. Some are built around creative work, like a house organized entirely around a vlogger’s daily routines. Others offer comfort through significant life transitions, from aging in place with Alzheimer’s to carving out a personal retreat in the wake of loss. From spaces where dogs and humans live as equals to playful structures prioritizing a child’s sense of freedom, each project shows how architecture can leave generalizations behind and create homes that fit real lives — quirks included! Vlogger Aguai’s Home By LZA, Baoshan, Shanghai, China Popular Choice Winner, 12th Annual A+Awards, Residential Interiors (< 3000 sq ft) This home rethinks the boundary between living and working to meet the needs of a growing online career. Centered around a custom scrapbooking workbench, the layout branches outward, organizing both private life and professional activity in one flexible environment. Curved pathways guide movement through the house, reflecting the layered flow of daily routines and creative work. Materials and spaces are carefully chosen to support content creation: the studio incorporates Aguai’s hobbies into its design, incubating inspiration and offering a welcoming backdrop for videos and workshops. By merging personal passion with professional needs, the home supports both focused work and relaxed living without drawing a hard line between them. Dog / Human By EKAR, Thailand Designed to nurture the relationship between dogs and humans, this house in Thailand adapts both its scale and function for its four-legged residents. A low, agricultural-style roof signals zones for walking, sitting and resting, while wide column bases are shaped to fit sleeping dogs. The house includes a dog hotel and salon, allowing other dogs to share the facilities and creating a social space for both pets and owners. Swimming pool steps are carefully sized for dogs to easily climb in and out; the roof intentionally lets rainwater fall freely to the ground. Every detail is shaped by mutual respect between species — a place where dogs and people live, grow and connect. Light Path By Bohlin Cywinski Jackson, Pennsylvania  Built for longtime clients preparing to age in place with Alzheimer’s, this home prioritizes clarity, safety and connection to nature. A simple cross-shaped layout helps with orientation and memory by offering clear, predictable pathways. Wide hallways, accessible bathrooms and same-level entry anticipate future mobility challenges. A 92-foot (28-meter) skylight and expansive windows flood the interiors with daylight, aiding wayfinding and stabilizing circadian rhythms. Natural materials like reclaimed pine and bluestone create a low-contrast, familiar environment, reducing visual confusion. Custom door handles and lowered counters offer easier grip and access, supporting physical independence as needs change over time. The Nearby House By Asooarch Company, Garmsar, Iran The Nearby House creates a shared meeting point for a brother and sister living apart, providing a simple, playful space between their homes. Set in an orchard, the tiny house is shaped by the needs of short visits and childlike exploration — from its curved brick walls that bend around existing trees to the blue-tiled water features that invite play. Every element is designed to support connection, whether through picking fruit, chasing light and shadow or gathering around shared spaces. The architecture remains low, tactile and open to nature, offering a familiar backdrop for memory-making. Rather than formal programs, the design prioritizes casual, spontaneous moments of togetherness, giving the siblings a place that belongs equally to both. Softie By OPA, Mill Valley, California Softie transforms a strict Modernist house into a place of private release, responding to a client’s wish for a free, light and untethered environment. Rather than reworking the structure, the architects introduced a series of soft, cloud-like forms that drift through the home. These interventions dissolve the rigid grid with curved entries, softened stairs and floating shapes that blur traditional spatial boundaries. Materials and details are kept deliberately fluid and irregular, allowing movement through the house to feel loose and intuitive. Even the terrace holds a “trapped cloud” above it, creating small, unexpected encounters with softness. By scattering these moments throughout all three levels, the design makes space for variation, daydreaming and quiet escape from external pressures. LÂM’s home By AD+studio, Vinh Long, Vietnam This project was created as a midday retreat for a mother and daughter, designed around a child’s sense of freedom and play. Built on a narrow 10-by-33-foot (3×10-meter) plot, the house uses a single structural element—the “tree”—to anchor the design. The branching structure carries floors, forms stairs, shades the interior and creates spaces for small tasks, all while maximizing openness. Communal areas are prioritized to strengthen the bond between mother and daughter, with flexible spaces that shift between play and daily routines. Combining functions rather than dividing them makes the house feel expansive despite its size. The light, playful structure echoes the daughter’s name, Lâm and the spirit of movement and growth it represents. Mourning Dovecote By S^A | Schwartz and Architecture, Sonoma, California Created as a quiet retreat for a homeowner navigating grief and change, this 390-square-foot addition focuses on intimacy, memory and connection to nature. Designed to support a slower, more reflective way of living, the compact space draws on simple, tactile materials and close ties to its surroundings. Openings frame the landscape while muffled sounds, like the calls of nearby doves, filter in to mark the passing hours. Rather than expanding outward, the design turns inward, offering a personal, enduring refuge. Built during the pandemic and following personal loss, the project prioritizes familiarity, ritual and small, everyday moments over formal gestures or size. Architects: Want to have your project featured? Showcase your work by uploading projects to Architizer and sign up for our inspirational newsletters. The post Oddly Specific: 7 Homes Designed for Very Particular Client Briefs appeared first on Journal.

Meadgard has you fighting to gather ingredents during the day and running your own Viking inn during the evening, keeping everyone happy. Chaotic cooking games are a dime a dozen, but this one feels like it’s well worth checking out. This game takes part in two stages, switching between chaotic cooking and gathering the items that you need and using your kitchen tools as weapons! Meadgard has tasked you and your friends to become innkeepers. You will need to work together to run the best Viking tavern, gathering resources and then running the inn in the evening, hoping to make some gold. During the day, you need to fight various monsters, using your kitchen tool of choice to stay alive. There are often hidden treasure chests and various items that can be found while you’re exploring and clobbering beasts before you move to your inn for the evening. When it’s opening time at the inn, you will need to plan your menu and then execute it. The menu will depend on what you have done during the day and reflect what you have gathered. There is a sort of skill in creating your menu in Meadgard, as some of the roasting items can be complex. When it’s time to open, you need to work together to bring Vikings to their table, take their order, then make their food. Sometimes they just need a pint of beer and other times you need to chop ingredients and then cook them to get what they are after. Even things like replacing the keg take time, so having more people working together helps! If you frustrate your customers, they are Vikings, so they might make a mess of the place. I played a demo of Meadgard at the European Game Showcase where I really enjoyed how fast cooking became when you played together as well as the diversity of play in this game. It’s still a work in progress, but if you like busy cooking games it’s one to keep an eye on. Meadgard is currently in development, but in the meantime, you can grab a demo or add it to yoru Wishlist on Steam. About The Author

Over the last few months, and especially the last few weeks, there’s been an explosion of news about proposed budget cuts to science in the US. One trend I’ve noticed: Researchers and civil servants are sounding the alarm that those cuts mean we might lose key data that helps us understand our world and how climate change is affecting it. My colleague James Temple has a new story out today about researchers who are attempting to measure the temperature of mountain snowpack across the western US. Snow that melts in the spring is a major water source across the region, and monitoring the temperature far below the top layer of snow could help scientists more accurately predict how fast water will flow down the mountains, allowing farmers, businesses, and residents to plan accordingly. But long-running government programs that monitor the snowpack across the West are among those being threatened by cuts across the US federal government. Also potentially in trouble: carbon dioxide measurements in Hawaii, hurricane forecasting tools, and a database that tracks the economic impact of natural disasters. It’s all got me thinking: What do we lose when data is in danger? Take for example the work at Mauna Loa Observatory, which sits on the northern side of the world’s largest active volcano. In this Hawaii facility, researchers have been measuring the concentration of carbon dioxide in the atmosphere since 1958. The resulting graph, called the Keeling Curve (after Charles David Keeling, the scientist who kicked off the effort) is a pillar of climate research. It shows that carbon dioxide, the main greenhouse gas warming the planet, has increased in the atmosphere from around 313 parts per million in 1958 to over 420 parts per million today. Proposed cuts to the National Oceanic and Atmospheric Administration (NOAA) jeopardize the Keeling Curve’s future. As Ralph Keeling (current steward of the curve and Keeling’s son) put it in a new piece for Wired, “If successful, this loss will be a nightmare scenario for climate science, not just in the United States, but the world.” This story has echoes across the climate world right now. A lab at Princeton that produces what some consider the top-of-the-line climate models used to make hurricane forecasts could be in trouble because of NOAA budget cuts. And last week, NOAA announced it would no longer track the economic impact of the biggest natural disasters in the US. Some of the largest-scale climate efforts will feel the effects of these cuts, and as James’s new story shows, they could also seep into all sorts of specialized fields. Even seemingly niche work can have a huge impact not just on research, but on people. The frozen reservoir of the Sierra snowpack provides about a third of California’s groundwater, as well as the majority used by towns and cities in northwest Nevada. Researchers there are hoping to help officials better forecast the timing of potential water supplies across the region. This story brought to mind my visit to El Paso, Texas, a few years ago. I spoke with farmers there who rely on water coming down the Rio Grande, alongside dwindling groundwater, to support their crops. There, water comes down from the mountains in Colorado and New Mexico in the spring and is held in the Elephant Butte Reservoir. One farmer I met showed me pages and pages of notes of reservoir records, which he had meticulously copied by hand. Those crinkled pages were a clear sign: Publicly available data was crucial to his work. The endeavor of scientific research, particularly when it involves patiently gathering data, isn’t always exciting. Its importance is often overlooked. But as cuts continue, we’re keeping a lookout, because losing data could harm our ability to track, address, and adapt to our changing climate.  This article is from The Spark, MIT Technology Review’s weekly climate newsletter. To receive it in your inbox every Wednesday, sign up here.

Over the last few months, and especially the last few weeks, there’s been an explosion of news about proposed budget cuts to science in the US. One trend I’ve noticed: Researchers and civil servants are sounding the alarm that those cuts mean we might lose key data that helps us understand our world and how climate change is affecting it. My colleague James Temple has a new story out today about researchers who are attempting to measure the temperature of mountain snowpack across the western US. Snow that melts in the spring is a major water source across the region, and monitoring the temperature far below the top layer of snow could help scientists more accurately predict how fast water will flow down the mountains, allowing farmers, businesses, and residents to plan accordingly. But long-running government programs that monitor the snowpack across the West are among those being threatened by cuts across the US federal government. Also potentially in trouble: carbon dioxide measurements in Hawaii, hurricane forecasting tools, and a database that tracks the economic impact of natural disasters. It’s all got me thinking: What do we lose when data is in danger? Take for example the work at Mauna Loa Observatory, which sits on the northern side of the world’s largest active volcano. In this Hawaii facility, researchers have been measuring the concentration of carbon dioxide in the atmosphere since 1958. The resulting graph, called the Keeling Curve (after Charles David Keeling, the scientist who kicked off the effort) is a pillar of climate research. It shows that carbon dioxide, the main greenhouse gas warming the planet, has increased in the atmosphere from around 313 parts per million in 1958 to over 420 parts per million today. Proposed cuts to the National Oceanic and Atmospheric Administration (NOAA) jeopardize the Keeling Curve’s future. As Ralph Keeling (current steward of the curve and Keeling’s son) put it in a new piece for Wired, “If successful, this loss will be a nightmare scenario for climate science, not just in the United States, but the world.” This story has echoes across the climate world right now. A lab at Princeton that produces what some consider the top-of-the-line climate models used to make hurricane forecasts could be in trouble because of NOAA budget cuts. And last week, NOAA announced it would no longer track the economic impact of the biggest natural disasters in the US. Some of the largest-scale climate efforts will feel the effects of these cuts, and as James’s new story shows, they could also seep into all sorts of specialized fields. Even seemingly niche work can have a huge impact not just on research, but on people. The frozen reservoir of the Sierra snowpack provides about a third of California’s groundwater, as well as the majority used by towns and cities in northwest Nevada. Researchers there are hoping to help officials better forecast the timing of potential water supplies across the region. This story brought to mind my visit to El Paso, Texas, a few years ago. I spoke with farmers there who rely on water coming down the Rio Grande, alongside dwindling groundwater, to support their crops. There, water comes down from the mountains in Colorado and New Mexico in the spring and is held in the Elephant Butte Reservoir. One farmer I met showed me pages and pages of notes of reservoir records, which he had meticulously copied by hand. Those crinkled pages were a clear sign: Publicly available data was crucial to his work. The endeavor of scientific research, particularly when it involves patiently gathering data, isn’t always exciting. Its importance is often overlooked. But as cuts continue, we’re keeping a lookout, because losing data could harm our ability to track, address, and adapt to our changing climate.  This article is from The Spark, MIT Technology Review’s weekly climate newsletter. To receive it in your inbox every Wednesday, sign up here.

In this tutorial, we demonstrate how to construct an automated Knowledge Graph (KG) pipeline using LangGraph and NetworkX. The pipeline simulates a sequence of intelligent agents that collaboratively perform tasks such as data gathering, entity extraction, relation identification, entity resolution, and graph validation. Starting from a user-provided topic, such as “Artificial Intelligence,” the system methodically extracts relevant entities and relationships, resolves duplicates, and integrates the information into a cohesive graphical structure. By visualizing the final knowledge graph, developers and data scientists gain clear insights into complex interrelations among concepts, making this approach highly beneficial for applications in semantic analysis, natural language processing, and knowledge management. !pip install langgraph langchain_core We install two essential Python libraries: LangGraph, which is used for creating and orchestrating agent-based computational workflows, and LangChain Core, which provides foundational classes and utilities for building language model-powered applications. These libraries enable seamless integration of agents into intelligent data pipelines. import re import networkx as nx import matplotlib.pyplot as plt from typing import TypedDict, List, Tuple, Dict, Any from langchain_core.messages import HumanMessage, AIMessage from langgraph.graph import StateGraph, END We import essential libraries to build an automated knowledge graph pipeline. It includes re for regular expression-based text processing, NetworkX and matplotlib for creating and visualizing graphs, TypedDict and typing annotations for structured data handling, and LangGraph along with langchain_core for orchestrating the interaction between AI agents within the workflow. class KGState(TypedDict): topic: str raw_text: str entities: List[str] relations: List[Tuple[str, str, str]] resolved_relations: List[Tuple[str, str, str]] graph: Any validation: Dict[str, Any] messages: List[Any] current_agent: str We define a structured data type, KGState, using Python’s TypedDict. It outlines the schema for managing state across different steps of the knowledge graph pipeline. It includes details like the chosen topic, gathered text, identified entities and relationships, resolved duplicates, the constructed graph object, validation results, interaction messages, and tracking the currently active agent. def data_gatherer(state: KGState) -> KGState: topic = state["topic"] print(f"📚 Data Gatherer: Searching for information about '{topic}'") collected_text = f"{topic} is an important concept. It relates to various entities like EntityA, EntityB, and EntityC. EntityA influences EntityB. EntityC is a type of EntityB." state["messages"].append(AIMessage(content=f"Collected raw text about {topic}")) state["raw_text"] = collected_text state["current_agent"] = "entity_extractor" return state This function, data_gatherer, acts as the first step in the pipeline. It simulates gathering raw text data about a provided topic (stored in state[“topic”]). It then stores this simulated data into state[“raw_text”], adds a message indicating the data collection completion, and updates the pipeline’s state by setting the next agent (entity_extractor) as active. def entity_extractor(state: KGState) -> KGState: print("🔍 Entity Extractor: Identifying entities in the text") text = state["raw_text"] entities = re.findall(r"Entity[A-Z]", text) entities = [state["topic"]] + entities state["entities"] = list(set(entities)) state["messages"].append(AIMessage(content=f"Extracted entities: {state['entities']}")) print(f" Found entities: {state['entities']}") state["current_agent"] = "relation_extractor" return state The entity_extractor function identifies entities from the collected raw text using a simple regular expression pattern that matches terms like “EntityA”, “EntityB”, etc. It also includes the main topic as an entity and ensures uniqueness by converting the list to a set. The extracted entities are stored in the state, an AI message logs the result, and the pipeline advances to the relation_extractor agent. def relation_extractor(state: KGState) -> KGState: print("🔗 Relation Extractor: Identifying relationships between entities") text = state["raw_text"] entities = state["entities"] relations = [] relation_patterns = [ (r"([A-Za-z]+) relates to ([A-Za-z]+)", "relates_to"), (r"([A-Za-z]+) influences ([A-Za-z]+)", "influences"), (r"([A-Za-z]+) is a type of ([A-Za-z]+)", "is_type_of") ] for e1 in entities: for e2 in entities: if e1 != e2: for pattern, rel_type in relation_patterns: if re.search(f"{e1}.*{rel_type}.*{e2}", text.replace("_", " "), re.IGNORECASE) or \ re.search(f"{e1}.*{e2}", text, re.IGNORECASE): relations.append((e1, rel_type, e2)) state["relations"] = relations state["messages"].append(AIMessage(content=f"Extracted relations: {relations}")) print(f" Found relations: {relations}") state["current_agent"] = "entity_resolver" return state The relation_extractor function detects semantic relationships between entities within the raw text. It uses predefined regex patterns to identify phrases like “influences” or “is a type of” between entity pairs. When a match is found, it adds the corresponding relation as a triple (subject, predicate, object) to the relations list. These extracted relations are stored in the state, a message is logged for agent communication, and control moves to the next agent: entity_resolver. def entity_resolver(state: KGState) -> KGState: print("🔄 Entity Resolver: Resolving duplicate entities") entity_map = {} for entity in state["entities"]: canonical_name = entity.lower().replace(" ", "_") entity_map[entity] = canonical_name resolved_relations = [] for s, p, o in state["relations"]: s_resolved = entity_map.get(s, s) o_resolved = entity_map.get(o, o) resolved_relations.append((s_resolved, p, o_resolved)) state["resolved_relations"] = resolved_relations state["messages"].append(AIMessage(content=f"Resolved relations: {resolved_relations}")) state["current_agent"] = "graph_integrator" return state The entity_resolver function standardizes entity names to avoid duplication and inconsistencies. It creates a mapping (entity_map) by converting each entity to lowercase and replacing spaces with underscores. Then, this mapping is applied to all subjects and objects in the extracted relations to produce resolved relations. These normalized triples are added to the state, a confirmation message is logged, and control is passed to the graph_integrator agent. def graph_integrator(state: KGState) -> KGState: print("📊 Graph Integrator: Building the knowledge graph") G = nx.DiGraph() for s, p, o in state["resolved_relations"]: if not G.has_node(s): G.add_node(s) if not G.has_node(o): G.add_node(o) G.add_edge(s, o, relation=p) state["graph"] = G state["messages"].append(AIMessage(content=f"Built graph with {len(G.nodes)} nodes and {len(G.edges)} edges")) state["current_agent"] = "graph_validator" return state The graph_integrator function constructs the actual knowledge graph using networkx.DiGraph() supports directed relationships. It iterates over the resolved triples (subject, predicate, object), ensures both nodes exist, and then adds a directed edge with the relation as metadata. The resulting graph is saved in the state, a summary message is appended, and the pipeline transitions to the graph_validator agent for final validation. def graph_validator(state: KGState) -> KGState: print("✅ Graph Validator: Validating knowledge graph") G = state["graph"] validation_report = { "num_nodes": len(G.nodes), "num_edges": len(G.edges), "is_connected": nx.is_weakly_connected(G) if G.nodes else False, "has_cycles": not nx.is_directed_acyclic_graph(G) if G.nodes else False } state["validation"] = validation_report state["messages"].append(AIMessage(content=f"Validation report: {validation_report}")) print(f" Validation report: {validation_report}") state["current_agent"] = END return state The graph_validator function performs a basic health check on the constructed knowledge graph. It compiles a validation report containing the number of nodes and edges, whether the graph is weakly connected (i.e., every node is reachable if direction is ignored), and whether the graph contains cycles. This report is added to the state and logged as an AI message. Once validation is complete, the pipeline is marked as finished by setting the current_agent to END. def router(state: KGState) -> str: return state["current_agent"] def visualize_graph(graph): plt.figure(figsize=(10, 6)) pos = nx.spring_layout(graph) nx.draw(graph, pos, with_labels=True, node_color='skyblue', node_size=1500, font_size=10) edge_labels = nx.get_edge_attributes(graph, 'relation') nx.draw_networkx_edge_labels(graph, pos, edge_labels=edge_labels) plt.title("Knowledge Graph") plt.tight_layout() plt.show() The router function directs the pipeline to the next agent based on the current_agent field in the state. Meanwhile, the visualize_graph function uses matplotlib and networkx to display the final knowledge graph, showing nodes, edges, and labeled relationships for intuitive visual understanding. def build_kg_graph(): workflow = StateGraph(KGState) workflow.add_node("data_gatherer", data_gatherer) workflow.add_node("entity_extractor", entity_extractor) workflow.add_node("relation_extractor", relation_extractor) workflow.add_node("entity_resolver", entity_resolver) workflow.add_node("graph_integrator", graph_integrator) workflow.add_node("graph_validator", graph_validator) workflow.add_conditional_edges("data_gatherer", router, {"entity_extractor": "entity_extractor"}) workflow.add_conditional_edges("entity_extractor", router, {"relation_extractor": "relation_extractor"}) workflow.add_conditional_edges("relation_extractor", router, {"entity_resolver": "entity_resolver"}) workflow.add_conditional_edges("entity_resolver", router, {"graph_integrator": "graph_integrator"}) workflow.add_conditional_edges("graph_integrator", router, {"graph_validator": "graph_validator"}) workflow.add_conditional_edges("graph_validator", router, {END: END}) workflow.set_entry_point("data_gatherer") return workflow.compile() The build_kg_graph function defines the complete knowledge graph workflow using LangGraph. It sequentially adds each agent as a node, from data collection to graph validation, and connects them through conditional transitions based on the current agent. The entry point is set to data_gatherer, and the graph is compiled into an executable workflow that guides the automated pipeline from start to finish. def run_knowledge_graph_pipeline(topic): print(f"🚀 Starting knowledge graph pipeline for: {topic}") initial_state = { "topic": topic, "raw_text": "", "entities": [], "relations": [], "resolved_relations": [], "graph": None, "validation": {}, "messages": [HumanMessage(content=f"Build a knowledge graph about {topic}")], "current_agent": "data_gatherer" } kg_app = build_kg_graph() final_state = kg_app.invoke(initial_state) print(f"✨ Knowledge graph construction complete for: {topic}") return final_state The run_knowledge_graph_pipeline function initializes the pipeline by setting up an empty state dictionary with the provided topic. It builds the workflow using build_kg_graph(), then runs it by invoking the compiled graph with the initial state. As each agent processes the data, the state evolves, and the final result contains the complete knowledge graph, validated and ready for use. if __name__ == "__main__": topic = "Artificial Intelligence" result = run_knowledge_graph_pipeline(topic) visualize_graph(result["graph"]) Finally, this block serves as the script’s entry point. When executed directly, it triggers the knowledge graph pipeline for the topic “Artificial Intelligence,” runs through all agent stages, and finally visualizes the resulting graph using the visualize_graph() function. It provides an end-to-end demonstration of automated knowledge graph generation. Output Generated from Knowledge Graph Execution In conclusion, we have learned how to seamlessly integrate multiple specialized agents into a cohesive knowledge graph pipeline through this structured approach, leveraging LangGraph and NetworkX. This workflow automates entity and relation extraction processes and visualizes intricate relationships, offering a clear and actionable representation of gathered information. By adjusting and enhancing individual agents, such as employing more sophisticated entity recognition methods or integrating real-time data sources, this foundational framework can be scaled and customized for advanced knowledge graph construction tasks across various domains. Check out the Colab Notebook. All credit for this research goes to the researchers of this project. Also, feel free to follow us on Twitter and don’t forget to join our 90k+ ML SubReddit. Asif RazzaqWebsite |  + postsBioAsif Razzaq is the CEO of Marktechpost Media Inc.. As a visionary entrepreneur and engineer, Asif is committed to harnessing the potential of Artificial Intelligence for social good. His most recent endeavor is the launch of an Artificial Intelligence Media Platform, Marktechpost, which stands out for its in-depth coverage of machine learning and deep learning news that is both technically sound and easily understandable by a wide audience. The platform boasts of over 2 million monthly views, illustrating its popularity among audiences.Asif Razzaqhttps://www.marktechpost.com/author/6flvq/Google DeepMind Introduces AlphaEvolve: A Gemini-Powered Coding AI Agent for Algorithm Discovery and Scientific OptimizationAsif Razzaqhttps://www.marktechpost.com/author/6flvq/Rime Introduces Arcana and Rimecaster (Open Source): Practical Voice AI Tools Built on Real-World SpeechAsif Razzaqhttps://www.marktechpost.com/author/6flvq/A Step-by-Step Guide to Build a Fast Semantic Search and RAG QA Engine on Web-Scraped Data Using Together AI Embeddings, FAISS Retrieval, and LangChainAsif Razzaqhttps://www.marktechpost.com/author/6flvq/Agent-Based Debugging Gets a Cost-Effective Alternative: Salesforce AI Presents SWERank for Accurate and Scalable Software Issue Localization

Over the last few months, and especially the last few weeks, there’s been an explosion of news about proposed budget cuts to science in the US. One trend I’ve noticed: Researchers and civil servants are sounding the alarm that those cuts mean we might lose key data that helps us understand our world and how climate change is affecting it. My colleague James Temple has a new story out today about researchers who are attempting to measure the temperature of mountain snowpack across the western US. Snow that melts in the spring is a major water source across the region, and monitoring the temperature far below the top layer of snow could help scientists more accurately predict how fast water will flow down the mountains, allowing farmers, businesses, and residents to plan accordingly. But long-running government programs that monitor the snowpack across the West are among those being threatened by cuts across the US federal government. Also potentially in trouble: carbon dioxide measurements in Hawaii, hurricane forecasting tools, and a database that tracks the economic impact of natural disasters. It’s all got me thinking: What do we lose when data is in danger? Take for example the work at Mauna Loa Observatory, which sits on the northern side of the world’s largest active volcano. In this Hawaii facility, researchers have been measuring the concentration of carbon dioxide in the atmosphere since 1958. The resulting graph, called the Keeling Curve (after Charles David Keeling, the scientist who kicked off the effort) is a pillar of climate research. It shows that carbon dioxide, the main greenhouse gas warming the planet, has increased in the atmosphere from around 313 parts per million in 1958 to over 420 parts per million today. Proposed cuts to the National Oceanic and Atmospheric Administration (NOAA) jeopardize the Keeling Curve’s future. As Ralph Keeling (current steward of the curve and Keeling’s son) put it in a new piece for Wired, “If successful, this loss will be a nightmare scenario for climate science, not just in the United States, but the world.” This story has echoes across the climate world right now. A lab at Princeton that produces what some consider the top-of-the-line climate models used to make hurricane forecasts could be in trouble because of NOAA budget cuts. And last week, NOAA announced it would no longer track the economic impact of the biggest natural disasters in the US. Some of the largest-scale climate efforts will feel the effects of these cuts, and as James’s new story shows, they could also seep into all sorts of specialized fields. Even seemingly niche work can have a huge impact not just on research, but on people. The frozen reservoir of the Sierra snowpack provides about a third of California’s groundwater, as well as the majority used by towns and cities in northwest Nevada. Researchers there are hoping to help officials better forecast the timing of potential water supplies across the region. This story brought to mind my visit to El Paso, Texas, a few years ago. I spoke with farmers there who rely on water coming down the Rio Grande, alongside dwindling groundwater, to support their crops. There, water comes down from the mountains in Colorado and New Mexico in the spring and is held in the Elephant Butte Reservoir. One farmer I met showed me pages and pages of notes of reservoir records, which he had meticulously copied by hand. Those crinkled pages were a clear sign: Publicly available data was crucial to his work. The endeavor of scientific research, particularly when it involves patiently gathering data, isn’t always exciting. Its importance is often overlooked. But as cuts continue, we’re keeping a lookout, because losing data could harm our ability to track, address, and adapt to our changing climate.  This article is from The Spark, MIT Technology Review’s weekly climate newsletter. To receive it in your inbox every Wednesday, sign up here.

La Libreria is a lightweight, demountable library designed by Diller Scofidio + Renfro for the Venice Architecture Biennale. Measuring 24 meters long, the pavilion is built for easy transport and can be set up in different locations to encourage reading and literacy. The structure uses principles from tensile architecture, inspired by research and work from French engineer Robert Le Ricolais. Instead of being anchored to the ground, La Libreria relies on a combination of ballasts and the weight of books for stability. Books are housed in wooden shelves that line the length of the library, helping to reinforce the frame while making literature easily accessible. This thoughtful design allows the library to remain flexible and adaptable, supporting community engagement wherever it goes. La Libreria shows how smart engineering and a love for books can come together in a functional, inviting space. Designer: Diller Scofidio + Renfro The library features a 24-metre-long span wrapped in Structural Transparent Fluorinated Envelope (STFE), a high-performance, lightweight architectural textile. This material, similar to what was used for The Shed in Manhattan’s Hudson Yards, was chosen for its clear transparency and portability. STFE allows the pavilion to be easily demounted and packed into a container for transport. While the structure is specifically designed for dismantling and reassembly in new locations, plans for where it will go next have not yet been announced. This thoughtful choice of material ensures both visual openness and practical mobility for the library. La Libreria stands in the Giardini della Biennale, close to the bookshop designed by James Stirling. It joins an array of national pavilions at this year’s Venice Architecture Biennale, including the Danish Pavilion—transformed into a construction site by Søren Pihlmann—and the Finnish Pavilion, which explores the lesser-known history of an Alvar Aalto building. This gathering of diverse and innovative spaces highlights the Biennale’s role as a showcase for architectural creativity and experimentation. La Libreria is more than just a temporary library – it proves how smart design can support literacy and bring people together in any setting. Its lightweight, portable structure and innovative use of materials reflect a forward-thinking approach to architecture—one that values adaptability, sustainability, and community impact. By blending engineering precision with a love for books, La Libreria creates a welcoming space where visitors can pause, reflect, and engage with literature, no matter where it travels next. As part of the Venice Architecture Biennale, it stands alongside other inventive projects, showing how architecture can respond to both practical needs and cultural aspirations. The post This Innovative Transparent Library With A Portable Design Is Reinventing Public Infrastructure first appeared on Yanko Design.

Athens Panathēnea: Re-celebrating innovation and connection with a modern festival of tech, art, and ... More startups, ending in an epic street party beneath the Acropolis.Timothy Papandreou Imagine a city where the spirit of innovation and connection has thrived for thousands of years. Last week in Athens, that spirit was reborn with the sold-out inaugural Panathēnea festival (with a waiting list!). This vibrant event, a modern echo of ancient gatherings, powerfully announced a bold ambition: this historic city is not just a birthplace of civilization, democracy and innovation, but a rising force aiming to be Europe's next major startup hub. Anchored by the timeless values of "connection, competition, celebration" and with the confident declaration, "throwing festivals since 566 BC," Panathēnea was more than an industry and arts convergence for me. It felt like a bright signal flare, clearly indicating Athens' readiness to take its rightful place on the global startup landscape. Returning to my Greek roots as part of the diaspora, I attended the multi-day event impressed by the student-driven and designed program (similar to SLUSH). A mini moonshot in itself, this went from idea to event in a few months! even the Mayor of Athens was surprised. What set thios apart was how the event drew in a significant international contingent, from the big AI tech giants like Microsoft, Amazon , OpenAI and Canva, to a surprise attendance of pop star Ke$ha to discuss her new startup Smash ( I was fanboying and also deeply touched by her personal story and drive to launch her startup). It was also a fantastic opportunity to meet with and learn about the burgeoning local startup scene in Athens, which is making great strides in areas from AI, defense, robotics, and more, demonstrating a growing global interest in the Greek capital’s talent. Meeting these founders and learning about their challenges and dreams was incredibly insightful and felt like were at the tip of an unstoppable force. A truly surreal moment for me was meeting former Prime Minister of Greece (George Papandreou) and having it confirmed we are distant relatives! At the intersection of tech and music: Jen Hall (Amazon) interviews Ke$ha on her innovative startup, ... More Smash.Timothy Papandreou The Unfolding Story: Athens' Potential as Europe's Next Tech Hub The trajectory of the global startup landscape, while dominated by established powerhouses from where I was based in San Francisco in the US consistently reveals the emergence of innovation from unexpected locales. The United States (particularly Californian cities), for instance, continues to lead in overall venture capital investment by a long shot followed by cities in China. However, several cities in Europe demonstrate significant strength in early-stage funding and deep tech development, indicating a robust capacity for future growth. According to several industry reports, early-stage funding in key startup hubs in Europe have shown consistent year-on-year increases, and deep tech investments are attracting a larger share of capital compared to a decade ago. This reflects a strategic shift towards longer-term, more research-intensive ventures with the potential for transformative impact. The ultimate success of these nascent ecosystems, however, hinges not so much on geography, but on fundamental drivers: product-market fit and the adaptability of founders. Location, while influential, serves as an amplifier of these core dynamics. A supportive environment can significantly increase a startup's chances of finding product-market fit and adapting to market changes, while a challenging environment can exacerbate these inherent risks. From Perth to global dominance: Lars Rasmussen (Co-0founder Google Maps and Panathēnea mentor) talks ... More (via live video box) scaling with Canva co-founders Melanie Perkins and Cliff Obrecht, exploring their design-wave ride and AI integration.Timothy Papandreou Why Athens? The Seeds of a Thriving Ecosystem The city presents a unique value proposition anchored by a substantial reservoir of highly educated, multilingual and technically proficient talent, a strategic geopolitical location at the nexus of Europe, Asia, and Africa offering access to diverse markets, and a significantly more attractive cost structure (critical for startup runway) compared to established European hubs in the north-west. Furthermore, the increasingly engaged global Greek diaspora in their own respective tech hubs from London, San Francisco, New York and as far as Sydney represent a potent source of capital, mentorship, and international networks. Athens has a unique opportunity to not just catch up, but to strategically leapfrog legacy issues hindering industries. By embracing the transformative power of AI, Athens start ups can bypass traditional talent, funding and other bottlenecks and pioneer innovative solutions and go-to-market products and services quicker than ever before. This future-forward approach allows Athens to transcend any notion of "too small" a market or succumb to "imposter syndrome." The confluence of factors, coupled with what I call a "gritty yet chic" urban energy is something of a unique and authentic offering in today’s overly generic, chain-store dominated and hollowed-out central cities. Sophia Nunes, Portugal's pioneering woman co-founder of the Unicorn startup Mambu, shares insights ... More on scaling for successTimothy Papandreou Germination Amidst the Grit: Addressing Foundational Needs The energy witnessed at Panathēnea and in conversations with local founders signals that the seeds of a thriving startup ecosystem are indeed beginning to germinate. Having personally observed similar early-stage vibrancy in the nascent phases of ecosystems like San Francisco, Berlin, London and Tel Aviv, it’s clear that Athens possesses the raw ingredients for success. However, for Athens ( like cities before it), to truly realize its moonshot potential, certain foundational elements require significant cultivation. Building upon initial steps, the immediate priority is laser focus policies to bolster startup infrastructure. This includes streamlining and digital one-stop-shop business formation, taxation, and residency processes to create a frictionless environment for entrepreneurs. Concurrently from the business community, fostering a more collaborative culture, one that actively encourages mentorship and currency of learning over internal competition, is paramount. To ensure long-term viability and attract significant investment, a concerted effort must be made to evolve the funding landscape, actively courting later-stage venture capital to complement existing seed funding. This unwavering focus on these core pillars from efficient infrastructure, a collaborative culture, and a mature funding ecosystem, will be crucial in attracting and retaining both domestic and international talent, ultimately solidifying Athens' position on the global startup map. The Decades in the Making: Athens' Emerging Startup LandscapeMarathon VC's Panos Papadopoulos and Hack The Box CEO Haris Pylarinos share their insights on ... More scaling passion projects into thriving international businessesTimothy Papandreou Athens is not without its hurdles; it is just recovering from a deeply painful and prolonged fiscal crisis, Covid shutdowns and acute cost of living impact. While the wounds over this last decade run deep, this is not the first time Athens has been tested. In fact, these ground-truths highlighted a recurring theme at the event- the resilience born from these hardships. While failure in startups can feel inevitable, it happens quickly, and the concept of 'failing forward’ means these Greek startups are unlikely to retreat easily. This tenacity gives the impression that Athens is already an overnight success, but in reality, it has been decades in the making. Credit is due to the founders, VCs, and policy supporters who have diligently addressed each barrier over the years. Addressing infrastructural limitations and fostering a risk-tolerant, 'fail fast’ investment culture will be crucial. However, the fundamental ingredients: the rising talent, strategic location, compelling value proposition, and burgeoning entrepreneurial spirit are undeniably present. The energy is shifting, the ambition and hunger is real, and the various pieces are starting to come together. The potential for Athens to become Europe’s next significant startup 'moonshot’ is increasingly viable. The world of venture capital and global innovation would be wise to pay close attention to the unfolding future story in this ancient city.

You’re looking for a reliable laptop at a reasonable price point? The Lenovo IdeaPad 1 is currently available on Amazon at a record low, and this is one of the best-sellers among its category right now. This 15″ laptop with 32GB RAM and 1TB storage boasts an impressive 4.8 out of 5 stars from customer reviews, and it has seen its price slashed by a huge 73%, now selling for just $399, down from its original $1,499 list price. If you’re searching for a great value for money laptop, that’s the one. See at Amazon Perfect for Home or Business The Lenovo IdeaPad 1 is designed to serve home and business users. It is powered by an Intel Celeron N4500 dual-core processor with a speed of up to 2.8 GHz. While this processor is designed for standard use (and not heavy gaming or video editing), it’s more than sufficient for web surfing, word processing, streaming media, and light gaming. The processor is also complemented with integrated Intel UHD Graphics to ensure smooth motion when watching videos. It also has an impressive 32GB DDR4 RAM and multitasking will be very easy. You can open various apps and browser tabs without noticing the lag which is a big advantage for professionals and students. The 1TB PCIe SSD provides you with lightning-fast boot-ups and ample space for all your documents, files, photos, and business information. The 15.6-inch Full HD anti-glare display screen is another great feature and it offers crisp text and vibrant colors. The thin configuration gives you ultimate screen real estate so you can stream your top shows, do work on papers or virtually attend classes with no compromise. Sound is one aspect that’s often sacrificed on budget notebooks, but IdeaPad 1 excels with its two Dolby Audio speakers. With the HD 720p camera featuring a privacy shutter, you can be sure and have full control over your online meeting or virtual gathering privacy. You will also enjoy several ports on the laptop, including USB 2.0, USB 3.2 Gen 1, USB-C 3.2 Gen 1 for data transfer, HDMI 1.4b, a card reader, and a headphone / microphone combo jack. It will be easy connect to external monitors, storage devices and other peripherals. What’s more, Windows 11 Pro is pre-installed and you’ll enjoy a modern, secure, and intuitive operating system perfect for work and play. The English non-backlit keyboard is comfortable to type on and the Cloud Grey color scheme gives it a fashionable, professional look. Last thing: This deal is unlikely to last long, so if you’re looking for a new laptop, now is the perfect time to act. See at Amazon

Eres tú For the first time, an Australian rocket will take aim at low-Earth orbit With its first launch, Gilmour Space is "looking for 10 to 20 seconds of stable flight." Stephen Clark – May 14, 2025 3:33 pm | 0 Gilmour's Eris rocket inside a hangar at the launch site in northeastern Australia. Credit: Gilmour Space Gilmour's Eris rocket inside a hangar at the launch site in northeastern Australia. Credit: Gilmour Space Story text Size Small Standard Large Width * Standard Wide Links Standard Orange * Subscribers only   Learn more Gilmour Space, a venture-backed startup based in Australia, is about to launch a small rocket from its privately owned spaceport on a remote stretch of the country's northeastern coastline. It's the first time anyone has attempted to reach orbit with a rocket designed and built in Australia. Gilmour's three-stage rocket, named Eris, could launch at any time during a 10-hour window Thursday, local time. In the United States, the launch window runs from 5:30 pm EDT Wednesday until 3:30 am EDT Thursday. The debut launch of Gilmour's Eris rocket is purely a test flight. Gilmour has tested the rocket's engines and rehearsed the countdown last year, loading propellant and getting within 10 seconds of launch. But Gilmour cautioned in a post on LinkedIn early Wednesday that "test launches are complex." Gilmour added on social media that "weather, systems checks, or technical issues may delay the flight—sometimes by hours, days, or longer." Gilmour, based in Gold Coast, Australia, was founded in 2012 by two brothers—Adam and James Gilmour—who came to the space industry after careers in banking and marketing. Today, Gilmour employs more than 200 people, mostly engineers and technicians. Most are recent engineering graduates in their 20s, along with a handful of space industry veterans with experience at companies like Rocket Lab, Firefly Aerospace, Avio, and Airbus. The company has raised approximately $90 million, primarily from venture capital firms, to get the first Eris rocket to the launch pad. The funding also paid for construction of Bowen Orbital Spaceport, Gilmour's launch site in the Australian state of Queensland. Apart from launch vehicles, Gilmour is working on its own satellite platform, which could launch on Eris or foreign rockets. Looking for stable flight But Eris is the core of Gilmour's business. Built to haul small satellites to orbit, the rocket stands 82 feet (25 meters) tall and has an unusual design for a modern launcher, with three stages, each powered by hybrid engines burning a proprietary solid fuel mixed with a liquid oxidizer. Hybrid engines are an unconventional choice. They have a low thrust density, meaning they produce less thrust per unit area of the engine's nozzle. Effectively, hybrid engines produce relatively little thrust for their size. Hybrid rocket engines also burn fuel more slowly than traditional solid- or liquid-fueled rockets, making it difficult to reach high thrust levels. Gilmour's Eris rocket stands on its launch pad in Queensland, Australia. Credit: Gilmour Space There are some advantages to hybrid engines. They are less complex (and probably cheaper) than a liquid-fueled rocket engine, and unlike a solid rocket motor, hybrid engines can be throttled or turned off in the event of a problem. For these reasons, Virgin Galactic's commercial suborbital rocket plane uses a hybrid engine burning a rubber-based solid fuel and liquid nitrous oxide. Gilmour's rocket uses hydrogen peroxide for an oxidizer. The company hasn't released details about the rocket's solid fuel, citing proprietary reasons. Four of Gilmour's Sirius engines power the first stage of the Eris rocket, collectively generating more than 100,000 pounds of thrust. A single Sirius engine is mounted on the second stage, and Eris' third stage is driven by a smaller liquid-fueled engine named Phoenix, also designed by Gilmour Space. Like many launch startups, Gilmour is setting modest expectations for the inaugural flight of Eris. The first time Gilmour will ignite four of its Sirius engines at the same time will be in the final moments before liftoff. "Eris is a first-of-its-kind rocket," Gilmour wrote on social media. "While it’s capable of reaching orbit, that’s not the expectation this time. (For context: SpaceX made orbit on its fourth try.) This mission is all about gathering critical data to improve future flights." Michelle Gilmour, the company's head of marketing and communications, told Ars the first milestone of the test flight "would simply be getting off the pad. Then, we’d be looking for 10 to 20 seconds of stable flight." A “manageable” drop zone If the rocket makes it that far, it will clear the coastline and head northeast, soaring over the Great Barrier Reef and the Coral Sea. This flight path raised concerns about environmental impacts to the Great Barrier Reef, but the government of Queensland determined the environmental risk "would likely be manageable" with drop zones for the first and second stages of the rocket outside the Great Barrier Reef World Heritage Area. The Eris rocket will fly northeast from Bowen Orbital Spaceport over the Great Barrier Reef. Credit: Queensland Government Australia's government approved a launch facility license for Gilmour Space in April of last year, and the Australian Space Agency granted a launch permit for the first flight of the Eris rocket in November. Australia's Civil Aviation Safety Authority gave Gilmour airspace approval in February. But then, Gilmour encountered more regulatory issues as a tropical cyclone churned off the coast of the launch site. The regulatory and weather delays abated, and the Australian Space Agency issued its final approval for Gilmour's launch last week. This is all uncharted territory for not just Gilmour, but also Australia's government. Australia hosted a handful of satellite launches with US and British rockets from 1967 through 1971, but Gilmour's Eris is the first all-Australian launch vehicle designed for orbital flight. The Eris rocket is capable of delivering about 670 pounds (305 kilograms) of mass into low-Earth orbit, a payload capacity roughly equivalent to Rocket Lab's Electron launch vehicle, which flies from New Zealand, home of the world's only other operational commercial spaceport in the Southern Hemisphere. A perfect flight for the Eris rocket would see it reach an orbit around 120 miles (200 kilometers) high at an inclination of 33 degrees to the equator, according to Gilmour. Just in case, the company has placed a jar of Vegemite, a popular food spread in Australia, on Eris' third stage in a tongue-in-cheek nod to Aussie culture. Stephen Clark Space Reporter Stephen Clark Space Reporter Stephen Clark is a space reporter at Ars Technica, covering private space companies and the world’s space agencies. Stephen writes about the nexus of technology, science, policy, and business on and off the planet. 0 Comments