Discord Update: March 25, 2025 Changelog (opens in new tab)

The Discord March 25, 2025, update focuses on a comprehensive modernization of the desktop client and its in-game integration capabilities. Through a modular overlay redesign and significant UI flexibility, the platform aims to enhance user agency and service reliability for its core gaming audience. ### Modular In-Game Overlay * The overlay has been transitioned to a widget-based system, allowing users to move and organize specific UI elements to suit different game genres. * New functional depth includes the ability to watch friend's streams or start a personal gameplay broadcast with a single click without leaving the game. * Native Soundboard support is now integrated directly into the overlay for immediate access during gameplay. * The update expands the library of supported games, ensuring notifications and widgets work across more titles. ### Desktop UI Refresh and Customization * Four new base themes—Light, Ash, Dark, and Onyx—have been introduced alongside three UI density options to adjust app spacing. * The interface has been decluttered by moving the Inbox to the title bar and centralizing voice and video call buttons into a single unified bar. * The channel list is now resizable, facilitating easier navigation for servers with long channel names. * Active camera status is now indicated by a persistent green button, providing better visual feedback when a user's video is live. ### Developer Integrations and Social Tools * A new API allows developers to implement Discord-powered text chat directly within their game clients, with initial support in titles like *Rust* and *Pax Dei*. * The "Ignore" feature provides a privacy layer that hides messages from specific users in DMs and servers without notifying the ignored party. * Discord’s App Launcher now includes "Spark: Hero Tactics," a new first-party deck-building battle game available on both desktop and mobile. ### Backend Reliability and API Deployment * Discord has overhauled its API deployment process to isolate and protect critical infrastructure from potential configuration errors. * This structural change is designed to minimize the frequency of outages and ensure that core messaging and voice services remain stable during maintenance cycles. To get the most out of this update, users should experiment with the new UI density settings to reclaim screen real estate and check the Overlay settings to configure their widget layout before their next gaming session.

Double Click: You Can Just Do Things—But Should You Always? | Figma Blog (opens in new tab)

Double click: When coding becomes conversation Developers are embracing a new way of building software that’s more conversation than code. But is it more mayhem than magic? Insights Engineering AI UI/UX Thought leadership Design

Geospatial Reasoning: Unlocking insights with generative AI and multiple foundation models (opens in new tab)

Google Research is introducing Geospatial Reasoning, a new framework that integrates generative AI with specialized foundation models to streamline complex geographical problem-solving. By combining large language models like Gemini with domain-specific data, the initiative seeks to make large-scale spatial analysis accessible to sectors like public health, urban development, and climate resilience. This research effort moves beyond traditional data silos, enabling agentic workflows that can interpret diverse data types—from satellite imagery to population dynamics—through natural language. ### Specialized Foundation Models for Human Activity * The Population Dynamics Foundation Model (PDFM) captures the complex interplay between human behaviors and their local environments. * A dedicated trajectory-based mobility foundation model has been developed to process and analyze movement patterns. * While initially tested in the US, experimental datasets are expanding to include the UK, Australia, Japan, Canada, and Malawi for selected partners. ### Remote Sensing and Vision Architectures * New models utilize advanced architectures including masked autoencoders, SigLIP, MaMMUT, and OWL-ViT, specifically adapted for the remote sensing domain. * Training involves high-resolution satellite and aerial imagery paired with text descriptions and bounding box annotations to enable precise object detection. * The models support zero-shot classification and retrieval, allowing users to locate specific features—such as "residential buildings with solar panels"—using flexible natural language queries. * Internal evaluations show state-of-the-art performance across multiple benchmarks, including image segmentation and post-disaster damage assessment. ### Agentic Workflows and Industry Collaboration * The Geospatial Reasoning framework utilizes LLMs like Gemini to manage complex datasets and orchestrate "agentic" workflows. * These workflows are grounded in geospatial data to ensure that the insights generated are both useful and contextually accurate. * Google is collaborating with inaugural industry partners, including Airbus, Maxar, Planet Labs, and WPP, to test these capabilities in real-world scenarios. Organizations interested in accelerating their geospatial analysis should consider applying for the trusted tester program to explore how these foundation models can be fine-tuned for specific proprietary data and use cases.

How to Stream Games and Applications to Discord from Desktop or Mobile (opens in new tab)

Discord’s streaming functionality aims to foster a sense of proximity among friends by allowing users to share their activities in real-time from any location. By offering a fast and integrated setup across various devices, the platform simplifies the process of broadcasting content directly to a community. This guide explores the mechanics of initiating a stream, the configuration settings involved, and the hardware compatibility for both PC and mobile users. ### Real-Time Sharing and Speed * Discord prioritizes speed in its streaming architecture, allowing users to start a broadcast almost instantly through the interface. * The feature is designed to mimic the casual experience of showing a physical screen to someone nearby, bridging the gap between remote users. ### Cross-Platform Integration * High-speed streaming is supported across both desktop and mobile applications, providing flexibility for different use cases. * The guide details the specific technical requirements and available platforms for both PC and mobile devices. * Users are presented with various configuration options during the setup phase to tailor the stream's performance and quality to their needs. To begin broadcasting, users should navigate to their desired voice channel and select the streaming icon to access the platform-specific configuration menu. Reviewing the available stream settings before going live ensures the best balance between visual quality and performance for your specific device.

Designing for Security and Usability: Figma's Modern Endpoint Strategy | Figma Blog (opens in new tab)

Server-side sandboxing: An introduction Inside Figma Security Engineering

Discord Patch Notes: April 3, 2025 (opens in new tab)

Discord’s latest Patch Notes highlight the engineering team's ongoing commitment to improving platform performance, reliability, and responsiveness through a series of incremental updates and bug fixes. While specific technical changes are currently being deployed across various platforms, the update emphasizes the collaborative role of the community in maintaining the app's stability. **Community Bug Tracking and Feedback** * Discord utilizes a Bimonthly Bug Megathread hosted on the r/DiscordApp subreddit to gather user-reported issues. * The Engineering team directly monitors these community reports to prioritize and resolve software regressions and usability obstacles. **Beta Testing and Pre-Release Development** * Users can participate in early-stage testing by opting into the Discord TestFlight version on iOS. * This testing environment allows for the identification of "pesky bugs" before features reach the general public, accessible via dis.gd/testflight. * All reported fixes are confirmed as committed and merged, though deployment timing may vary depending on the individual platform’s rollout schedule. To maintain the best user experience, it is recommended to keep the application updated and participate in official feedback channels to ensure that performance issues are addressed by the development team in a timely manner.

Evaluating progress of LLMs on scientific problem-solving (opens in new tab)

Current scientific benchmarks for large language models (LLMs) often focus on simple knowledge recall and multiple-choice responses, which do not reflect the complex, context-rich reasoning required in real-world research. To bridge this gap, Google Research has introduced CURIE, alongside the SPIQA and FEABench datasets, to evaluate LLMs on their ability to understand long-form documents, analyze multimodal data, and solve multi-step problems. These benchmarks aim to move AI from merely surfacing facts to actively assisting scientists in workflows involving information extraction, algebraic manipulation, and tool use. ### The CURIE Multitask Benchmark * CURIE spans six diverse scientific disciplines: materials science, condensed matter physics, quantum computing, geospatial analysis, biodiversity, and proteins. * The benchmark includes 10 challenging tasks, such as concept tracking, information aggregation, and cross-domain expertise, based on 429 full-length research documents. * The complexity of the benchmark is reflected in its scale, with input queries averaging 15,000 words and ground truth responses averaging 954 words. * Domain experts were involved in every phase of development, from sourcing papers to creating nuanced ground-truth answers in formats like JSON, LaTeX, and YAML. ### Multimodal Reasoning and Agentic Simulation * The SPIQA (Scientific Paper Image Question Answering) dataset evaluates the ability of multimodal LLMs to ground their answers in complex figures and tables found in scientific literature. * FEABench (Finite Element Analysis Benchmark) measures the ability of LLM agents to simulate and solve multiphysics, mathematics, and engineering problems. * These tools specifically test whether models can choose the correct computational tools and reason through the physical constraints of a given problem. ### Programmatic and Model-Based Evaluation * Because scientific answers are often descriptive or formatted heterogeneously, the evaluation uses programmatic metrics like ROUGE-L and Intersection-over-Union (IoU). * For free-form and complex technical generation, the framework incorporates model-based evaluations to ensure AI responses align with expert assessments. * Task difficulty is quantified by expert ratings, ensuring the benchmark measures high-level reasoning rather than just pattern matching. These new benchmarks provide a rigorous framework for developing LLMs that can act as true collaborators in the scientific process. By focusing on long-context understanding and tool-integrated reasoning, researchers can better track the progress of AI in handling the actual complexities of modern scientific discovery.

Why Design is for Everyone | Figma Blog (opens in new tab)

The new competitive moat is emotion Insights Thought leadership Product management

ECLeKTic: A novel benchmark for evaluating cross-lingual knowledge transfer in LLMs (opens in new tab)

ECLeKTic is a novel benchmark designed to evaluate how effectively large language models (LLMs) transfer knowledge between languages, addressing a common limitation where models possess information in a source language but fail to access it in others. By utilizing a closed-book question-answering format based on language-specific Wikipedia entries, the benchmark quantifies the gap between human-like cross-lingual understanding and current machine performance. Initial testing reveals that even state-of-the-art models have significant room for improvement, with the highest-performing model, Gemini 2.5 Pro, achieving only a 52.6% success rate. ## Methodology and Dataset Construction The researchers built the ECLeKTic dataset by focusing on "information silos" within Wikipedia to ensure the models would need to perform internal transfer rather than simply recalling translated training data. * The dataset targets 12 languages: English, French, German, Hebrew, Hindi, Indonesian, Italian, Japanese, Korean, Mandarin Chinese, Portuguese, and Spanish. * Researchers selected 100 articles per language from a July 2023 Wikipedia snapshot that existed exclusively in that specific language and had no equivalent articles in the other 11 targeted languages. * This approach uses Wikipedia presence as a proxy to identify facts likely encountered by the model in only one language during its training phase. ## Human Refinement and Decontextualization To ensure the quality and portability of the questions, the team employed native speakers to refine and verify the data generated by AI. * Human annotators filtered Gemini-generated question-and-answer pairs to ensure they were answerable in a closed-book setting without referring to external context. * Annotators performed "decontextualization" by adding specific details to ambiguous terms; for example, a reference to the "Supreme Court" was clarified as the "Israeli Supreme Court" to ensure the question remained accurate after translation. * Questions were curated to focus on cultural and local salience rather than general global knowledge like science or universal current events. * The final dataset consists of 384 unique questions, which were translated and verified across all 11 target languages, resulting in 4,224 total examples. ## Benchmarking Model Performance The benchmark evaluates models using a specific metric called "overall success," which measures a model's ability to answer a question correctly in both the original source language and the target language. * The benchmark was used to test eight leading open and proprietary LLMs. * Gemini 2.0 Pro initially set a high bar with 41.6% success, which was later surpassed by Gemini 2.5 Pro at 52.6%. * The results demonstrate that while models are improving, they still struggle to maintain consistent knowledge across different linguistic contexts, representing a major hurdle for equitable global information access. The release of ECLeKTic as an open-source benchmark on Kaggle provides a vital tool for the AI community to bridge the "knowledge gap" between high-resource and low-resource languages. Developers and researchers should use this data to refine training methodologies, aiming for models that can express their internal knowledge regardless of the language used in the prompt.

The Designer's Handbook for Developer Handoff | Figma Blog (opens in new tab)

5 things designers need to know for a smooth handoff Working Well Collaboration Design

Revamped Overlay & Refreshed Desktop Give Game Time a Boost (opens in new tab)

Discord is launching a comprehensive update to its desktop client focused on improving the integration between communication and active gameplay. By introducing a completely rebuilt overlay and a modernized interface, the update aims to provide a more responsive and customizable experience for PC gamers. ### Enhanced Game Overlay and Performance * Features a completely rewritten architecture to ensure broader compatibility across a wider range of gaming titles. * Delivers significant performance improvements designed to minimize the technical footprint of the overlay during high-intensity sessions. * Provides a modernized aesthetic that aligns with the app's updated design language. ### Desktop Visual Refresh and Customization * Introduces a refreshed look for the desktop client, streamlining the user interface for better navigation. * Includes new tools for tweaking and customizing the app, allowing users to tailor the Discord experience to their specific needs. * Focuses on flexibility, giving gamers more control over how the application looks and functions on their specific PC setups. These updates represent a significant step in making Discord a more seamless part of the PC gaming ecosystem. Users should explore the new customization settings to optimize their interface layout and test the rebuilt overlay in-game to experience the performance gains firsthand.

The evolution of graph learning (opens in new tab)

The evolution of graph learning has transformed from classical mathematical puzzles into a cornerstone of modern machine learning, enabling the modeling of complex relational data. By bridging the gap between discrete graph algorithms and neural networks, researchers have unlocked the ability to generate powerful embeddings that capture structural similarities. This progression, spearheaded by milestones like PageRank and DeepWalk, has established graph-based models as essential tools for solving real-world challenges ranging from traffic prediction to molecular analysis. **Foundations of Graph Theory and Classical Algorithms** * Graph theory originated in 1736 with Leonhard Euler’s analysis of the Seven Bridges of Königsberg, which established the mathematical framework for representing connections between entities. * Pre-deep learning efforts focused on structural properties, such as community detection and centrality, or solving discrete problems like shortest paths and maximum flow. * The 1996 development of PageRank by Google’s founders applied these principles at scale, treating the internet as a massive graph of nodes (pages) and edges (hyperlinks) to revolutionize information retrieval. **Bridging Graph Data and Neural Networks via DeepWalk** * A primary challenge in the field was the difficulty of integrating discrete graph structures into neural network architectures, which typically favor feature-based embeddings over relational ones. * Developed in 2014, DeepWalk became the first practical method to bridge this gap by utilizing a neural network encoder to create graph embeddings. * These embeddings convert complex relational data into numeric representations that preserve the structural similarity between objects, allowing graph data to be processed by modern machine learning pipelines. **The Rise of Graph Convolutional Networks and Message Passing** * Following the success of graph embeddings, the field moved toward Graph Convolutional Networks (GCNs) in 2016 to better handle non-Euclidean data. * Modern frameworks now utilize Message Passing Neural Networks (MPNNs), which allow nodes to aggregate information from their neighbors to learn more nuanced representations. * These advancements are supported by specialized libraries in TensorFlow and JAX, enabling the application of graph learning to diverse fields such as physics simulations, disease spread modeling, and fake news detection. To effectively model complex systems where relationships are as important as the entities themselves, practitioners should transition from traditional feature-based models to graph-aware architectures. Utilizing contemporary libraries like those available for JAX and TensorFlow allows for the integration of relational structure directly into the learning process, providing more robust insights into interconnected data.

How to Create & Upload Your Own Stickers on Discord (opens in new tab)

Discord has evolved beyond standard text to incorporate expressive visual elements like emojis and large-scale "Stickers." These high-impact graphics provide a more dynamic way to communicate emotions and personality within server conversations. By mastering how to find, use, and upload custom assets, users can significantly enhance their messaging experience on the platform. **The Role of Stickers in Communication** * Stickers function as "big emojis," utilizing an enormous size to provide more visual punch than standard icons. * They are designed to convey complex emotions and reactions that small-scale characters like 😬 might not fully capture. * They serve as a primary tool for adding personal flair and emphasis to posts within the Discord interface. **Accessing and Customizing Sticker Libraries** * The platform provides access to hundreds of existing stickers that are ready for immediate use across different servers. * Users can expand their library by uploading their own custom stickers, allowing for a personalized set of assets tailored to a specific community. * The interface includes dedicated sections for finding, managing, and deploying these assets within a chat window. To get the most out of Discord's visual suite, users should experiment with integrating both standard emojis and large-format stickers to match the tone and energy of their digital interactions.

Checkpoint 2: Our First Year With Discord Quests (opens in new tab)

Discord is leveraging its massive community of over 200 million monthly active users to solve the persistent challenge of game discovery for developers. By analyzing engagement data across thousands of titles, the platform has identified a unique "long-tail" trend where niche games receive higher relative playtime compared to the broader industry. To capitalize on this, Discord has introduced Quests, a rewarded ad format designed to connect players with new titles through authentic, community-centric experiences. ### Discord’s Gaming Ecosystem and User Engagement * The platform currently supports over 200 million monthly active users who use the service as a primary social hub for gaming. * Monthly gameplay exceeds 1.5 billion hours across more than 8,000 different titles on PC alone. * Discord facilitates a higher percentage of playtime for a diverse "long-tail" of games than is typically seen in the wider gaming market. * The platform serves as a critical environment for developers to reach specific audiences that are already highly engaged with digital social interaction. ### Quests and the Rewarded Ad Model * Quests represent a strategic shift toward helping brands and developers reach players through an innovative rewarded ad format. * The system is built to be "player-centric," offering rewards to users for engaging with specific game content. * By integrating advertising directly into the social ecosystem, Discord aims to facilitate game discovery in a way that feels natural rather than intrusive. * This format provides a bridge between developer marketing needs and the authentic social behavior of the Discord community. For developers and brands, the launch of Quests offers a high-precision tool for navigating a crowded gaming market. By utilizing Discord’s infrastructure to reach players where they are already socially active, creators can tap into a massive, pre-existing audience to drive title awareness and long-term engagement.

Figma Localizes Product and Support for Spanish Market | Figma Blog (opens in new tab)

Figma localizes product and support for Spanish market Inside Figma News Figma adds Spanish as its second localized language, after Japanese, with more languages expected later this year. Figma is localizing for the Spanish market. This includes full product translation, cultura…