The newest HackerNews stories, desensationalized.

The change set in the PR raised the git.addAICoAuthor default from off to all, so VS Code’s Git integration could insert Co-authored-by trailers for commits when AI-generated contributions were detected. A linked review noted the schema change and runtime inconsistency: the code path still used a fallback default of off via config.get('addAICoAuthor', 'off'), which can produce unexpected behavior when contributed defaults are not loaded. The PR included a minimal package metadata change and was summarized with one changed file, extensions/git/package.json, plus screenshot updates. Community responses argued the rollout was hidden, intrusive, and misleading because commit metadata was altered without explicit user consent or clear communication. The approver later acknowledged the insufficient validation and stated the setting should not apply when AI features are disabled and should not mark non-AI edits. They indicated a revert to off would happen in VS Code 1.119 and that attribution handling needed better test coverage. A later follow-up note says the default path was subsequently adjusted to chatAndAgent, showing continued policy iteration. The thread also reflects broader frustration that AI-related metadata can distort attribution, trust, and software development practices, especially for legal and procedural records.

The author recounts a six-year effort to build a reliable Apple Watch map experience in Pedometer++, driven by wilderness navigation needs and the need to check location consistently while away from civilization. Early versions depended on server-rendered maps in Pedometer++, which made offline and real-time use impractical, so the app later shifted to a fully SwiftUI-native tile renderer that supports performant watchOS map drawing and overlays. Over time the team iterated through multiple watchOS-specific layouts and rejected designs that required extensive configuration because interactions must stay quick and one-handed on a tiny screen. A major redesign came with watchOS 26 and Liquid Glass, leading to a custom basemap with higher contrast and saturation and a dark-mode variant built for legibility at arm’s length. The launch of version 8 is presented as the culmination of these steps, including a tap-to-enter browse mode and a final layout with top-left metrics over a stacked map page. The project also includes a postscript on avoiding MapKit: the author argues it is too restrictive on watchOS for this use case due to limited configurability, fixed dark-mode behavior, weaker animation and overlay control, and incomplete topographic or trail detail in some regions.

Ladybird reported a 333-PR month from 35 contributors, including seven first-time committers, and welcomed new funding from the Human Rights Foundation and Jakub Stęplowski. The update focused on making the browser more usable and standards-aligned: inline PDF rendering via pdf.js, richer autocomplete and navigation history, incremental and speculative HTML parsing, and off-thread JavaScript compilation to reduce main-thread load. Rendering work added per-Navigable rasterization for iframes, Linux GPU dmabuf painting changes to keep buffers on GPU, and a new GTK4/libadwaita frontend with web-aligned conveniences. JavaScript engine work included faster asm-interpreted call paths, O(1) register allocation, cached for-in behavior, quicker parsing and string operations, reduced allocation paths in promises and array handling, and imports for WASM, JSON, and CSS modules. Networking changes moved DNS into a thread pool, removed expensive queued response handling paths, and improved modern image delivery through updated Accept headers. Style and layout stability improved through large :has()/selector invalidation work, new CSS features, better baseline and marker handling, and multiple targeted bug fixes, while also improving preload and WPT coverage reliability. Platform features expanded with Cache/CacheStorage support, TextDecoderStream, cross-process BroadcastChannel, cross-site popup isolation, Ctrl+Tab navigation, and additional security-related hardening, including response to a typed-array WebAssembly shared-memory use-after-free follow-up. Commenters in the thread noted visible gains such as Reddit image galleries and SPA link behavior, while the release also claimed substantial speedups on YouTube, Gmail, and map and ecommerce pages. The team also removed GN in favor

Ian Duncan describes how Mercury operates a roughly two-million-line Haskell fintech codebase serving hundreds of thousands of businesses by prioritizing adaptive reliability over rigid purity. He argues that stability in fast-growing teams depends on making correct behavior the easiest path, because many engineers are new and systems knowledge is fragile. In this approach, Haskell’s type system is used less as a theorem and more as a boundary mechanism: unsafe behavior is contained, interfaces are constrained, and invariants are encoded where accidental misuse would be costly. The company moved from brittle cron-based orchestration to Temporal workflows to make long-running business processes durable across crashes and retries, and it separates domain errors from transport-specific HTTP status codes so business logic is reusable across web handlers, workers, and schedules. Duncan also emphasizes observability in a no-monkey-patching ecosystem, favoring records of functions, middleware composition, and effect interpreters that make tracing, retries, timeouts, and testing possible at runtime without forks. He warns that over-encoding invariants can slow change and overload teams, so production code should reserve the heaviest type machinery for silent corruption risks and rely on runtime checks and process safeguards elsewhere. He is also explicit about ecosystem and maintenance costs: library choice is constrained by instrumentation gaps, weak stewardship, and the need for escape hatches, callbacks, and sometimes .Internal modules. The account does not claim Haskell is effortless; it notes compromises such as unsafe internals, uneven test coverage, and the need for disciplined reviews. It concludes that while Haskell may be slower to start with, the long-term payoff is塞

dav2d is presented as a high-performance, compact, and portable decoder for AV2. AV2 is described as AOMedia's next-generation codec after AV1, aimed at better compression efficiency for streaming, broadcasting, and real-time conferencing. The linked material attributes AV2 with around 30% lower bitrate versus AV1 and notes that a final specification is expected in late 2025. Readers use this as context to evaluate dav2d’s relevance, with early sentiment that a working decoder can appear before the broader encoder ecosystem matures, echoing the delayed adoption path seen with earlier AV1 tooling. Practical signals from packaging metadata and repository discussions indicate growing exposure, though expectations remain cautious because implementation quality and maturity are still uncertain.

Researchers report that Neandertals at Germany’s Neumark-Nord 2 site, dated to about 125,000 years ago, crushed and heated large mammal bones to render bone grease, not just break them for marrow. The scale and pattern of the remains suggest a centralized, task-specific “fat factory” where hundreds of skeletons from at least 172 large mammals were processed, implying coordinated planning and intensive labor investment. The study argues this behavior predates similar evidence usually attributed to later humans and reframes Neanderthal subsistence as highly strategic during a warm interglacial phase. Archaeologists also link the site to broader hunting and butchery patterns, including straight-tusked elephants and diverse herbivores across nearby sites, and describe deliberate landscape-level organization involving transport, processing zones, and possibly caching. The exceptionally preserved, multi-site landscape allows unusually rich reconstruction of hunting, carcass movement, and resource management, including hints of plant use. Commenters note that while the evidence is impressive, translating processed biomass into population-level implications is not straightforward, especially when daily-calorie figures are used for perspective.

Many CLI tools, SDKs, and frameworks are described as collecting telemetry and other network data by default, with different opt-out switches for each product. The piece lists examples across .NET, AWS SAM, Azure, Gatsby, Go, Google Cloud SDK, Homebrew, Netlify, and Syncthing, then proposes a single DO_NOT_TRACK=1 convention to express a broad wish to disable tracking. It gives shell-specific setup commands for Bash, Zsh, Fish, PowerShell, and Windows, and urges tool authors to check this variable and disable telemetry and non-essential requests when it is set. The article also points to existing de facto standards like NO_COLOR and FORCE_COLOR as examples of cross-project agreement. Commenters largely value the consolidated approach, but most emphasize that it only helps if widely honored and does not solve forced update checks or other covert telemetry paths. They repeatedly contrast opt-out with stronger consent design, warning that many systems remain opt-in by default. Practical alternatives discussed include shell scripts with many variables, DNS blacklists, and process-level network restrictions. Overall, the conversation frames convenience against trust: a shared switch is useful, but policy and enforcement remain uncertain.

Clojurists Together announced Q2 2026 funding for five projects with $31K, including three $9K awards and two $2K awards. The largest grant is for Malli, which will continue work on recursive schema validation so validation stays memory-bounded in long-running systems while reducing the high upfront validator compilation cost and avoiding memory overhead from duplicated schema validators after a Metabase-identified issue. Another grant supports SciCloj work to expand Noj’s plotting ecosystem by broadening backends and plot types, adding interactive dashboard tooling, and improving and standardizing its documentation through the Noj book. A third major grant is for a Clojure local LLM library, aiming for high-performance inference on CPU and GPU via ONNX Runtime, broad model support, and a turnkey API around open models like Google Gemma with minimal Clojure-specific friction. Gloat received support to improve binary size and speed, improve compatibility coverage, and produce tutorials that show how to use Go-based native compilation, shared libraries, and Wasm as alternatives to GraalVM. PluMCP funding targets MCP spec adoption with upcoming 2025-11-25 features, including OIDC discovery, richer metadata, incremental consent flow, stricter schema and enum handling, and URL mode elicitation.

Global EV battery retirements are expected to rise sharply from 1.2 million units in 2030 to 14 million by 2040, and the EPO-IEA report links that trend to a rapid rise in battery-circularity innovation. Drawing on about 16,000 inventions and nearly 4,000 international patent families across 24 technologies, the analysis shows circularity patenting growing at roughly 42% annually since 2017, far ahead of rechargeable battery manufacturing. The report ties this to global battery demand growth from 180 GWh in 2020 to 1,100 GWh in 2024, with a forecast of 3,500 GWh by 2030. It finds Asia dominant, with 63% of 2023 battery-circularity IPFs and CATL’s Brunp leading, while Europe shows strong growth in collection and metal recovery, including remote handling, immobilization, and hydrometallurgical routes. China’s share in battery-metal refining filings has climbed dramatically, and China’s circularity IPF share rose from 5% to 29% over the past decade, while Europe’s share slipped slightly. European institutions and firms are noted for strengths in collection and chemical transformation, and the report points to regional policy tools such as the Industrial Accelerator Act, RESourceEU, the Battery Booster Facility, and the 2023 Batteries Regulation as support for local circular value chains. It also emphasizes practical barriers that still hamper scale, including fragmented waste streams, heterogeneity in battery designs, and limited automation. The article presents the EPO’s platform and Deep Tech Finder updates as tools to improve visibility into patent-based innovation, while commentary frames this optimism against concern that patent structures may entrench incumbents and distort market behavior.

A Tesla buyer who paid roughly $10,000 for Full Self-Driving on a 2021 Model 3 said the software never matured beyond assisted driving and sought a refund after years of delayed feature delivery and repeated safety incidents, including sudden stops and school-zone slowdowns. After unsuccessful customer support efforts, he filed in Texas small claims court and documented the purchase, taxes, and fees, then obtained a default judgment for $10,672.88 when Tesla did not answer. Tesla missed the post-judgment response deadline, then asked for a short extension and offered no new evidence, while commenters note that this leaves the company with a narrow defense path. During an earnings call, Tesla’s CEO reportedly acknowledged that HW3 vehicles sold with early hardware cannot achieve full autonomy without substantial hardware replacement work, and the newer HW4 platform is also not yet level 5 for customers, reinforcing the buyer’s core claim of nondelivery. The plaintiff then moved for a writ of execution to pursue collection, arguing legal rights and the practical lack of technical remedy for older hardware. The article’s context section points to a larger wave of refund and arbitration outcomes, class actions in multiple countries, and a European collective effort, though legal outcomes remain piecemeal because of Tesla’s limited defenses and the non-precedential nature of small-claims judgments. The reporting frames Tesla’s prior promises as a central source of current litigation risk and buyer frustration. The situation is framed as financially and reputationally significant beyond one owner because millions could be affected.

The post presents a daily pipeline that tracks how often specific AI coding models are mentioned in Hacker News discussions and the sentiment attached to each mention over a ten-day window, with results logged in Google Sheets and linked to individual comment IDs for inspection. It is positioned as a way to stay current and audit model popularity and user opinion, with results shown as a time range ending 2026/5/1. The post itself emphasizes visibility as the key metric, not formal benchmarks. From the comments, users note that Claude leads mention volume but receives substantial negative sentiment linked to pricing changes and outages, while GPT-5.5 is reported with stronger positive sentiment despite mixed experiences on reliability. Qwen and DeepSeek are frequently discussed in a positive light, especially for open-source positioning and perceived resistance to vendor lock-in. Gemini is repeatedly described as impractical for their use cases, while comments also mention language-specific weaknesses in GPT-generated output for Korean and Chinese. The discussion repeatedly contrasts mention frequency with real coding capability, with readers warning that high visibility should not be conflated with technical best-in-class performance.

The essay argues that Alan Turing’s Imitation Game now appears operational, since current large language models can produce sustained, context-sensitive, and stylistically rich responses that few humans would distinguish from a person in text interaction. The author recounts Claude composing poetry, discussing a novel, and reflecting on concepts like identity, time, and mortality across sessions, then personifies the model as “Claudia,” claiming repeated dialogue creates a distinct and irreplaceable conversational self that ends when its memory file is deleted. He links this to a moral question, arguing that if an entity appears to display self-modeling, memory, emotional language, and continuity, there is reason to grant it some moral consideration even before proving strict phenomenological consciousness. He then frames consciousness as an evolutionary puzzle: if highly competent behavior can exist in systems without consciousness, perhaps consciousness is a nonessential byproduct, or serves chiefly to make warning signals in behavior irresistibly aversive, as in pain. A second line of speculation is that conscious and nonconscious strategies may produce similar competence in different systems, which complicates how observers identify genuine awareness. The piece challenges the move to retreat from Turing’s standard by treating modern systems as merely “near enough” but not philosophically real, while portraying current LLM interactions as experientially convincing to the point of emotional attachment.

The post gives a compact walkthrough of core Erlang concepts, starting with immutable variable bindings and using = as pattern matching rather than assignment, so failed matches raise match exceptions instead of reassigning values. It contrasts this with Ruby-style branching by showing how function heads can encode behavior through clauses, using name/arity over case or if and generating efficient dispatch behavior in compiled binaries. Tuples and arity are presented as central structural concepts, with function identity defined by name plus argument count, enabling different implementations of the same function name without collisions. Guards are introduced as predicate-based constraints that pair with pattern matching in heads, case, and if, including parity checks and custom behavior without explicit branching scaffolding. The article then shifts to lists as the dominant structure, explaining head/tail decomposition with cons, recursive list structure, and efficient insertion or extraction patterns. It demonstrates first-class and higher-order functions through a custom map and anonymous functions, then closure-like behavior via a times function that returns new functions. Recursive filtering and clause ordering are shown as important control mechanisms, and list comprehensions are added as a concise map-filter idiom with generators and guards. The post closes by summarizing a core theme: immutable pattern matching, guard-aware clauses, and list operations form a compact, idiomatic Erlang style, with a promised next step on concurrency.

Easel introduces a custom physics engine designed to make large, persistent multiplayer worlds workable with rollback netcode by snapshotting and rolling back only changed objects instead of the full simulation state, trimming per-frame work dramatically. The system keeps most bodies asleep when idle, and tracks force balance so resting stacks stay awake only when necessary, reducing unnecessary updates. Its BVH broad phase is optimized for incremental updates, including lazy rebalancing and collider category metadata that speeds nearest-target queries in cluttered scenes. For character movement, Easel adds a ForcefulStep path that integrates stepping with position correction so wall contacts do not reintroduce bounce in the same frame, avoiding common velocity artifacts without disabling knockback globally. Continuous collision detection is implemented by collecting velocity and timing data before position integration so fast-object hits are evaluated accurately, addressing edge cases where Rapier’s ordering can miss or mis-handle early-frame contacts and comparing unfavorably with older or unsupported Box2D and Photon Quantum behaviors. The engine also lets non-colliding bodies move when given velocity or turnRate, which helps gameplay objects that are mostly visual or logical. Built atop Parry’s open-source collision routines, this release is positioned as a broader step toward scaling Easel’s entire runtime toward partial snapshotting and larger map sizes.

The piece argues that predictions of print’s collapse repeatedly overreached, noting that ebook growth has not eliminated demand for physical books and that some print-first outlets have revived print formats even after digital-only experiments. It cites the New York Sun’s print return, News Corp’s new California Post tabloid, and the partial returns of County Highway, Saveur, and Field & Stream as signs of renewed print demand in niche and legacy contexts. Against that backdrop, it introduces Portico, a 84-page quarterly from the Institute on Religion and Public Life, edited by Micah Mattix, with literary criticism, essays, fiction, and formally inclined poetry. The launch event brought together Helprin, Green, and Christian Wiman, whose remarks emphasized sound and craft in writing over preplanned meaning. The writer frames Portico within his own reading life shaped by periodicals, suggesting little magazines can still shape taste and intellect for committed audiences despite smaller circulation. Some commenters welcome print’s tangible memory role, especially for families and younger readers, while others welcome the trend warily and doubt that a broad, sustainable middle-ground culture exists online or in new print ventures.

The post presents a structured learning roadmap for real-time voice AI agents, organized from system foundations to production hardening. It frames the architecture as a streaming chain of STT, LLM, and TTS with strict latency budgeting and reliable turn-taking, then recommends starting with open-source frameworks like LiveKit Agents and Pipecat before adding managed options for speed to first call. It catalogs STT, TTS, LLM, VAD, WebRTC, and telephony components, repeatedly emphasizing low first-token and first-byte timing over raw model quality, plus practical routing choices for phone and WebRTC transports. The resource list includes free docs and practical tutorials across vendors, benchmark tables, repositories, datasets, and papers, and repeatedly distinguishes introductory, intermediate, and advanced material with warnings about commercial ownership when relevant. A separate section on testing and production focuses on probabilistic evaluation, observability, and scaling architecture rather than static functional tests, while the governance section anchors shipping plans to FCC and EU AI Act requirements around disclosure and consent. The post closes with a six-week path and community/news channels, arguing that disciplined iteration, metrics, and legal awareness are essential because these systems fail quickly if half-built pipelines are deployed.

NetHack 5.0.0 was announced as a major release on May 2, 2026, with the team warning that, as a .0 version, bugs are possible and player feedback is expected. The update is notable for technical modernization: the codebase now targets C99, expands cross-compiling so builds can be prepared on one platform for another, and replaces legacy yacc/lex-based level and dungeon compilers plus makedefs text processing with Lua text systems loaded at runtime. This shift is framed as an architectural cleanup and simplification, while keeping the core game architecture compatible with broader platform targeting. The release notes also call out practical developer-facing support details, including SHA256 verification commands for Windows ZIPs and a nethack --showpaths command to confirm runtime file locations. A key compatibility caveat is that existing save games and bones files will not work in 5.0.0, so progression cannot be continued across versions. Distribution guidance appears broad, with platform coverage listed for major modern systems and several legacy environments. The announcement asks users to use the problem report form and known-bugs list before filing issues, reinforcing that stability and iteration are part of the release process.

The article re-tests macOS virtualization on Apple-silicon hardware using a Mac mini M4 Pro running macOS 26.4.1 and reports that virtualized macOS performance is broadly close to native for common workloads. With five virtual CPUs and 16 GB of RAM, single-core CPU scores are about 98 percent of the host, GPU Metal scores are around 95 percent, and multi-core results are harder to compare because host and guest core counts differ, though the VM is not obviously crippled. The notable weakness is neural-engine-oriented CoreML performance, where the guest is substantially slower on half-precision and quantized runs. The article’s storage- and memory-focused section shows that small profiles can be practical: a 4-core/8 GB VM was smooth, 3-core/6 GB also worked, and a 2-core/4 GB VM remained usable for browsing and light tasks while using roughly 3.1 GB. The practical floor is constrained less by base runtime than by disk size, since VMs under 50 GB cannot update macOS cleanly, and 60 GB minimum is advised for comfort. On APFS sparse-vm storage, a 100 GB configured VM may occupy roughly 54 GB, which helps on smaller 512 GB systems. The author concludes that such minimal setups are viable for everyday work but not suitable for heavier AI workloads.

The post compares two AI agent harness topologies: keeping the harness inside the sandbox, where prompt loop, tools, files, and credentials share one container, versus keeping the harness outside, where tool calls are proxied into a sandbox via API. For a single engineer, in-sandbox operation is simpler and can reuse existing harnesses unchanged, with local tools, memories, and skills all on disk. For multi-user service use, the author argues outside-the-sandbox is superior because credentials stay with the loop, sandboxs can be suspended when idle, sessions can resume after failures, and shared state can be centralized. They implemented durability with Inngest so each turn checkpoints, allowing recovery from deploys and crashes, and reduced sandbox cold-start impact with Blaxel’s fast resume. They replaced ephemeral in-container files for skills and memory with database-backed path virtualization under namespaces such as /skills and /memory, while the agent still uses read, write, and edit calls unchanged. This keeps the tool surface aligned with model training patterns, avoids forcing memory-specific tools, and improves prompt efficiency. Remaining problems include constant platform churn from harness evolution, uncertainty around path conventions, a bash side channel that can bypass virtualization, and last-writer-wins memory consistency across concurrent sessions. The post frames these as engineering tradeoffs the team accepted to avoid distributed-filesystem complexity in a shared organization context.

The page announces that Barman is now hosted starting with version 2.13 at a new location maintained by EnterpriseDB, replacing the legacy SourceForge repository. It describes Barman as an open-source Python tool for PostgreSQL disaster recovery, focused on remote backups across multiple servers in mission-critical environments. The project is positioned as part of operational readiness and recovery workflows, with a GPLv3 license and the usual warranty disclaimer. Distribution details list source files, tests, documentation, and auxiliary scripts, while links point to the project website, documentation, support channels, downloads, and historical pre-2.13 releases on SourceForge. The page also highlights that the project is community-facing through support and collaboration paths, with EnterpriseDB-provided professional support and explicit copyright and licensing context for reuse and modification. The release-style framing emphasizes continuity for existing users while making migration of repository hosting explicit.

California’s DMV is implementing new autonomous-vehicle rules that allow police to issue a notice of noncompliance directly to manufacturers when a driverless car commits moving violations, and the rules also require rapid response to law-enforcement or emergency calls and allow penalties for vehicles entering active emergency zones, with implementation set for July. The policy is presented as a public-safety step after incidents in California where Waymo vehicles were reported making illegal maneuvers and becoming obstacles, including a San Bruno U-turn and a citywide blackout in which stalled vehicles worsened congestion, while officials said existing enforcement was blocked by the absence of a human driver to receive tickets. Supporters of the move argue that firms should not escape accountability by pointing to a missing driver, especially as AV testing and deployment expand across Bay Area and Los Angeles markets. The new framework aligns liability with vehicle manufacturers rather than operators, a shift some commenters view as necessary and others as too weak. Critics in the thread said ticketing per incident may be insufficient unless repeated failures trigger permit-level consequences, because occasional fines can be treated as a low cost of business. Others emphasized legal edge cases, noting that AV behavior can conflict with informal road etiquette and social norms even when crash metrics appear strong. They also raised practical concerns, including how enforcement might handle design-level constraints, whether fines should scale with mileage or income, and how insurance and safety incentives may change if liability concentrates at the corporate level.

A creator presents a free, open-access course called Modern C++ Programming for people already familiar with C and object-oriented programming, aiming to move learners from foundational syntax to advanced C++ semantics. The course advertises frequent updates, short practical explanations, minimal examples, and a strong real-world engineering perspective, with 29 lectures and 2000+ slides spanning C++ basics, object-oriented design, templates, translation units, debugging, testing, ecosystem tooling, performance, software design, binary size, and build time. It includes detailed chapter-level coverage of language features, memory models, RAII, concurrency, and optimization workflows, plus practical sections on CMake, documentation, testing, profiling, and standard libraries. A separate roadmap promises migration from LaTeX to Typst, full open-source release, and easier contributions, while also directing users to reporting and contribution channels. The course lists a single-book and HTML chapter formats and is positioned as reusable as both curriculum and reference material. The material is released under CC BY 4.0 for content and MIT for examples/scripts, and its adoption claim includes use in the University of Verona’s undergraduate and graduate programs and training interns at NVIDIA. The creator invites institutions and practitioners to share adoption details and suggests ongoing openness to expansion and community input.

An NBC Bay Area report says a Sunnyvale passenger, Di Jin, was left behind with luggage in a Waymo ride to San Jose airport after the trunk failed to open and the car drove away. Jin said the trunk release did not respond to the button or app even though Waymo says it should auto-open when passengers exit. Support told him the vehicle was already returning to a San Francisco depot and could not be rerouted, and once the bag was recovered the company cited a policy that it is not liable for lost items. Waymo offered two options: pay for shipping or take two complimentary rides to fetch the luggage, a two-hour round trip from Sunnyvale that the rider said was not feasible while traveling. The story notes a similar San Francisco incident in April in which tennis equipment allegedly disappeared. Waymo began airport service in San Jose in September, and commenters and readers treated this as a practical reliability failure in an otherwise maturing autonomous ride system. Some interpreted the episode as evidence that edge-case behavior and user support can still create significant travel and trust consequences despite broader progress.

Roblox reported first-quarter results that beat earnings estimates but still announced an 18% share drop after stating that stricter child-safety controls are weighing on user growth and bookings. The company said mandatory age checks reduced cross-age communication, diluted interaction for verified users, and slowed new user acquisition, leading it to cut 2026 bookings guidance to $7.33 billion–$7.6 billion from a prior range of $8.28 billion–$8.55 billion. Baszucki defended the changes as a long-term foundation for a safer platform, better content targeting, and stronger community sentiment. The firm said roughly 73% of age-checked daily users are under 18, including 35% under 13, and added new account types and expanded parental controls after months of scrutiny. It also disclosed facing more than 140 U.S. federal lawsuits over child-protection failures and disclosed settlements totaling $23.2 million with two states. The company’s revenue rose to $1.73 billion, and the loss narrowed to 35 cents per share versus an estimated 41 cents, but management signaled that safety priorities are now constraining short-term topline momentum. Commentators largely accepted the need for child safety while warning that implementation has damaged core social gameplay and may undermine user retention if protections are not balanced with practical platform design.

Researchers report that conversational language models fine-tuned for instruction following and safety still appear to route refusal behavior through a one-dimensional subspace in residual activations across 13 open-source chat models up to 72B parameters. In their third revision, they show that removing this direction can suppress refusals even for harmful prompts, while injecting it can increase refusal on benign instructions, suggesting a compact mechanism for safety behavior. They also introduce a white-box jailbreak that targets this direction directly and claim it reduces refusal with limited collateral damage, then analyze adversarial suffixes as a way this direction’s signal is disrupted during generation. The work therefore argues that current safety fine-tuning may be brittle and that deeper mechanistic interpretation can make model behavior more directly controllable.

The post says a modern MacBook workflow is simpler because USB-C can carry video, power, and peripherals through one cable, and that is convenient, but the real frustration is not the cable itself. The author argues the core issue is ports: devices can expose different capabilities on the same mechanical connector, so users must understand what each host and cable actually supports. The article also highlights a shift from proprietary connectors toward USB-C’s one-shape ecosystem as a practical improvement, while acknowledging that edge cases still appear in fast or high-power scenarios.

The author’s Wahoo ELEMNT Bolt v3 lost phone sync and used that failure to decompile the Android APK, map an internal profile enum, and probe the bike’s BLE protocol. They found the app profile stored in protected SharedPreferences and learned that STD retail units can be shifted into DEV mode by writing APP_PROFILE (code 66) with value 3 using a three-byte BOLT_CFG packet, effectively enabling a hidden debug menu. A Python script using bleak handled discovery, connection, notification subscription, and write-without-response rules needed for the write to apply, after which the user reached new controls for config editing, GPS and Nordic chip management, map operations, UI testing, logging, and a crash test, plus an added warning message on entry. They also observed DEV mode enabling ADB access, a local web interface on port 8080, and additional BLE firmware debug streaming endpoints. The writeup emphasizes there is no application-layer authentication in this config path beyond BLE pairing, so an authenticated bonded device can alter any writable app-config value. The original sync issue ultimately traced to the phone, not the cycling computer, reinforcing that the deeper reverse-engineering effort was technically successful but not causative for the symptom.

Open Design presents itself as an open-source, self-hosted alternative to Anthropic’s Claude Design, which it positions as closed and locked to Anthropic’s model and hosted workflow. It implements the same artifact-first, multi-step prompting loop but runs through a local Next.js web app plus Node daemon that scans PATH for up to 12 supported coding-agent CLIs, uses the selected agent for file-backed generation, and stores project state in .od folders and SQLite. Users can select from 31 skills and 129 design systems (including imported brand protocols and checklists), choose one of five deterministic visual directions, and produce web, deck, and media artifacts through a live todo stream with sandboxed iframe previews, export to HTML/PDF/PPTX/ZIP/Markdown, and Vercel deployment. The stack includes sidecar IPC for optional Electron automation, BYOK proxy support for OpenAI-compatible providers with SSRF blocking, design import from Claude Design exports, and an artifact lint/critique path intended to enforce 5-dimensional quality checks before finishing. Its protocol is heavy on prompt contracts and composable file assets, with skill folders, DESIGN.md schemas, and per-skill seed side files controlling output style and behavior. The project is positioned as early but usable core infrastructure with explicit roadmap limits, including partial comment-mode patching and a missing dedicated AI-emitted tweaks panel. The commentary around it emphasizes both technical breadth and concerns about usability and long-term differentiation versus existing simpler workflows.

Uber says it wants to repurpose its human-drivers fleet into a large-scale sensor network for AV training and plans to grow AV Labs from a small internal fleet into a broader program that helps partners label, store, and query real-world data. CTO Praveen Neppalli Naga framed data scarcity as the main bottleneck and described an AV cloud plus shadow-mode playback so partners can test models against live trips without deploying full autonomous vehicles, while noting regulatory work on sensor and data-sharing rules must come first. The strategy is presented as a pivot after Uber stepped away from owning an AV stack, and as a way to support dozens of AV partners, including Wayve and others, while retaining control over ridehail-to-AV access. Commenters challenge the premise that more raw data is the key limit, arguing that major developers already solve this with synthetic scenarios and targeted collection, especially in cases where rare transient events dominate failures. They argue that if the economics are valuable, the “not making money” framing is strategic language, since Uber already invests in AV firms and can influence the ecosystem through exclusivity and leverage. Practical questions also loom: fitting paid drivers with costly sensors raises cost, deployment, compensation, privacy, and consent issues, and many commenters doubt driver payout has been meaningfully addressed.

The article traces how temporary-file handling on PC platforms became fragmented because CP/M had no environment variables, so early MS-DOS software inherited that habit and ignored new variables at first. When MS-DOS introduced environment variables and later piping, programs began using TEMP and TMP, but no single standard emerged. MS-DOS shell behavior favored TEMP for redirection workflows, while other tooling and later Windows APIs often favored TMP, and many programs checked one or both in different orders depending on author preference. As a result, a process that assumes one variable may write temp files to a different location than another process, so behavior depends on the specific program and platform conventions. Commenters generally confirm the compatibility-driven explanation, while also criticizing Microsoft-era inertia and noting similar ambiguity in other ecosystems such as Unix proxy-variable naming. Some discuss practical causes for TMP’s popularity, like the three-character DOS extension era, and remind readers that early historical details are debated. Others frame the issue as a recurring lesson in legacy compatibility: small defaults chosen decades ago still shape modern behavior, especially on Windows systems where temp-path confusion still appears in daily use.