HackerNews Digest

None

Paraloid B‑72 is a thermoplastic acrylic resin (ethyl methacrylate–methyl acrylate copolymer) originally developed by Rohm and Haas for surface coatings and flexographic ink vehicles. It is widely used by conservators as an adhesive and consolidant for ceramics, glass, fossils, piano hammers, and museum labeling. The resin is durable, non‑yellowing, and offers higher strength and hardness than polyvinyl acetate while retaining flexibility, reducing brittleness under stress. It dissolves in acetone, ethanol, toluene, xylenes, and mixed solvents; acetone is the preferred solvent, but blends adjust working time and final hardness/flexibility. Unlike cellulose nitrate, B‑72 requires no plasticizers for durability; fumed colloidal silica can be added to improve workability and stress distribution during drying and curing. Recent applications include cast B‑72 sheets as transparent fill material in glass conservation.

Humpback whales are increasingly aggregating into large “super‑groups,” a phenomenon likened to a rapid population surge after a prolonged low‑activity period. Photographers Monique and Chris Fallows spent a pre‑dawn night on a small boat, drifting and listening for breach sounds to locate these gatherings and capture identification photographs for Happywhale, a global citizen‑science photo‑ID project. Their strategy involved intermittent engine shutdowns to reduce disturbance and using the acoustic cues of whale blows, which can be heard from miles away. The Fallows documented over 40‑ton whales breaching, described the visual effect as a “Manhattan skyline of blows,” and set a record for the most individual whales photographed in a single day. Commentary from marine biologist Ted Cheeseman emphasizes that the observed whales represent a rebounding population. The remainder of the text lists numerous unrelated image alt texts, which are not pertinent to the whale observations.

The author examined a RODECaster Duo audio interface and discovered that its firmware can be captured and updated without signature verification. Using macOS Instruments, they located a gzipped tarball containing the device’s binaries and a shell script for updates; the device employs two boot partitions for redundancy. SSH is enabled by default, restricted to public‑key authentication, with two RSA and two Ed25519 keys pre‑installed. By connecting via Ethernet, the author accessed a root shell (kernel 5.10.17‑rt32‑yocto‑preempt‑rt‑rode, aarch64). Firmware updates are triggered over HID: sending ASCII ‘M’ puts the device in update mode, then a tar.gz archive and its MD5 checksum are copied to the exposed disk, followed by ‘U’ to flash and reboot. The lack of signature checks allowed the author to build a custom firmware image that enables password authentication and adds their own key, then flash it using the same HID sequence. They reported the issue to RODE but received no response.

None

The author contrasts two project habits: (1) quickly implementing an idea with clear success criteria, and (2) spending extensive time researching prior art, expanding scope, and delaying execution. A recent woodworking project illustrates the first approach—defined goals, rapid iteration, and completion in a weekend. Conversely, attempts to improve structural/semantic diffing for Emacs led to four hours of tool survey and indecision. The surveyed tools include semanticdiff.com (VS Code plugin, no library), diffsitter (treesitter‑based, MCP server), Gumtree (Java, unsuitable), mergiraf (Rust, treesitter merge driver using Dijkstra mapping), weave (Rust, treesitter driver with extensive heuristics), diffast (tree‑edit‑distance algorithm), and autochrome (Clojure diff). The author’s use case is reviewing LLM‑generated code changes entity‑wise within Emacs. Planned solution: a minimal Rust treesitter entity extractor, greedy matching, command‑line diff output, later integrated into a Magit‑style Emacs UI, with incremental language support and possible advanced matching. The goal is a functional, private tool rather than a public, feature‑heavy project.

The article argues that generative AI, exemplified by large language models such as ChatGPT, cannot replace true education because it conflates linguistic fluency with genuine learning. While AI can summarize texts, draft essays, translate, and generate code—functions useful for instructors, researchers, and administrators—it does not foster the intellectual formation central to Catholic education: judgment, responsibility, and the capacity to engage with uncertainty. Citing John Milton’s 1644 critique of teaching finished performances before minds mature, the author warns that AI industrializes this mistake by providing polished language without the necessary reading, questioning, revision, and personal ownership of ideas. The solution proposed is pedagogical redesign: more in‑class writing, oral defenses, seminars driven by live questions, and transparent disclosure of AI assistance. The teacher’s role is emphasized as a guide to inquiry rather than a content dispenser. Ultimately, education should aim at forming persons capable of truth, judgment, and intellectual honesty, goals that machines cannot achieve.

American diners, once widespread, remain cultural landmarks and are documented in Library of Congress photographs. Many were prefabricated to resemble train cars, allowing shipment as rail cars; examples include a corrugated‑metal diner in Columbus, Georgia, and the silvery‑sided Country Girl Diner in Vermont. Historical menu pricing is shown in a 1940 Maryland photo (hot dogs 5¢, “platter” 25¢) and a 1959 New York City diner (ham ’n’ eggs 75¢ with sides). Customer demographics featured truck drivers, with 24‑hour service to accommodate long‑hour workers, as illustrated by a Maryland diner counter scene. Recent images (last decade) reveal modern diners retaining mid‑century design cues: a Tennessee diner with a period Ford Fairlane, and Phoenix’s 5 & Diner displaying checkerboard flooring, red accents, and classic vanilla ice‑cream sodas. Collectively, the photos demonstrate the evolution, pricing, architecture, and enduring aesthetic of American diners.

The excerpt consists solely of bibliographic metadata for a paper titled “There Will Be a Scientific Theory of Deep Learning” (arXiv identifier 2604.21691). It lists a series of image placeholders with alt‑text labels: “Cornell University,” “arxiv logo,” “arXiv logo,” “Cornell University Logo,” “license icon,” “BibSonomy,” and “Reddit.” No abstract, introduction, methodology, results, or discussion sections are provided, and there is no substantive textual content describing the paper’s arguments, experiments, or conclusions. Consequently, the only discernible information is the paper’s title, its arXiv reference, and associated institutional and licensing graphics. No technical details or scientific insights can be extracted from the given material.

The piece promotes “working with the garage door up,” a practice of publicly sharing unfinished work and process rather than only finished announcements. It contrasts this with typical social‑media self‑promotion, arguing that continual, transparent updates (e.g., livestreams, podcasts, digital gardening) foster deeper audience engagement, create a perception of competence, and can grant access to exclusive professional circles. Maggie Appleton is cited, noting that public learning leads others to assume higher skill levels and opens networking opportunities. The author links the idea to Robin Sloan’s essay on physical businesses, which uses open workshop doors as a metaphor for visible, ongoing labor that enlivens public space. The lack of such visible “open‑door” signals online contributes to a bias toward constant speakers, making quieter creators disappear. By maintaining an open, process‑focused presence, creators can counter selection bias, build a more authentic following, and encourage serendipitous collaboration.