Cowork: Claude Code for the rest of your work
Summary
Claude’s new “Cowork” feature, available as a research preview for Claude Max subscribers on macOS, lets users grant the AI access to a chosen local folder. Within that folder Claude can read, edit, create, rename, and organize files, executing tasks such as sorting downloads, generating spreadsheets from screenshots, or drafting reports from notes. Unlike a standard chat, Cowork provides the model with agency: it plans, progresses, and updates the user while handling multiple queued tasks in parallel. Users control which folders and external connectors Claude can use, and Claude asks before performing significant actions. The system includes safeguards against destructive commands and prompt‑injection attacks, though safety remains an active research area. Future updates aim to add cross‑device sync, Windows support, and enhanced safety measures. Non‑Max users can join a waitlist for access.
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Community Discussion
Comments express a mix of cautious optimism and significant concern. Users appreciate the productivity gains and flexibility of Claude Code and the new Cowork interface for automating file management, data summarization, and personal tasks, especially when integrated with existing workflows. However, many stress security risks, noting the lack of sandboxing, version‑control snapshots, and reliance on non‑technical users to detect prompt‑injection attacks, which could lead to data loss or privacy breaches. Technical glitches, extension failures, and limited UI capabilities also generate frustration. Overall, there is interest in the concept but a strong demand for stronger safety mechanisms and more reliable implementations.
TimeCapsuleLLM: LLM trained only on data from 1800-1875
Summary
The repository “haykgrigo3/TimeCapsuleLLM” presents a language model trained exclusively on data from selected historical periods, aiming to mitigate contemporary biases present in modern corpora. The project’s visual assets illustrate sample outputs, examples of bias (pronoun, geographic, and temporal) identified in standard models, and a historical reference (“1834 protest”). The images also reference the author’s handle (@haykgrigo3) and a related account (@openaitx-system). The repository’s main description emphasizes the model’s temporal constraints as a method for reducing modern bias in language generation. No additional textual documentation or code details are provided in the extracted content.
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Community Discussion
The discussion shows broad enthusiasm for preserving and training LLMs on historically bounded corpora, viewing such models as useful for research, bias analysis, and speculative tests of scientific discovery. Contributors repeatedly request open datasets, reproducible training pipelines, and accessible demos, while noting the scarcity and skew of pre‑modern text and questioning whether limited data can yield coherent output. Opinions diverge between optimism that early‑era models could reveal insights or test AGI hypotheses and skepticism about their accuracy, bias, and practical utility.
The Cray-1 Computer System (1977) [pdf]
Community Discussion
The discussion recounts the complex effort required to install a second‑hand Cray‑1 at a university, describing structural modifications, a custom voltage regeneration system, and cooling challenges with flourinert, alongside anecdotal details such as a plastic lobster mascot and quirky terminal hardware. It reflects a nostalgic tone about the machine’s performance, its role in large‑scale computations, and later repurposing, while also noting similar, more routine installations for governmental modeling projects.
Postal Arbitrage
Community Discussion
Comments focus on exploiting Amazon’s free‑shipping loophole as a cheap‑shipping hack, noting similar arbitrage tactics on other platforms and in different countries. Many point out that the practice relies on subsidised pricing, may be short‑lived, and can be undermined by platform or postal‑service changes. Critics highlight hidden costs such as Prime fees, environmental impacts, and potential encouragement of Amazon’s market dominance, while others treat the idea humorously or suggest alternative low‑cost mailing methods. Overall sentiment is skeptical about scalability and sustainability despite occasional enthusiasm for the trick.
The chess bot on Delta Air Lines will destroy you (2024) [video]
Summary
The excerpt is a footer navigation list from YouTube’s website, presenting the primary informational and functional categories available to users and partners. It includes links to corporate and media information (About, Press, Copyright), user support (Contact us, How YouTube works), creator resources (Creators), advertising services (Advertise), developer tools (Developers), and legal documentation (Terms, Privacy, Policy & Safety). Additional items reference product testing (Test new features) and a specific subscription offering (NFL Sunday Ticket). The footer concludes with a copyright notice indicating the page’s currency: © 2026 Google LLC. These sections collectively provide access to corporate details, policy compliance, developer and creator guidance, advertising opportunities, and feature‑preview channels typical of a large‑scale online platform.
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Community Discussion
Comments convey mixed feelings about Delta’s in‑flight chess bot. Many recall it fondly but note it has been removed, prompting disappointment. Users describe the engine as generally weak—players rated around 1600‑2100 can beat it consistently—though some recall occasional strong play and occasional bugs that cause illegal moves or crashes. Comparisons to other airlines’ bots highlight similar quality issues, and several remarks call for fixes to difficulty labeling and overall improvement of the in‑flight chess experience.
Some ecologists fear their field is losing touch with nature
Summary
The article documents a rapid shift in ecology toward AI‑driven, indoor research. Researchers such as Tadeo Ramirez‑Parada use machine‑learning on digitized herbarium captions to map flowering‑time shifts, while projects like CamAlien, automated insect camera traps, and the TABMON acoustic network deploy AI to identify species, track invasives, and generate continent‑wide biodiversity indicators. Over one billion museum specimens have been digitized, and citizen‑science platforms (iNaturalist, GBIF) now supply hundreds of millions of observations. Concurrently, a decline in field‑based studies is reported: a 20 % drop in field papers (1980‑2014) versus 600–800 % rises in modelling and data‑analysis work. Critics warn of an “extinction of experience,” reduced community engagement, and “AI colonialism” when data from low‑income regions are processed elsewhere. Drivers include perceived funding cuts for fieldwork, urban research bases, childcare constraints, carbon‑footprint concerns, and publication incentives favoring data mining over specimen collection. Some ecologists balance both approaches, using sensors to extend field presence while maintaining on‑site work.
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Community Discussion
Comments emphasize that field work remains essential despite its logistical hardships, high costs, and funding challenges, arguing that direct data collection and verification cannot be fully replaced by remote sensing or AI modeling. While many acknowledge the efficiency and scalability of desk‑based analysis and advanced computational tools, they stress the need for integration of rigorous field observations with modern data assimilation. The overall view supports a balanced approach, maintaining support for both traditional field efforts and emerging analytical methods.
Fabrice Bellard's TS Zip (2024)
Summary
ts_zip is a text‑only compression tool that leverages the RWKV‑169M‑v4 language model (8‑bit quantized, evaluated in BF16). It predicts next‑token probabilities, which an arithmetic coder uses to encode the text. Key characteristics:
- Requires a GPU (≥4 GB RAM) for acceptable speed; on an RTX 4090 it reaches up to 1 MiB/s for both compression and decompression, slower than traditional compressors.
- Compression ratio is reported in bits per byte (bpb); benchmark results on enwik8/enwik9 are referenced in the Large Text Compression Benchmark.
- Only effective on textual data; binary files gain little compression. The model, trained mainly on English, also handles other languages and source code.
- Deterministic and reproducible encoding ensures that compressed files can be decompressed on different hardware or software configurations.
- The project is experimental; backward compatibility across versions is not guaranteed. A related tool, ts_sms, targets small‑message compression.
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Community Discussion
The comments highlight NNCP’s recent leadership in the Large Text Compression Benchmark, noting its small archive size and strong performance on enwik8 while trailing on enwik9. Users express surprise at PPMd’s effectiveness and discuss connections between compression, prediction, and intelligence, including potential LLM‑based approaches and steganographic uses. There is also concern that benchmark rules should count model and code size, preventing trivial “compressed” files. Overall sentiment is appreciative of the technical advances, curious about future methods, and mildly critical of evaluation criteria.
Floppy disks turn out to be the greatest TV remote for kids
Summary
The author built a tangible TV remote for a 3‑year‑old using floppy‑disk hardware to trigger Chromecast playback. A floppy drive is powered by 18650 Li‑ion cells through an XL6009 boost converter; a 1000 µF capacitor stabilizes the ATmega’s supply during the multi‑amp spin‑up surge. Disk insertion is sensed via a custom rolling switch, since standard “disk‑change” pins are unused. An AVR‑based Arduino (ATmega) reads an “autoexec.sh” file from the disk’s FAT filesystem using the Arduino FDC library, then forwards the data via serial to an ESP8266 that handles WiFi communication. Both controllers employ sleep modes: the ATmega wakes on disk insertion, resets the ESP, sends “diskin”/“diskout” messages, reads the file, and powers down the drive; the ESP transmits the command to a netcat‑controlled server which issues Chromecast play/pause actions. The enclosure is laser‑cut MDF, and disks are labeled for selection. The system proved usable by the child, with head‑damage mitigated by moving the read head to an empty track after reading.
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Community Discussion
Comments show strong enthusiasm for tangible, physical interfaces such as floppy‑disk‑style cards, NFC/RFID tags, and DIY Raspberry Pi setups as ways to simplify media selection for young children and provide parental limits. Many cite existing products like Yoto and share similar hobbyist projects, highlighting the tactile appeal and educational value. At the same time, several participants question the practicality for toddlers, argue that screen exposure at that age is undesirable, and note that complex solutions may be unnecessary compared to simpler parental controls. Overall, the idea is viewed as creative but its usefulness is debated.
Unauthenticated remote code execution in OpenCode
Community Discussion
Comments converge on strong criticism of the tool’s unauthenticated local HTTP server, describing it as a serious security flaw that permits arbitrary code execution and lacks clear activation signals. Users lament slow or absent maintainer responses, inadequate vulnerability handling, and the absence of bug‑bounty or audit processes. Many recommend sandboxing, containerization, or network‑boundary protections to mitigate risk, while a minority argue the issue is mitigated by modern browsers and user responsibility. Overall sentiment reflects distrust in the project’s security priorities, governance, and recent data‑leak incidents.
Date is out, Temporal is in
Summary
The article critiques JavaScript’s built‑in Date object for its inconsistent parsing, lack of time‑zone handling beyond local/GMT, reliance on the Gregorian calendar, and mutable nature despite representing immutable real‑world dates. It explains that primitives in JavaScript are immutable and passed by value, whereas objects—including Date instances—are mutable and passed by reference, leading to unintended side effects when a Date is modified (e.g., adding a day alters the original object). To address these shortcomings, the proposal Temporal is introduced as a namespace object (similar to Math) offering immutable, well‑typed temporal representations such as PlainDate and Instant. Temporal’s methods (e.g., add, subtract, since) return new objects rather than mutating the original, provide clear time‑zone support, and include utilities like plainDateISO for date‑only values. The draft is at stage 3 of standardization and already available in recent Chrome and Firefox builds, inviting developers to experiment before final adoption. The article demonstrates replacing a verbose Date‑based “today/tomorrow” example with concise Temporal code.
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Community Discussion
Comments express widespread frustration with JavaScript’s Date API, highlighting its parsing inconsistencies, mutable design, lack of leap‑second handling, and confusing timezone behavior, while also noting factual errors in the article. Many acknowledge the Temporal proposal as a cleaner, immutable alternative but point out its limited browser support and slow adoption, especially in Safari. Comparisons to Ruby on Rails and other language libraries appear, with users appreciating the article’s overview yet criticizing its exaggerated tone and occasional inaccuracies. Overall, there is demand for more robust, standards‑compliant date‑time tooling.