HackerNews Digest

A recent study demonstrates that increased adoption of electric vehicles (EVs) correlates with measurable reductions in ambient air pollution levels. Using real‑world emissions data, researchers quantified decreases in pollutants such as nitrogen oxides (NOx) and particulate matter (PM2.5) in regions with higher EV penetration, attributing these improvements to the displacement of internal‑combustion‑engine traffic. The analysis controls for confounding factors like weather and industrial activity, reinforcing the causal link between EV usage and cleaner air. Accompanying visual elements on the source page include unrelated photographs: a teacher with an inattentive student, a pregnant woman with water, generic traffic‑related pollution imagery, tobacco‑product packaging, and a family beside an EV charging station at sunset. These images serve illustrative purposes but do not add technical data to the study’s findings.

BirdyChat is positioned as Europe’s first chat application that interoperates directly with WhatsApp. The service allows users to initiate one‑to‑one conversations with WhatsApp contacts by entering the recipient’s phone number. Communication supports text messages, photos, and file attachments, all transmitted over an encrypted connection to ensure security. BirdyChat permits users to register with a work‑related email address rather than a personal mobile number, enabling a clear distinction between professional and private communications while maintaining continuous availability. The platform’s core features focus on cross‑platform messaging, end‑to‑end encryption, and identity management via corporate email credentials.

Eclypsium used an industrial X‑ray system to compare a suspect FTDI USB‑to‑UART cable with a verified authentic cable purchased from DigiKey. The suspect cable exhibited functional failures at higher transfer speeds, prompting analysis. X‑ray inspection revealed several construction differences: the authentic cable showed copper ground pours, ground stapling, decoupling components placed close to the FTDI IC, additional isolation passives on the USB data lines, a thermal pad under the IC, engineered strain‑relief, more solder on the USB‑A connector tabs, a smaller silicon process, and better passive alignment. The questionable cable lacked these features. The study highlights that visual and X‑ray cues can indicate counterfeit hardware, but detection is non‑trivial. Eclypsium stresses that counterfeit components pose broader supply‑chain risks, especially when they involve network gear or servers that may contain hidden backdoors, and urges organizations to prioritize hardware‑level supply‑chain security.

Albedo’s first satellite, Clarity‑1, launched 14 Mar 2025 on SpaceX Transporter‑13 to demonstrate sustainable very‑low‑Earth‑orbit (VLEO) operations. The mission validated the in‑house Precision bus (TRL‑9) and achieved 98 % of the technology required for 10 cm visible and 2 m thermal‑IR imaging. Key results: drag coefficient 12 % better than target, supporting a projected five‑year lifetime at 275 km; atomic‑oxygen‑resistant solar arrays maintained constant power despite increased AO fluence; controlled 100 km altitude descent with sub‑meter thrust‑planning accuracy; radiation tolerance 4× lower single‑event upsets than expected. The bus performed all subsystems, including CMG‑based attitude control, thermal management, and cloud‑native ground operations with automated contact planning, thrust planning, and 14 on‑orbit software updates (including an FPGA flash). Imaging demonstrated end‑to‑end processing within seconds, line‑scan strips 20‑30 km long, jitter 11× lower than goal, and successful infrared detection with a low‑cost microbolometer. CMG bearing failures limited sustained high‑resolution imaging; the satellite lost TT&C contact after nine months, likely due to memory corruption. VLEO performance data, AO mitigation, and bus design are confirmed, guiding design fixes (lower CMG temperatures, stiffer mirror structure, increased heater capacity) for the next VLEO mission.

The author submitted a two‑design ASIC to a GlobalFoundries 180 nm experimental Tiny Tapeout shuttle, receiving free tape‑out. The chip contains (1) a custom JTAG TAP for silicon debug and (2) a 2 × 2 systolic array that multiplies 8‑bit signed integer matrices. The project was completed in ten days using the Open‑ROAD/Librelane flow, with stages of architecture, RTL design, Cocotb‑based simulation, FPGA emulation, firmware bring‑up, and ASIC implementation. Constraints include eight input, eight output, and eight configurable pins, an assumed 50 MHz I/O clock, and no SRAM macro (the shuttle’s macro power‑gating was unavailable). Each compute unit implements a Booth‑radix‑4 multiplier with a Wallace‑tree adder, followed by a clamping step to retain 8‑bit results; weights are stored locally in each unit and loaded over four cycles. An array controller reshapes input streams and buffers output to meet I/O limits. Validation employed randomized test vectors across icarus‑verilog and CVC‑timed netlists. The design demonstrates how Tiny Tapeout’s automated flow enables rapid, low‑cost ASIC prototypes despite tight timelines.

- **Hardware evolution**: Pi 1 (2012) used a 700 MHz ARM1176 core, 512 MB DDR RAM, 100 Mb Ethernet, micro‑USB power (0.7 A). Pi 2 (2015) introduced a quad‑core 900 MHz Cortex‑A7 SOC, 1 GB RAM, two extra USB 2.0 ports, micro‑SD, and 0.8 A power. Pi 3 (2016) upgraded to 64‑bit Cortex‑A53 cores at 1.2 GHz, added Wi‑Fi (2.4 GHz) and Bluetooth 4.1; the 3B+ later raised clock to 1.4 GHz, added Gigabit Ethernet over USB 2.0, dual‑band Wi‑Fi, and 1.34 A power. Pi 4 (2019) employed a BCM2711 with four Cortex‑A72 cores at 1.5 GHz, VideoCore VI GPU, LPDDR4 (1‑8 GB), USB‑C power (1.25 A), two USB 3.0 ports, dual micro‑HDMI, and true Gigabit Ethernet. Pi 5 (2023) uses a BCM2712 with four Cortex‑A76 cores at 2.4 GHz, VideoCore VII GPU (800 MHz), PCIe (NVMe support), 2‑8 GB LPDDR4X, USB‑C power up to 5 A, and a dedicated fan header. - **Performance tests**: 1080 p YouTube playback is impossible on Pi 1, choppy on Pi 2‑3, acceptable on Pi 4, smooth on Pi 5. Sysbench single‑core scores rise from 68 (Pi 1) to >40 000 (Pi 5), yielding ≈600× speedup over Pi 1; multicore scaling shows similar gains. GLMark2 GPU scores improve from sub‑100 (Pi 1‑3) to >250 (Pi 4) and >600 (Pi 5). Storage bandwidth climbs with bus speed (25 MHz → 100 MHz). iPerf shows Pi 1 below 100 Mbps, Pi 2 meets it, Pi 3 B+ near theoretical USB 2.0 limits, Pi 4‑5 reach Gigabit. Power draw at idle varies <2 W; under load Pi 5 consumes ~3× Pi 1 but delivers ~200× performance per watt.

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L10N::CY is the Welsh localization module for the Raku programming language. The distribution installs a `draig` executable that automatically activates the Welsh locale, and it can also be enabled in specific scripts with a `use L10N::CY` statement. Example usage shown in the synopsis: ``` draig -e 'dywedyd "Helo Byd"' ``` outputs “Helo Byd”. The module requires the environment variable `RAKUDO_RAKUAST=1` to be set. It contains the logic needed to provide Welsh language support throughout Raku. The documentation references “Creating a new programming language – Draig”. Author is Richard Hainsworth ([email protected]). Copyright © 2024‑2025 Raku Localization Team; the library is released under the Artistic License 2.0. Images listed are generic “Actions Status” placeholders.

Software engineering estimation is fundamentally unreliable because most work involves unknown problems that dominate effort. Small, well‑defined tasks (e.g., a simple deployment) can be timed accurately, but large‑scale changes require research, system exploration, and architectural decisions that cannot be quantified beforehand. Estimates are therefore not generated by engineers to aid execution; they serve as political tools for managers, VPs, and executives to allocate resources, set expectations, and decide which projects proceed. In practice, managers often arrive with a desired timeline and force teams to fit a solution within that constraint, reversing the usual “estimate‑then‑plan” flow. Effective estimation, according to the author, involves gathering political context, assessing risk, and presenting multiple feasible approaches—each tied to the given time frame—rather than a single fixed duration. When a project is genuinely impossible, a team can signal this, but only if prior trust exists. The post emphasizes that estimation should focus on unknowns, provide ranges with associated risks, and be used as a negotiation aid, not a precise forecast.

Professor Kim Jung‑ho of KAIST projected that the high‑bandwidth flash (HBF) market could surpass high‑bandwidth memory (HBM) by 2038, with Samsung and SanDisk aiming to integrate HBF into Nvidia, AMD, and Google products by late 2027‑early 2028. He described a three‑tier memory hierarchy: HBM as a fast GPU cache, a 512 GB HBF layer delivering 1.638 TB/s, and higher‑capacity networked SSD storage accessed via BlueField‑4. A 512 GB HBF chip would require stacking two 2‑Tb (250 GB) 3D NAND dies, totaling 642 NAND layers across six strings, fabricated with through‑silicon vias (TSVs) or plugs that pass through lower stacks, increasing die area. SK Hynix is developing AIN‑BNAND HBF products, showing a base/logic die on an interposer with NAND core layers above; SanDisk presents similar TSV‑based stacks. Prototypes are expected from SK Hynix (later this month) and Kioxia (5 TB PCIe Gen 6 x8 module). Samsung has joined a consortium with MOUs; Micron, Nvidia, and AMD have not yet announced HBF plans.