1. Apple M5 chip Total comment counts : 88 Summary Apple unveils M5, the AI-focused 3nm Apple silicon with a 10-core GPU, each core housing a Neural Accelerator, delivering over 4x peak GPU compute vs M4 and up to 6x AI vs M1. It features a faster 16-core Neural Engine, a new 10-core CPU (up to six efficiency and four performance cores), and 153 GB/s unified memory bandwidth (nearly 30% higher)....
1. Why your boss isn’t worried about AI – “can’t you just turn it off?” Total comment counts : 15 Summary Public misreads AI bugs as typical software bugs that experts can fix with debugging. In modern AI, most issues come from training data, not code, and datasets are enormous (e.g., FineWeb ~11.25 trillion words) so no one reads all training material. When AIs err, tracing the exact data cause is usually impossible; fixes involve retraining or data curation....
1. NanoChat – The best ChatGPT that $100 can buy Total comment counts : 28 Summary NanoChat is a full-stack, minimal LLM project designed to resemble ChatGPT in a single, hackable codebase. It runs on one 8XH100 GPU and uses speedrun.sh to complete the full pipeline—from tokenization and pretraining to finetuning, evaluation, inference, and a web UI. A typical run takes about 4 hours; after that you can chat with the LLM via a ChatGPT-like UI....
1. Wireguard FPGA Total comment counts : 12 Summary An open-source project to implement WireGuard VPN in hardware on an affordable Artix-7 FPGA using open tools. It emphasizes transparency and backdoor scrutiny of RTL, embedded, build, and delivery. Phase 1 is a proof-of-concept to establish HW/SW partitioning, a basic WireGuard datapath for a few channels, and groundwork for Phase 2 to scale channels, add GUI, and improve usability. Realistic limits include Artix-7 I/O up to ~600MHz and core ~100MHz; the project is WIP with no deployment guarantees....
1. Rating 26 years of Java changes Total comment counts : 11 Summary An IBM veteran reflects on 26 years of Java SE evolution, selectively rating notable language and core-library changes (UI/graphics and VM/GC excluded). Highlights include: Collections Framework (4/10), assert (3/10), regular expressions (9/10), NIO (0/10; clunky APIs), crypto APIs (1/10), Generics (8/10), Annotations (5/10), Autoboxing (7/10), Enums (6/10). Vararg methods are mentioned but the excerpt ends mid-sentence. Overall, Java has dramatically evolved since early 1....
1. A small number of samples can poison LLMs of any size Total comment counts : 48 Summary New research from Anthropic, the UK AI Security Institute, and The Alan Turing Institute shows that poisoning a pretrained LLM with only 250 malicious documents can implant a backdoor that makes the model output random gibberish when it encounters a trigger, across models from 600M to 13B parameters. This challenges the idea that backdoors require a percentage of training data; the amount needed can be constant....
1. Svelte is that fast Total comment counts : 19 Summary An academic study comparing Angular, React, Vue, Svelte, and Blazor investigates how rendering strategies affect performance. It notes many benchmarks are flawed and uses an MVVM-like component model. React, Vue, and Blazor rely on a virtual DOM with diffing (often cited as O(n) in practice but can be O(n^3) worst case), while Angular and Svelte update the DOM directly without a diff step....
1. Gemini 2.5 Computer Use model Total comment counts : 9 Summary Google released the Gemini 2.5 Computer Use model via the Gemini API, a specialized version built on Gemini 2.5 Pro’s visual understanding to power agents that interact with user interfaces. It outperforms other web and mobile control models with lower latency. Available in Google AI Studio and Vertex AI, developers can build UI agents and share feedback in the Developer Forum....
1. OpenZL: An open source format-aware compression framework Total comment counts : 8 Summary OpenZL is a public release of a lossless data compression framework for structured data. It combines a sequence of reversible transforms with an offline trainer that builds a data-shape–specific Plan, improving compression by exposing structure rather than just bytes. Users provide the data shape (via presets, SDDL, or a custom parser); the trainer produces a Plan that encodes into the frame....
1. Fire destroys S. Korean government’s cloud storage system, no backups available Total comment counts : 24 Summary A fire at the National Information Resources Service (NIRS) data center in Daejeon damaged equipment, prompting a major disruption to online government services. Officials report slow but partial recovery: over 55% of top-priority systems back online, but only 17.3% of online services restored, with restoration hampered by the shutdown of the national database command center....