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homebench benchmarks local LLMs (speed, memory, and quality) with a single-command TUI leaderboard. It auto-discovers models from Ollama, LM Studio, llama.cpp, vLLM, or OpenAI-compatible servers, runs a curated quality suite, and reports tok/s, TTFT, memory usage, and 31 tasks. Optional LLM-as-judge adds open-ended scoring. Install with pip install homebench and run homebench (use --all or --full for more). Features include hardware fit, provider selection, batch-throughput, custom task packs, and export options (JSON/Markdown). Local-first, zero-config, offline-friendly; results depend on machine state and are not a definitive ranking.
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A Rust tutorial page with hands-on code samples: defining a Person struct with impl and a Greet trait, demonstrating functional iterators, filters, and maps to parse and transform numbers, and an advanced example using an enum, generics, and a HashMap. The page also invites contributions and lists tools (GoHugo, Pagefind, e25DX) used to build the site.
Mathieu Ropert reviews Claude and similar LLMs in software work. They help with research, summarizing long texts, and searching internal knowledge bases by turning natural queries into parallel searches, but are limited by hallucinations and unreliable source selection. They’re not great at writing code; in Unity/C++, outputs can be over-engineered or incorrect due to training-data bias, and they’re expensive to run. In enterprises, LLM search can surface past discussions but must index sources and avoid self-reinforcing loops. Overall useful for discovery and learning, but verify value, cost, and sustainability; not a replacement for programmers.
HTTP 429 Too Many Requests: the user has sent too many requests in a given amount of time.
An automated house in Allendale, California, on August 4, 2026, carries on its routine for a family who no longer exists. Robotic cleaners, a weather box, and holographic nursery scenes fill the home as five wall silhouettes memorialize the missing family. A dog arrives and dies; a fire breaks out and the house’s pumps battle it, but the flames prevail. The destruction ends with the house collapsing and a lone voice repeating the date as the city lies in ashes.
Mini Retirements are shorter sabbaticals (1–3 months) taken after milestones to disconnect from work, rest, and gain fresh perspectives. Inspired by Austin Kleon and Paul Millerd’s Pathless Path, they should be regular, not rare, interruptions—daily/weekly/monthly pauses if needed. The piece contrasts mini-retirements with vacations and shares the author’s three-month sabbatical: saved a small salary, studied English in Cairns, and solo-traveled Australia’s east coast, fostering self-knowledge, resilience, and lasting friendships.
Everything I Know is a Buckminster Fuller Institute publication of 42 hours of Fuller’s January 1975 lectures, outlining his life work—from the Dymaxion house, car and map to geodesic domes, tensegrity, World Game and Synergetics. The printed work is a verbatim transcript, unedited, with Fuller’s wide-ranging discussions on design science, architecture, math, economics, and education. The Institute invites public annotation and edits via comments and submissions. Acknowledgments credit volunteers; the material is also available online at archive.org, and the project published in 1997.
picburn lets you upload a PNG/JPG/GIF/WebP up to 15 MB and share it via a private, non-indexed link. No accounts or tracking. Files self-destruct after a chosen timer (5 minutes, 1 hour, 1 day, 1 week, or no timer) or after a view limit (unlimited, 1, 3, 10, 50). If set to 1 view, it burns after the first open. Preview is for you and doesn’t count. The image is stored briefly on a small server and deleted when limits hit; links are random IDs and not indexed.
DeepSeek-V4-Flash on a single AMD MI300X: a production config to run 304B DeepSeek-V4-Flash-0731 with Docker Compose, pinned ROCm vLLM, and MI300X-specific patches (FP8, AITER, MoE, DSpark). Includes patches, diffs, tuning tables, and a 20 GB GPU KV + 96 GiB CPU offload; fits in 192 GB HBM with 5.3 TB/s bandwidth. Scheduler: 2,048-token budget, 1,024-token long-prefill cap. Performance: ~168.6 tok/s single-stream decode; prefill ~7.9–8.5K tok/s; up to 64 streams ~830 tok/s aggregate.
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Italian tech firm Bending Spoons agreed to acquire Airtable in an all-cash deal valued at about $1.285 billion, marking its first post-IPO acquisition since a Nasdaq debut last month. Airtable offers a spreadsheet-database platform for building apps and workflows. Bending Spoons has pursued rapid acquisitions, including AOL and Eventbrite, this year. Airtable’s net cash implies an equity value around $2.25 billion. The deal is expected to close by year-end, subject to regulatory approvals. Bending Spoons’ stock closed above its IPO price.
Could not summarize article.
FFmpeg 9.0 "Lei" released, about four months after FFmpeg 8.1. A complete changelog is at the project root, with the full Git history at https://git.ffmpeg.org/gitweb/ffmpeg.git. For questions, join the #ffmpeg IRC channel on irc.libera.chat or ask on the mailing lists.
Intel reportedly granted RosaicLabs access to Atom RTL, enabling a potential x86 core paired with a large matrix engine, a notable departure for Intel. Separately, an unnamed entity describes 16- and 32-tile AMX implementations beyond Intel’s eight, hinting at a matrix-acceleration x86 design. Rosaic’s May 2026 incorporation and timing raise timeline/ownership questions; other candidates include Zhaoxin, Hygon, hyperscalers, or an Intel-backed spinout. Overall, the stories suggest a more open x86 ecosystem with external work around Intel’s IP.
Explores harness engineering as the driver of recursive self-improvement (RSI) in AI, arguing the deployment layer — the system around a base model for planning, tools, memory, evaluation, and context — is key to RSI, more than raw weights. It surveys design patterns (workflow automation, persistent memory, sub-agents) and a coding-agent case study. It covers Meta Context Engineering (ACE, MCE), Meta-Harness, and evolutionary search (Promptbreeder, AlphaEvolve, ThetaEvolve, DemoEvolve), Self-Harness, STOP, AFlow, ADAS, SIA. Near-term progress comes from optimizing harnesses, with human oversight and challenges in memory, reward hacking, and evaluation.
Ugliness is not the main driver of opposition to new development. NIMBYs resist for local concerns, while conservationism grew from a perceived ugliness in postwar modernist buildings, not from destruction alone. Heritage protections shield prewar stock and city centers, restricting dense redevelopment and shaping urban forms. Densification often occurs where conservation is weaker, but housing shortages persist partly because historic-area restrictions curb new construction. The author argues that breaking the “curse” of ugliness depends on showing that change can be attractive, not disfiguring, to unlock cities.
CollectWise, YC-backed, is hiring an AI Agent Engineer in NYC to build voice AI infrastructure and prompting systems for autonomous debt-collection agents. You’ll design real-time architectures (LiveKit), end-to-end prompting, testing and KPI-driven optimization, and migrate clients from legacy to new systems. Requirements: 2+ years in voice/conversational AI; 3+ years backend/infrastructure; proficient with Node.js, AWS, and SQL; experience with live/telephony workflows a plus. Compensation: $200k–$300k plus 0.25–1% equity. Founders: Sean O’Brien.
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