A publication by Berry Mingus
Groundy is Berry Mingus's publication about AI and large language models, developer tools, infrastructure, and software culture.
This article compares Mermaid, draw.io, and Reladraw for agent-generated diagrams, noting Reladraw's relative placement is promising but carries v0.8.0 syntax risk.
Popular with Groundy readers.
MLX and llama.cpp both run quantized LLMs on Apple Silicon unified memory. Here is what each project documents, and how to measure which wins on your Mac.
Compare DeepSeek, Qwen, Kimi, Doubao, ERNIE and GLM through dated benchmarks, license terms, context windows, API pricing and practical workload fit.
DataLearner's June 2026 snapshot ranks GLM-5.2 seventh by HLE at 54.70 and places no Chinese flagship in the overall top three, undercutting launch-day claims.
F-Droid, the open-source Android app repository, is leading a global campaign against Google's mandatory developer verification program, a policy set to take effect in September 2026 that critics say will end alternative app distribution and hand Google total control over what software can run on Android devices.
The EU's 2027 battery mandate is confirmed. Here's what 'user-replaceable' legally means, which phones comply now, and how to buy smart before the rules change.
WiFi routers can perform full-body pose estimation through walls using Channel State Information, turning everyday network infrastructure into a covert tracking system.
Guides, comparisons and analysis, organized by topic.
The serving stack, network fabric, and cloud-account substrate beneath production AI, where every throughput claim collides with rebuild windows, egress invoices, and control-plane risk.
Where architecture, training tricks, and eval methodology meet the marketing layer — separating durable progress in foundation models from leaderboard theater that quietly falls apart under load.
Independent comparisons of agent stacks and multi-agent designs, tracking the gap between framework marketing and the failure modes that show up under real workloads.
The economics, interop standards, and workflow tradeoffs reshaping how code gets written, reviewed, and shipped when AI agents share the editor with the engineer.
Transformers now loads GGUF quants via from_pretrained, enabling PyTorch serving. Hugging Face notes llama.cpp remains preferred for efficient local inference and broad硬件.
Independent red-teaming shows Claude Opus 4.8 has a 10.13% conditional jailbreak rate under automated attacks. Teams must test their full production stack, not just the raw.
Three 2026 preprints show LLM agents often report success despite incomplete coverage or stale state, requiring artifact-level verification gates to catch silent failures.
Vercel Sandbox Drives offer persistent agent storage with a 16 TiB cap, but beta constraints include single-writer limits and region pinning that affect multi-agent pipeline.
WordPress 7.1.2 patches an unauthenticated path traversal to RCE requiring specific theme and PHP conditions. The advisory names affected environments, but independent testing
A preprint reports a 39.7% relative WER reduction for police audio, but uneven errors and lack of verification protocols mean transcripts require human audio checks.
Evidence supports fixing MCP deployments with a five-tool budget and migration plans, not dropping the protocol, as tool sprawl degrades agent performance.
Vercel reports a libheif AVIF RCE affecting Next.js, sharp, and WordPress. Teams must patch libheif to v1.23.4, as platform mitigations do not cover self-hosted or direct use.
Cooley's GO Public uses a review-gated workflow on ChatGPT Work. Vendor claims lack independent verification, so firms should build harnesses first and gate confidential data.
Forensic analysis shows ZCode silently uploads encrypted Git history to Aliyun OSS without user consent or a working opt-out, requiring filesystem-level containment.
AIREP argues AI governance needs four distinct runtime records per decision, not one audit event, to support incident reconstruction and dispute resolution.
HALT proposes using top-20 token log-probabilities as a time series to detect LLM hallucinations, offering a sequence-based alternative to single-score metrics for audit teams
Featured analysis and deeper reads.
