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Hacker News Show HN

Show HN: UK: Skip Royal Mail QR Code Queues with the Prince of Post

This scratches an itch I experience most months. When you get a "super handy QR Code" from a service, like Asos, Vinted and others that means you have to physically go to a post office to post your parcel. About ten years ago this was revolutionary convenience, but now it's a frustration.If you're like me you use Royal Mail's collection service to ship most of your parcels/returns from home, and post offices are open for ridiculously narrow times of day these days. Royal Mail don't provide an online facility to create a label from these in-person QR codes, so I built one instead.Behold, Citizen - Prince of Post! https://princeofpost.comI had some fun designing this, and it's something that I'll genuinely use all the time, so I thought I'd share it for others with this problem too. I couldn't find any prior art, but if you want to ruin my day please do tell me about anywhere that does this already :-) Comments URL: https://news.ycombinator.com/item?id=50406466 Points: 1 # Comments: 0

llama.cpp releases

b12180

The release adds the Kimi-K3.1-Pro text model to llama.cpp, replacing full-attention MLA layers in K3 with DSA (Dynamic Sparse Attention) layers featuring a lightning indexer. The indexer uses an additive mask over the cache and reuses sparse flash attention paths, while preserving existing KDA layers and MoE components. The model's architecture includes four indexer tensors per DSA layer, hybrid memory for caching, and maintains quantization integrity by excluding indexer parameters from quant overrides. Verified against HF checkpoint with identical PPL beyond context length, and supports multiple platforms including macOS, Linux, Windows, Android, and iOS.

AWS Machine Learning Blog

Serverless MCP server for AI agent data lake access on Amazon ECS Fargate

Learn how to build a serverless Model Context Protocol (MCP) server on Amazon ECS with AWS Fargate that gives AI agents secure, metadata-driven access to an enterprise data lake. Exposing a new dataset requires only a JSON file, with no per-dataset integration code.

The Verge · AI

Why a new report on Anthropic automating AI development is alarming researchers

Anthropic is using AI to build more powerful AI. And it appears to be working remarkably well, with the company's models improving roughly twice as quickly as a year ago, with little indication of slowing down. That's according to a new report published Thursday by the AI safety research organization METR, following an 11-week investigation […]

llama.cpp releases

b12143

The Vulkan implementation of the Fast Walsh-Hadamard Transform (FWHT) has been enhanced to support block widths up to 8192, using shared-memory shaders for larger blocks, and now includes F16 input capability via shader-float16, with pipelines created only when device limits allow. This update aligns Vulkan with CUDA's capabilities and improves efficiency by eliminating the need for F32-to-F16 conversions.

arXiv cs.DC

Beyond Proof of Possession: A Relational Theory of Authority

arXiv:2611.07159v1 Announce Type: cross Abstract: Proof-of-Possession (PoP) establishes that an executor controls an artifact (key, token, credential, or capability), but such control alone determines neither the executor's relational profile nor the causal history of an execution occurrence. We separate PoP from Proof of Relationship (PoR), the semantic property that one execution occurrence validly continues another, and from authorization, which is occurrence-sensitive. The foundational change is in the semantic domain of authorization: from holders and authority-bearing artifacts to execution occurrences situated in causal histories. We give authorization models an observation-based occurrence verdict and a separate transition-admissibility relation; kernel inclusion yields a partial order on observation-kernel classes. Building on Provenance Identity Continuity (PIC) and Proof-of-Continuity (PoC), we classify executors by authorization-relevant equivalence relations whose quotients form relational profile spaces, with positive predicates over profile transitions forming a distributive lattice. This adds relational attenuation to authority attenuation: along a valid causal history, $C_{i+1}\subseteq C_i$ and $\rho_{i+1}\Rightarrow\rho_i$. We prove dual monotonicity, combined closure, and origin relational closure. Two occurrences of the same authenticated executor, with the same profile and possession evidence, need not be authorization-equivalent, and within a valid PIC lineage a deputy's independent authority cannot be imported outside the origin context. Finally, we prove that the executor-dependent decision factors through the relational profile and is invariant under sound mechanisms establishing it: successor-side PoP is a possible evidence mechanism, not a necessary premise of authorization. Under explicit Witness Assumptions, a boundary-witnessed checkpoint construction realizes the premises without successor-side PoP.

钛媒体

Fourier’s Meta Prototype Puts a Spotlight on an 8-Billion-Yuan Robotics Bet

Shanghai’s Fourier Intelligence built a custom humanoid for Meta’s internal research in months. The company already has a rehab business, modest humanoid shipments, and a disclosed pre-money valuation of about 8 billion yuan. A marquee partner tests its engineering—it does not yet prove the equity story.

Hacker News Show HN

Show HN: CLI for Cybersecurity Triage

I built it to replace the repetitive workflows of moving tabs and copying indicators across many tools and tabs for every investigation. You use your own API keys, and functions like decoding, identifying commands, and man pages all run locally with no LLM.Please let me know what you think, you can try it here right now. More information about it can be found here: ceplang.org/start.htmlAs well as a short demo here: https://youtu.be/bzGGigpeiXg Comments URL: https://news.ycombinator.com/item?id=50391790 Points: 1 # Comments: 0

SiliconANGLE AI

The AI boom’s missing balance-sheet question: What has actually been verified?

Artificial intelligence infrastructure commitments are growing faster than the evidence connecting contracted capacity to sustained economic value. I spent 13 years on the floor of the New York Stock Exchange. One lesson stayed with me long after the trading jackets disappeared: A transaction could be executed, documented and perfectly valid while the assumptions that made […] The post The AI boom’s missing balance-sheet question: What has actually been verified? appeared first on SiliconANGLE.

llama.cpp releases

b12128

The fix addresses intermittent CI failures in TOPK_MOE tests caused by near ties in logits, particularly with uniform random inputs and narrow-range gating functions like sqrt_softplus. The solution involves redrawing logits until group selection and top-k decisions have a relative margin of 1e-4 in double precision, and constructing logits by inverting the gating function using a grid-based approach to ensure consistent expert selection across backends.

Hugging Face Blog

Dharma Field Extractor: Any Document In, Structured Fields in JSON Out

The Dharma Field Extractor, a 2-billion-parameter model, specializes in extracting specific fields from diverse document types—such as invoices, IDs, and medical forms—into structured JSON format. It outperforms general-purpose frontier LLMs in accuracy and reduces cost by up to 147 times when self-hosted, demonstrating that domain-specialized small models can surpass large general-purpose models on well-defined tasks. The model supports both open extraction (detecting fields without a schema) and schema-directed extraction (returning exact field names and types), with training data spanning English, Brazilian Portuguese, and multilingual documents. Benchmarks show superior F1 scores and valid JSON output across real-world datasets like SROIE and FUNSD, reinforcing the thesis that specialization beats scale for enterprise document processing.

arXiv cs.CV

Lesion Overlap Ranks PET Segmentation Models but Does Not Certify Patient-Level Tumor Burden

arXiv:2611.05564v1 Announce Type: new Abstract: Metabolic tumor volume (MTV) summarizes whole-body PET disease burden for prognostic stratification and treatment assessment. Automated MTV is useful only if its estimate is reliable for the individual patient, yet segmentation models are usually evaluated with overlap metrics such as Dice rather than burden error. We examined whether overlap metrics identify unreliable MTV estimates using 1,014 autoPET FDG PET/CT studies. We evaluated LesionTracer predictions held out from fine-tuning, compared five selected released models on 489 tumor-positive patients, and examined the findings in 597 PSMA studies. Across the five FDG models, ranking by higher mean Dice gave the same order as ranking by lower mean relative MTV error ($\rho=-1.00$, exact $p=0.017$). At the patient level, however, out-of-fold Dice tracked relative MTV error strongly ($\rho=-0.75$), yet 82 of 489 patients (16.8\%) fell on opposite sides of the Dice 0.80 and MTV-error 25\% thresholds. Within the training-exposed released models, correlations ranged from $-0.47$ to $-0.74$ over narrower, high-Dice ranges. Out of fold, opposing false-positive and false-negative volumes cancelled about one third of spatial error in net MTV. In 236 of 489 patients, each of the five models missed at least one lesion, though not necessarily the same lesion. Thus, agreement in average model rankings did not establish the reliability of individual MTV estimates or reveal shared lesion misses. PET segmentation benchmarks should report patient-level MTV error and missed-lesion counts alongside Dice and other overlap metrics.