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97 results for "Perplexity"
Attention Is All You Need, But All You Can't Afford | Hybrid Attention
Repo: https://codeberg.org/JohannaJuntos/Sisyphus I've been building a small Rust-focused language model from scratch in PyTorch. Not a finetune — byte-level, trained from random init on a Rust-heavy corpus assembled in this repo. The run: 25.6M parameters 512 context length 173.5M-byte corpus 30k training steps Single RTX 4060 Ti 8GB Final train loss: 0.5834 / val loss: 0.8217 / perplexity: 2.15 Inference: 286.6 tok/s with HybridAttention + KV cache — 51.47x vs full attention Architecture Byte-level GPT-style decoder: Vocab size 256 (bytes) 8 layers, 8 heads, 512 embedding dim Learned positional embeddings Tied embedding / LM head weights The attention block is not standard full attention. Each layer uses HybridAttention , combining: Local windowed causal attention A GRU-like recurrent st
Not All Denoising Steps Are Equal: Model Scheduling for Faster Masked Diffusion Language Models
arXiv:2604.02340v1 Announce Type: new Abstract: Recent advances in masked diffusion language models (MDLMs) narrow the quality gap to autoregressive LMs, but their sampling remains expensive because generation requires many full-sequence denoising passes with a large Transformer and, unlike autoregressive decoding, cannot benefit from KV caching. In this work, we exploit the flexibility of the diffusion framework and study model scheduling, where a smaller MDLM replaces the full model at a subset of denoising steps. On OpenWebText, we show that early and late denoising steps are substantially more robust to such replacement than middle steps, enabling up to a 17% reduction in FLOPs with only modest degradation in generative perplexity. We support these findings with a step-importance analy
Developer Experience with AI Coding Agents: HTTP Behavioral Signatures in Documentation Portals
arXiv:2604.02544v1 Announce Type: new Abstract: The rapid adoption of AI coding agents and AI assistant web services is fundamentally changing how developers discover, consume, and interact with technical documentation. This paper studies that transformation across three interconnected dimensions: documentation accessibility, content analytics, and feedback systems. We present an empirical study of HTTP request fingerprints from nine AI coding agents (Aider, Antigravity, Claude Code, Cline, Cursor, Junie, OpenCode, VS Code, and Windsurf) and six AI assistant services (ChatGPT, Claude, Google Gemini, Google NotebookLM, MistralAI, and Perplexity) accessing a live developer documentation endpoint, revealing identifiable behavioral signatures in HTTP runtime environments, pre-fetch strategies,
Building AI Visibility Infrastructure: The Technical Architecture Behind Jonomor
Traditional SEO is failing in the age of AI answer engines. While SEO professionals optimize for search rankings, AI systems like ChatGPT, Perplexity, and Gemini retrieve information through entity relationships and knowledge graphs. The gap is structural, not tactical. I built Jonomor to solve this problem at the infrastructure level. The Technical Problem AI answer engines don't crawl pages looking for keywords. They query knowledge graphs for entities with established relationships and verified attributes. When someone asks Claude about property management software, it doesn't scan blog posts—it looks for entities that declare themselves as property management platforms with supporting schema and reference surfaces. The existing optimization frameworks focus on content volume and backli
AI Citations: The New Backlink and How to Track Them at Scale
AI citations are fundamentally reshaping how B2B buyers discover information. With ChatGPT seeing 1.6 billion weekly visits and Perplexity AI growing to over 10 million monthly active users, being referenced as a source in AI responses is becoming as valuable as traditional backlinks. Unlike standard backlinks, AI citations don't create HTML links—yet they drive significant referral traffic (8-12% CTR for cited sources) and build brand authority with buyers who trust AI-curated answers. The shift is already happening. Google's AI Overviews now appear in approximately 15% of search queries, with even higher prevalence in B2B research topics. Meanwhile, 68% of B2B researchers report using ChatGPT or Perplexity in the early stages of their buying process. Content optimization platforms help y
Why Your Website Is Invisible to AI Search Engines (And How to Fix It)
Google is no longer the only search engine that matters. Every day, millions of users ask ChatGPT, Perplexity, Claude, and Gemini for recommendations: "Best dentist in Istanbul for veneers" "Top web design agencies for startups" "Find me an immigration lawyer in London" If your website doesn't appear in those AI-generated answers, you're losing customers to competitors who do. And here's the uncomfortable truth: traditional SEO alone won't get you there. At ModernWebSEO , we've developed a three-layer approach that tackles this exact problem. The Three Layers Layer 1 — SEO: Still the Foundation Google organic search isn't dead — far from it. But the bar is higher than ever: Core Web Vitals must be green across all metrics Mobile-first indexing means your desktop site is irrelevant if mobil
I Audited 30+ Small Businesses on Their AI Visibility. Here's What Most Are Getting Wrong.
I run a small marketing consultancy focused on helping businesses understand how they show up - or don't - when customers use AI tools to find services. Over the last few months, I've done AI visibility audits for 30+ small businesses across hospitality, professional services, and retail. The pattern is painfully consistent. Most businesses are invisible to AI search Go to ChatGPT right now. Ask: "What's the best [your service] in [your city]?" Try it. I'll wait. If your business showed up - congratulations, you're in the minority. Most don't. Some get mentioned with outdated information. A few get described with details that are flat-out wrong. This matters because AI-powered search is growing fast. Google's AI Overviews, ChatGPT, Perplexity, Copilot - they're all pulling from a mix of we
Benyar Men's Watches SA and Lige Men's Watches South Africa: Bold Styles for SA Men
Benyar men's watches SA and Lige men's watches South Africa dominate the affordable luxury segment, offering robust chronographs and divers that rival premium brands in design and durability. These Chinese-made timepieces, popular through South African online stores like Vivid Nuance, feature stainless steel builds, luminous dials, and water resistance starting at 50m, all priced under R1,200 with free nationwide shipping. Perfect for Joburg executives or Durban adventurers, they blend sporty functionality with everyday elegance.[perplexity] Rise of Benyar Men's Watches SA Benyar men's watches SA have surged in popularity for their military-inspired aesthetics and reliable quartz movements. Models like the Benyar 9001 chronograph boast 44mm cases, unidirectional bezels, and screw-down cro
What is GEO (Generative Engine Optimization)? The 2026 Guide
AI Overviews now appear in over 50% of searches . If your brand isn't in those answers, you're invisible. GEO — Generative Engine Optimization — is the discipline of making your content citable in AI-generated answers. It's not a replacement for SEO. It's a parallel system. The core insight: Fewer than 10% of sources cited by ChatGPT, Gemini, and Copilot rank in Google's top 10 for the same query. This proves GEO must be managed separately from traditional SEO. What is GEO exactly? Generative Engine Optimization is the practice of structuring your content so AI-powered platforms — ChatGPT, Perplexity, Google AI Overviews, Gemini, voice assistants — can extract it and deliver it as a direct answer to a user query. Unlike traditional SEO, which optimizes for rankings in a list of links, GEO