Results for “speed-reading”

Launch RSVP speed reader for text

Launch RSVP speed reader for text

Launch RSVP speed reader for text

Launches an RSVP speed reader to display text one word at a time with Spritz-style highlighting.

Launch RSVP speed reader for text

Launch RSVP speed reader for text

Launch RSVP speed reader for text

Launch RSVP speed reader for text

Launch RSVP speed reader for text

Launch RSVP speed reader for text

Launch RSVP speed reader for text

Launch RSVP speed reader for text

Launches an RSVP speed reader to display text one word at a time with Spritz-style highlighting.

Launches an RSVP speed reader to display text one word at a time with Spritz-style highlighting.

Launch RSVP speed reader for text

Launch RSVP speed reader for text

Launch RSVP speed reader for text

Launch RSVP speed reader for text

Accelerate LLM inference using speculative decoding, Medusa multiple heads, and lookahead decoding techniques for 1.5-3.6× speedup without quality loss.

AI 论文速读 Skill：三档深度（裸读 / 引导 / 精读）+ 页码级 Provenance 防幻觉 + 多篇对比。 触发词：论文速读、读这篇论文、抓核心观点、论文对比、多篇对比、与我研究方向的关联、 第几页提到 X、这篇论文的数据集怎么构造的、论文精读、 paper summary、summarize this paper、compare these papers、literature skim、extract methodology。 不做：论文检索、文献管理、论文翻译、扫描件 OCR、论文写作 / 降重。

Design reading plans with retention strategies. TRIGGERS - Use when user needs help with reading-plan related tasks.

Design reading plans with retention strategies. TRIGGERS - Use when user needs help with reading-plan related tasks.

Download, split, and deeply read academic PDFs. Use when asked to read, review, or summarize an academic paper. Splits PDFs into 4-page chunks, reads them in small batches, and produces structured reading notes — avoiding context window crashes and shallow comprehension.

Train reinforcement learning agents at millions of steps per second using optimized PPO, vectorized environments, and multi-agent support.

Layer 4 of the keyword research pipeline. Spawns a "skeptical SEO" adversarial sub-agent to argue against every survivor of Layers 1-3. Catches mechanical-classifier blind spots — wrong SERP intent, hidden link-graph gauntlets, AIO trajectory shifts, vanity-rank metrics. Same pattern as quality-check's adversarial draft read, applied to keyword selection.

Use when the app is slow, pages take too long to load, API responses exceed 200ms, memory usage is high, or renders are excessive. For profiling, identifying bottlenecks, optimizing React renders, reducing bundle size, improving database query speed, and measuring before/after improvements. Activate when user says "it's slow", "optimize this", "reduce load time", or "too many re-renders".

Expert guidance for distributed training with DeepSpeed - ZeRO optimization stages, pipeline parallelism, FP16/BF16/FP8, 1-bit Adam, sparse attention

A stakeholder asks to make search faster.

Build students' capacity to read historical documents closely — attending to word choice, tone, and rhetoric as evidence of perspective. Use when students summarise sources without analysing language.

Accelerate LLM inference using speculative decoding, Medusa multiple heads, and lookahead decoding techniques. Use when optimizing inference speed (1.5-3.6× speedup), reducing latency for real-time applications, or deploying models with limited compute. Covers draft models, tree-based attention, Jacobi iteration, parallel token generation, and production deployment strategies.

Reads URLs and PDFs by fetching source content, defaulting to concise summaries for plain read requests and clean Markdown when asked to convert, save, quote, cite, or feed downstream work. Use when users ask in any language to read, fetch, check, summarize, quote, cite, convert, or save a URL or PDF. Not for local text files already in the repo.

基于论文文本的通用读论文助手。用户提供论文文本（文件路径或直接粘贴），解答各类读论文需求——总结、精读、内容问答、概念解释、批判性分析等，并将结果以 Markdown 写入当前工作目录。触发词：读论文、论文总结、精读这篇论文、帮我分析这篇论文、这篇论文讲了什么、论文问答、论文笔记。输入为纯文本/Markdown 论文内容；不做论文检索下载、不做扫描件 OCR、不做论文写作降重。

Plan a sprint by estimating team capacity, selecting and sequencing stories, and identifying risks.