optimization

"私が出した結論はやっぱり、自分で書くべきところ、ないしはアウトプットするところは残しておいた方が良いというのが暫定の結論である。出来るだけ最小単位で AI を使って、コアの部分は自分が実装してレビューしてもらうのが良いのではないかと考えた。"

"schema markup alone shifts precise information extraction from 16% to 54%. That's not a marginal gain — that's the difference between being cited and being invisible."

"Tech industry lays off nearly 80,000 employees in the first quarter of 2026 — almost 50% of affected positions cut due to AI"

"Thinking of building a tool where you paste in a prospect’s name, company, and what you’re selling, and it generates a personalized cold email in seconds. Handles tone, subject line, CTA, the whole thing."

"GEO is not the successor to SEO, but a parallel engineering problem."

"This improvement is seen as a typical embodiment of Microsoft's return to the 'core function optimization' route, because it directly optimizes the widely used file management component rather than further expanding AI functions like Copilot."

"I’m implementing a self-pruning neural network with learnable gates on CIFAR-10, and I wanted your advice on the best way to approach the training and architecture"

"I'm based in San Francisco but open to relocation and remote roles and have 5+ years of experience in multimodal training, inference and optimization."

"Opus 4.7 introduced a new tokenizer, increasing token consumption by up to 35% for the exact same prompts (according to a Finout.io survey)."

"In an accounting department invoice aggregation task, a process that previously took 8 hours a month was reduced to just 36 minutes, achieving a 92% reduction in workload."

"The AI Visibility Index evaluates sites with a total of 100 points across four axes: Crawlability (0-30 points), Basic Meta Information (0-25 points), Structured Data (0-25 points), and Description Consistency (0-20 points)."

"Rather than dedicating all 8GB of VRAM to a single model, use multiple small models tailored for specific tasks."

"GEOとは、ChatGPT・Perplexity・Gemini・Claude などの生成AI（LLM）が回答を生成する際に、自社のコンテンツや情報が引用・推薦されやすくする取り組みです。"

"If SEO is optimization to 'be evaluated by Google,' then GEO is optimization to 'be cited and recommended by AI (LLMs).'"

"「軽い定型処理だから Haiku で十分」の意図で入れていた model: haiku の 1 行が、Opus セッションで呼んだときに逆に /compact を誘発していました。"

"Overall, from my tests, this vae produces identical results to original, but at 3x less vram, and at better speed."

""When the three phases are balanced, one direction in channel space - the DC direction - is left empty by construction, geometrically orthogonal to all three phases.""

""コストの可視化 → いくら使ってるかを把握する""

"Results show that student models can match or outperform the CVaR teacher in several settings, while achieving improved robustness under regime shifts and reduced turnover."

"Opus 4.7は常に適応的推論(adaptive reasoning)で動作し、MAX_THINKING_TOKENSやCLAUDE_CODE_DISABLE_ADAPTIVE_THINKINGは効きません。"

"The problem isn't 'how old' the data is. A 10-turn-old 'reason for this design' still has value today. A grep result from a turn ago is already obsolete. We shouldn't divide by time, but by kind."

"meta descriptionがない場合、AIは本文を自力で解析しますが 精度が大幅に落ちます。"

"Image Captioning Practical Verification: 42.8% speedup (9.53 seconds to 5.45 seconds) through reuse of Vision Encoder vectors, with no degradation in quality."

"The token consumption difference is not due to the presence or absence of an in-house proxy, but rather the structural difference in the billing models of Enterprise and MAX as the main cause."

"CLAUDE.md is advisory only (~70% compliance). Hooks are executed 100% deterministically. CLAUDE.md is merely a soft instruction to the LLM. It is only probabilistically followed. On the other hand, Hooks are executed as shell commands and work 100% of the time."

"Rather than just simple string matching, we utilized AI to analyze the context of whether a listing is genuinely what the user is searching for, or just an unrelated item stuffed with keywords."

"The proposed framework is able to jointly learn the 参数 of a dimension reduction technique (e.g. linear projection or a neural network) and cluster the data based on the resulting features (e.g. under a Gaussian Mixture Model framework)."

"We introduce MixAtlas, a principled framework for compute-efficient multimodal mixture optimization via systematic domain decomposition and smaller proxy models…"

"we study constructive feedback generation, the task of producing targeted, actionable feedback that helps authors improve both their research and its presentation."

"use the HyperPod automated infrastructure, cost optimization features, and performance enhancements to reduce your total cost of ownership by up to 40% while accelerating your generative AI deployments"