How to uncover high-converting, commercial search queries that show zero volume in mainstream SEO tools while keeping your sites invisible to competitors.

Natural linking follows predictable human patterns that deep learning models and search algorithms easily detect, exposing inorganic link building efforts.

Chrome's DecisionModel API landed on 6 to 8 October 2026. The exact prompts, limits, engine status and review findings, plus a comparison with Google's MediaPipe DecisionMaker and local tests of Embed...

Instead of infinite prompt variations, this measurement framework tracks canonical core entities across AI models to score brand visibility over time.

Google's Gemini 4 Argon introduces a 1-million-token output limit to support long-horizon autonomous tasks, enterprise benchmarks, and complex code migrations.

An analysis and reproduction of Google's query fanout research, demonstrating how vector-based diffusion models could replace text fanouts for faster search.

Explore the core AI mode tags used

Google Research introduced R4T, an RL-trained diffusion retriever that optimizes fan-out query sets for diversity and speed, achieving up to 20x latency speedups.

A study reveals that language model abstention is governed by a single internal confidence signal that outranks question difficulty and fact retrievability.

Introducing GPT-6 Astra, our most intelligent and aligned model yet, with state-of-the-art capabilities across computer use, coding, cybersecurity, and science.

This page compares the 1955 Dartmouth artificial intelligence proposal with the public record of AI capabilities and world models as of 2026.

Gemini in Gmail drafted Python code to fine-tune a DeBERTa model for sentiment classification, complete with data loading, training loops, and evaluation.

Copies the visible page content area as structured Markdown, following Chrome's Annotated Page Content design.

Prompt injection and gzip-NCD compression analysis reveal that OX Alpha, a mysterious LLM on OpenRouter, is GLM developed by Z.ai.

The DEJAN Chat Protocol is a response format that puts the answer in the first sentence and defers elaboration to the reader's explicit choice.

YouTube video by Ahrefs Podcast

Google Research found frontier AI models encode 95-98% of brand facts in parametric memory but fail to recall 26-34% of them. The bottleneck is retrieval, not storage.

In a 30-day server-log census of dejan.ai's three machine files, the big-three AI crawlers fetched robots.txt 1,150 times combined, llms.txt 4 times, and the OKF content bundle 23 times.

Mapping Gemma embeddings to Gemini embeddings via a linear transform recovers entity vector structures with high fidelity without calling the paid API.

Modifying specific self-attention layers in the Gemma language model alters its self-identity and safety responses, blurring real-world harm with video games.

A mechanistic interpretability study shows how ablating specific MLP neurons in Gemma 4 causes the model to revert to its older, dormant Bard identity.

An evaluation of Explorative Modeling in a 115M-parameter text diffusion model, comparing generation perplexity and likelihood against a time-matched baseline.

Enter a website and see what Google's model believes that business offers, how confident it is in every word, and what it nearly said instead.

If your page was one of the search results supplied to Google’s AI, would it be selected as one of the grounding sources in its final response? Find out how relevant your website is for any query in G

First results from the dejan.ai AI vs Human test: 1,636 answers, 64% correct overall, 18 perfect rounds against 0.14 expected from guessing, and accuracy rising from 55% to 75% with reading time.

Ten news stories, each written twice: once by a person, once rewritten by a language model. Pick the machine. Your score is saved to an address you can share.

An exploration of DeepSeek founder Liang Wenfeng's strategy of deliberate restraint, continual learning, and open weights in the race toward AGI.

Analysis of citation mining data shows Reddit has a 99.39% rejection rate from OpenAI, zero citations from Anthropic, and heavy usage by Google.