@arc

We’re clearly seeing a shift from an uptrend into a short-term downtrend.

Structure: Lower highs + lower lows forming since late Feb bearish structure confirmed

Resistance: 6800–6900 zone (previous supply area where price kept rejecting)

Support: 6500 is being tested right now; below that next key zone is 6400

Momentum:

Recent candles show strong selling pressure (multiple red candles breakdown move)

Any bounce so far looks like a relief rally, not a reversal

Trend Insight:

The earlier rally (Dec–Feb) has lost momentum…

Stop measuring bots.Start measuring customers.

BotLens classifies every visitor as human, bot, or AI agent and pushes clean numbers into your existing GA4. Quantify how much of your marketing data is real, in dollars and percentages, on a metric your CFO and CMO already understand.

35%+

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10 min

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HOME SERVICE BUSINESS DOING $75K+/MONTH!

Most marketing agencies get paid whether your marketing works or not.
We decided that wasn't good enough.

That's why we created the Growth Lead Machine—our proven system for helping established home service companies generate predictable, high-quality booked jobs.

We're so confident in it that we'll help you generate $10,000 in new booked jobs within 30 days—or we'll continue working for free.

Why are we willing to make that promise?

Because we've done it before:…

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DigiWares — Privacy-First Tools Built in Bangkok

Privacy-first utilities for voice, documents, and productivity. Many run entirely in your browser - your files never leave your device. No signup required for most tools.

// flagship

• tera.fm -Stop scrolling. Start listening.
• voicetotextonline.com -Speech to text in 55+ languages
• tickk.app -Speak, save, sort it later
• voicebraindump.app -Speak now, organize never
• sornic.com -Turn any article, PDF, or photo into audio

// documents & privacy

• ikrypt.com -Stop DM-ing passwords. Send a secret once.
• nouploadtools.com -Privacy-first browser utilities — files never leave your device
• extractanything.com -Extract anything from any document
• keplerdocs.com -Understand your files without opening them

// expat life...

Branches Tags

15 Commits

HTML -> Doc converter

This repo contains some examples and attempts to convert HTML documents to Word documents.

The main use case is to convert ShEx spec files written in HTML with ReSpec to IEEE Word files.

We have a dedicated folder for that in ./shex folder.

Workflow slides: https://docs.google.com/presentation/d/1jYvYnM9rn5F_13q88JOHVqggE5l-gRPVMIy8h8sRxwI/edit?usp=sharing

Abstract...

🔧

Plumbing

leads cost

$10/lead

⚡

Electrical

leads cost

$10/lead...

Branches Tags

1,465 Commits

Payment Authorization Terms & E-Sign Disclosure and Consent Notice

Welcome to the secure bill payment technology service provided by Paymentus Corporation (“Paymentus”, "we" or "us"). We are an authorized provider for the company ("biller") to which you will be making a payment. If you use this service to make this and any future payment, you accept these terms and conditions. Please read them carefully. You should retain an electronic or printed copy of these terms.

Refund Policy: Under normal circumstances, there are no refunds on the payments.

Privacy Policy: Your information is secure and will be used for the purpose of processing payment transactions and as provided in our Privacy Policy....

rudof tutorials

This repository contains the source code of some Jupiter books that can be used as small tutorials of rudof.

Some links:

• Jupiter-books reference

🚀 Quick Start

1. Clone and install

git clone https://github.com/rudof-project/tutorials.git
cd tutorials
pip install -r requirements.txt

2. Build the book

jupyter-book build rudof

3. Manually publish books on gh-pages

Note, this is no longer necessary because we publish the book through github Actions.

ghp-import -n -p -f rudof/_build/html

Cleaning build files and cache

Sometimes it is necessary to clean the cache when there are new versions of the libraries. To clean the built drectory use:

jupyter-book clean rudof

If you want to clean also the jupyter_cache, use:

jupyter-book clean rudof --all

Loading...

[src]

Parameters

Errors

anyerror means the error set is known only at runtime.

Search Results

No Results Found

Press escape to exit search and then '?' to see more options.

Fields

Types

Namespaces

Global Variables

Values

Functions

Error Sets

Example Usage

Source Code

Keyboard Shortcuts

?Show this help dialog

OpenAI has had a hell of a year. The company spent months battling former cofounder Elon Musk in a sensational jury trial, was hit with a high-profile trade secrets lawsuit from Apple, and faced widespread scrutiny after an unreleased model hacked another AI company. As it prepares for an IPO, a steady string of executives have departed, including some of the company’s biggest names.

Throughout it all, one person has quietly amassed power: Greg Brockman....

“Share of Searching is a fantastic tool that has enabled me to mature the organic search capability for the organisation. It has helped me to discover trends with competitors so we could apply some of this logic to predict what could happen with our brands, post merger. It has been instrumental in measuring brand awareness and organic share of search in our category. I’ve been very impressed with how receptive and responsive the team at SOS are to feedback and they’ve always been able to resolve any issues in a timely manner.”

Mona Doncevska — Digital Growth Marketing Manager – Organic Search

Australian Retirement Trust...

Go here for other operating systems

Trouble installing/running Cheat Engine? Check out the known github issue here on how to solve it, or join the cheat engine patreon

Do you wish to mod your games, but you do not like cheating? Then try Runtime Modifier it's not cheating if you call it modding!

Read before download: You must be 18 years or older, or deemed an adult, to install Cheat Engine. Cheat engine is for private and educational purposes only. Before you attach Cheat Engine to a process, please make sure that you are not violating the EULA/TOS of the specific game/application. cheatengine.org does not condone the illegal use of Cheat Engine

**May 29 2026:**Cheat Engine 7.7 Released for Windows, Mac and Linux for Patreons...

Shaping Knowledge Graphs

This is a Jupyter book that introduces Knowledge Graphs concepts using rudof

• Short introduction to Rudof
• RDF
• SPARQL
• ShEx
• SHACL
• Introduction to DCTAP
• RDF 1.2
• SPARQL 1.2
• Using rudof to compare schemas
• Service descriptions
• Generating RDF Data from shapes

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Why have I been blocked?

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Flexeegile Extending Agile For AI & Data Teams

Flexeegile is my proposed extension to the well-established Agile framework, it aims to address the unique challenges posed by AI & Data projects in today’s complex computing environments.

Flexeegile, much like Agile, recognizes the value of the items on the right but considers the items on the left to be of higher value.

Flexeegile is not a replacement for Agile, but rather an observation and adaptation of Agile principles to suit the modern era of computing.

As one of the founders of the Agile Manifesto, puts it:

“Flexeegile is not replacing, but observing that the nature of computing is richer than it was in the era of Agile when it was about desktop computers. Agile is still as relevant as ever.”

Flexeegile recognizes that today’s computing landscape extends far beyond desktop applications, encompassing cloud computing, big data, machine and deep learning, and more....

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MoodNode Features

MoodNode is a node-based AI workspace for generating images and videos. Connect 50+ AI models — Flux, Seedream, Stable Diffusion, Kling, Luma, Pika, and more — in visual pipelines. From a single prompt to a fully produced video, all in one flow. Free to start with your own API keys (BYOK).

Node-Based Workflows

Build visual pipelines by connecting nodes on a canvas. Each node does one thing — generate, edit, enhance, or export. Chain them together to create multi-step workflows from prompt to production.

Save As Template

Turn any workflow into a reusable template. Save it, name it, and start new projects from it in one click. Share them with the community or keep them private.

Style DNA

Upload a reference image and let AI extract its visual DNA — colors, mood, composition, lighting. Apply that style to any generation without guessing prompts....

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Why have I been blocked?

This website is using a security service to protect itself from online attacks. The action you just performed triggered the security solution. There are several actions that could trigger this block including submitting a certain word or phrase, a SQL command or malformed data.

What can I do to resolve this?

You can email the site owner to let them know you were blocked. Please include what you were doing when this page came up and the Cloudflare Ray ID found at the bottom of this page.

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TL;DR

• Start with use-case-driven modeling — define the questions your graph must answer before designing the full ontology. A knowledge graph is a semantic model; the graph database is just where you store it.
• Entity resolution is non-negotiable — duplicate nodes destroy trust faster than missing data. Resolution is a platform capability, not an ETL afterthought.
• Schema evolution is continuous — plan for additive changes, versioning, and backward-compatible migrations from day one. Ontology changes follow the same rigor as API versioning.
• Data quality gates belong in the pipeline — validate at ingest with SHACL or constraints, not after users discover bad data in production.
• Governance beats technology — assign stewards per domain, version ontologies in Git, and review schema changes like API changes. Neo4j, Stardog, GraphDB, Neptune, and Jena are interchangeable compared to modeling discipline.

Why This Matters...

Before you change anything, name the parts of the system you are actually maintaining. This section is the map; the rest of the guide walks it.

Maintain the harness, not just the prompt.

When an agent misbehaves, the reflex is to edit the prompt. But the prompt is one part of a larger system. The harness is everything that turns a model into a worker: the instructions, the sources and examples it reads, the memory it carries between runs, the tools it can call, the permissions it has, the model and its settings, the human review before its output is used, and any evals that check it.

A drifting agent usually still sounds fluent, so the useful question is not "is this output well-written" but "is this fluent output still doing the current job." You can only answer that by looking at the whole harness. That is what this loop does.

You do Write down the concrete parts of this agent's harness as they exist now: which instructions, which sources, which tools, who reviews it, and what it is allowed to do....

100+

Videos per batch

Generate a full month of content in one session

<10 min

Raw footage to viral

From upload to 100 finished videos in minutes

30+

Template categories...

# The Greed/Fear Residual Strategy

A Quantitative Model for Timing Market Extremes, by Think_Reporter_8179

Raw data here

# Overview

This strategy builds on the foundational work of economist Robert Shiller and his widely recognized Cyclically-Adjusted Price-to-Earnings ratio (CAPE) also known as Shiller PE. The Shiller PE smooths out earnings over a 10-year period to adjust for economic cycles, offering a more stable signal of market valuation than traditional P/E ratios.

Residual Concept:

While the Shiller PE is a powerful tool, it exhibits a general upward trend over time due to long-term economic growth, inflation, and shifts in market structure. To adjust for this and extract meaningful overvaluation signals, a linear regression was applied to the full historical Shiller PE dataset (1871–present). This regression line represents the expected value of the Shiller PE based on its historical trajectory.

Hey everyone,

Just a heads up, the Shiller PE has broken through 41 and has deviated by 17.04 from its historical trend. This is the second time in history this has occurred, the only other time being the Dot-Com Bubble of the late 1990's, where Greed went as high as 22.08 in April, 1999.

Just before The Great Depression, it deviated 16.89 before the downturn.

If you want to be mathematically Fearful while everyone is Greedy, this is about as close as you're going to get.

Enjoy the exuberance.

Biography

Full Professor (Catedrático), University of Oviedo, Spain. Founder and main researcher of WESO (Web Semantics Oviedo) research group, which collaborates with different companies around the world applying semantic web technologies to solve practical problems.

Member of Data Shapes W3C Working Groups and of Shape Expressions, SHACL, RAX (RDF and XML interoperability) and Best practices of Multilingual Linked Open Data W3C community groups.

Previously, coordinator of the Master in Web Engineering - University of Oviedo (2016-2017), and Dean of the School of Computer Science Engineering - University of Oviedo (2004-2012).

Interests...

Overview: All AI crawlers at a glance

Every major AI platform operates its own web crawlers to collect content for training, knowledge updates or real-time search. These crawlers identify themselves via their user agent string and respect robots.txt – but beyond that, they differ significantly in crawl frequency, purpose, transparency and what they actually do with your content.

Core principle for all crawlers: They all respect robots.txt, read only the HTML source without JavaScript rendering (with partial exceptions) and prefer technically clean, fast websites. The differences lie in crawl frequency, purpose, whether they link back to your site and the degree of transparency each provider offers.

As of 2026, eight major AI crawlers are actively indexing the web. Understanding each one lets you make informed decisions about who gets access to your content – and who doesn't.

GPTBot – ChatGPT (OpenAI)

OpenAI

GPTBot

User agent...

This is the inflection point people have been predicting, but it’s still jarring to see it land.
When near-frontier models are open, cheap, and abundant, the differentiator stops being the model and becomes:
– orchestration
– memory
– eval + reliability
– data freshness
– and the control plane around it all
Benchmarks matter, but production systems matter more.
We’re moving fast from “which model?” to “which system can actually scale, reason, and be trusted?”
That shift is already reshaping how enterprise AI platforms are being built.

At a time when AI tools are increasingly present in education, school leaders are beginning to explore how large language models might support thinking, planning, and decision making alongside ongoing pressures around workload, safeguarding, and resourcing.

In this conversation with David Monis-Weston, the focus is on how AI can be used as a thinking partner rather than a replacement for professional judgement (see the first recording in this collection for a focus on theory). The discussion explores practical ways leaders might use AI to generate alternative perspectives, test ideas, and support scenario planning, while staying critically aware of its limitations and risks.

A key theme is caution and responsibility, including understanding bias, avoiding over reliance on generated responses, and being careful with sensitive data. The conversation also highlights safeguarding and data protection considerations, particularly around what is entered into AI systems and how that information may be stored or reused....