JULIAN ASSANGE: "The goal is to have an endless war, not a successful war."
War is a taxation based money laundering racket for the transnational security elite - it matters very little to them whether it's in Ukraine or Afghanistan, the goal is theft of public money.
Jimmy Dore is right. Capitalism died long ago.
The rentier elites no longer need a market. They need the state, and they have it: an economy planned by Wall Street and enforced by the Federal Reserve. Bail out the banks, print the money, inflate the assets, freeze the wage.
They invented the "welfare queen" so you would spend four decades furious at a woman buying steak with food stamps.
The real welfare queens are oligarchs with a treasury and a printing press.
They socialize the losses, extract the wealth, and bill you three times: in frozen wages, in rising rents, in ever-growing debts.
In 1526, the king of Kongo wrote to the king of Portugal and begged him to stop the slave trade.
The letters still exist. You can read them.
King Afonso I — Nzinga Mbemba.
He was not a victim of ignorance about Europe. He was literate in Portuguese, Catholic, and had welcomed Portuguese traders as partners. Then he watched what the trade actually did.
He writes that merchants are seizing people every day — nobles, family members, free subjects — and that his country is being emptied. He asks for teachers and doctors instead of ships. He asks, plainly, for it to stop.
Portugal's king replied with a letter pointing out how profitable Kongo's trade was and how little else it had to offer.
The trade continued for another three hundred years and helped destroy the kingdom.
An African head of state put his objection in writing in 1526, in the language of the people doing it, and was told the arithmetic did not work in his favour.
"They didn't know" has never been available as an excuse. The correspondence is in the archives.
These videos on Iranian science are completely misleading. They conveniently leave out the fact that those scientists were also philosophers. Some of them even wrote their dissertation on mathematics and philosophy. That's why they were able to make judgements about the type of weapons to make. Unlike Americans who throw so much money at sophisticated weapons that are cumbersome to operate, Iranians made simple weapons.
That's a philosophical decision. There's no science without humanities.
You're better off listening to @s_m_marandi about Iran's warfare than Anglo-Americans who are anti-intellectual and hate philosophical sophistication. And let me just mention that he's a professor of English and literature. https://t.co/dXjK5tGUsK
Stop whatever you're doing and listen carefully:
AFRICOM has announced the launch of a new psychological operation meant to influence Africans towards US interests by deploying a US army cyber unit to impersonate Africans online.
Its name "Drongo" comes from the African bird that mimics other animals so that it can steal their food.
That account trying to gaslight you on Twitter with "Traoré is a brutal dictator", "The worst democracy is better than the best dictatorship", and "Stop blaming white people and hold your leaders accountable" may just be an American soldier carrying out his mission.
Use your discernment on the internet!
Shannon sharpe wakes it up . He says Argentina is the first country to the reach the FIFA World Cup semi finals in its 96 years history to not have faced a top 15 ranked country . He says this is not a conspiracy they want Messi to win the tournament
A physicist put 22 cars on a circular track and asked every driver to hold a steady 30 km/h, about 19 mph. No lights, no lanes, no obstacles. Within a minute the cars started bunching, and soon a full stop appeared out of nowhere, then drifted backward around the loop.
This was Yuki Sugiyama at Nagoya University in 2008. His team spaced the cars evenly on a 230-meter ring and filmed them from overhead. For a while the flow stayed smooth. Then the tiny differences no human can avoid, one driver a hair slower, the next a hair too close, began to feed on themselves.
One car eases off slightly. The driver behind sees the brake lights, reacts a fraction of a second late, and brakes a little harder to be safe. The next driver brakes harder still. A dozen cars back, someone is stopping dead. The squeeze rolls backward through the line like a compression running down a Slinky, and it keeps going long after the first driver has sped up again.
Car count was the tipping point. With fewer than 22 on that track, the bunching sorted itself out. At 22, a jam formed every time. Engineers call that a critical density, the point where a road holds just enough cars that one small tap can snowball into a standstill.
These waves are eerily consistent. Measured on highways around the world, the jam rolls backward against the traffic at roughly 20 km/h, and that speed barely shifts from one country to the next. Different drivers, different roads, same number.
The same setup later became the cure. In 2017, a US team rebuilt Sugiyama's ring with 22 cars and turned just one of them into a self-driving car running a program to smooth its own speed. That single car soaked up the small slowdowns instead of passing them back, and the waves died. Fuel use across every car fell by up to 40 percent. Fewer than 5 percent of the vehicles had to be automated to steady the whole group.
In 2022 the idea moved onto a live highway. Researchers ran 100 cars with cruise control guided by AI into the morning rush on Interstate 24 near Nashville, mixed into normal traffic. Early numbers pointed the same way: a small share of smoother-driving cars, up to 40 percent less fuel for everyone around them.
The jam you sat in this morning likely had no crash and no cause you could see. It was a few hundred drivers, each braking a moment too late.
China isn’t just pushing frontier AI models to be free. It’s also pushing open-source hardware by releasing datasheets and DIY guides to build devices like Ray-Ban Meta-style glasses.
The strategy is simple: commoditize software and services. If AI models and hardware designs become free, the real value shifts 100% to manufacturing. Components, chips, batteries, sensors, optics, and supply chains.
In that world, China is the one capturing most of the profits because it’s the one selling the physical infrastructure.
Trump just turned on Netanyahu, and Alex Jones argues the shift is real, but the reasons behind it are darker and more dangerous than almost anyone is saying...
In this conversation, Alex makes his case that Trump was manipulated into the war with false intelligence promising the Iranian regime would collapse in 4 days, and that once it backfired on the economy and his midterm numbers, he started hunting for an exit ramp that Israel keeps blocking.
He points to JD Vance, Tulsi Gabbard, and Joe Kent warning against the war from the start, and to the 2027 NDAA provision merging the US and Israeli militaries as the line that finally snapped.
The part that will get the most attention is his theory on the leverage.
Alex doesn't think Trump is simply blackmailed over Epstein.
His more provocative claim is that Trump tied himself into that network for power and survival, and is now enraged that the people he partnered with refuse to take orders.
He also gets into Ben-Gvir's "all of Lebanon must burn" rhetoric, the positioning of Marco Rubio as the next pro-Israel favorite, and his fear of a major provocation designed to keep America in the war.
His warning is one I keep hearing: a cornered Likud is at its most dangerous, and Israel is gambling everything on keeping the US in this fight.
@RealAlexJones
A 22-year-old computer science student in Rochester, New York got so frustrated with the way JavaScript worked differently in every browser that he wrote a library to fix it.
He released it for free at an unconference in January 2006. That library became the foundation of the web for an entire generation.
It now runs on 77 percent of the top 10 million websites on Earth. He never started a company around it. He gave it away and went to work on education and Japanese art.
His name is John Resig. The library is called jQuery.
Here is the story.
John was born on May 8, 1984 in Boston, Massachusetts. He grew up fascinated by computers and programming. He attended the Rochester Institute of Technology and studied computer science with concentrations in economics and psychology. During college he lived in Computer Science House, an on-campus living and project community where students build things for fun. His housemates voted him Member of the Year during his sophomore year.
The problem that consumed him at RIT was cross-browser JavaScript. In 2005 the web was a mess. Internet Explorer, Firefox, Safari, and Opera all handled JavaScript differently. Writing code that worked the same way in every browser was painful, repetitive, and fragile. Developers spent more time fighting browser inconsistencies than building features.
John spent years at RIT building personal tools and libraries to make JavaScript easier to write. He wanted to share them with the world in a clear and concise way. In 2005, while still a student, he started building jQuery.
In January 2006 he released it at BarCamp NYC, a tech unconference whose core rule was no spectators, only participants. He was 22 years old. The library was small, elegant, and solved the exact problem every web developer was struggling with. You could traverse the DOM, handle events, animate elements, and make Ajax calls in a few lines of code that worked the same way everywhere.
The adoption was immediate. jQuery was the only open-source JavaScript library at the time that shipped with documentation. Most libraries expected developers to read the source code. John's first hire was not a developer. It was a community manager, someone to help answer questions from developers who were adopting the library. He understood from the beginning that adoption was a human problem, not a technical one.
Drupal selected jQuery as a core component. WordPress built on it. Microsoft adopted it. Apple used it. Google, IBM, Amazon, and AOL incorporated it into their websites. Django and Rails integrated it. Mozilla built with it.
By the early 2010s jQuery was everywhere. It became the most deployed JavaScript library in history by a margin so large that the second place contender was not even close. As of recent measurements, jQuery runs on approximately 77 percent of the top 10 million websites.
John worked at the Mozilla Corporation from 2007 to 2011 as a JavaScript evangelist and tool developer. He authored two books, Pro JavaScript Techniques and Secrets of the JavaScript Ninja. He created Processing.js, a port of the Processing language to JavaScript. He created Sizzle, a standalone CSS selector engine. He created QUnit, a testing framework.
In 2011 he joined Khan Academy as Chief Software Architect. He has been there ever since, building the technology behind one of the largest free education platforms on Earth.
Then he did something nobody expected from a JavaScript legend. He became a scholar of Japanese woodblock prints.
John is a Visiting Researcher at Ritsumeikan University in Kyoto, studying Ukiyo-e, the Japanese art of woodblock printing from the 17th to 19th centuries. He built ukiyo-e .org, a comprehensive database and image search engine that lets anyone search across hundreds of thousands of prints from museums and collections worldwide. He applied the same engineering instincts that made jQuery work, simplify, document, and make accessible, to a centuries-old art form.
He was inducted into RIT's Innovation Hall of Fame in 2010. He lives in the Hudson Valley of New York.
A frustrated college student wrote a JavaScript library in his dorm room and gave it away for free.
It became the invisible foundation of the modern web.
He went to Kyoto to study woodblock prints.
10 GitHub Repositories you should definitely check as an AI Engineer!
1. Hands on AI Engineering
Curated repository of AI-powered applications and agentic systems showcasing practical use cases of LLMs
👉 Check this out: https://t.co/pR5riPhGDO
2. Hands on Large Language Models
This repository contains the complete code examples from the book Hands-On Large Language Models.
It includes notebook examples that cover everything from the introduction to language models to fine-tuning them.
👉 Check this out: https://t.co/TuFg99vK5o
3. AI Agents for Begineers
Beginner friendly course on AI Agents
This Free 11-lesson course will teach you everything you need to get started with building AI agents.
👉 Check this out: https://t.co/UHk9lCk18P
4. GenAI Agents
This repository provides tutorials and implementations for various Generative AI Agent techniques, from basic to advanced.
It serves as a comprehensive guide for building intelligent, interactive AI systems.
👉 Check this out: https://t.co/4c1JL0lZHe
5. Made with ML
Learn how to design, develop, deploy and iterate on production-grade ML applications.
Check this out: https://t.co/TBcsWr1DOi
6. Learn Harness Engineering
A project-based course on building the environment, state management, verification, and control mechanisms that make AI coding agents work reliably.
👉 Check this out: https://t.co/MfqVEA9hiB
7. AutoResearch by Andrej Karpathy
Learn how to build autonomous ML experiment loops where AI agents modify training code, run experiments, and iterate on their own.
This 630-line Python script shows you how to set up an agentic research workflow that runs ~100 experiments overnight on a single GPU. Practical implementation of autonomous research systems.
👉 Check this out: https://t.co/bfdhkX2u17
8. Designing Machine Learning Systems
This repo contains the summaries and resources for Designing Machine Learning Systems book
👉 Check this out: https://t.co/dBbKls3oOr
9. Awesome LLM Inference
Curated list of LLM/VLM inference papers with codes covering Flash-Attention, Paged-Attention, WINT8/4, Parallelism, and more.
Comprehensive resource for LLM inference optimization techniques including quantization, KV cache management, attention mechanisms, and deployment strategies.
👉 Check this out: https://t.co/Dtvkw7uwuR
10. LLM Course: The best hands-on course to learn Large Language Models with roadmaps and Colab notebooks!
👉 Check this out: https://t.co/dNJqw8a7pd
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