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No Justice No Peace
When Corrupt Politicians Start Going To Jail, Then We Can Start Trusting The Government Again.
ECP NetHappenings AI is failing and owes us money
Andrew Yang is right. Taxing AI companies will be a cornerstone of a post-labor economy.
But we should go further.
AI was trained on our data, our writing, our code, our images. Society created the raw material.
So society should own a piece of it.
Not just taxes. Shared ownership and AI dividends.
If AI becomes the most productive technology in history, the wealth it creates should flow back to the people who helped create it.
https://x.com/VraserX/status/2032888994720264273
@Surrealist888
https://x.com/Surrealist888/status/2032622088499114106
My comments on this article: “We live in a world where A.I. companies are grabbing every bit of writing, art and music without consent.”
This is the foundation on which we should judge generative AI. It does not belong to the corporations who stole our entire culture without consent. Our work, our writing, our art, our compositions, our poetry belong to us. Our right to own our own output must be the primary consideration. Our expressions, our imaginations, our deeply felt sense of being alive and gifting that to the world though our creativity should not be exploited by corporations.
Creativity is what makes us human. We must fight against machine exploitation and hold on to our shared humanity and our priceless human art and writing.
Gift Article
Insane A complete 7-week Agentic RAG bootcamp was just open-sourced.
https://x.com/thetripathi58/status/2032911740447633460
AI academies charge $10,000 for this curriculum. You can get it for free.
It covers everything from basic keyword search to building production-grade Agentic RAG systems with LangGraph. This is not a toy project tutorial. It is a full production pipeline.
Here is what is inside:
– 7 weeks of building an AI research assistant from scratch
– Complete infrastructure setup with Docker, FastAPI, and PostgreSQL
– Production keyword and hybrid search using OpenSearch
– Local LLM deployment with streaming responses
– Production monitoring with Langfuse tracing and Redis caching
– Agentic workflows using LangGraph and Telegram bots
Here is the core value:
It forces you to build the way successful companies do. You do not just jump to vector search. You build solid search foundations first, then enhance with AI. Theory and practice in one place. Thousands of developers are using this to master production AI.
Summary of the Production Agentic RAG Course:
– It gives you a senior AI engineer curriculum for free
– It bridges the gap between basic RAG and production systems
– It forces you to build an actual end-to-end portfolio project
You still have to write the code. It just removes the guesswork.
https://github.com/jamwithai/production-agentic-rag-course
Researchers just surveyed 1,500 workers and 52 AI experts and discovered that 41% of everything companies are currently automating with AI falls into what they call the “unwanted or impossible” zone.
Businesses are spending billions automating the wrong things.
The study introduced something called the WORKBank database, which maps worker desires against actual AI capabilities across 844 tasks spanning 104 occupations.
https://x.com/Whizz_ai/status/2032751126202962252
FREE TO BUILD
FREE FROM HARVARD
@heynavtoor
Harvard just open sourced the entire textbook they use to teach Machine Learning Systems.
It’s called Machine Learning Systems (MLSysBook.)
A full, free textbook that covers everything from training models on a single GPU to deploying them at production scale.
This isn’t a blog post. This isn’t a YouTube playlist. It’s the actual course material Harvard students use. Now anyone can access it.
Here’s what’s inside:
→ 15+ chapters covering the full ML systems lifecycle
→ 50+ hands-on lab exercises
→ A framework called TinyTorch that teaches you to build ML infrastructure from scratch
→ Real hardware labs on Arduino and Raspberry Pi
→ Data processing, model training, deployment, and monitoring
→ Volume I covers single-machine ML (1 to 8 GPUs)
→ Volume II covers distributed systems and production infrastructure
Here’s the wildest part:
It comes with actual hardware kits. You don’t just read about edge computing. You deploy models on real devices. Arduino, Raspberry Pi, and other edge hardware. Theory and practice in one place.
Over 100,000 students and educators have already used this material worldwide.
This is what people pay $60K/year in tuition to access.
It’s completely free.
Jeffrey Epstein saying Donald Trump would begin bombing Iran if “cornered like a rat.”
“You guys need to understand that he is psychotic,” Epstein warned.
https://x.com/AmberWoods100/status/2032645997046698196/photo/2
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