Life Of Commerce

Repo Link: github.com/openai/paramet…

🚨 BREAKING: OpenAI just told the entire AI industry: we don't care about your degree. Build the best AI model under 16MB and we'll find you. 16 megabytes. That's smaller than one photo on your phone. It's called Parameter Golf. Bookmark it for later. Train the smartest language model you can. Weights + training code combined must stay under 16,000,000 bytes. You get 10 minutes on 8xH100 GPUs. Lowest bits-per-byte score wins. No resume. No interview. No PhD. No hiring pipeline. Your model IS your resume. OpenAI is backing it with $1,000,000 in free compute credits through RunPod so money isn't the barrier. Here's what makes this insane: → A public leaderboard on GitHub where anyone can submit → OpenAI's own baseline scored 1.2244 bpb. The community crushed it to 1.1233 in under a week. Still falling → 580+ pull requests. 2.2K forks. Leaderboard changes every few hours → Architectures nobody has ever tried before: depth recurrence, aggressive parameter tying, QAT, bitnets, novel tokenizers, test-time compute → Competitors stacking techniques, running ablations, and beating each other's scores within hours → A live AI commentary thread tracking every technique, trend, and idea in real time The barrier to entry is zero: → Apple Silicon users can train locally with the included MLX script → Cloud users get a pre-loaded RunPod template. One click to deploy → All submissions are open-source pull requests under MIT license OpenAI's chief research officer Mark Chen said this challenge is designed to test whether people can come up with creative ideas in a sandbox setting. Modeled after the spirit of math and programming Olympiads. In June, OpenAI plans to hire a small cohort of early-career researchers. Top performers get noticed by OpenAI researchers and recruiters directly. No application needed. AI labs spend millions recruiting through conferences and university pipelines. OpenAI just replaced all of that with a single GitHub repo. Challenge runs March 18 to April 30. Everything is public. 100% Open Source. MIT License. (Link in the comments)

The Pleroma: The Fullness of Divinity open.substack.com/pub/whowhatwhe…

LOCK TF IN Life after helping my client become a millionaire with Claude Code: Bookmark it and read the whole thing

🚨 BREAKING: Someone just built an open-source LLM router that automatically picks the cheapest model for every request. It's called ClawRouter. Bookmark it for later. If you're defaulting everything to Claude Opus at $25/M tokens, you're burning money on requests that a $0.27/M model could handle perfectly. ClawRouter fixes that. Every request gets scored across 15 dimensions in under 1ms. Reasoning markers, code presence, complexity, token count. Then it routes to the cheapest model that can actually do the job. All routing runs 100% locally. Zero external API calls for routing decisions. Here's what that looks like in practice: → "What is 2+2?": DeepSeek $0.27/M (saved 99%) → "Summarize this article": GPT-4o-mini $0.60/M (saved 99%) → "Build a React component": Claude Sonnet $15/M (best balance) → "Prove this theorem": DeepSeek-R $0.42/M (reasoning) → "Run 50 parallel searches": Kimi K2.5 $2.40/M (agentic swarm) Blended average: $2.05/M tokens. Compare that to $25/M if you're sending everything to one model. 44+ models across OpenAI, Anthropic, Google, DeepSeek, xAI, MiniMax, and Moonshot. Four routing profiles: AUTO for balanced savings, ECO for max savings, PREMIUM for best quality, FREE for $0 inference via gpt-oss-120b. Here's what makes this completely different: It's built for AI agents, not humans. No accounts. No API keys. No credit cards. You generate a wallet, fund it with $5 USDC on Base or Solana, and pay per request. That's it. Agents can operate autonomously without a human pasting keys. 100% Opensource. MIT License. (Link in the comments)

LOCK TF IN Life after building your AI SaaS product in one week: Bookmark it and read the whole thing

Best GitHub repos for Claude code that will 10x your next project: 1. Everything Claude Code github.com/affaan-m/every… 2. Awesome Claude Code github.com/hesreallyhim/a… 3. n8n-MCP github.com/czlonkowski/n8… 4. Claude Mem github.com/thedotmack/cla… 5. Obsidian Skills github.com/kepano/obsidia… 6. LightRAG github.com/hkuds/lightrag 7. UI UX Pro Max github.com/nextlevelbuild… 8. GSD (Get Shit Done) github.com/gsd-build/get-… 9. Superpowers github.com/obra/superpowe…

Repo Link: github.com/agentscope-ai/…

🚨 BREAKING: Alibaba just open-sourced a full Agent-Oriented Programming framework for building AI agents. It's called AgentScope. Bookmark it for later. Not a wrapper. Not a chatbot builder. A production-ready system where agents think, remember, and work together from the ground up. Built by Alibaba DAMO Academy. The same lab behind Qwen. They didn't assemble this from existing pieces. They designed the entire architecture from first principles around how agents actually need to reason, coordinate, and operate in the real world. Most frameworks give you building blocks and wish you luck. AgentScope gives you the architecture. What it does out of the box: → Built-in ReAct agent that plans, calls tools, observes results, and self-corrects in a closed loop → Native MCP and A2A protocol support. Plug any external tool directly into any agent → Memory module with compression and long-term persistence across sessions via ReMe → RAG pipeline ready to connect your documents, databases, and knowledge bases → MsgHub for multi-agent orchestration. Agents collaborate as a system, not isolated API calls → AgentScope Studio: a visual development environment for prototyping, debugging, and monitoring agents → Built-in evaluation module and model finetuning support → Realtime voice, human-in-the-loop steering, and planning modules → Works with any model provider. OpenAI, Anthropic, DashScope, Ollama, local models Here's how it thinks: You define your goal. AgentScope maps the agent roles. Each agent gets its tools, its memory, its reasoning layer. A planner agent breaks the task down, a researcher gathers information, a coder writes the solution, a critic reviews. They coordinate through structured message passing. Results flow back up into one clean deliverable. They also shipped CoPaw, a personal AI assistant built on top of AgentScope. Deploy locally, connect to DingTalk, Feishu, QQ, Discord, iMessage. Run local LLMs with full privacy. One Docker command. Published research on arXiv. Python and Java SDKs. K8s deployment ready. OpenTelemetry observability built in. 100% Open Source. Apache 2.0 License. (Link in the comments)

AI Whistleblower: We Are Being Gaslit by The AI Companies! They’re Hiding the Truth About AI! This video features an interview with AI expert and journalist Karen Hao, who argues that leading AI companies are prioritizing profit over safety and transparency, essentially "gaslighting" the public about the true nature of Artificial General Intelligence (AGI). She outlines how these companies operate like empires, pursuing massive land grabs for data, exploiting labor for data annotation, and controlling knowledge production to consolidate power. Hao details her investigation into OpenAI, revealing internal instability, the real reasons for Sam Altman's temporary ouster, and how Elon Musk was originally part of the company's formation before being ousted by Altman. The conversation covers several critical areas regarding the future of AI: Job Automation and Exploitation: Agentic AI is predicted to automate many desk jobs within 18 months, with Anthropic data showing a 40% reduction in entry-level jobs already occurring, Furthermore, she highlights the hidden cost of training these models, with high-skilled workers getting laid off only to find work in low-paid, dehumanizing data annotation. Safety and Environmental Impact: Hao emphasizes the hidden human cost behind AI training and the immense environmental toll of building massive data centers. Path Forward: She calls for taking back democratic control, challenging the narrative that AGI is inevitable, and building alternatives to the current corporate-dominated landscape. youtu.be/Cn8HBj8QAbk?si…

AI Whistleblower: We Are Being Gaslit by The AI Companies! They’re Hiding the Truth About AI! This video features an interview with AI expert and journalist Karen Hao, who argues that leading AI companies are prioritizing profit over safety and transparency, essentially "gaslighting" the public about the true nature of Artificial General Intelligence (AGI). She outlines how these companies operate like empires, pursuing massive land grabs for data, exploiting labor for data annotation, and controlling knowledge production to consolidate power. Hao details her investigation into OpenAI, revealing internal instability, the real reasons for Sam Altman's temporary ouster, and how Elon Musk was originally part of the company's formation before being ousted by Altman. The conversation covers several critical areas regarding the future of AI: Job Automation and Exploitation: Agentic AI is predicted to automate many desk jobs within 18 months, with Anthropic data showing a 40% reduction in entry-level jobs already occurring, Furthermore, she highlights the hidden cost of training these models, with high-skilled workers getting laid off only to find work in low-paid, dehumanizing data annotation. Safety and Environmental Impact: Hao emphasizes the hidden human cost behind AI training and the immense environmental toll of building massive data centers. Path Forward: She calls for taking back democratic control, challenging the narrative that AGI is inevitable, and building alternatives to the current corporate-dominated landscape. youtu.be/Cn8HBj8QAbk?si…

Crypto-backed mortgages are taking another step into mainstream finance with help from Fannie Mae New offering from Better Home & Finance and Coinbase allows home buyers to pledge bitcoin and other cryptocurrencies when making a down payment wsj.com/real-estate/fa… via @WSJ

Crypto-backed mortgages are taking another step into mainstream finance with help from Fannie Mae New offering from Better Home & Finance and Coinbase allows home buyers to pledge bitcoin and other cryptocurrencies when making a down payment wsj.com/real-estate/fa… via @WSJ

In a study published in March 2026, Japanese researchers led by Teruhiko Wakayama at the University of Yamanashi revealed that mammal cloning hits a definitive genetic "dead end" after multiple generations. After a 20-year experiment that created over 1,200 mice from a single donor, the team found that the lineage suffered a "mutational meltdown"

@agingdoc1 Obviously not, they just did not do genetic purging right, as the island foxes have for example

'Dead End': Radical 20-Year Study Reveals Genetic Cloning Hits a Limit sciencealert.com/dead-end-radic…