

Akash ML
53 posts

@akashnetAI
AI development will never be the same. Built by @ovrclk_ on @akashnet.





AkashAgents is built with pride by @waiting4ragi Use it to quick-deploy your Hermes and Openclaw agents on Akash complete with AkashML integration. agents.akash.network



Running agents is expensive. Rather than pay exorbitant frontier model prices, you can hook up your agent to @akashnet’s AkashML API and enjoy open models like Mini-Max 2.5 with near frontier benchmarks for a fraction of the price.

OpenAI reached an agreement with the Department of War @OpenAI plans to deploy its models inside the DoW’s classified network under strict conditions. Sam Altman says the department showed strong respect for safety and that the terms align with existing law and policy. The deal includes safeguards tied to OpenAI’s core principles, including bans on domestic mass surveillance and keeping humans responsible for use of force. It also requires technical controls requested by the DoW, cloud-only deployment, and dedicated oversight teams to ensure models behave as intended. Altman added that OpenAI wants similar standards applied across all AI companies and emphasized a preference for cooperation over legal conflict, saying the goal remains serving humanity in a complex and sometimes dangerous world.

🚨 Stanford just analyzed the privacy policies of the six biggest AI companies in America. Amazon. Anthropic. Google. Meta. Microsoft. OpenAI. All six use your conversations to train their models. By default. Without meaningfully asking. Here's what the paper actually found. The researchers at Stanford HAI examined 28 privacy documents across these six companies not just the main privacy policy, but every linked subpolicy, FAQ, and guidance page accessible from the chat interfaces. They evaluated all of them against the California Consumer Privacy Act, the most comprehensive privacy law in the United States. The results are worse than you think. Every single company collects your chat data and feeds it back into model training by default. Some retain your conversations indefinitely. There is no expiration. No auto-delete. Your data just sits there, forever, feeding future versions of the model. Some of these companies let human employees read your chat transcripts as part of the training process. Not anonymized summaries. Your actual conversations. But here's where it gets genuinely dangerous. For companies like Google, Meta, Microsoft, and Amazon companies that also run search engines, social media platforms, e-commerce sites, and cloud services your AI conversations don't stay inside the chatbot. They get merged with everything else those companies already know about you. Your search history. Your purchase data. Your social media activity. Your uploaded files. The researchers describe a realistic scenario that should make you pause: You ask an AI chatbot for heart-healthy dinner recipes. The model infers you may have a cardiovascular condition. That classification flows through the company's broader ecosystem. You start seeing ads for medications. The information reaches insurance databases. The effects compound over time. You shared a dinner question. The system built a health profile. It gets worse when you look at children's data. Four of the six companies appear to include children's chat data in their model training. Google announced it would train on teenager data with opt-in consent. Anthropic says it doesn't collect children's data but doesn't verify ages. Microsoft says it collects data from users under 18 but claims not to use it for training. Children cannot legally consent to this. Most parents don't know it's happening. The opt-out mechanisms are a maze. Some companies offer opt-outs. Some don't. The ones that do bury the option deep inside settings pages that most users will never find. The privacy policies themselves are written in dense legal language that researchers people whose job is reading these documents found difficult to interpret. And here's the structural problem nobody is addressing. There is no comprehensive federal privacy law in the United States governing how AI companies handle chat data. The patchwork of state laws leaves massive gaps. The researchers specifically call for three things: mandatory federal regulation, affirmative opt-in (not opt-out) for model training, and automatic filtering of personal information from chat inputs before they ever reach a training pipeline. None of those exist today. The uncomfortable truth is this: every time you type something into ChatGPT, Gemini, Claude, Meta AI, Copilot, or Alexa, you are contributing to a training dataset. Your medical questions. Your relationship problems. Your financial details. Your uploaded documents. You are not the customer. You are the curriculum. And the companies doing this have made it as hard as possible for you to stop.


Anthropic’s Claude Chatbot Goes Down for Thousands of Users bloomberg.com/news/articles/…










MiniMax-M2.5 is now available for managed inference on AkashML. As a 229B-parameter frontier AI model trained using large-scale reinforcement learning, M2.5 delivers state-of-the-art performance in coding, tool use, and complex real-world reasoning. This open-source model executes multi-step task decompositions and agentic loops 37% faster than prior generations. Deploy your first autonomous agent with $100 in free trial credits today → playground.akashml.com








AI Agent Builder Night w/ @akashnet & @aitxcommunity 📍 Austin, TX | 🗓️ Jan 14 🛠️ Build an AI agent in 90 minutes Register: luma.com/AIAgentBuildNi…

Wanted to test AkashML so I vibecoded a LinkedIn roaster with Claude Code. It calls you out for saying "passionate about driving synergies" 💀 Nothing fancy, just showing how easy it is to build AI stuff on Akash now. 🧵 Here's the whole setup: