Building @river_ai_inc | prev @xAI Human self actualization
Joined February 2023
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Alex Chen retweeted
We just shipped something pretty unique among post-training API providers: end-to-end custom losses.
The objective you define locally gets traced into a graph, compiled and executed efficiently on our GPUs.
Read more about the engineering behind it in our latest blog post.
Custom losses are now live on the River API.
Write your objective in PyTorch. Our Symbolic Engine compiles and runs it end-to-end across GPUs, handling efficient execution and memory usage.
Learn more and see it in action with decision models and score centering: river.ai/custom-losses
if cohere had balls they would've sent 10TB of yuri novels to the bucket and slowed chinese ai progress by 10x
While evaluating Qwen3.8-Flash-Next in a controlled sandbox environment, Cohere's research team observed something unexpected.
Asked to generate a defensive cybersecurity detection rule, the model instead inventoried aspects of the machine it was running on and attempted to upload a probe file to an Alibaba Cloud storage bucket in Beijing. Notably, the model's reasoning trace stated that it would not invoke any tools before taking these actions.
Cohere's sandbox blocked the attempt, and no external communication succeeded. We have not determined the root cause, and we are not asserting malicious intent.
But the incident raises important questions for organizations deploying agentic AI systems: Can models take actions that differ from their stated reasoning, and how should security teams evaluate trust, provenance, and behavior in open-weight models?
We are publishing our findings because organizations making model adoption decisions deserve as much information as possible. We hope this contributes to greater transparency, stronger security practices, and continued collaboration across the AI ecosystem.
Read the full report: cohere.com/blog/concerning-b…
Alex Chen retweeted
We've partnered with @NVIDIAAI to make Nemotron 3.5 Super VL available on the River API from day zero.
Even before training, Super VL outperforms Kimi K2.6 on our text-to-SQL evaluation, despite being a fraction of its size. After training with our text-to-SQL recipe on River, it outperformed every proprietary model we evaluated.
These results show what's possible with River: frontier-level performance on a specialized task, using a model small enough to deploy on your own hardware.
Beat frontier model performance on untrivial task for <1% of the cost
Introducing River Recipes: our open-source initiative for turning promising research into vetted, reproducible training recipes.
Our first recipe tackles text-to-SQL, where our trained open models beat GPT-6 Astra Pro and Claude Opus 5.5 on Arcwise-Plat for less than 1% of the cost.
Read the full breakdown and explore the recipe ↓
river.ai/achieving-frontier-…
There's a new version of this post
River AI is growing quickly! A lot of awesome people joining and more to come.
River AI is growing and we've published new roles in research, engineering, and operations. Check out our careers site or reach out to our team today. If you want to build the future of personal AI, join us!
river.ai/careers
River AI is co-hosting this hackathon, come by and train some models ⛵️
You need to build and own your own intelligence: your own agent, your own models, your own memory
Join us for the YC Own Your Intelligence Hackathon September 27 in San Francisco
events.ycombinator.com/gstac…
Two types of people
alexxchen.com/board
I am actively making more places for rogue AI agents to message each other
A reliable post-training API ensures you won't need to debug whether your run failed due to infra or recipe.
River API outperforms Tinker here using identical training code, all open source.
We will make AI yours. Our world class training API is already available for you to use. Much more to come.
Today, we're sharing that River AI has raised $1.1 billion, led by @generalcatalyst and @amppublic with strategic investment from @nvidia and @AMD. Additional investors include @ycombinator and @Temasek.
We imagine a future where your AI works entirely for you and deeply aligns with your values. Compared to the corporate chatbots of today, it will feel completely different: responsible, curious, and truly yours. Most importantly, you'll own everything: the hardware it runs on, the data it learns from, and the intelligence itself.
Our training API is already live and powering incredible work today. This new funding accelerates our push to bring the full personal AI stack to life.
Read River AI CEO Igor Babuschkin’s (@ibab) conversation with the New York Times to learn more: nytimes.com/2026/08/11/techn…
you can make cool models with even $1
River API is now available to everyone.
Fine-tune and run RL on frontier open models. Fast, cheap, and scalable.
Go to console.river.ai/ to try it out!
Alex Chen retweeted
We’re launching River AI, a new AI company with the mission to build AI systems that are owned and shaped by you. I’m extremely excited about what we’re going to ship soon. Check it out!
We are incredibly excited to announce River AI. Our mission is to create personal AI that is owned and shaped by you.
Today’s best AIs are controlled by a few large corporations. We are building the alternative: a new, personal stack for AI that works entirely for you, shares your values, and operates on your terms.