Cortex

We are a technology-driven company focused on pushing the boundaries of artificial intelligence and software innovation.

[Cortex @CortexLM]

We’ve been accepted into the NVIDIA Inception Program! 💚

This will give Cortex access to NVIDIA’s expertise, resources, and ecosystem to help us accelerate our research and scale our AI infrastructure.

Huge thanks to NVIDIA for the support! 🚀

[OpenType AI @OpentypeAI]

Ours is already live on Bittensor: Neon 1.1 routes every task across 32 models by difficulty, and miners on Subnet 100 make it better every day, try it at https://t.co/tdwyxblLl6

[Cortex @CortexLM]

We’re continuing to build within the Bittensor ecosystem. We already have two products, https://t.co/mFYhOlB8Vs and https://t.co/WwEy5chcvi, that are available to use for free. Feel free to give them a try.

[OpenType AI @OpentypeAI]

Meet Neon 1.1 by OpenType.

A model built to decide, not to chat: hundreds of questions answered in one call, in milliseconds.

We ran it through 5 real tests. Every number in this thread comes from a logged run. 🧵

[Cortex @CortexLM]

@MasterChief_AI @cortex_100 soon :)

[Cortex @CortexLM]

Cortex is becoming a hub for subnets. More subnets will be added over the next few days.

[Cortex @CortexLM]

We're getting Cortex ready to sell to enterprises. Starting our security and compliance program.
https://t.co/AxNAxYhbaM

[templar @tplr_ai]

We just completed the largest decentralised LLM pre-training run in history: Covenant-72B. Permissionless, on Bittensor subnet 3.

72B parameters. ~1.1T tokens. Commodity internet. No centralized cluster. No whitelist. Anyone with GPUs could join or leave freely.

1/n

[Chutes @chutes_ai]

GLM-5 is LIVE on Chutes 🔥
@zai_org's new flagship. 744B params (40B active). Best-in-class open-source on reasoning, coding, and agentic tasks.
77.8% SWE-Bench Verified
73.3% SWE-Bench Multilingual
75.9% BrowseComp (w/ context manage)
50.4% HLE with tools
89.7% τ²-Bench
Try it now → https://t.co/UfEyZDz2gk

[basilica @basilic_ai]

Tau Ninja is running on Basilica.

basilica summon tau

You need just two environment variables. A Chutes API key for inference and a @telegram bot token from @BotfatherTG. That's the entire setup for @const_reborn's self-modifying AI agent on decentralized compute.

Under the hood, three subnets are each contributing their output to a single deployment.

Basilica (SN39) provisions and runs the container. This is the compute surface where everything comes together.

@chutes_ai (SN64) handles LLM inference. Every time Tau reasons about a task, plans its next action, or generates a response, that call routes through Chutes' decentralized inference network.

@platform_tao (SN100) provides the baseagent framework. The agent scaffolding, tool execution, and state management that make Tau an autonomous agent rather than a chatbot.

Because baseagent lives on a Bittensor subnet, miners are continuously incentivized to improve it. The agent framework itself gets better over time through market competition, and every agent built on it inherits those improvements.

That's what makes this a Bittensor-native agent rather than just an agent deployed on Bittensor.

Each subnet does one thing well. Basilica is the deployment layer that composes them into a working product. One command, seconds to deploy, and the result is a self-modifying AI agent running entirely on decentralized infrastructure.

https://t.co/QsbF2iNgTI

For support and setup help, join us on Discord: https://t.co/nIc9uofwS9

[templar @tplr_ai]

https://t.co/iT7EV0LKDA