Tensorplex Stake & Bridge have been deprecated. To prioritise safety, users will have to manually withdraw their existing balances. Please visit the staking page for more details. Should you wish to stake on Bittensor, visit @BackpropFinance Thank you for being part of this!

The Bittensor Conclave @ Token 2049 Singapore, featuring subnet owners @const_reborn, @macrocrux, @6329, and @DistStateAndMe Happy to see miners, validators, builders and investors coming together to share their vision on what the future of decentralised AI will look like!

The future of decentralized intelligence converges in Singapore. Bittensor Conclave @ Token2049 Singapore 📍 October 1, 2025 · 4–8pm SGT Where subnets meet. Where builders unite. Where TAO accelerates. ➤ State of Bittensor ➤ Subnet presentations ➤ Panels & networking Subnets are building. The community is uniting. TAO is accelerating. 🔗 Secure your spot: lu.ma/0a2ye5or

Potential use-cases for DOJO-INTERFACE-CODER-7B: - Adaptive educational interfaces - Privacy-centric customizable journaling tools - Dynamic UIs for enhanced human-AI collaboration 6/8

Surprisingly, human-driven training (DPO) also boosted performance on general coding benchmarks like HumanEval and MBPP, even though training focused solely on UI tasks. 5/8

Adding a 12.5k-completion DPO dataset evaluated by human contributors significantly improved UI alignment with real user preferences. The DPO-trained model clearly outperformed the SFT version in human evaluations. 4/8

Here's how it works: - Validators on Dojo network generate diverse UI outputs using advanced AI models. - Human evaluators (miners) rate these UIs based on aesthetics, interactivity, and alignment with the intended task. - Feedback is collected into specialized datasets (SFT and DPO) to further enhance training. 2/8

🚀 Tensorplex Dojo (Subnet 52) in action! Meet DOJO-INTERFACE-CODER-7B: Qwen2.5-Coder-7B-Instruct, fine-tuned with Dojo datasets to craft stunning front-end UIs! ✨ Generates beautiful, interactive interfaces ✨ Trained on synthetic data with distributed human feedback ✨ Powered by dojo.network (Subnet 52) on Bittensor 👇

Tensorplex Labs will be representing the Bittensor community at the SuperAI exhibition Singapore 18-19 June, alongside @inference_labs @tplr_ai @404gen_ @TeamRizzoAI @GraphiteSubnet 👇

Excited about solving frontier problems in open-source reinforcement learning? Tensorplex Labs is hiring Research Engineers focused on: 1. Scalable synthetic data generation 2. Open, attack-resistant human feedback collection 3. Seamless human-AI task delegation & hallucination detection If you're keen to explore any of these topics, send over your background & publications via DM.

2/ What is Kami? Written in TypeScript, Kami is built from the ground up to interact directly with Bittensor chain using Substrate Runtime API with robust error logging. Kami addresses key challenges during subnet development to allow builders to focus on pushing AI forward.