0xdaveeee
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@0xdaveeee__
|| Ghost-Writer • Threador • Trader • TG Moderator👤 || DeFi Researcher 🔬|| Pro Raider/Shiller • DM for my services 📩
Community News! As part of this next phase, we’ve invested in strengthening our community operations. We’re pleased to announce that @CryptoManicc and @HardwireMedia are joining Praxis as Community Managers to lead community efforts moving forward. Together, they bring 15 years of experience across crypto, developer communities, and ecosystem growth. They will be responsible for community building and coordination around announcements and partnerships, with a clear goal to help build a strong, resilient community that will back Praxis’s growth in 2026 and beyond. We are very excited to take this next step which marks the beginning of a great 2026 Wish them a warm welcome. PRAXIS
Prediction markets process over $75B annually. Yet 2.5M+ traders still lack a single interface to make informed bets. That just changed with pulseterminal.io
Gradient $GRAY Burn #6 Recent trading volume on the Gradient has funded the acquisition and burn of 12,000 $GRAY tokens. Track our burns on Dune. dune.com/usethegradient
there is no way a 9-5 job is worse than what we have gone through in last 30 days in finance markets
The Gradient APIs are now live. Protocols can now fetch real-time Gradient exchange data, orderbooks, & liquidity stats. This will allow for the integrations of our exchange within third-party platforms— becoming our main focus following the full release of the Gradient. View the documentations below. docs.gradient.trade/gradient-api/a…
Over the past few months, most of the heavy work has happened behind the scenes. Our focus has been on setting the foundation for the full Setary ecosystem to operate smoothly and scale securely. That meant building four key layers: AI infrastructure, the RWA pipeline, real-time data flow and indexing, and backend stability. Each piece connects to ensure Setary can process on-chain and off-chain data seamlessly and compliantly. A dedicated team across AI, blockchain, legal, product, and business development has been driving this work. Once the token is live, we’ll share more about how each layer comes together under Setary’s architecture. For now, we’re focused on building what comes next.
VLA Fine-tuning Module Update A. Fine-Tuning Pipeline Enhancements - Added default configurations and state management for multiple optimizers, including SGD, SGD with Momentum, Adam, and AdamW, enabling end-users to experiment with different optimization strategies. github.com/RoboraDev/VLA_… - Integrated several learning rate scheduler wrappers -> StepLR, CosineAnnealing, LinearDecay, and ExponentialDecay, allowing seamless selection and comparison through Wandb for fine-tuning analytics. github.com/RoboraDev/VLA_… - Default implementations for Pi0, Pi0.5, and SmolVLA support a maximum action and observation dimension of 32. For high-complexity robotic agents such as Humanoid, the action encoder, state encoder, and action decoder feature dimensions will need to be scaled accordingly, these can be done easily as these are 3 lines of pytorch code but have to be implemented from scratch. For each model, this will be specified inside config.py and the corresponding WithExpert.py file will inherit it. github.com/RoboraDev/VLA_… B. PI0 Policy Implementation - Implemented the Pi0 Policy architecture in PyTorch, referencing the Physical Intelligence OpenPI repository for core design principles & configurations. - Implemented PI0Config, will also be added yaml, json support for custom configs in fine-tuning. github.com/RoboraDev/VLA_… C. VLA Util helper functions Implementation - get_device_info, torch_device, device_name for accelerators - JSON Serialize & deserialize functions to store the optimizers state on disk. - Parameters utility helpers : get device, dtype, output shape etc github.com/RoboraDev/VLA_… Plan for Tomorrow: - Support for SmolVLA and Pi0.5 will be implemented next, as these architectures share a common Vision-Language Model (VLM) architecture with minor variations in module structure and feature dimensions. - Lerobot dataset framework integration for dataset management: will integrate online dataset as a Proof-of-concept.
$SET will power the entire Setary ecosystem. It will fuel staking for rewards or lower fees, fund compliance services, unlock AI agent access, and enable governance, allowing holders to vote on upgrades, asset onboarding, and platform direction. As adoption grows, demand for $SET will increase, while buybacks and burns will continually reduce supply. This creates a self-reinforcing cycle where adoption drives demand, reduced supply strengthens value, and the flywheel accelerates overall ecosystem growth. Launch coming soon, marking the beginning of a self-sustaining growth cycle powered by $SET.
