🤝 Top Collaborators
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🤓 Latest Submissions
TableMate: Auditable Bimanual AI
TableMate is a simulation-first workstation for bimanual robotic manipulation. Given a dinner-table instruction and camera observations, it coordinates two simulated SO-101 arms in MuJoCo through a vision-language planner, a task supervisor, and bounded learned manipulation skills. The first release covers drawer opening, utensil retrieval, plate and cup placement, and physical object hand-off between the arms. The system is designed for reliable, inspectable operation rather than hidden demonstrations. Grasping and hand-offs are represented through physics contacts; objects are never teleported or artificially attached. The supervisor owns task state, arm assignment, prerequisites, timeouts, action validation, cancellation, and recovery. Every attempt records synchronized observations, actions, camera frames, simulation time, wall-clock time, contacts, failures, and artifact hashes. We train LeRobot ACT policies from contact-based scripted teacher demonstrations and keep simulator ground truth separate from deployed camera and joint observations. The repository includes versioned contracts, native Apple Silicon setup, reproducible CLI workflows, run manifests, dataset lineage, a FastAPI operator portal, a React interface, GitHub Actions checks, and a public learning website that teaches the robotics concepts alongside the build. Our local evidence demonstrates a complete contact-based teacher foundation, successful corrective demonstrations, ACT training, planner and supervisor integration, and fail-closed safety behavior. During learned physical evaluation, the system correctly stopped when a placement trajectory exceeded the workbench-overlap limit instead of silently claiming success. This failure is preserved as auditable evidence and used to define corrective data. Intel Core Ultra/OpenVINO execution is the next hardware-validation gate; no unsupported Intel result is claimed.
16 Sep 2026
Stable Income Generator
Stable Income Generator is an automated, paper-only options trading platform built around our QQQ Option wheel strategy. We selected QQQ because technology is a long-term driver of economic development, then backtested the strategy over 644 sessions and compared its equity path and risk metrics with SPY and QQQ buy-and-hold benchmarks. The live V13.5 canary runs against an Alpaca paper account. Our public dashboard publishes sanitized broker-reported equity, P&L, freshness, and the ten most recent system fills on a five-minute weekday schedule, while keeping credentials and trading controls private. Trading authority remains deterministic and auditable: configuration-driven strategy logic, sizing, risk approval, execution preflight, reconciliation, and hash-bound records control every executable decision. The broader platform adds an economics-aware Gemini 3.6 Flash advisory gate that can only allow the unchanged deterministic proposal or veto it; it cannot rewrite an order or bypass risk limits. Role-specific containers, internal PostgreSQL state, and portable deployment make the system straightforward to reproduce locally or move to a VM or cloud environment. Judges can inspect our backtest artifacts, architecture diagrams, live paper evidence, and credential-free replay workflow.
4 Sep 2026
BEG Digest by Boston Eating Group
BEG Digest stands at the intersection of innovation and efficiency, a cutting-edge AI-powered application built by the Boston Eating Group. The app transforms voice into text and then leverages advanced language model technology to craft summaries from the converted text. Designed for the modern learner, podcast enthusiast, or any individual looking to streamline their content absorption, BEG Digest turns lengthy lectures or podcast episodes into bite-sized overviews in mere minutes. Whether you're revising from class recordings or want a quick rundown of your latest podcast episode, our app makes the task a breeze. It's the perfect tool for optimizing your time and enhancing knowledge retention. Immerse yourself in the world of AI-driven learning, redefining the way we consume and understand information in the digital era. BEG Digest: Listen, Transcribe, Summarize, and Absorb.
10 Jul 2023
