Muhammad Yousuf Maqbool@myousufk8737941

DUET turns a spoken sentence into coordinated two-arm manipulation. Say "Set the dinner table." and DUET transcribes it live with Speechmatics, parses it into structured intents, plans a dependency graph of arm actions, and executes it with both arms running concurrently: 27 steps, 3 hand-offs, 2x parallelism. Three things make that harder than it sounds. PRECONDITIONS. The cutlery starts inside a closed drawer, so it must be opened first, exactly once, however many later steps depend on it. Nothing instructs the planner to do this; it falls out of the dependency graph. HAND-OFFS THAT ARE FORCED, NOT SCRIPTED. Each place setting is verified at scene-generation time to sit inside exactly one arm's reach envelope, so moving an object across the table is physically impossible single-armed. When the holding arm cannot reach the destination and the other can, the planner inserts a give/take transfer. 28 hand-offs were required across 40 benchmark runs and none are special-cased. ROBUSTNESS. Placement, mass, friction, shape and lighting are randomized per seed. Grasps can genuinely fail, and failures propagate rather than being silently ignored. The planner is deterministic and no language model sits in the action path. A model may explain a plan; it never chooses one. The same sentence against the same seed yields a byte-identical plan, and the test suite enforces it. Measured: 39 of 40 seeded evaluation runs succeed (98%) in DUET's deterministic simulator, where success requires the command to plan with no errors, every step to execute, AND the world to end in the requested state. 53/53 automated tests pass. No physical robot is involved or claimed, and no OpenVINO or Intel Core Ultra execution is claimed. Runs entirely in the browser: no install, no sign-up, no microphone needed.

ThesisCircuit asks a different question from most trading agents: not “Can an AI generate a trade?” but “Can it produce a decision that remains safe, explainable, and idempotent under real operating conditions?” Three deterministic agents—Trend, Range, and Defensive—independently analyze current Alpaca market and options data. A Decision Council compares their typed theses, a Critic challenges stale evidence and hidden assumptions, and a deterministic risk governor has the final vote. Agent language can never override a rejection. NO TRADE, shadow ideas, and counterfactuals are preserved as first-class evidence without being shown as real broker activity. ThesisCircuit uses Alpaca’s official alpaca-py SDK and PAPER endpoint only. Supabase provides an RLS-protected audit trail, durable cycle locks, atomic order-intent claims, restart recovery, and bounded execution-session budgets. Railway hosts the FastAPI control plane, while the Vercel dashboard exposes account state, agent debate, risk decisions, the actual paper order lifecycle, and clear disclosures. The system proved its complete path with exactly one authorized opening order: one SPY Sep 4 $768 long call, submitted as a DAY limit at $1.88 and filled by Alpaca PAPER at $1.84. The planned maximum premium risk was $188. The proposal, 18-gate risk decision, fill, resulting position, and trace were persisted and rendered in production. No additional or closing order was placed. Production now rests fail-closed with execution and autonomous trading disabled. Bounded activation, shutdown, lock recovery, duplicate prevention, and eight-worker race behavior were verified synthetically with zero additional broker calls. SIMULATED PAPER TRADING — NO REAL FUNDS. Results are hypothetical and are not investment advice. Options carry significant risk, and all investments involve risk.

CaptionForge AI is a Fireworks-powered video captioning prototype built for AMD Developer Hackathon Act II, Track 2. The app helps creators turn short videos into multiple ready-to-use caption styles without manually brainstorming different tones. A user uploads a short clip, optionally adds context or a transcript, extracts five representative preview frames, and generates four caption styles: formal, sarcastic, humorous-tech, and humorous-non-tech. The system uses Fireworks Vision through a secure Next.js API route to read sampled video frames and produce captions, a visual summary, and a safety note. If the selected vision model is unavailable, the app can fall back to Fireworks Text using the user-provided context, and if Fireworks is unavailable entirely, it keeps the demo running with mock captions. The goal is not to replace human judgment. CaptionForge AI is designed as a creative assistant where the user still reviews every caption before publishing. The interface clearly includes responsible AI notes, warns users not to misrepresent people or events, and avoids unsupported claims such as audio analysis or identity recognition unless the user provides that information. The project is built with Next.js, TypeScript, Tailwind CSS, Fireworks AI, and a Docker-ready production setup. It demonstrates a practical workflow for short-form video creators: upload, sample frames, generate captions, review, and copy.

🌎 Hybrid Hackathon | 💻 Online Build: September 10–16, 2026 | 📍 On-site: September 15–17, 2026 The official hackathon of AI Infra Summit — co-organized by Kisaco Research and lablab.ai. Build production-grade AI applications on the modern AI infrastructure stack, alongside 8,000+ attendees, researchers, founders, and infra leaders. 📍 On-site Venue (September 15–17): Santa Clara Convention Center 5001 Great America Pkwy, Santa Clara, CA 📍 On-site participation is by invitation only. Travel and accommodation expenses will not be covered.

🌎 Online Hackathon | 💻 Dates: 28 August–4 September 2026 | 🏆 $6,000 Prize Pool Build AI trading agents on Alpaca — autonomous agents and trading apps using Alpaca's Trading API, MCP server and CLI. 🌍 Fully online hackathon. Join and build from anywhere in the world.

To participate in the hackathon, simply click Sign up with AMD. If you are not already a member of the AMD AI Developer Program (ADP), you will need to create an account. ADP members can access AI tutorials, experts, and community support. In addition, new members can claim a free month of DeepLearning.ai pro, $100 in AMD GPU cloud credits, and $50 in Fireworks AI API credits. All hackathon participants will receive on hackathon launch additional compute and API credits for their projects. Ready to build what's next on AMD? Sign up with AMD below to secure your spot.