SUMAN SHAKTI@sumanshakti1040287

Alpha Hunter is an autonomous AI trading scientist built to close the loop between quantitative research, strategy validation, portfolio allocation, and execution. Instead of simply asking an AI what to buy, Alpha Hunter first asks whether a trading strategy actually has a robust edge. The system discovers strategy hypotheses and evaluates them using market data, historical performance, out-of-sample validation, robustness analysis, and market-regime compatibility. An adversarial AI layer then attempts to break promising strategies by looking for weaknesses such as overfitting, instability, regime dependence, concentration, and poor generalization. Surviving strategies receive an Edge Score and can compete for capital through Alpha Hunter's adaptive allocation engine. Allocation considers strategy quality, risk, volatility, portfolio exposure, correlation, market regime, and current opportunity rather than blindly increasing every position. Alpha Hunter supports equities, ETFs, and crypto. Crypto is not permanently excluded; when its risk-adjusted opportunity deteriorates, the system can pause new allocation while continuing to monitor existing positions. A deterministic risk engine acts as a safety layer between AI recommendations and execution. It enforces portfolio and position constraints while allowing profitable positions to use adaptive trailing protection designed to protect accumulated gains and let strong trades continue running. The execution layer connects to Alpaca Paper Trading. Current positions, quantities, orders, P&L, and broker execution states are reconciled with Alpaca rather than being simulated in the UI. The result is a complete autonomous trading research loop: Discover → Test → Challenge → Score → Allocate → Execute → Monitor → Learn. Alpha Hunter is designed not merely to generate trades, but to continuously determine which strategies deserve trust and where capital has the best risk-adjusted opportunity.

🌎 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 | 💻 Month-long challenge | Dates: Sep 1–30, 2026 | 🏆 $10,000 Prize Pool ($5k cash + $5k in AAI credits) A month-long online challenge run by lablab.ai together with AssemblyAI, the Voice AI infrastructure company for builders. Every participant builds on AssemblyAI. You can join at any point — registration stays open for the whole build window, so you can start on day one or pick the project up halfway through and still submit. 🌍 Fully online hackathon. Join and build from anywhere in the world.

🌎 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.