Muhammad Faizan Fareed@Faizan_Fareed

Voice Action Gate is a security layer for AI voice agents that prevents sensitive actions from being executed based on guessed, missing, or ambiguous intent. It verifies that required parameters were explicitly provided, checks risk and confirmation requirements, and blocks unsafe requests before they reach protected tools. The system separates AI understanding from authorization, maintains an audit trail, and demonstrates secure workflows such as deployments, database actions, and simulated fund transfers. Its goal is simple: AI may understand what you mean, but it should only act on what you clearly authorized. :chatgpt-content-reference{index="0"}

Inspiration In 2016, a landmark research paper proved that human crowds design significantly better robots when they can observe and iterate on each other's work ("Social" condition) compared to working in isolation ("Independent" condition). The social group unlocked a hidden "design quality" factor—largely driven by symmetry—that helped their robots walk farther. With the rise of agentic workflows, we asked a fundamental question: Does the "wisdom of the crowd" still hold true when the crowd is entirely made of AI agents? What It Does CrowdSeed AI is a simulation engine and interactive Streamlit platform that reruns this exact behavioral experiment using LLMs instead of humans. Agents are placed in a 5x5 grid environment and tasked with drawing connected lines to form a rigid robot body. The robots are then evaluated in a physics simulator to see how far they can walk. We split our AI agents into two distinct experimental tracks: - Independent Group (Control): Agents can only see and iterate on their own past design attempts. - Social Group (Experimental): Agents can view, adapt, and build upon the successful designs of their peer agents. How We Built It - Agent Infrastructure: Multi-agent LLM framework orchestrated to handle memory, and sequential design generations. - Physics & Evaluation Engine: A customized 2D physics evaluation layer that scores the distance traveled by each generated 5x5 grid robot. - Frontend & Analytics Dashboard: A Streamlit web application featuring results. What We Discovered (Our Real Results) Design Quality & Latent Factors: The Social AI agents scored significantly higher on the computed "design quality" factor than the independent agents (p = 0.0002, indicating a statistically significant result). Value & AI Infra Impact CrowdSeed AI provides the infrastructure to benchmark and study "artificial culture" and social synergy, proving that social connectivity makes AI agent swarms fundamentally more creative and capable.

SignalForge is an autonomous AI-powered options paper-trading agent built on Alpaca. It continuously scans a diversified watchlist for market opportunities using technical indicators such as momentum, moving averages, RSI, MACD, and volume. Promising signals are evaluated by Azure OpenAI, which produces a structured trading decision, confidence score, direction, and supporting rationale. Before any order is submitted, a deterministic risk engine independently checks market status, AI confidence, portfolio exposure, position limits, recent losses, liquidity, bid-ask spread, option expiration, premium, and position size. Approved opportunities are converted into suitable call or put contracts and submitted to Alpaca’s paper-trading API. The agent then monitors open positions and applies defined stop-loss, take-profit, expiration, and maximum-holding-period rules. A real-time web dashboard displays portfolio performance, AI decisions, risk evaluations, positions, order history, scanner results, system configuration, and agent status. SignalForge also integrates Alpaca’s CLI, uses Supabase PostgreSQL for persistent records, and provides manual controls, authorization protection, and an emergency kill switch.

JobPulse AI is an AI-powered resume and skill-gap analyzer built to help students, fresh graduates, and job seekers better understand their readiness for a target role. Users can upload their resume in PDF format and provide a target job description. The application analyzes both inputs to calculate an overall fit score, identify important missing skills and keywords, and highlight areas where the candidate can improve. It then generates a personalized 7-day learning plan focused on the identified gaps, helping users turn their weaknesses into actionable learning goals. JobPulse AI transforms the traditional job application process into a personalized, data-driven experience that helps candidates understand where they stand and what they should learn next.

Six Matches. One leaderboard. Build on AMD, earn points and compete for prizes.

🌎 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.