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OpenAI ChatGPT

The ChatGPT model has been trained on a vast amount of text data, including conversations and other types of human-generated text, which allows it to generate text that is similar in style and content to human conversation. ChatGPT can be used to generate responses to questions, code, make suggestions, or provide information in a conversational manner, and it is able to do so in a way that is often indistinguishable from human-generated text. The initial model has been trained using Reinforcement Learning from Human Feedback (RLHF), using methods similar to InstructGPT, but with slight differences in the data collection setup. The model is trained using supervised fine-tuning, where human AI trainers provided conversations in which they played both sides—the user and an AI assistant. The trainers would have had access to model-written suggestions to help them compose their responses.

General
Relese dateNovember 30, 2022
AuthorOpenAI
API DocumentationChatGPT API
TypeAutoregressive, Transformer, Language model

Start building with ChatGPT

GPT-3 have a rich ecosystem of libraries and resources to help you get started. We have collected the best GPT-3 libraries and resources to help you get started to build with GPT-3 today. To see what others are building with GPT-3, check out the community built GPT-3 Use Cases and Applications.

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ChatGPT Boilerplates

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ChatGPT API libraries and connectors

The ChatGPT API endpoint provides a convenient way to incorporate advanced language understanding into your applications.

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OpenAI ChatGPT AI technology Hackathon projects

Discover innovative solutions crafted with OpenAI ChatGPT AI technology, developed by our community members during our engaging hackathons.

Verified News

Verified News

**Verified News** is a real-time narrative verification platform that combats misinformation by autonomously fact-checking claims against live web data, social signals, community notes, and fact-checking databases. Where services like Ground News show *bias*, Verified News answers a harder question: **is it true?** The platform deploys a multi-agent swarm built on **CrewAI**, powered by **Bright Data's** full web data infrastructure (MCP Server, SERP API, Web Unlocker, Scraping Browser, Web Scraper API), with all reasoning running through **AI/ML API** and **Gemma 4 31B**. Verdicts are delivered as color-coded trust badges (🔵 Blue, 🟢 Green, 🟡 Yellow, 🟠 Orange, 🔴 Red, ⚪ Gray) with full evidentiary transparency. For **enterprises**, Verified News is two products in one: - ** Security & Compliance:** A threat intelligence layer that detects disinformation campaigns, false product recall rumors, fake executive statements, and leaked data narratives before they crater stock prices or trigger regulatory action. - ** GTM Intelligence:** A brand health and competitive intelligence platform that verifies market narratives and competitor claims, giving revenue teams accurate ground truth for messaging and positioning.

SpoofVane — AI Brand-Impersonation Defense

SpoofVane — AI Brand-Impersonation Defense

/ 600 chars, max 2000 chars) Paste this (≈1,950 chars): SpoofVane catches brand-impersonation infrastructure the day it goes live by fingerprinting the page itself, not just the domain name. The problem: phishing kits clone a brand's login and payment pages, hide behind Cloudflare, geo-target the victim country, and actively block security scanners. Domain-only tools miss them. How it works: 1. Discovery — 8 sources surface suspect URLs per brand sweep: Google SERP + paid ads, certificate-transparency logs, newly-registered-domain deltas, app stores and APK sideloads, GitHub kit leaks, Telegram kit marketplaces, and social-platform impersonation. 2. Inspection — Bright Data's Scraping Browser, Web Unlocker, and geo-pinned residential proxies render each suspect page in real Chrome from the victim's country, reaching adversarial pages ordinary scanners can't. Multi-region rendering detects geo-cloaking. 3. Scoring — perceptual image hashing, DOM-tree similarity, logo detection, and favicon matching, plus phishing-kit family fingerprinting (16Shop, EvilProxy, Tycoon-2FA and more). 4. AI verdict — Claude reasons over the screenshot, DOM, and metadata to return a structured phish / suspicious / benign verdict with evidence and a drafted takedown notice. 5. Triage copilot — an agentic, read-only Claude tool-use loop an analyst works in natural language; it queries the alert store autonomously and cites alert IDs, but never sends a takedown — a human owns that gate. 6. Delivery — multi-tenant SOC console, evidence-pack PDFs, SIEM/SOAR webhooks (ServiceNow, Sentinel, Splunk, PagerDuty, STIX/TAXII, Slack), and an MCP server so analysts can query SpoofVane from inside Claude. Why Bright Data is essential: of any Track 3 entry, SpoofVane has the most load-bearing dependency. Without the adversarial-access stack it literally cannot reach the pages it exists to find. 7/7 Bright Data products integrated; 601 tests green; 76 backend modules.

Kizuna: Cross-Border Strategic Intelligence

Kizuna: Cross-Border Strategic Intelligence

An American enterprise wants to partner with a precision manufacturing firm in Shizuoka, Japan. If you search for them in English, you find a clean, basic marketing website. No red flags. But when American enterprises review overseas bids, they are flying blind with no deep knowledge. Enter Kizuna. Kizuna is an autonomous, multi-agent intelligence suite that bypasses regional geo-blocks to scrape, translate, and synthesize native-language corporate data. It exposes hidden legal, ESG, and operational risks in Asian supply chains before Western enterprises sign high-stakes MOUs, Joint Ventures, or procurement contracts. At its core Kizuna is a digital investigator which finds the trust points before corporations make the wrong move. When Western enterprises evaluate Asian manufacturing and tech partners (in Japan, South Korea, or Taiwan) for Solicitations, Joint Ventures, or MOUs, they face a massive intelligence asymmetry. The critical red flags wildcat strikes, domestic IP lawsuits, environmental fines, or rumours of bankruptcy remain invisible. Procurement teams are blind. Western search engines and static LLMs cannot see local labour disputes, regional bankruptcy whispers, or domestic lawsuits because that data is hidden in native languages, behind aggressive government geo-blocks, and heavily protected local search engines like EDINET. Western hardware and tech companies rely entirely on Asian supply chains (Taiwan for semiconductors, Korea for displays/batteries, Japan for precision robotics). When American enterprises put out a "Solicitation for Bid," they get proposals from overseas contractors they know nothing about.

SignalWindow: GTM Intent Radar

SignalWindow: GTM Intent Radar

GTM teams lose deals because the strongest buying signals never make it into their stack. Churn threads on Reddit, pricing complaints on Hacker News, and switching intent on G2 sit behind bot protection, JavaScript rendering, and rate limits—so RevOps and AEs research manually and still miss the window. SignalWindow is not a chatbot. It is a closed-loop intelligence pipeline built for the Bright Data hackathon. For each watchlist company, Bright Data SERP API discovers what changed (pricing, careers, changelog, community queries). Web Unlocker and Browser API extract blocked pages as markdown with source URLs and timestamps. A deterministic Window Score ranks winnability in Python; AI/ML API only explains why—never inventing the score. Cognee plus Redis remember signals across runs so context compounds. When the score crosses threshold, TriggerWare or Slack delivers an action-ready brief with outreach draft. The Streamlit demo runs end-to-end in demo mode with pre-cached extracts, or live against real Bright Data endpoints. Toggle “Simulate change” to inject a synthetic churn signal, watch the diff fire, score jump, and alert execute on stage—proving Discover → Extract → Score → Reason → Remember → Act in under five minutes. We surface buying intent before it appears in ZoomInfo or Clearbit: evidence-grade, cited, and automated. Bright Data unlocks the web; SignalWindow turns it into GTM action.

OpportunityOS AI

OpportunityOS AI

# OpportunityOS AI OpportunityOS AI is an AI-powered opportunity intelligence platform that helps students, job seekers, freelancers, startups, and organizations discover the most relevant opportunities from across the web in real time. Today, millions of opportunities such as scholarships, remote jobs, internships, hackathons, grants, startup accelerators, funding programs, competitions, and public tenders are published across thousands of websites. Finding them requires significant manual effort, and many people miss life-changing opportunities simply because they were not aware of them at the right time. OpportunityOS AI solves this problem by combining Bright Data's web intelligence infrastructure with advanced AI agents. Using Bright Data SERP API, Web Scraper API, MCP Server, and Web Unlocker, the platform continuously monitors and extracts opportunity data from multiple public sources worldwide. AI agents then analyze, categorize, summarize, and rank opportunities based on each user's profile, skills, education level, goals, and interests. The platform provides personalized opportunity recommendations, AI-generated summaries, eligibility analysis, deadline tracking, and compatibility scores. It also includes an Opportunity Gap Detector that identifies missing skills, certifications, or requirements and generates a personalized roadmap to help users become eligible for future opportunities. By transforming unstructured web data into actionable intelligence, OpportunityOS AI acts as a personal opportunity discovery agent, ensuring that users never miss important opportunities that could advance their education, career, business, or professional growth.

Corporate Truth Terminal

Corporate Truth Terminal

Companies leave clues about their future every single day — in job postings, pricing changes, employee sentiment, and security disclosures. The challenge is that these signals are scattered across dozens of sources, and by the time most analysts connect the dots, the opportunity or risk has already passed. Corporate Truth Terminal is an AI-powered intelligence agent that solves this problem. Users simply enter a company name, and the platform continuously monitors live public web data to analyze key signals: hiring activity, financial indicators, security exposure, company sentiment, and market behavior. Instead of hours of manual research, users receive a continuously updated intelligence report generated in minutes. What sets Corporate Truth Terminal apart is its Predictive Signal Engine, which analyzes trends across multiple data sources to identify emerging opportunities and risks before they become obvious. Alongside this, Sentinel Mode detects combinations of signals historically associated with corporate distress, operational challenges, or elevated risk — giving users early warning when it matters most. The platform is built for three core audiences: go-to-market teams tracking buying intent and competitor signals, financial analysts monitoring growth trends and pricing strategy, and security professionals assessing third-party risk and exposure changes. Live web data access is powered by Bright Data's Web Unlocker, enabling reliable, real-time data collection at scale across sources protected by anti-bot systems and dynamic content. This infrastructure is what makes true predictive intelligence possible. Corporate Truth Terminal doesn't just report what companies are doing today — it helps users understand what companies may do tomorrow.