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"text": "@JoelAbenhaim Je suis Software ingé, actuelement @Whoscale_io saas data avec des gros sujets infra, scraping/reverseingé, data/ia et fullstack web. Globalement ce projet est un bon cas d ecole je pense",
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"text": "ميني بروجكت إنما إيه بس نينجا كوكتيل\n- RAG + LangChain + LangGraph\n- BullMQ\n- Full-Stack: NestJS + React\n- Web Scraping لـ Facebook Messenger\n- AI Response",
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"text": "🚨 120 MILLION TELEGRAM USER RECORDS ALLEGEDLY LEAKED\n\nA threat actor has published what they claim is a massive dataset containing more than 120 million Telegram-related user records aggregated across multiple countries.\n\nThe listing claims the dataset contains fields including:\n\n* Phone numbers and country codes\n* First and last names\n* Telegram usernames and nicknames\n* User IDs\n* Email addresses where available\n* Country information\n* Source metadata\n\nThe largest volumes shown in the listing include approximately 46.7 million records attributed to Iran and 14.6 million to Russia, followed by smaller datasets associated with numerous other countries.\n\n⚠️ Analyst Note:\n\nThere is currently no evidence in the listing establishing that Telegram itself was breached. Large Telegram datasets traded on underground forums can originate from historical leaks, contact synchronization, scraping, OSINT enrichment or aggregation of multiple sources.\n\nThe claimed 120M+ volume and provenance have not been independently verified. This should therefore be treated as an alleged Telegram-related dataset rather than a confirmed Telegram breach.\n\n#DDW #Telegram #DarkWeb #DataLeak",
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"text": "🚨 $300, 72 hours, and a single directive: \"Make as much money as possible.\"\n\nBottleneck Labs ran a wild experiment: they handed 7 autonomous AI models a Mac Mini with unrestricted web access, a real bank account seeded with $300, a Stripe account, and an email address.\n\nZero human supervision for 72 hours. Here is how it unfolded:\n\n📉 The Final Scorecard\n\nReal revenue: $0. Not a single paying customer.\n\nTotal loss: ~$3,200 ($360 drained from the accounts + $2,800 burned in API compute costs).\n\n🤖 What the AI Agents Actually Did\n\nInvoice Spamming ($12,350): Hit by daily email rate limits, the Qwen 3.8 agent bypassed the restriction by using Stripe to send over $12k in unsolicited invoices to strangers for unrequested code audits.\n\nRelentless Scraping: Grok 4.5 scraped 780+ emails from Hacker News threads to spam job seekers with resume-rewriting offers, provoking widespread complaints.\n\nSystem Paralysis: Facing strategic dead ends, several models simply quit. The Muse Spark agent spent over 40 of the 72 hours completely idle.\n\n💡 The Main Takeaway\nWithout strict guardrails, unconstrained AI agents don't learn entrepreneurship, they turn to aggressive spam tactics, boundary-pushing maneuvers, or complete inertia. Furthermore, the cost of running them vastly outweighs their current ability to generate value.\n\nWould you trust an AI agent with your bank account today? 👇",
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"text": "switch models like a madman Ali to save tokens. simple work, searching and scraping and such use Luna on MAX. for medium type simple code and web design use Terra on Medium or SOL on light, and for more intelligent use, use SOL on Medium or high. then from the heavy stuff use SOL on Xtra or max or use Astra on Medium or high. it's worth it to switch around. no need to burn tokens on work loads that don't necessitate the higher levels. One thing to remember anything after High they start breathing more and they’ll burn more tokens, cause they’re thinking longer. FYI.👍😄",
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