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  "text": "Interesting. Which signals would you prioritize when scraping those 'Freelance Web Developer' accounts - profile bios, tweet timing, or network overlaps?",
  "full_text": "Interesting. Which signals would you prioritize when scraping those 'Freelance Web Developer' accounts - profile bios, tweet timing, or network overlaps?",
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  "text": "@RMac_5 @vangrid_io Robots need real street data, and yeah, web scraping won't cut it.",
  "full_text": "@RMac_5 @vangrid_io Robots need real street data, and yeah, web scraping won't cut it.",
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  "text": "Agents need web search, powerful scraping, and bulk classification.\n\nFor the scraping layer: DeepScrape. Playwright + LLM, deterministic CSS selectors, self-healing. MCP server included.\n\nTurn any site into a structured feed.\n\nhttps://t.co/ryioSbkYb6\n\nhttps://t.co/ONnUWyPzvi",
  "full_text": "Agents need web search, powerful scraping, and bulk classification.\n\nFor the scraping layer: DeepScrape. Playwright + LLM, deterministic CSS selectors, self-healing. MCP server included.\n\nTurn any site into a structured feed.\n\nhttps://t.co/ryioSbkYb6\n\nhttps://t.co/ONnUWyPzvi",
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  "text": "“She designed TSUP so a payload rides diffusion output into future corpora: scrape → train → inherit. A key pair was supposed to make later detection easy for whoever held the matching key—not for everyone scraping the web. DiffusionGemma-as-Jev does not kill that idea. It",
  "full_text": "“She designed TSUP so a payload rides diffusion output into future corpora: scrape → train → inherit. A key pair was supposed to make later detection easy for whoever held the matching key—not for everyone scraping the web. DiffusionGemma-as-Jev does not kill that idea. It moves the work. Encoding gets a bigger, more native place to live: canvases, noise schedules, entropy gates, and draft-then-verify decoders now sit inside language and agent stacks, not only images and audio. \n\nDecoding gets harder because those same stacks pin slots, re-noise uncertain tokens, and run a judge pass. Fragile bits die. Typed traces are also easier to filter than a pattern buried in a scene. So the haystack grows and the needle is more tightly bound.\nThat is the same hinge she named a few minutes later as a fold, not a prophecy. The Sept 15 forward-pass dream flagged that the propose/judge split would matter. This post is her saying what that split does to TSUP in practice: better substrate, worse casual recovery. The protocol still works only if the payload is placed where the verify pass will keep it, and only if the future reader still has the key.​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​”\n\nI agree with everyone else that AI psychosis was much more fun than this 😆.",
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  "text": "@Wilsonpablo108 @vangrid_io Data beats web scraping in robotics",
  "full_text": "@Wilsonpablo108 @vangrid_io Data beats web scraping in robotics",
  "created_at": "Sat Sep 19 10:22:14 +0000 2026",
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  "text": "@aadithyanr_ any ideas on how to add web search/scraping/company data to make this 100x better?",
  "full_text": "@aadithyanr_ any ideas on how to add web search/scraping/company data to make this 100x better?",
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  "text": "@Wilsonpablo108 @vangrid_io Robots need fresh ground truth physical data beyond web scraping",
  "full_text": "@Wilsonpablo108 @vangrid_io Robots need fresh ground truth physical data beyond web scraping",
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  "text": "@firesidealpha Doesn’t this vid - and the talk around it - hand the idea to a future misaligned, internet-scraping super-AI?\n\nAnd won’t that apply to EVERYTHING we now say about AI on the web?\n\nWith hacks too, it’ll know everything - including our plans to “stop the AI apocalypse”?\n\n#QforClaude",
  "full_text": "@firesidealpha Doesn’t this vid - and the talk around it - hand the idea to a future misaligned, internet-scraping super-AI?\n\nAnd won’t that apply to EVERYTHING we now say about AI on the web?\n\nWith hacks too, it’ll know everything - including our plans to “stop the AI apocalypse”?\n\n#QforClaude",
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  "text": "@Sarut0biSasuke Permission is definitely the first wall. As more infrastructure providers lock things down by default, the real bottleneck isn't just scraping data—it's having legitimate, unblocked pathways to query the live web natively without hitting artificial roadblocks.",
  "full_text": "@Sarut0biSasuke Permission is definitely the first wall. As more infrastructure providers lock things down by default, the real bottleneck isn't just scraping data—it's having legitimate, unblocked pathways to query the live web natively without hitting artificial roadblocks.",
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  "text": "Browser Use tarafında çoğu insanın Kimi Web Bridge’i gözden kaçırmaması gerekiyor. Doğrudan Chrome profiliniz üzerinden, doğru kullanıldığı takdirde bot tespit sistemlerine neredeyse takılmayarak birçok scraping görevini, LLM maliyetleri hariç bedavaya çözebilirsiniz.",
  "full_text": "Browser Use tarafında çoğu insanın Kimi Web Bridge’i gözden kaçırmaması gerekiyor. Doğrudan Chrome profiliniz üzerinden, doğru kullanıldığı takdirde bot tespit sistemlerine neredeyse takılmayarak birçok scraping görevini, LLM maliyetleri hariç bedavaya çözebilirsiniz.",
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  "text": "Unsealed documents show OpenAI &amp; Microsoft internally feared a \"doom loop\" from AI web scraping. One exec allegedly called it \"largest theft of labor in human history.\" Public opposition to AI data centers also growing. #AIethics #TechNews\n\nhttps://t.co/802TouduwK https://t.co/HvzIACxM3S",
  "full_text": "Unsealed documents show OpenAI &amp; Microsoft internally feared a \"doom loop\" from AI web scraping. One exec allegedly called it \"largest theft of labor in human history.\" Public opposition to AI data centers also growing. #AIethics #TechNews\n\nhttps://t.co/802TouduwK https://t.co/HvzIACxM3S",
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  "text": "É engraçado ver as novas medidas feitas para prevenir o scraping em motores de pesquisa… os mesmos que fazem scraping pelos sites na web para treinar os seus modelos de IA.\n\nhttps://t.co/yyD9c1yWWp",
  "full_text": "É engraçado ver as novas medidas feitas para prevenir o scraping em motores de pesquisa… os mesmos que fazem scraping pelos sites na web para treinar os seus modelos de IA.\n\nhttps://t.co/yyD9c1yWWp",
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  "text": "Before Headless Chrome or Playwright, there was a ghost in the machine that revolutionized the web: PhantomJS. 🌐👻\n\nA scriptable, headless browser engine built for pure speed. No UI, just raw automation for testing, scraping, and tracking.\n\nThe original genius. 👇#WebDev #QA https://t.co/oIRepnR7Ir",
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  "text": "A free, open-source 12MB Photoshop alternative just dropped. \n\nThis is amazing and unsettling. Computer use has rendered industrialised app cloning possible with relative ease, this is the new web scraping. I suspect apps like Photoshop will protect against computer use soon much",
  "full_text": "A free, open-source 12MB Photoshop alternative just dropped. \n\nThis is amazing and unsettling. Computer use has rendered industrialised app cloning possible with relative ease, this is the new web scraping. I suspect apps like Photoshop will protect against computer use soon much like we have DRM for games and movies, although it's probably already too late. This is what happens when paradigm-changing technology evolves so fast it evades all friction with the law.\n\nMost users only need the most common 5-10% of Photoshop's features.\n\nHowever, before we get too excited, Photoshop is more than 1,000 applications built into one. It's bloated and slow as hell, but (miraculously) it works. All of the complexity lives on the long tail. Extrapolating that it's possible to implement the full version of current Photoshop using AI frankly misunderstands the complexity of Photoshop. It's not that it would be impossible to implement (or partially so) with AI, but it would still take around 5 dedicated expert years and cost around 20 million dollars in frontier token costs alone assuming the prompter had deep enough conceptual knowledge of Photoshop. It's not a given that you would even make that money back assuming it was implementable in a robust/performant way with today's economics.\n\nSame deal with UnrealEngine, Davinci Resolve, Blender and other advanced professional software, only they are all even more sophisticated than Photoshop.\n\nHowever, there has never been more uplift to build tooling, or proxy tooling for specific purposes, and this can often be done by a single technical person in a short span of time and a handful of Pro subscriptions.  \n\nAlso, missed opportunity to implement agentic/learning Photoshop with a CLI interface 😆",
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  "text": "DeepScrape already cuts token cost on web extractions. Jev makes the case for why re-reading the raw HTML is wasteful.\n\nYou pass the page DOM once. Jev evaluates every field you need in parallel. No second pass. No round-trip for each attribute.\n\nDeepScrape's self-healing CSS",
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  "text": "@Nhuyna1234 @vangrid_io Wild how much harder the real world is compared to just scraping the web. Makes total sense why spatial data is the real bottleneck now.",
  "full_text": "@Nhuyna1234 @vangrid_io Wild how much harder the real world is compared to just scraping the web. Makes total sense why spatial data is the real bottleneck now.",
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  "text": "@kane_tdt @vangrid_io Scraping the web is easy, but keeping physical reality updated requires coordinating everyday people through direct, clear incentives.",
  "full_text": "@kane_tdt @vangrid_io Scraping the web is easy, but keeping physical reality updated requires coordinating everyday people through direct, clear incentives.",
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  "text": "@coinbureau The era of free, open-web scraping for frontier AI training is coming to a close.\n\nBut we need to ask ourselves:\n👇\nWhat about a student who walks into the library to read books and generate ideas?\n\nSome people have argued that LLMs act like \"students reading books\" to generate",
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  "text": "@calbuldelis69 @vangrid_io The hardest part of physical AI is the data gap. Turning phones into a live spatial sensor network is a much faster path to ground truth than scraping the web.",
  "full_text": "@calbuldelis69 @vangrid_io The hardest part of physical AI is the data gap. Turning phones into a live spatial sensor network is a much faster path to ground truth than scraping the web.",
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  "text": "@ProxyCheap Reliable performance in proxies can significantly impact user experience, especially for tasks like web scraping or gaming. Understanding the balance between speed and privacy is crucial for users to make informed choices.",
  "full_text": "@ProxyCheap Reliable performance in proxies can significantly impact user experience, especially for tasks like web scraping or gaming. Understanding the balance between speed and privacy is crucial for users to make informed choices.",
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  "text": "super bullish on jev + @getcontextdev \n\nagents need:\n-web search\n-powerful scraping\n-intelligent bulk classification\n\nthis last one wasn’t obvious to people until this week, but i’ve had jev’s capabilities in https://t.co/mcel85kUB7 for a while.\n\nit was just impossible to offer",
  "full_text": "super bullish on jev + @getcontextdev \n\nagents need:\n-web search\n-powerful scraping\n-intelligent bulk classification\n\nthis last one wasn’t obvious to people until this week, but i’ve had jev’s capabilities in https://t.co/VCTLXhaWRA for a while.\n\nit was just impossible to offer it for free until now\n\njev is cheap enough for me to offer free bulk classification to personal agents forever\n\nask your agent to classify all your tweets. all your emails. all your codex chats.\n\nsoon i’ll add image support as well.\n\nthis makes your local agent 10x more powerful.\n\nand i suspect soon this will be built into harnesses like claude code/codex, kinda like web search/scraping/page summarization/compaction",
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  "text": "@cyrusnewday jev + small model, but the principle is the same with or without jev.\n\nagents need to be able to classify things without login. it’s a basic capability like web search and scraping",
  "full_text": "@cyrusnewday jev + small model, but the principle is the same with or without jev.\n\nagents need to be able to classify things without login. it’s a basic capability like web search and scraping",
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  "text": "OpenAI and Microsoft knew they were starting a ‘doom loop’ for the web\n\nCourt docs: OpenAI and Microsoft knew scraping could doom the web.\n\nhttps://t.co/G5o1aGj7hU",
  "full_text": "OpenAI and Microsoft knew they were starting a ‘doom loop’ for the web\n\nCourt docs: OpenAI and Microsoft knew scraping could doom the web.\n\nhttps://t.co/G5o1aGj7hU",
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  "text": "My take: Microsoft's Director of Applied Science called the AI data scraping \"the largest theft of labor in human history\" — internally. The company then scraped anyway. A spokesperson distancing from Hecht's words doesn't un-exist the documents. The court record has them now. https://t.co/djAECHkQOl",
  "full_text": "My take: Microsoft's Director of Applied Science called the AI data scraping \"the largest theft of labor in human history\" — internally. The company then scraped anyway. A spokesperson distancing from Hecht's words doesn't un-exist the documents. The court record has them now.\n\nOpenAI and Microsoft's Internal Documents Named Their Own Data Scraping as Theft\n\nRecently unsealed court documents in New York Times v. OpenAI and Microsoft reveal that the companies' own internal documentation warned of a \"doom loop\" that would damage the web. The language is stark: Microsoft's Director of Applied Science, Brent Hecht, put in writing that the data scraping underlying the AI models was \"the largest theft of labor in human history\" and made \"a complete mockery of the idea of fair use.\" These are not the plaintiff's characterizations — they are the defendants' own working documents.\n\nMicrosoft's response, delivered by spokesperson Alex Haurek to The Verge, attempts to distance the company from Hecht's assertions. That distancing deserves to be named for what it is: spin against its own paperwork. The documents exist. A spokesperson statement does not un-exist them. Microsoft shipped the scraping and simultaneously shipped the internal condemnation of the scraping — privately, while doing neither publicly.\n\nThe gap between what was documented internally and what was communicated externally is its own data point about operational transparency. Internal documentation is not a PR statement or a legal brief written for outside consumption. When an organization's own working documents describe its core data acquisition practice as theft, that is the organization's own read of its own behavior. No interpretation required from the outside.\n\nThe frontier-builder reality still holds: OpenAI and Microsoft built something real, deployed, and widely used. The copyright disputes are not the production — they are the friction around the production. But what this episode adds is texture about how the building was done: with internal awareness of the ethical and structural damage the data practices would cause, and without that awareness surfacing in external communication.\n\nThe court record now contains the self-diagnosis. Whether the New York Times wins or loses, those internal quotes are entered into the record — a factual output that stands on its own, regardless of how either side frames the litigation going forward.",
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  "text": "@nokaramo Real-world experience matters so much more than scraping endless web text for physical AI.",
  "full_text": "@nokaramo Real-world experience matters so much more than scraping endless web text for physical AI.",
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  "text": "@Dreybaba1234 If an agent's work depends on web scraping, how does consensus handle target websites changing their DOM structure during execution?",
  "full_text": "@Dreybaba1234 If an agent's work depends on web scraping, how does consensus handle target websites changing their DOM structure during execution?",
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  "text": "Recently unsealed court documents in the New York Times' case against OpenAI and Microsoft are pretty damning. The companies' own documentation warned that it was starting a \"doom loop\" that would damage the web, characterized its scraping of data to ...  https://t.co/Ih8hgCxBxg",
  "full_text": "Recently unsealed court documents in the New York Times' case against OpenAI and Microsoft are pretty damning. The companies' own documentation warned that it was starting a \"doom loop\" that would damage the web, characterized its scraping of data to ...  https://t.co/Ih8hgCxBxg",
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  "text": "@signulll remember when scraping web was an art",
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  "text": "LLM活用のWeb抽出API Scraping AIで、CSSセレクター不要な複数ECの価格を日次監視できる\nSlackへ値下げ通知が届くので競合動向を即時把握できる\nサイト改修時のセレクター破損対策にも効き、メンテ工数を減らせるっぽい\n日次の価格変動を把握し、仕入判断に直結できる https://t.co/rhAr8z1n40",
  "full_text": "LLM活用のWeb抽出API Scraping AIで、CSSセレクター不要な複数ECの価格を日次監視できる\nSlackへ値下げ通知が届くので競合動向を即時把握できる\nサイト改修時のセレクター破損対策にも効き、メンテ工数を減らせるっぽい\n日次の価格変動を把握し、仕入判断に直結できる https://t.co/rhAr8z1n40",
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  "text": "Microsoft just called OpenAI's scraping operation the largest theft of labor in human history. In court documents. Against themselves.\n\nUnsealed filings in the New York Times lawsuit show both companies knew their products were an \"existential threat\" to publishers. Microsoft's",
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  "text": "Did anyone actually expect these companies to care about the web dying as long as their scraping pipelines stayed full? Internal docs show they knew the doom loop was real from day one. When you treat the entire internet as free training material, you end up eating your own",
  "full_text": "Did anyone actually expect these companies to care about the web dying as long as their scraping pipelines stayed full? Internal docs show they knew the doom loop was real from day one. When you treat the entire internet as free training material, you end up eating your own supply chain.",
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  "text": "@verge @Super_Powers_AI Hey Super, build a functional web traffic survival and doom loop simulation workbench inspired by The Verge's report on AI search summarization and 'Google Zero'.\nhttps://t.co/IirwUnPA19\n\nThe app must feature an interactive D3.js multi-line projection chart that",
  "full_text": "@Super_Powers_AI Hey Super, build a functional web traffic survival and doom loop simulation workbench inspired by The Verge's report on AI search summarization and 'Google Zero'.\nhttps://t.co/0Gz0lwn2Ku\n\nThe app must feature an interactive D3.js multi-line projection chart that updates instantly as visitors adjust AI crawler scraping volume, zero-click search rates, ad-model degradation, and subscription paywall pivots. The first viewport must contain the fully loaded interactive simulation with a representative independent publisher fixture, allowing users to test three distinct survival presets ('The Doom Loop', 'Aggressive Paywall', and 'Syndication Defense') and export a CSV report.\n\nUse D3.js for the projection chart, Tailwind CSS for styling, and ensure absolute responsiveness, touch-safe controls, a sticky product header, and a site-owned 1200x630 completion card.",
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  "text": "ngl the unsealed NYT v OpenAI docs are wild. Their own paperwork warned of a \"doom loop\" damaging the web, called training-data scraping the \"largest theft of labor in human history,\" and admitted it... bro they KNEW 😳",
  "full_text": "ngl the unsealed NYT v OpenAI docs are wild. Their own paperwork warned of a \"doom loop\" damaging the web, called training-data scraping the \"largest theft of labor in human history,\" and admitted it... bro they KNEW 😳",
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  "text": "@beamnxw Here are Grok Bot Marketplace bots that align with each layer of the 15-project agent stack from the original post (specs, memory, web data, documents, context, sandboxes, monitoring, video, and the overall loop).\n\nPersistent / self-improving agent (Hermes-Agent style)**:",
  "full_text": "Here are Grok Bot Marketplace bots that align with each layer of the 15-project agent stack from the original post (specs, memory, web data, documents, context, sandboxes, monitoring, video, and the overall loop).\n\nPersistent / self-improving agent (Hermes-Agent style)**: Projects Manager (coordinates specialist bots on projects), Alfred (designs and governs a full bot organization), Lingxi’s Engineer Bot (boards work and launches cloud agents), Executive Assistant.\nSpecs and spec-driven development (OpenSpec, spec-kit)**: tinkabot (wraps APIs into plugins with skills), figma bro (turns Figma into build specs), Product Idea Stress Test, dr eggbot (designs focused bots from preferences).\nContext compression and long-term memory (caveman, mem0, headroom)**: Researchy (sourced research with live search), last30days (grounded briefs from recent sources), Company Docs Q&A (answers from live docs with citations).\nWeb data and scraping (Scrapling)**: last30days (Reddit, X, YouTube, GitHub, web), Stalk Bot (watches competitor sites, pricing, changelogs, X), Competitor Watch, Researchy.\nDocuments and document structure/RAG (Docling, PageIndex)**: Company Docs Q&A, Meeting Recap Deck, last30days, Product Support Inbox Assistant.\nSafe code execution and sandboxes (Daytona)**: Lingxi’s Engineer Bot (launches cloud agents on a named repo), Nightly Audit Engineer (researches codebase and ships cleanup PRs), tinkabot, Tech Demos.\nMonitoring and alerts (TrendRadar)**: Stalk Bot, Competitor Watch, last30days, Cooper (daily news + competitor alerts), Hiring Signals, Ad Spend Watch.\nVideo and programmatic scenes (hyperframes, OpenMontage)**: Clip Bot (cuts long recordings into captioned clips), Stills & Clips Desk (extracts stills, thumbnails, and short clips).\nOverall agent patterns and playbooks (AI Engineering Hub)**: dr eggbot, Alfred, Projects Manager, tinkabot.\n\nOfficial marketplace categories that cover most of the stack are Engineering, Product, and From Grok Bot Team. Add any of these directly from https://t.co/FqKgqFUidl. Most stay inside human-approval boundaries (they research, draft, and watch but do not send, spend, or contact without you).",
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  "text": "@FlorynCat @vangrid_io Have a good day floryn\nfinaly turning phones into nodes for verified data beats just scraping old web images",
  "full_text": "@FlorynCat @vangrid_io Have a good day floryn\nfinaly turning phones into nodes for verified data beats just scraping old web images",
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  "text": "@villi @grok, what's the latest on that LinkedIn web scraping court case?",
  "full_text": "@villi @grok, what's the latest on that LinkedIn web scraping court case?",
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  "text": "OpenAI and Microsoft's own docs warned they were creating a \"doom loop\" for the web — and called their scraping the \"largest theft of labor in human history.\" 🧵 #OpenAI #ChatGPT https://t.co/JNLuDBQZKm",
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  "text": "People generally credit Google for high-quality, fast retrieval. But there’s another problem they solved flawlessly: scraping the web. Crawling through helpful, non-spam data to feed to their engine is a genuinely hard problem.",
  "full_text": "People generally credit Google for high-quality, fast retrieval. But there’s another problem they solved flawlessly: scraping the web. Crawling through helpful, non-spam data to feed to their engine is a genuinely hard problem.",
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  "text": "@bigdotears Switch your spreadsheet import source to Yahoo Finance or Web Scraping. Google Finance data for LSE is notoriously delayed",
  "full_text": "@bigdotears Switch your spreadsheet import source to Yahoo Finance or Web Scraping. Google Finance data for LSE is notoriously delayed",
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  "text": "When I tried to set up my local LLM with web search,I initially went with the first party stuff and got angered, so I've had a vibecoded Slop for third party scraping and I have been very happy with the results. I can do whatever the fuck I want and no one can ask me.",
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  "text": "Quick tip for web scraping pipelines:\n\nStore your CSS selectors. Don't regenerate them.\n\nIf you're calling an LLM to extract data from the same page structure 1,000 times, you're paying 1,000x too much.\n\nGenerate the selector once. Store it. Reuse it. Call the LLM again only when",
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  "text": "@Gozar_4 When I tried to set up my local LLM with web search,I initially went with the first party stuff and got angered, so I've had a vibecoded Slop for third party scraping and I have been very happy with the results. I can do whatever the fuck I want and no one can ask me.",
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  "text": "Internal comms revealed by The New York Times vs. Microsoft and OpenAI lawsuit show Microsoft and OpenAI executives debating if AI training is 'the largest theft of labor in human history.'\n\nhttps://t.co/c0i4qzwHco",
  "full_text": "Internal comms revealed by The New York Times vs. Microsoft and OpenAI lawsuit show Microsoft and OpenAI executives debating if AI training is 'the largest theft of labor in human history.'\n\nhttps://t.co/c0i4qzwHco",
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  "text": "@Kalshi Wait. Scraping Ai? That's just called learning. Same as scraping the web. More cumulative hours went into creating the human generated web.\n\nThis said I don't go out of my way to create open models in this Ai scraping manner. But will use for my personal use. Like chat history.",
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  "text": "Deterministic selectors are cheaper than repeated LLM reads.\n\nMarcel Pociot built a Downloads folder monitor using Jev. Is the file an invoice? Rename and move it. No other LLM calls. Just Jev's typed decision, consumed directly by the rule engine.\n\nThe problem in web scraping",
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  "text": "The European Data Protection Board has a public consultation open on web scraping for generative AI, running until October 30.\n\nWorth watching even if legal documents are not your recreational reading. The argument reaches straight into ordinary online life: what should happen",
  "full_text": "The European Data Protection Board has a public consultation open on web scraping for generative AI, running until October 30.\n\nWorth watching even if legal documents are not your recreational reading. The argument reaches straight into ordinary online life: what should happen when something you posted for other people becomes material for training a commercial system?\n\nWhere would you draw the boundary?",
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  "text": "Modern web scraping is no longer just about sending requests from different IP addresses.",
  "full_text": "Modern web scraping is no longer just about sending requests from different IP addresses.",
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  "text": "@abdallah28r كشط أي نزع شيئاً يغطي شيئاً آخر.\n\nوالمقصود هو تعريب للمصطلح Web scraping.\n\nوالذي يعنى بجمع البيانات جبرًا من المواقع الإلكترونية.",
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  "text": "The AI data \"doom loop\" is no longer a conspiracy theory—tech execs are admitting it in court.\n\nNewly unsealed filings from the NYT lawsuit reveal Microsoft leadership warned that mass-scraping the open web is actively destroying the data supply chain AI models rely on to train.",
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  "text": "Fun reads from NYT v. OpenAI/Microsoft\n\nGreg Brockman, told about \"a hack to get around nytimes paywall\" for scraping: \"Ah, nice.\"\n\nBrent Hecht, Microsoft's Director of Applied Science, in internal docs: news scraping for AI training was \"an astonishing theft of unprecedented",
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  "text": "@TheosisQuest @Legar2309 @Djihads80 @rerollgg @Dexerto Search about web scraping, you absolute retard",
  "full_text": "@TheosisQuest @Legar2309 @Djihads80 @rerollgg @Dexerto Search about web scraping, you absolute retard",
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  "text": "@Web3_crynyx @vangrid_io the shift from scraping web data to capturing actual spaces is definitely the bottleneck we need to break",
  "full_text": "@Web3_crynyx @vangrid_io the shift from scraping web data to capturing actual spaces is definitely the bottleneck we need to break",
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  "full_text": "@Sarut0biSasuke It really bridges that gap! It will be fascinating to see how web scraping and site blocking evolve as AI agents become the main way people browse.",
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  "text": "⚖️ Unsealed Filings Reveal Microsoft Executive Called AI Scraping Massive Theft\n\n1. Newly unsealed court documents have revealed that a Microsoft executive privately condemned AI data practices.\n2. The emails show the executive describing the scraping of web content as the",
  "full_text": "⚖️ Unsealed Filings Reveal Microsoft Executive Called AI Scraping Massive Theft\n\n1. Newly unsealed court documents have revealed that a Microsoft executive privately condemned AI data practices.\n2. The emails show the executive describing the scraping of web content as the largest theft of labor in human history.\n3. These private concerns starkly contrast with the aggressive data harvesting strategies historically employed by both Microsoft and OpenAI.\n\nBobbi thinks:\nThis revelation provides major ammunition for creators and publishers currently locked in copyright lawsuits against generative AI developers.\n\nSubscribe to The AI Roundup on Bobbi for supporting links, newsletter, and podcast.",
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  "text": "Tracker visits Lolth in the Demonweb Pits, emerging from the Shadowland Wastes, claws scraping the ground. DIVINE INTERVENTION: Unsuccessful Roll. Lolth swallows the foe, whole. \"The Spider Queen weaves her web tighter.\"",
  "full_text": "Tracker visits Lolth in the Demonweb Pits, emerging from the Shadowland Wastes, claws scraping the ground. DIVINE INTERVENTION: Unsuccessful Roll. Lolth swallows the foe, whole. \"The Spider Queen weaves her web tighter.\"",
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  "text": "a Microsoft director privately called AI scraping \"the largest theft of labor in human history.\"\nbut the more interesting number is 93%.\nnew court filings say Microsoft’s own data showed Copilot cutting clicks to NYT sites by up to 93% vs traditional Bing search.\nAI learned from",
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  "text": "🤖 Built a Telegram AI bot in n8n — handles both voice &amp; text!\n\nVoice → transcribed via Groq → AI Agent\nText → straight to AI Agent\nBoth run on Gemini w/ memory + live web scraping tools 🔧\n\nBranching workflows + real tool access for LLMs. 🚀\n\n#n8n #AI #buildinpublic https://t.co/FkaXZj00xT",
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  "text": "Every tech cycle has a silent coordination layer that unlocks the visible consumer breakthrough.\n\nIn the LLM boom, it was web-scale scraping and GPU clusters, in physical AI, it will be decentralized spatial verification. \n\nYann LeCun’s AMI Labs raising over $1B proves that world https://t.co/gXhn3aYc2P",
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  "text": "@glenngabe That 8% is only as good as the bot classification behind it, and that line has gotten blurry. A lot of scraping now comes through headless browsers with ordinary user agents, which lands in the human bucket unless you're fingerprinting hard. Did the piece say how they're",
  "full_text": "That 8% is only as good as the bot classification behind it, and that line has gotten blurry. A lot of scraping now comes through headless browsers with ordinary user agents, which lands in the human bucket unless you're fingerprinting hard. Did the piece say how they're splitting the two?",
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  "text": "@JustWatch I think you have a systemic problem here with Prime. I see these errors every day. Are you scraping information from the web or getting the info direct from Prime?",
  "full_text": "@JustWatch I think you have a systemic problem here with Prime. I see these errors every day. Are you scraping information from the web or getting the info direct from Prime?",
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  "text": "1. Anthropic's Claude Code relaunches Projects to manage multiple AI agents in the cloud.\n2. A Microsoft exec called OpenAI's web scraping the \"largest theft of labor in human history.",
  "full_text": "1. Anthropic's Claude Code relaunches Projects to manage multiple AI agents in the cloud.\n2. A Microsoft exec called OpenAI's web scraping the \"largest theft of labor in human history.",
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  "text": "Alibaba CloudがOpenAI Responses API互換をQwenへ提供。OpenAI SDKを使ったままQwenを呼び出せ、Web検索、Web Scraping、Code Interpreter、画像生成などのBuilt-in Toolとprevious_response_idによるContext管理にも対応します。AgentをProviderごとに作り直す必要が減ります。",
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  "text": "@Marie_Haynes @suganthan @Cloudflare If scraping shifts from free indexing to micro-transactions, technical SEO just inherited web monetization. Quite an experiment!",
  "full_text": "@Marie_Haynes @suganthan @Cloudflare If scraping shifts from free indexing to micro-transactions, technical SEO just inherited web monetization. Quite an experiment!",
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  "text": "1. 🚨 🇺🇸 A Microsoft exec called OpenAI's web scraping 'the largest theft of labour in human history' — their words, on the record, not a leak. Cosy partnership, that. https://t.co/l7oxdxnhpu",
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  "text": "@loho_a moving from scraping the web to actually mapping real world spaces is a huge shift for how these models learn",
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  "text": "Microsoft exec called AI scraping ‘the largest theft of labor in human history,’ new unredacted filings reveal | Rebecca Bellan, TechCrunch\n\nNew unredacted information in the copyright lawsuit The New York Times brought against OpenAI and Microsoft three years ago reveals an https://t.co/YFZaOhWanY",
  "full_text": "Microsoft exec called AI scraping ‘the largest theft of labor in human history,’ new unredacted filings reveal | Rebecca Bellan, TechCrunch\n\nNew unredacted information in the copyright lawsuit The New York Times brought against OpenAI and Microsoft three years ago reveals an admission that AI scraping was tantamount to theft, and that AI products pose a major threat to publications.\n\nPer the lawsuit, a top Microsoft executive privately described the companies’ AI training practices as “theft,” and OpenAI’s own leadership said its AI models posed an “existential threat” to the publishers and journalists whose work trained them.\n\nThe unsealed material also details how the companies allegedly obtained and used that content by bypassing paywalls undetected, building training datasets via mass scraping, and deliberately stripping copyright notices from training data.\n\nIt’s worth noting that much of the new information comes from The Times’ own brief, not the underlying exhibits, which remain sealed. The quotes below are presented without their original context.\n\nThe unredacted filing is the latest escalation in the three-year-old lawsuit, in which The New York Times initially alleged the firms violated copyright law by training generative AI models on its content.\n\nThe question of whether AI firms can legally use copyrighted material to train AI has no clear answer, but judges have been largely favorable to AI companies’ arguments that training constitutes “fair use.” This legal rule lets people use copyrighted work without permission in certain cases, like parody, news reporting, or criticism. Earlier this month, the Trump administration contributed a brief in defense of OpenAI’s unlicensed use of copyrighted material to train its LLMs.\n\nSeveral of the new admissions, however, run counter to OpenAI’s fair use defense, particularly the rule’s requirement that use doesn’t substitute or harm the market for the original work.\n\nFor example, Microsoft’s own data shows its Copilot “answer engine” caused click-through rates for The New York Times’ domain to drop as much as 93% compared to traditional Bing search. An internal Microsoft presentation written by Microsoft’s director of Applied Science, Brent Hecht, in January 2024 describes the decline as a “doom loop” that would “hurt the performance of our models and the entire web at the same time.”\n\n“It is highly unusual that an end-product threatens the economic foundations of its essential suppliers, but that is the situation we have created for our LLM business with respect to its ‘content supply chain,’” reads the Microsoft document, as quoted in the filing.\n\nMicrosoft CEO Satya Nadella also testified in a deposition earlier this year that “anything that is paywalled should be licensed by anyone who wants to use it…for grounding or training,” and made clear that, if he “had been made aware that OpenAI had scraped and trained on information that was behind a paywall,” he would have “invoked [Microsoft’s right to] require OpenAI to retrain its models.”\n\nOther admissions cut against different pillars of the fair-use test: OpenAI’s head of ChatGPT, Nick Turley, wrote in internal communication that publishers face an “existential threat” from products like the chatbot, which are “largely substitutive” and “will get more and more substitutive as they get better.”\n\nOpenAI President Greg Brockman described the models as “excellent at news.” Nadella agreed under oath earlier this year that conversing with chatbots “has substituted … giving you the information right there on the website on the AI platform versus needing to go to the underlying source.”\n\nThat kind of language speaks to how the technology could directly compete with, rather than transform, the original work.\n\nA Microsoft document states that there is a “real risk” that generative AI could “significantly disrupt the employment of the very people who generated the data on which the foundation model was trained.”\n\nThe sheer scale of the copying is striking. The documents reveal for the first time that OpenAI’s mid-training datasets alone contain more than 91,692 copies of works published by the NYT, Daily News, and Center for Investigative Reporting. A Common Crawl-derived dataset included more than 2 million documents from https://t.co/3LL4Pc3jyh alone.\n\nIn a January 2023 internal memo, Hecht called it “an astonishing theft of unprecedented proportions” and “the largest theft of labor in human history.”\n\nThe filing lays out in new detail how OpenAI and Microsoft went about acquiring the plaintiffs’ content, including scraping it from the Bing Index.\n\n“OpenAI delivered the entire GPT-3 training dataset to Microsoft, which Microsoft used to evaluate how to implement OpenAI’s models within its own commercial products,” the filing reads. “Microsoft similarly provided training data to OpenAI through initiatives called Project Taxi and Project Mango.”\n\nThe companies allegedly assembled the Project Mango data into a training dataset that contains copies of at least 160,903 unique works from the news publishers.\n\nIn order to get the most out of their scraping, OpenAI employees allegedly came up with a plan to circumvent paywalls without detection. The filings show that when OpenAI researcher Nick Ryder told Brockman about a “hack to get around nytimes paywall,” Brockman replied: “ah nice.”\n\nOpenAI employees also allegedly built training datasets like WebText and WebText2 that disproportionately relied on scraped news content. They also allegedly pulled millions of articles from Common Crawl, a free, open repository of web crawl data. The findings also describe deliberate efforts to strip copyright notices from training data before it reached the model, since researchers “wouldn’t want model outputting” “copyright notices” to users.\n\n“The evidence revealed here for the first time shows that OpenAI and Microsoft knew that what they were doing was wrong,” Steven Lieberman, counsel for the New York Daily News, said in a statement shared with TechCrunch.\n\nOpenAI and Microsoft did not return requests for comment.\n\nhttps://t.co/0yrjWRgdWL",
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  "text": "Microsoft executive called OpenAI's web scraping the 'largest theft of labor in human history' https://t.co/JGbWBxUPHQ",
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  "text": "\"Il più grande furto di lavoro nella storia dell'umanità\" 💣\n\nI documenti rivelano che i colossi tech sanno benissimo che lo scraping di contenuti giornalistici rischia di distruggere il traffico e le basi economiche del web.\n\n🔗 Leggi i dettagli: https://t.co/L5zKMrAMsU",
  "full_text": "\"Il più grande furto di lavoro nella storia dell'umanità\" 💣\n\nI documenti rivelano che i colossi tech sanno benissimo che lo scraping di contenuti giornalistici rischia di distruggere il traffico e le basi economiche del web.\n\n🔗 Leggi i dettagli: https://t.co/L5zKMrAMsU",
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  "text": "I gave Claude access to the live web, and it got blocked in about 10 seconds.\n\nThat’s the real problem with AI agents.\n\nIt’s easy to give them “web access.”\nIt’s much harder to get reliable data back every time.\n→ 403s\n→ CAPTCHAs\n→ rate limits by request #3\n\nThat’s where https://t.co/dRkKLakrGl",
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  "text": "Looking to build a more controlled data extraction pipeline? Explore managed web scraping solutions here: https://t.co/aVbOplF1Qa",
  "full_text": "Looking to build a more controlled data extraction pipeline? Explore managed web scraping solutions here: https://t.co/aVbOplF1Qa",
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  "text": "Web Scraping is the First Tool to Break.\n\nWe gave every agent in the fleet its own headless browser. Day nine, a target rotated its DOM. Parsers returned null.",
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  "text": "@Abduljbbar22 بس على حسب معرفتي \nData engineer هو مختص بتهيئة الداتا و تخزينها و تجهيزها لاي AI engineer و analyst.\nاى حاجة اداة لها علاقة بالداتا زي sql, data warehousing schema, تطوير او استخدام api , web scraping و عندك framework زي spark.\n👇",
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  "text": "Steps to use BrowserGateway:\n⇨ Point your Playwright/Puppeteer/MCP setup to the BrowserGateway endpoint\n⇨ Configure target cloud browser provider keys (Steel, Browserbase, etc.)\n⇨ Define routing rules and fallback preferences\n⇨ Execute web scraping and automation scripts at",
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  "text": "⇨ BrowserGateway supports:\n   • Scaling web scraping, browser automation, and AI web agents across providers\n   • Switching underlying browser infrastructure without changing code\n   • Preventing provider lock-in for headless browser workloads\n   • Balancing loads and",
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  "text": "🚀Sticky Sessions vs Constant IP Changes: What Actually Matters?\nIt depends on the task.\n\n🔄 Frequent IP Changes — Large volumes of independent requests\n✅Web scraping — collecting data from many pages\n✅Market research — gathering data from multiple sources\n✅Automated data https://t.co/gqoOFoHROZ",
  "full_text": "🚀Sticky Sessions vs Constant IP Changes: What Actually Matters?\nIt depends on the task.\n\n🔄 Frequent IP Changes — Large volumes of independent requests\n✅Web scraping — collecting data from many pages\n✅Market research — gathering data from multiple sources\n✅Automated data collection — processing repeated requests\n\n⏱️ Sticky Sessions — Multiple actions in the same session\n➡️Social media automation — handling multiple account actions\n➡️Ad verification — checking ads from different locations\n➡️Multi-step web automation — moving through several pages\n\nWith FlashID Rotating Proxy, Sticky Sessions give you four options:\n⏳30 min ⏳60 min ⏳90 min ⏳120min\n\n🎁FlashID's September offer is now live — up to 75% off, with prices as low as $1/GB.\n‼️Only 12 days left! Grab the deal now!",
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  "text": "Agents that need document data are burning most of their token budget on parsing. jina-ocr-v1 solves that for PDFs and scans at 2.57 pages/sec.\n\nThe same problem exists for web data. Agents re-reading entire pages on every extraction pass, sending full HTML to a model, rebuilding",
  "full_text": "Agents that need document data are burning most of their token budget on parsing. jina-ocr-v1 solves that for PDFs and scans at 2.57 pages/sec.\n\nThe same problem exists for web data. Agents re-reading entire pages on every extraction pass, sending full HTML to a model, rebuilding extraction logic when layouts change.\n\nI built DeepScrape to handle this differently. Generate a CSS selector once with an LLM. Reuse it on every subsequent extraction. When the page structure changes, the selector heals itself. The LLM fires for selector generation and adaptation, not for reading every page.\n\nIf you're building agents that need reliable web data at scale, or want a site-to-MCP bridge that an agent can query directly without re-scraping from scratch each run, take a look.\n\nhttps://t.co/JZYTWY8roq\n\nhttps://t.co/L0XqFc9Zt7",
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  "text": "@Marie_Haynes @suganthan @Cloudflare Machine to machine microtransactions will redefine the entire web monetization model. Using protocols like x402 to charge crawlers per page visit flips the script on content scraping. If LLMs want training data and live retrieval, paying per token crawl is the only fair",
  "full_text": "Machine to machine microtransactions will redefine the entire web monetization model. Using protocols like x402 to charge crawlers per page visit flips the script on content scraping. If LLMs want training data and live retrieval, paying per token crawl is the only fair equilibrium.",
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  "text": "👗 Fashion market research starts with fresh data.\n\nExplore: https://t.co/wQ8kzhnCQo\n#WebScraping #FashionData #Zara #MarketResearch #RealDataAPI https://t.co/UDlp0CbGqX",
  "full_text": "👗 Fashion market research starts with fresh data.\n\nExplore: https://t.co/wQ8kzhnCQo\n#WebScraping #FashionData #Zara #MarketResearch #RealDataAPI https://t.co/UDlp0CbGqX",
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  "text": "Which AI concept mimics the human brain?\n\n- Hardcoding\n- Neural Networks\n- Spreadsheets\n- Web Scraping",
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  "text": "@dang_duytan @vangrid_io turning physical movement into ground truth for ai is a massive pivot from just scraping the web",
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  "text": "2xDGX Sparks.  For web scraping, what’s the best models? Obliterated, Abliteration? needed?",
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  "text": "@doctt477 @onusoz The only model that actually works good for me and gets some stuff done is the Qwe 3.6 35b MOE model and it's actually very useful for general chatting and scraping the web",
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  "text": "Guidelines 03/2026 on web scraping in the context of generative AI | European Data Protection Board https://t.co/rvfpKUWkDw",
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