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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?",
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"text": "Who is behind the onslaught of these obvious bot accounts? 🤔\n\n‘Freelance Web Developer’.\n\nCan we run an analysis over their following list / comments to pinpoint exactly who they’re trying to boost? https://t.co/E3HgHkDheL",
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"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",
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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",
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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 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",
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"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",
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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",
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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",
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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.\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": "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": "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",
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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 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. 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