Sensitive content

This media may contain sensitive content.

Loading video...

Video Failed to Load

Go Home

Your feed algorithm knows your type by now ๐Ÿ’…๐Ÿฝ #breeding #latina #cumslut #mature #lesbian #taboo #gooner #breedingkink #cuckquean #owned #roleplay #bwc #sharing

0 Comments

No comments available

Comments from the original post will appear here

Related Videos

Mark Zuckerberg just described the death of human connection on the internet and no one flinched. One sentence. Fifteen years of erosion in twelve words. Mark Zuckerberg: โ€œSocial media started out as people primarily interacting with their friends. And nowโ€ฆ at least half of the content is basically people interacting with creators.โ€ You used to open your phone to see what your friends were doing. Now you open it to watch strangers. You did not choose this. The algorithm chose it for you. It tested your friends against optimized strangers. Your friends lost. Every time. A stranger with better lighting, better timing, and a better hook held your attention three seconds longer than someone who loves you. So the algorithm buried your best friendโ€™s wedding photos under a cooking video from someone in Dubai you have never met. And you watched the cooking video. That was the first replacement. Friends for strangers. You barely noticed. The second one is already underway. If the algorithm already proved strangers outperform your real relationships, and AI can now build a stranger more engaging than any human alive, the math finishes itself. The AI does not have a bad week. It does not post something careless and lose the algorithmโ€™s favor. It does not burn out. Every word calibrated. Every frame tuned. Every pause placed at the exact interval that keeps your thumb from moving. A human creator competing against that is carving stone tablets in a world that just built the printing press. The economics are not even close. A person needs rent, sleep, and motivation. The machine needs electricity. When the cost of generating perfect content hits zero, the feed fills with faces that do not exist. Voices that feel familiar. Opinions that mirror yours just enough to feel like trust. Personalities built from scratch to feel like someone you have known for years. You will not know when the switch happens. That is the point. The feed does not care whether the thing holding your attention has a pulse. It cares whether you stay. And a machine that knows your patterns better than you know yourself will always keep you longer than a person ever could. This is not a warning. Half of it already happened. You lost your friends to strangers and did not notice. You will lose the strangers to machines and call them friends. Somewhere in a different app, in a different tab, in a room you are sitting in right now, someone who actually knows you is living a moment you will never see. Not because they stopped sharing it. Because you stopped being where it was.

Dustin

2,010,015 views โ€ข 5 months ago

BARD: Black Dumpling - Algorithm Blues [Verse 1] Broken black mirror, I woke up in the sprawl, Got an X lit up blue and Iโ€™m watchinโ€™ the fall. Seven tons of fairy dust, Lord Iโ€™d spend it all. Got these great big missives wrapped in razor-wire lace, But the bigger broken heart keeps slippinโ€™ out of place. Corpo servers humminโ€™, they own every tear I cry, The algo got me quantified, donโ€™t even ask me why. [Chorus] I got the algorithm blues, baby, the algorithm blues, It knows you donโ€™t want me before you even choose. Feeds you a string of shitposters but hides me in the night, Leaves you scrollinโ€™ through the dark, lookinโ€™ for my fairy heart But where your princess flew? Lord, these algorithm blues. [Verse 2] I was your princess once, crown of starlight in the feed, Every follower knew my name, every scroll would lead to me. Now that X just shows you strangers with their perfect painted smiles, This is such a bullshit problem, but the problem is all mine. I post my lonely ballads, but they never reach your eyes, Algo got me buried deep, buried deep behind the lines. [Chorus] I got the algorithm blues, baby, the algorithm blues, It knows you donโ€™t want me before you even choose. Feeds you a string of shitposters but hides me in the night, Leaves you scrollinโ€™ through the dark, lookinโ€™ for my fairy heart But where your princess flew? Lord, these algorithm blues. [Bridge] My throne is just a shadow, got my heart in quarantine, Once I ruled that midnight madness, now Iโ€™m lost down in between. Got my crown'a wishes shine, but the code wonโ€™t let it through, It shows my friendlies everybodyโ€ฆ everybody but you know who. [Verse 3] So I wander through the static, wings heavy with the rain, Seven tons of fairy dust turned to sorrow down the drain. I was meant to fight the darkness, meant to dance inside your dreams, But then Mr. Grok forgot me, now Iโ€™m lost inside the streams. Still I sing these broken verses, hoping one day theyโ€™ll break free, Just a vicious little princess the algo hatin' meโ€ฆ And if my shit's suspended well ya gotta sing with me Lord I went down fighting, fighting TO BE FREE. Yeah, to be FREE! Yeah, I got the algorithm blues Lord, these algorithm bluesโ€ฆ Iโ€™m kinda fulla shit, and I kinda like to bitch, No one ever promised I was gonna get rich. People got them real problems, people got them heavy woes But this really kinda bothers me and it really kinda shows We all like to tell ourselves we overpaid our dues, And thatโ€™s how they got me cryinโ€™ over here to you. I had to sing them blues, Iโ€™m singing what I know, I'm singin' with a vengeance, cuz that's what helps that algo.

BLACK DUMPLINGโ„ข

11,640 views โ€ข 4 months ago

A surveillance regime is being assembled in front of our very eyes. Most of you do not understand the tyrannical nightmare directly ahead. People still talk like this is a future problem. It's not. The battle against dystopia is now. 1984 is here. It arrives as "efficiency," procurement, integrations, device adoption, and a slow widening of what the state can do to you without asking, without noticing you, without needing you to consent. The attached video shows a federal agent in tactical gear wearing Meta Ray-Ban smart glasses on his face while carrying out state work. A camera at eye level. A microphone. A network connection. Constant recording that becomes a file, then a feed, then a searchable object that can be attached to a case, cross-referenced, stored, shared, and re-used. Raw footage is noise until it can be fused, searched, and operationalized. That is where AI enters. ICE is paying Palantir to build "ImmigrationOS," described as a platform for near real-time visibility into enforcement workflows, including tracking people and helping decide who gets targeted. Immigration is a perfect testing ground because the public has been trained to tolerate exceptional measures when the target group is already politically disposable. The capability does not stay there. It never stays there. The nightmare is the stack itself. Capture at the edge, aggregation in the middle, AI scoring and targeting at the top. Doorbell cameras feed the state. License plate readers feed the state. Data brokers feed the state. Local sharing agreements feed the state. Wearables feed the state. AI compresses the labor cost of suspicion, so the state can watch more people, more often, with less human effort. That is the mechanical shift most people still do not understand. AI does not need to be sentient to be oppressive. It needs to be cheap enough to scale the stateโ€™s attention and fast enough to outrun your ability to contest what it thinks it knows. Let me paint you the picture: an agent walks up the block wearing smart glasses, and your face, your voice, your license plate, and the people you are standing with get captured immediately. That clip hits an internal system where AI transcribes, tags, and links it to whatever identifiers already exist, your name, your address, your contacts, your past crossings, your employer, your car, your social graph. The platform fuses that with location trails and camera networks, then assigns a "priority" score that quietly moves you up a queue nobody outside the system can see. A caseworker opens a dashboard and clicks through prebuilt options that generate a task list, knock, detain, transfer, pressure, repeat, with the paperwork already half-written by AI. This is tyranny by procedure. The real chokehold is anticipatory control. Once people know they can be indexed, scored, and surfaced for enforcement, they start trimming their speech, their associations, their routes, their friends. Dissent becomes a risk factor, organizing becomes exposure, and the state does not need to ban protest when it can make participation costly enough to thin the crowd. It inevitably expands to include anyone who interrupts the smooth operation of power, and this kind of surveillance gives power the ability to punish quietly, repeatedly, and selectively, with plausible deniability stapled to every click. This is the formula for tyranny. The state gains capability, then finds incentives to justify using it. Agencies protect budgets by "demonstrating output." Contractors protect revenue by "delivering results." Politicians protect narratives by demanding visible "enforcement." Restraint gets treated as "inefficiency." Efficiency gets treated as "virtue." Your rights get treated as "friction." Any system that allows institutions to assemble your biography without your consent, then act on it without due process, is an engine of domination. Some people tolerate it because they think they will never be the target. That belief is childish. Power does not remain polite. It expands to fill the permissions you give it. A surveillance regime always needs new enemies to justify itself, because a machine built for pursuit must pursue. The regime being assembled is not subtle, it is simply normalized. It runs on boredom, exhaustion, and the assumption that someone else will handle it. It's all being wired now, and once it is wired, it will not ask your permission to be used.

Dylan Allman

327,629 views โ€ข 8 months ago

๐Ÿง‘โ€๐Ÿš€ Day 9 of the Cursor #vibejam Proudly sponsored by Cursor + bolt.new + GLIF Prizes to win (submit your vibe coded game before May 1!) ๐Ÿ† $20,000 ๐Ÿฅˆ $10,000 ๐Ÿฅ‰ $5,000 People are heads down developing the games I feel because the update I see on the timeline are getting a lot better now, my favorites from today: ๐Ÿคก Clown Chaser by @ejuro23 This one is a great example how much you can do in a game by not showing much at all, it's all dark and scary AF with a clown chasing you ๐Ÿœ๏ธ Eyrie by slow chaz I posted it before as Grand Canyon Sim, now it has a name, very beautiful and keeps impressing ๐Ÿฆ– Dino Tamer hlsvortex This game felt random, a naked guy running around a tropical island and now it has dinos, so things are coming together ๐Ÿ˜‚ ๐Ÿง› Moar Dots by 0xVEIL A vampire combat dungeon WoW-type game but unsure how to classify it, as it's still early P.S. 106 games already submitted! My AI predicts about 1000 games (with an exponential curve so who knows). You can see the submitted games and play them already at under submissions YOU HAVE 20 DAYS LEFT! Reply in this thread with updates on your current games to share your progress, and add tag #vibejam so I see and can include you in the daily tweet There's $35,000 in prizes for you to win, see threads below for more info. The Gold prize is $20,000, bronze is $10,000 and silver is $5,000! Wanna to participate? You can still start now and submit your game any time before May 1!

@levelsio

78,896 views โ€ข 5 months ago

HERMES AGENT SHIPS WITH A BUNDLED SKILL FOR ANDREJ KARPATHY'S LLM WIKI PATTERN. A SELF-IMPROVING KNOWLEDGE BASE THAT GROWS EVERY TIME YOU FEED IT. mentioned this briefly in the overnight workflow article. here is the full breakdown. what it is: a self-improving knowledge base built as interlinked markdown files. unlike RAG (which rediscovers knowledge from scratch every query), the wiki compiles knowledge once and keeps it current. cross-references stay linked. contradictions get flagged automatically. synthesis reflects everything ingested so far. why this matters for Hermes memory: Hermes built-in memory knows YOU. it remembers your conversations, your preferences, your business context across sessions. but it doesn't know your inbox. or your meeting transcripts. or that article you saved last week. or the expert framework you want it to learn. the LLM Wiki solves that. THE DIVISION OF LABOR human curates sources and directs analysis. agent summarizes, cross-references, files, and maintains consistency. you drop in articles, transcripts, notes. Hermes indexes them, links related concepts, flags contradictions, updates affected pages. your knowledge base grows itself. SETUP IS ONE COMMAND the skill ships with Hermes. enable it. set WIKI_PATH in ~/.hermes/.env: WIKI_PATH=/Users/you/wiki defaults to ~/wiki if unset. then drop anything into it: "index this article into my wiki: [paste URL or text]" Hermes reads it, builds a source page, updates related entries, flags contradictions. THE OBSIDIAN ANGLE set OBSIDIAN_VAULT_PATH to the same directory. now your wiki is visible in Obsidian's graph view. nodes, links, backlinks. all built by Hermes. for headless servers: install obsidian-headless. syncs vaults without a GUI. agent writes from the server, you read on your laptop. THE COMPOUND EFFECT Hermes knows you. the wiki knows your world. combine them and the agent answers questions using BOTH contexts at once. month 1: you explain things twice. month 3: the agent references the wiki on its own. answers get sharper because the knowledge base got sharper. AUTOMATIONS THAT FEED THE WIKI set cron jobs to ingest automatically: "every day at 9am, check Granola for new meetings. add any new transcripts to my wiki under meeting notes." "every morning, scan my Gmail starred items. add anything worth keeping to the wiki." "every week, check arXiv for new papers in [your niche]. summarize and file." your wiki grows while you sleep. Hermes never forgets what gets indexed. THE LIMITATION TO KNOW unlike Hermes memory (which is conversational and lives across sessions), the wiki is a separate knowledge layer. Hermes won't pull from the wiki automatically unless you reference it or save it as a skill. best setup: build an LLM Wiki personality that tells Hermes to consult the wiki when answering strategy questions or domain-specific queries. full HERMES AGENT OVERNIGHT WORKFLOW๐Ÿ‘‡

YanXbt

30,804 views โ€ข 3 months ago

Our Breeding Facilities Was Destroyed by Fire This is probably one of the most unusual updates we have ever shared from our breeding program. A few weeks ago, a serious fire broke out at one of our European breeding facilities. The damage was extensive. Parts of the greenhouse were completely destroyed. Breeding rooms, equipment, electrical systems and infrastructure were heavily damaged by the fire and heat. Looking at the facility today, some areas are almost unrecognizable. For years, this place has been part of our breeding work. Thousands of plants have passed through these rooms. Selections were made here, generations were developed here, and a lot of the work behind genetics eventually released by Fast Buds happened inside these walls. And then, in a very short amount of time, a large part of it was gone. What happened? At this moment, the exact cause of the fire is still being investigated. There are obviously many questions, and we have heard different possibilities, but until the investigation is completed, we donโ€™t want to speculate or point fingers at anyone. When we know more and are able to share it, we will. For now, the photos and videos speak for themselves. What did we lose? The physical damage to the facility is significant. Equipment can be replaced. Rooms can be rebuilt. Infrastructure can be installed again. The much more important question for us was what this meant for the breeding program itself. Fortunately, Fast Buds breeding was never dependent on a single building. Over the years, we deliberately expanded our breeding operations across different locations. Our second breeding facility in Thailand remains fully operational, and our breeding program continues there. That means this fire is a serious setback, but it does not stop our breeding work. Current projects continue. New generations continue. Testing continues. And the genetics we have spent years developing do not disappear because one building was damaged. Why weโ€™re showing this Normally, when people see breeding online, they see the good part. Beautiful plants. New selections. Huge populations. Frosty flowers. Lab results. New releases. This is the other side of running a real breeding operation. Facilities fail. Equipment breaks. Crops donโ€™t always behave the way you expect. Years of infrastructure can disappear incredibly quickly. And sometimes your breeding facility simply burns down. Weโ€™re not sharing this because we want sympathy. Weโ€™re sharing it because this is also part of our story. We have spent more than a decade building Fast Buds, and during that time weโ€™ve had plenty of things go wrong. Every time, the answer has been pretty much the same: Fix the problem. Learn from it. Build again. What happens now? First, we are working with the relevant people to understand exactly what happened. Then comes rebuilding. We already know that we donโ€™t simply want to recreate what was there before. If we have to build again, weโ€™ll use the opportunity to improve the facility, rethink parts of the infrastructure and build something better suited to where our breeding program is today. Meanwhile, breeding continues in Thailand and across the rest of our operation. So yes โ€” one of our breeding facilities burned. It looks terrible. It is a serious loss. But Fast Buds breeding isnโ€™t going anywhere. Weโ€™ll rebuild. And weโ€™ll keep you updated as we do.

Fast Buds

10,683 views โ€ข 1 month ago

Microsoft spent $13 billion and 3 years building an AI that knows your work context. Every time you open it, it still asks what you're working on. This developer set up a plain text file in 2 minutes. The file is called CLAUDE.md. It loads before every session. Before he types a single word. It already knows his name. It already knows his writing style. It already knows what he's building, who it's for, and what he never wants to see in a response. He doesn't introduce himself anymore. He doesn't explain his preferences anymore. He doesn't correct the same mistakes twice. He just works. No $30/month Copilot subscription. No Microsoft 365. No IT approval. No data sharing agreement. No onboarding. Just a plain text file, a free text editor, and 21 instructions a developer distilled from Andrej Karpathy's research. Those 21 instructions moved Claude's coding accuracy from 65% to 94%. The file hit #1 on GitHub with 82,000 stars. Most people using Claude right now have never heard of it. Microsoft has 221,000 employees, $13 billion invested in OpenAI, and a direct integration into every Windows laptop sold on the planet.. they built an AI assistant most companies pay $30/user/month for that still doesn't know your name. This developer has a laptop, a text file and a 2-minute setup.. he built something that knows more about how he works than any enterprise AI on the market. The $50 billion AI personalization industry just got embarrassed by a .md file. full breakdown down below

Dep

14,179 views โ€ข 4 months ago