DreamDancer

55.7K posts

DreamDancer

DreamDancer

@ChristinDancer

As a general warning, I have a low follower count because I will check profiles. There is no criteria I use to permit people to follow me. 🚫🤖

Katılım Haziran 2018
592 Takip Edilen201 Takipçiler
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Uncensored.AI
Uncensored.AI@GoUncensored·
The two missiles shot at Diego Garcia were a false flag likely conducted by Israel. Two days later they’re being used to justify world war 3. At the exact moment Israel needs help the most.
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Sama Hoole
Sama Hoole@SamaHoole·
The soy industry kills the Amazon. This needs saying plainly, because somehow it has been filed under "environmental problems with meat" when soy is the thing doing it. Brazil is the world's largest soy producer. Between 2001 and 2020, soy expansion drove the loss of millions of hectares of Cerrado and Amazon forest. This soy, and here is where the story performs a disappearing act, is overwhelmingly used to produce soybean oil, with the defatted meal then sold as animal feed. The oil is the product. The chickens get the leftovers. The deforestation is happening to make the cooking oil in your shop-bought hummus. Glyphosate use on soy is among the highest of any agricultural commodity on Earth. Then the nutrition. Soy contains phytoestrogens, isoflavones, that structurally resemble oestrogen and bind to oestrogen receptors. Whether this matters at normal consumption levels is contested. What isn't contested: the cumulative exposure across soy protein isolate in protein bars, meat alternatives, infant formula, and oat milk is not being tracked by anyone. Soy also contains phytic acid, lectins, and trypsin inhibitors. Traditional fermented preparations: miso, tempeh, natto, break these down substantially. Soy protein isolate, ultra-processed and added to half the products in the wellness aisle, does not. The protein content is real. The amino acid profile is reasonable for a plant. These facts exist. But a product that cleared the Amazon, is littered with defensive toxins, runs on glyphosate, and arrives in your protein bar as a hexane-extracted isolate has somehow become the healthy and environmentally ethical choice. At least the cow ate grass.
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Chibi Reviews
Chibi Reviews@ChibiReviews·
BREAKING CENSORSHIP NEWS: Currently there's a growing group of people advocating to get the EU to force censorship onto Zenless Zone Zero. They are comparing their tactic to what the CCP "Chinese Communist Party" does with reports and are encouraging it.
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Food Pleaser
Food Pleaser@FoodPleaser·
Would you???
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Handre
Handre@Handre·
So you know how hospitals cost a fucking fortune, right? Well, back in 1964, New York basically invented this brilliant idea called "certificate of need" laws. The state said hospitals couldn't expand or build new facilities without government permission - you know, to control costs and prevent "wasteful duplication." (Because nothing says efficiency like bureaucrats deciding where sick people can get treatment.) The feds loved this shit so much that by 1974, they were bribing states with Medicare dollars to adopt these laws nationwide. By 1982, almost every state had jumped on board. Then something hilarious happened - the federal government looked around in the '80s, realized these laws were actually making healthcare MORE expensive (shocking!), and repealed the federal requirements in 1987. But here's where it gets really good. Thirty-five states just kept their certificate of need laws anyway, because why give up power once you've got it? Today, if you want to open a hospital in North Carolina or build an MRI center in Virginia, you've got to prove to some panel of bureaucrats that your community "needs" it. Meanwhile, the 15 states that ditched these laws? They've got more hospitals, lower prices, and better access to care. You're literally sitting in a state where the government decides whether you deserve a nearby hospital based on their fucking spreadsheets. And we wonder why an ambulance ride costs more than a used car.
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Vivid Publishing
Vivid Publishing@Dreamkeepers·
How romantic!❤️❤️❤️ How... it's romantic right? (Lilith draining Bast in Volume 4.)
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Vivid Publishing
Vivid Publishing@Dreamkeepers·
DAMN- right over the edge.🧗‍♂️ 💨 😮 There's something very wrong with Bast, or very right. Maybe both.
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Vivid Publishing
Vivid Publishing@Dreamkeepers·
Not sure if they teach this in girlscouts- She probably read it in a book.📚 (AND YOU CAN TOO! Graphic novels discounted for our store moving sale: dreamkeeperscomic.com/store )
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Mr. Mike
Mr. Mike@mrmikeMTL·
Be honest for a second: If your best friend called you at 3am and said “don’t ask questions, just come”, would you actually show up?
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Restoring Your Faith in Humanity
A Polish dance group, Fair Play Crew, drew global attention by recreating on stage the stiff and synchronized movements of 1980s fighting video games, such as the classic International Karate. I've seen this so many times, still cracks me up 😂
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God of Prompt
God of Prompt@godofprompt·
🚨 Holy shit… Columbia University just dropped one of the most unsettling papers on AI inference I’ve read in a long time. They proved that the entire private AI inference industry built the wrong thing. Prior methods: encrypt the full transformer. 280GB per query. 60-second latency. Enterprise-grade security theater. GPT, Gemini, Qwen, and Mistral independently converged to nearly identical internal representations. One linear equation connects them. > Sub-second inference. 1MB of communication. Same security guarantees. > The private AI inference problem is real. Hospitals can't send patient data to OpenAI. Banks can't send transaction records to Google. Legal firms can't send case files to Anthropic. The solution the industry built: encrypt everything every layer, every attention head, every weight using homomorphic encryption and secure multi-party computation. The result: 280GB of encrypted communication per query. 60-second latency. > Infrastructure costs that make production deployment practically impossible. > Columbia University found the shortcut everyone missed. The Platonic Representation Hypothesis the observation that large models trained on enough data tend to converge toward a shared statistical understanding of the world turns out to be exploitable. GPT, Gemini, Qwen, Mistral, and Cohere, trained independently on different data with different architectures for different objectives, developed internal representations with CKA similarity scores between 0.595 and 0.881. That's not close. > That's essentially the same space. > If the spaces are the same, you don't need to encrypt the model. You learn a single affine transformation one matrix that maps your model's internal representations into the provider's space. Encrypt that matrix. > Send it. The provider runs one linear classification operation on encrypted data and returns the encrypted prediction. You decrypt locally. The transformer never gets encrypted. The weights never get exposed. The query never leaves your control in readable form. > HELIX is the system they built on this insight. During training, the client encrypts their embeddings from public data and sends them to the provider, who computes the alignment map under encryption and returns it. During inference, the client applies the alignment locally, encrypts the transformed representation, and sends it. The provider applies a linear classifier homomorphically and returns the encrypted prediction. > Multiplicative depth of one. No bootstrapping required. 128-bit security by CKKS standard. → Prior methods communication cost: 280.99GB per query (Iron), 25.74GB (BOLT), 68.6GB (MPCFormer) → HELIX communication cost: less than 1MB per query → Prior methods latency: 20-60+ seconds per query → HELIX latency: sub-second → Cross-model CKA similarity: 0.595 to 0.881 across GPT, Gemini, Qwen, Mistral, Cohere → Text generation quality: 60-70% of single-model baseline for high-compatibility pairs → Tokenizer compatibility predicts generation quality with r=0.898 The finding that should end careers: models above 4B parameters with tokenizer compatibility above 0.7 exact match rate can generate coherent text across model families using only a linear transformation. Qwen encoding. Llama decoding. No fine-tuning. No weight sharing. No data transfer. Just matrix multiplication applied to the boundary between two independently trained systems that accidentally became the same thing.
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Bob the Unvaxxed Tomato ✝️🪔🕊
Taxation isn't just theft. It's a fine for existing. The Harlot of Babylon doesn't need my tax dollars.
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rabbitholebot
rabbitholebot@rabbitholebot·
How far down the rabbit hole do you want to go?
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Bronymon
Bronymon@Bronymon_·
If you cube apples and put them in a salad, you’ve added 𝙛𝙧𝙪𝙞𝙩𝙤𝙣𝙨.
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Old Salty Marine
Old Salty Marine@BamaSaltyMarine·
Would you attend a funeral of someone who never attended yours? Be honest...
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Espiritu
Espiritu@OtakuEspiritu·
A site run by the most insane left, wants YOUR personal information....... Yes I TOTS trust them to not dox me........./s
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