Maidan Nezalezhnosti, Kyiv, 1920s.

If the shoe fits…

GPT-Image-2 vs Nano Banana Pro social media is cooked 🤯 prompt below

If other countries were paying the tariffs, why are US businesses getting refunds for them?

1923 – earthquake in Kamchatka 1924 – Lenin died 1952 – earthquake in Kamchatka 1953 – Stalin died 2006 – earthquake in Kamchatka 2007 – Yeltsin died 2025 – earthquake in Kamchatka 2026 - ???

Moroccan architecture

まじでそういうのいいから早く渡ってくれ…

Structural Innovation & Ultra-High Context Efficiency 🔹 Novel Attention: Token-wise compression + DSA (DeepSeek Sparse Attention). 🔹 Peak Efficiency: World-leading long context with drastically reduced compute & memory costs. 🔹 1M Standard: 1M context is now the default

DeepSeek-V3: Dec 26, 2024 DeepSeek-V4: Apr 24, 2026 484 days later, we humbly share our labor of love. As always, we stay true to long-termism and open source for all. AGI belongs to everyone. ❤️🌍 #DeepSeekV4 #AGIforEveryone #OpenSource

DeepSeek 4 arrives huggingface.co/deepseek-ai/De…

Structural Innovation & Ultra-High Context Efficiency 90% compression on context is a massive deal This tech will be ported to other smaller models, 1M context window on home models to come. Novel Attention: Token-wise compression + DSA (DeepSeek Sparse Attention). Peak

DeepSeek has always excelled in new architecture. V3 gave us MOE mixture of experts, mixed precision training, multi-token prediction, multi-head latent attention. That cascaded into wildly improved smaller OS models for self hosting. Expect 1M context context on other models

전체 오픈소스 로컬LLM 모델 성능 비교표 아래 맥에서 구동 가능 Qwen3.6-27b : 32gb Minimax-M2.7 : 64gb~ DeepSeek-V4-Flash : 128gb~ GLM-5.1 : 256gb~ Kimi-K2.6 : 512gb~ DeepSeek-V4-Pro : 512gb~ 당신은 어떤 모델을 사용할건가요?

Mt. Fuji, Japan 🇯🇵

A kinetic sculpture, moving with wind but balanced by science.

“The Death Star is under attack. Where is Vader?” “He’s in the ballroom, sir.”

The attacks on Russian refineries will continue until NAFO gets a ballroom.