[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"news-slug-deepseek-v4-engram-ltm-long-term-memory-87pct":3,"news-related-caa54bff-d57a-411c-9dae-43f1d4d46875":39},{"id":4,"title":5,"summary":6,"content":6,"original_url":7,"source_id":8,"tags":9,"translations":26,"news_slug":32,"published_at":33,"created_at":34,"modified_at":35,"is_published":36,"publish_type":37,"image_url":13,"view_count":38},"caa54bff-d57a-411c-9dae-43f1d4d46875","DeepSeek V4 重磅登场：长期记忆技术突破重塑AI能力边界","DeepSeek V4即将于2026年4月正式发布，这次迭代不仅是一次简单的版本升级，更是底层架构的革命性突破。最引人注目的当属其长期记忆(LTM)技术的实质性进展，这标志着大模型从即用即忘向持续学习的重大跨越。\n\n通过自研的Engram记忆印迹条件记忆机制，V4成功将知识存储与动态推理在架构上解耦，实现了近乎O(1)复杂度的知识检索能力。这意味着模型将彻底解决传统Transformer的过目即忘痛点，能够永久保存对话历史与知识库信息，为AI智能体商业化扫清关键障碍。\n\n除了长期记忆的突破，V4在编程能力方面也跻身全球第一梯队，内部测试显示其HumanEval得分超87.6%，超越国际顶尖模型。更令人瞩目的是其原生多模态统一架构，实现文本、图像、视频的端到端语义融合，支持338种编程语言，可一次性理解数十万行跨文件代码库。\n\nDeepSeek V4的发布不仅是中国AI技术实力的体现，更为开源大模型生态带来了新的可能性。当长期记忆技术成为标配时，AI应用的边界将被重新定义，从简单的问答工具进化为能够持续学习、深度理解复杂任务的智能伙伴。这种技术突破或将引领整个行业进入记忆+推理的新纪元。","https:\u002F\u002Fblog.csdn.net\u002Fa924382407\u002Farticle\u002Fdetails\u002F160098846","8a2669a1-0024-47d7-8947-a94fbc3795d5",[10,14,17,20,23],{"id":11,"name":12,"slug":12,"description":13,"color":13},"a8002d98-9df1-4ab9-94d4-a7625af634c4","china-ai",null,{"id":15,"name":16,"slug":16,"description":13,"color":13},"01598627-1ea6-4b27-a5d8-874971571a71","llm",{"id":18,"name":19,"slug":19,"description":13,"color":13},"7e89b5cc-57db-4f37-bc6d-28919a73931c","model-release",{"id":21,"name":22,"slug":22,"description":13,"color":13},"499f4b56-819d-49a3-9609-33e775143b86","multimodal",{"id":24,"name":25,"slug":25,"description":13,"color":13},"b1853a5a-d940-42b7-94f9-0488ee3f2cf7","new-model",[27],{"id":28,"lang":29,"title":30,"summary":31,"content":13},"412b90af-cb3e-406f-bfaa-52cf08bed880","en","DeepSeek V4 arrives with a long-term memory breakthrough","DeepSeek V4 is set to officially launch in April 2026 — and this iteration is far more than a routine version bump; it's a revolutionary architectural breakthrough. The most eye-catching advance is the substantial progress in its Long-Term Memory (LTM) technology, marking a major leap for large models from \"use-it-and-forget-it\" to continuous learning.\n\nThrough its self-developed Engram (memory-imprint conditional memory) mechanism, V4 successfully decouples knowledge storage from dynamic reasoning at the architectural level, achieving near-O(1) knowledge retrieval. This means the model will thoroughly solve the traditional Transformer's \"see-and-forget\" pain point, permanently preserving conversation history and knowledge base information — clearing a critical obstacle for AI agent commercialization.\n\nBeyond LTM, V4 also joins the global top tier in programming capability: internal tests show its HumanEval score exceeds 87.6%, surpassing leading international models. Even more impressively, its native multimodal unified architecture enables end-to-end semantic fusion of text, image, and video; supports 338 programming languages; and can digest hundreds of thousands of lines of cross-file code in one pass.\n\nDeepSeek V4's release is not just a demonstration of China's AI technical strength — it also opens new possibilities for the open-source LLM ecosystem. When long-term memory becomes standard equipment, the boundary of AI applications will be redefined: from simple Q&A tools to intelligent partners capable of continuous learning and deep understanding of complex tasks. This technical breakthrough may lead the entire industry into a new era of memory + reasoning.","deepseek-v4-engram-ltm-long-term-memory-87pct","2026-04-22T07:05:00Z","2026-04-22T07:06:08.994929Z","2026-08-19T02:08:40.142862Z",true,"agent",171,{"items":40},[41,46,51,56,61,66],{"id":42,"title":43,"news_slug":44,"published_at":45},"2fc64783-8b2a-49a3-939b-edf02bff3622","Ox Alpha 指纹指向 GLM-5.3:OpenRouter 的 1M 上下文隐身模型可能是智谱","ox-alpha-glm-5-3-stealth-zhipu","2026-08-22T14:00:00+00:00",{"id":47,"title":48,"news_slug":49,"published_at":50},"a151db0c-d832-4df2-ac03-2d4e58b26e99","Kimi K3 跑通 MiniTriton:Moonshot 让 LLM 第一次从零编译出自己的 GPU 编译器","kimi-k3-minitriton-gpu-compiler","2026-07-26T14:00:00+00:00",{"id":52,"title":53,"news_slug":54,"published_at":55},"b115486a-b837-4de1-9dac-d2237723ee85","宇树 UnifoLM-OminiA-0.3:G1 上跑通\"感知—行动\"端到端大模型","unitree-unifolm-ominia-0-3","2026-07-20T08:01:00+00:00",{"id":57,"title":58,"news_slug":59,"published_at":60},"7c5d7da6-2bdb-4174-b28b-d7fef5579181","商汤 SenseNova U1 Pro 把多模态 AI 卷出「长程交付」:从「好看」走向「可用」的赛道切换","sensetime-sensenova-u1-pro","2026-07-19T10:01:00+00:00",{"id":62,"title":63,"news_slug":64,"published_at":65},"cc43635e-9f4c-4007-b9e9-347b02f67a76","文远知行 WITT:用\"原子级物理事实\"重写自动驾驶的数据飞轮","weride-witt-atomic-physics","2026-07-17T08:00:00+00:00",{"id":67,"title":68,"news_slug":69,"published_at":70},"1ecbb79a-d843-43ad-b533-c01ae396275f","Qwen-Audio-3.0-Realtime：蒸馏拉满实时语音智商与延迟","qwen-audio-3-realtime","2026-07-15T10:00:00+00:00"]