В России изменились программы в автошколах22:30
The fierce standoff over Claude isn’t just a contract fight. It’s about who controls the future of military AI. In Washington and Silicon Valley, a conflict once relegated to specialist policy briefings has burst into view as arms-length diplomacy between the U.S. Department of Defense and Anthropic, the San Francisco-based AI lab, approaches a critical […]
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在四足机器人领域，宇树全球垄断级领先。2024年销量2.37万台，全球市占率达69.75%，贡献了全公司65%的营收；2025年上半年，中国四足机器人市场CR3(前三企业集中度)高达85.17%，其中宇树以60.11%的占有率稳居第一。
2月28日，美国和以色列对伊朗发动军事打击，伊朗伊斯兰革命卫队当晚宣布，禁止任何船只通过霍尔木兹海峡。据伊朗迈赫尔通讯社3月1日报道，一艘未经授权的油轮试图通过霍尔木兹海峡时被击中。霍尔木兹海峡连接波斯湾和阿曼湾，是沙特阿拉伯、伊拉克、卡塔尔、阿联酋等中东产油国的原油出口必经之路，通过这一海峡运输的石油约占全球石油运输总量的五分之一。（新华社）
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Abstract:Humans shift between different personas depending on social context. Large Language Models (LLMs) demonstrate a similar flexibility in adopting different personas and behaviors. Existing approaches, however, typically adapt such behavior through external knowledge such as prompting, retrieval-augmented generation (RAG), or fine-tuning. We ask: do LLMs really need external context or parameters to adapt to different behaviors, or do they already have such knowledge embedded in their parameters? In this work, we show that LLMs already contain persona-specialized subnetworks in their parameter space. Using small calibration datasets, we identify distinct activation signatures associated with different personas. Guided by these statistics, we develop a masking strategy that isolates lightweight persona subnetworks. Building on the findings, we further discuss: how can we discover opposing subnetwork from the model that lead to binary-opposing personas, such as introvert-extrovert? To further enhance separation in binary opposition scenarios, we introduce a contrastive pruning strategy that identifies parameters responsible for the statistical divergence between opposing personas. Our method is entirely training-free and relies solely on the language model's existing parameter space. Across diverse evaluation settings, the resulting subnetworks exhibit significantly stronger persona alignment than baselines that require external knowledge while being more efficient. Our findings suggest that diverse human-like behaviors are not merely induced in LLMs, but are already embedded in their parameter space, pointing toward a new perspective on controllable and interpretable personalization in large language models.
"We did share last quarter that memory and storage costs made up roughly 15 percent to 18 percent of our PC bill of materials, and we now currently estimate this to be roughly 35 percent for the year," said CFO Karen Parkhill on the company's latest earnings call. She also confirmed that part of the company's response will be price increases. Samsung similarly warned of potential price increases due to AI-induced memory shortages.，推荐阅读91视频获取更多信息