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Researchers proved AI has deleted every reason universities exist. Harvard University ran a controlled experiment pitting a custom AI against their own top-tier classrooms. And the results are going to collapse the higher education bubble. They took 194 undergraduates and split them up. One group learned physics in one of Harvard’s best hands-on, active-learning physical classrooms. Group work. Instructor support. The premium university experience. The other group went home and learned the exact same material with an AI tutor. The AI didn't just win. It embarrassed the institution. Students using the AI learned more than twice as much as the students in the elite Harvard classroom. They scored 30% higher on the final assessment. And they did it in less time. Let that sink in. A piece of software sitting on a laptop outperformed a world-class faculty in one of the most elite learning environments on Earth. Universities have always justified their exorbitant tuition with two things: access to elite knowledge and the physical classroom experience. This study just proved both of those moats are gone. When software can teach you complex physics twice as well as a $60,000-a-year institution, the math of higher education breaks permanently. The AI didn't just give the students answers. It used strict pedagogical guardrails. It guided. It questioned. It forced the students to do the cognitive work. It offered perfect, one-to-one tutoring, personalized to the exact moment a student misunderstood a concept. That level of attention is mathematically impossible to scale in a physical lecture hall. For a thousand years, the university was the only place to get a premium education. Now, it’s the bottleneck. If AI can double your learning speed for a fraction of the cost, what exactly are students taking on decades of debt to pay for?

With @Cybertruck, we introduced & scaled many automotive firsts 48V architecture: 4x lower current that enables thinner, lighter wiring True Steer-by-Wire with no mechanical steering link, enabling variable steering response Combined with rear-wheel steering, this also brought coordinated front + rear steering for greater low speed maneuverability & high speed stability Structural stainless-steel exoskeleton: allows exterior panels to carry structural loads, resulting in far higher torsional stiffness Full-hard stainless air bending: forms ultra-hard exterior panels without damaging the visible surface Etherloop: gigabit vehicle network that eliminates ~70% of cross-vehicle wiring

LATEST: 🚨 Cybersecurity firm Rapid7 says a crypto phishing campaign dubbed "Operation Asterix" targeted roughly 885,000 phone numbers to steal seed phrases via fake Ledger, Trezor, and Exodus apps.

Chinese scientists' VR wings offer glimpse into future of embodied intelligence In a recent virtual reality (VR)-based study, a research team from Peking University in Beijing has demonstrated that the human brain can incorporate virtual wings into its body schema, offering new insights for the development of embodied intelligence technologies including brain-computer interfaces and smart exoskeletons.

Roman is nearly ready for its journey to L2, where it will map billions of galaxies, study exoplanets, and probe dark energy! Preparations here at Kennedy continue, and it is now on its specialized work platform, known as the Pantheon. Targeting launch no earlier than Aug. 30 on a @SpaceX Falcon Heavy from LC-39A!

#チャウ・シンチー# 監督最新作「#功夫女足# Kung Fu Soccer」 7月11日中国公開 チャン・シャオフェイ/ディリラバ/レイ(EXO) 特別出演：カリーナ・ラウ/#佐藤健！# 「#少林サッカー」から25年、新たな物語が始まる。# #香港映画# #中国映画# #KungfuSoccer# #周星馳# #StephenChow#

如果你手里正好有两三台 Mac，exo 可能是目前最值得折腾的本地 AI 项目之一。 它做的事情很直接： 把多台设备组成一个 AI 集群。 设备自动发现，模型根据各节点的内存、算力和网络情况进行切分。单台机器装不下的大模型，可以交给多台机器一起运行，推理过程留在本地，还能通过 OpenAI、Claude 和 Ollama 兼容接口接入现有工具。 官方展示过用 4 台高内存 M3 Ultra Mac Studio 运行 Qwen3 235B、DeepSeek 671B 和 Kimi K2 Thinking。 更有意思的是，借助 Thunderbolt 5 RDMA，增加节点不只是增加可用内存，还可能提高推理速度。 不过别被“闲置手机变 H100”带偏。 当前最成熟的还是 Apple Silicon Mac 集群，RDMA 对系统、设备和线缆都有要求；Linux GPU 支持仍在开发。它也不是零成本方案，高内存 Mac 本身并不便宜。 但 exo 指出的方向很有意思： 未来跑本地大模型，未必只能不断购买更强的单机，也可以把已有设备真正组织起来。 本地 AI 正从“攒一台神机”，走向“搭一套自己的算力网络”。