这位金发女孩签约伯恩茅斯女足时，俱乐部的官宣视频在各大平台累积了数千万次播放，一夜之间将她推上了网络焦点。

1、米6体育 在 WAIC 当晚这场“Agent 的‘最后一公里’——从能对话到能赚钱”的圆桌讨论中，来自中国、美国和新加坡的 AI 创业者——Jobright.ai 联合创始人郑玉典（Ethan Zheng）、Agnes AI 合伙人孙卓（Will）、Cloudsway AI 创始人杜知恒（William）、红熊 AI 执行总裁杨晓煜——围绕 Agent 商业化展开讨论，共同探寻不同商业模式下的困惑、机遇与生存法则。

中国公司，不管是大模型公司，还是大厂，亦或是传统产业公司，对AI的觉醒程度都显著高于东南亚、日韩等市场，差距非常明显。米6体育葡萄牙积4分排名第二，末轮打平就能出线，但如果输球，而刚果又赢了乌兹别克斯坦，那么两队同积4分，需要比较净胜球等数据，葡萄牙存在理论上的出局风险。

2、送暴力隔扣！杨瀚森8中7高效18+10+5，开拓者夏联大胜森林狼

在过去数周里，平衡6月30日前的账面收支是巴萨的首要任务。

3、育碧CEO力挺索尼“砍光盘”：没什么大不了

但这件事，真的只是"别人家的孩子真牛"吗？ 我看未必。

4、迪奥戈-科斯塔：那个三连扑拯救C罗的男人

时至今日，这种敌意已经深深嵌入了阿根廷的球迷文化之中。

5、2026怡宝中国足球超级联赛 第10轮 北京国安主场赛事票务公告

迈阿密国际并非唯一运用此类操作手法的俱乐部，温哥华白帽当初签下穆勒时，也是先用定向分配款合同过渡，今年再转为指定球员合同。

文本生成 3D、图片转 3D 模型会降低设计门槛，但真实打印还要解决结构强度、支撑设计、尺寸误差、材料匹配、装配关系和版权归属。

国资领导敢在投决会上签字，很大程度上是因为合同里写满了这类兜底条款。

6、逆转！马刺114-93击败开拓者，文班创59年纪录，此战诞生5个事实

十笔高度相关的交易，不是十次分散试错，而是同一场赌博被拆成了十个筹码。

约1.05亿欧元用于今年夏窗，剩余1.05亿欧元留给明年一月动用。

7、农业农村部答闪电新闻：实施奋战100天强田管抗灾害夺秋粮丰收行动 全力夺取秋粮和全年粮食丰收

英格兰人与米兰的合同截止到2027年，到现在续约还没有任何进展。

其次是即战力，镰田大地已经在德甲和英超证明过自己，并且有1年的意甲比赛经验，不需要太长的磨合时间。

8、输球输人！阿根廷3大输不起行为：背对冠军领奖 球员打人 拒绝采访

即战力与经验的完美契合 对于急需补强中场的曼联而言，蒂莱曼斯的到来无疑是一场及时雨。

根据机构预测，北方华创2028年归母净利润有望达到136亿元，对应当前股价的市盈率降至48.9倍。

东方甄选发布公告：进一步聚焦产品和品控，2026财年营收和利润增速加快 7月23日，东方甄选发布公告，预期在2026财年（注：2025年6月1日至2026年5月31日），总营收及溢利均实现大幅增长。

9、COMO Cordeillan-Bages于波尔多梅多克腹地正式启幕

300 万台产能意味着更强的采购能力和制造摊薄能力，也意味着当竞争者跟进时，头部公司有更强的降价空间。

真正反转需要三个条件：AI泡沫担忧重现、降息预期重启、美元信用担忧升温，目前均未显现。

10、号外！上海山西争抢胡金秋，已向广厦报价，广厦超市正式开张？无人是非卖品？

埃及队与比利时、新西兰、伊朗同组，最终以1胜2平积5分的成绩排名小组第二，队史首次晋级世界杯淘汰赛，他们累计打入5球失3球，进攻端表现明显优于澳大利亚。

The crowded, snake-like queue at WAIC led to a single attraction: an AI guitar capable of "improvisational jamming." During the 2026 World Artificial Intelligence Conference (WAIC), the annual updated edition of the Tianpule AI Guitar made its public debut. Over the same period, Quwan Technology, the parent company behind the instrument, released the Tianpule Large Model V4.7, pushing music-focused foundation models toward a new frontier where they can "understand revision feedback." It was unmistakable to anyone on the floor that this year’s WAIC generated unprecedented buzz. Yet the AI industry itself, having weathered countless hype cycles and technical trends, is bidding farewell to the hollow "compute arms race." The commercial value of large models is finally being realized within vertical, domain-specific scenarios. Industry observers are increasingly turning their focus toward a path distinct from general-purpose large language models: vertical integration. Compared with tech giants basking in haloed reputations and star AI startups boasting eye-watering valuations, vertical AI developers have quietly stepped into the center stage of the AI era. Grounded in user scenarios and equipped with self-sustaining revenue capabilities, they have emerged as pragmatic, viable models for the industry. By anchoring its strategy strictly on AI music and AI voice, and extending those capabilities into AI hardware, Quwan Technology offers a compelling case study of this trajectory. Bidding Farewell to the Compute Arms Race: A New Narrative in Vertical AI Commercialization The standard competitive posture in the large-model arena has long been a classic arms race: parameter count, context window length, and multimodal capabilities served as explicit metrics of a company’s worth. By this year, however, this model of horizontal expansion has hit diminishing marginal returns. On one hand, general-purpose models suffer from worsening homogeneity, and products that rely solely on model API outputs struggle to build user stickiness. On the other hand, as AI penetrates deep into everyday life rather than acting merely as a productivity tool, technology must be embedded into concrete scenarios to solve real pain points. Quwan Technology abandoned the illusion of building a jack-of-all-trades general platform, choosing instead to double down on two vertical domains characterized by high emotional value and dense interaction: AI music and AI voice. Though operating in different tracks, their underlying logic is remarkably similar: humanity’s most natural, non-textual modes of expression have long been constrained by professional barriers, and both possess an inherent capacity to stretch from digital content into physical hardware. The foundation of Quwan’s AI music ecosystem is the proprietary Tianpule Large Model. Steering clear of open-source fine-tuning, Quwan built the model from scratch to optimize for real-time interaction, laying the groundwork for a conversational creative experience powered by AI agents. During WAIC 2026, Quwan rolled out Tianpule Large Model V4.7, making AI-generated music far easier to control and iterate upon. Across two evaluation frameworks, Meta Audiobox Aesthetics and SongEval, V4.7 earned high marks in metrics such as content enjoyment, memorability, and vocal clarity, while ranking in the top tier for musicality, coherence, and naturalness. V4.7 powers Tunee, Quwan’s conversational music creation agent. This "conversation as creation" interaction model represents a true breakthrough in its capacity for proactive co-creation. Moving beyond passive "one-click generation" tools, Tunee acts more like a patient, music-savvy collaborator. Since its official launch last September, Tunee’s official website has maintained over a million monthly visits, making it one of the fastest-growing breakout products in China’s AI agent space. What has truly commanded the industry's attention, however, is the Tianpule AI Guitar. As a pioneer in the global generative AI guitar category, it was the first to embed an AI music foundation model into a physical guitar, enabling people without musical training or theory knowledge to experience the joy of playing and composing music. At WAIC 2026, the new Tianpule AI Guitar placed heavy emphasis on its core feature introduced this year: "AI Improvisation." Users can generate personalized music directly on the instrument and jam along, drastically simplifying the complex journey from composition to performance. Coupled with features like AI score transcription and hum-to-song conversion, complete beginners can quickly begin playing and writing music. The industrial significance of the Tianpule AI Guitar extends far beyond consumer electronics. It frees generative AI from behind the glass screen, turning it into a physical object that can be touched, plucked, and felt through resonance. For professional musicians, it serves as a catalyst for inspiration; for novices, it is the first key to unlocking the world of music. As Jasper Jia, Vice President of Quwan Technology, put it: only when ordinary people can use music to express emotions and document their lives as naturally as taking a photo or shooting a video will music truly become an inclusive medium for creation. The physical medium of the guitar allows AI music to step outside smartphones and laptops, truly weaving itself into everyday life. Quwan Technology’s vertical integration has constructed more than just a tech flywheel—where the model grants intelligence to the application, and the application breathes fresh experiences into the hardware. Simultaneously, the hardware feeds real-world user interaction data back into the model, establishing a system-level moat. In truth, AI has already made creation ubiquitous. But how to make good content visible, scalable, and profitable has become the stark reality facing the second half of the AIGC race. Quwan Technology’s answer to that reality is AI voice. In recent years, the overseas expansion of Chinese film and television productions has accelerated rapidly. Dubbing and localization, however, have remained a persistent industry pain point. High quality, high efficiency, and low cost form a classic impossible trinity. Against this backdrop, Quwan Technology collaborated with The Chinese University of Hong Kong, Shenzhen, to develop the MaskGCT voice foundation model. On October 24, 2024, MaskGCT was officially open-sourced to the world via the Amphion framework. Across multiple text-to-speech (TTS) benchmark datasets, MaskGCT achieved state-of-the-art (SOTA) performance, even outperforming human baselines on select metrics. All Voice Lab (Quwan Qianyin) represents the commercial application built atop the MaskGCT model. As a one-stop video translation and AI dubbing platform, All Voice Lab slashes AI translation and dubbing costs by 90% compared with traditional human labor while boosting speed more than 50-fold, handling a monthly translation volume of up to 500,000 minutes (roughly 5,000 drama episodes). Since its launch, All Voice Lab has assisted over 100 film, TV, and animation clients in solving localization hurdles. It processes nearly 10,000 short drama episodes per month across single languages for overseas markets, reaching over 30 countries and regions globally and helping clients boost monthly YouTube channel revenue by 10% to 30%. Driven twin-engine style by AI music and AI voice, Quwan Technology is transitioning into a "new infrastructure" provider for the entertainment industry. It proves that vertical AI companies do not need to serve everyone; by achieving excellence within targeted vertical domains, they can unearth vast commercial value. From Mobile Voice to AI Creation: Quwan’s 12-Year Evolution of "Interest" The first half of Quwan Technology's journey followed a textbook mobile internet success story. Its flagship product, TT Voice, evolved from a simple voice tool designed to help gamers find teammates into an interest-based social platform boasting over 200 million registered users. When the AI wave swept the globe, the company pivoted proactively, laying early groundwork in AI as far back as 2021 to secure its current position as a leader in AI entertainment. The essence of the company’s 12-year evolution represents a strategic leap from "connecting interests" to "creating interests." Yet the underlying logic running through it all has always been a focus on "interest" and a "human-centric" philosophy. For instance, TT Voice’s early positioning was remarkably simple—a "gaming walkie-talkie." But what fundamentally transformed founder Song Ke's understanding of the product’s value was the spontaneous behavior of its users. He noticed that many users did not leave the voice rooms after finishing their games; instead, they stayed to sing, chat, and share their lives. He realized then that while the platform ostensibly solved an efficiency problem ("how to play games better"), it was actually fulfilling an emotional need ("how to connect better with people"). Grounded in this insight, TT Voice quickly evolved from a tool into a community. Beyond gaming matchmaking rooms, it rolled out diverse interest spaces including singing rooms, chat rooms, and audio-visual rooms. In cultivating the social space, Quwan Technology identified an emerging industry trend: the new generation of users was no longer satisfied with merely consuming content; they craved autonomous creation and self-expression. This was no mere hypothesis. On the TT Voice platform, users were already looking beyond finding gaming buddies—they were singing in voice rooms, sharing life moments in chat rooms, and expressing themselves in communities. As AI technology matured, these deeper desires could finally become reality. In the past, completing a song—from lyrics and composition to arrangement, mixing, and recording—demanded specialized skills at every step. Many possessed creative sparks or deep emotions but struggled to translate the melodies in their heads into finished works. In 2024, the team set out from scratch to build "Tianpule," a multimodal music generation model, choosing a self-developed path distinct from open-source fine-tuning. In the AI voice domain, Quwan partnered with CUHK-Shenzhen to open-source the MaskGCT voice model. Quwan develops both AI music and AI voice; it launches AI hardware while maintaining an interest-based social platform with over 200 million registered users. While its business scope appears broad, it is built upon a single, continuously expanding set of core AI interaction capabilities. Across its distinct business lines, Quwan serves diverse sectors—music creation, content globalization, public services, and social networking. From an architectural standpoint, however, they all draw from the same underlying AI interaction capability. Looking back at Quwan Technology's 12-year trajectory, a clear thread emerges: the first half was about "connecting interests"—using interest communities to bring together young people seeking belonging; the second half is about "creating interests"—using AI to lower creative barriers so anyone can convert ideas into digital assets and passion into sustainable expression. Sustaining this arc is not the pursuit of tech trends, but an unwavering understanding of "interest" and "people." Whether with TT Voice or AI music, Quwan’s ethos places user insight ahead of technical R&D. This product philosophy—starting with the human element and designing backward from the ultimate user goal—ensures that technical iterations always revolve around real-world scenarios rather than descending into pure technical rivalry. Moving from "connecting interests" to "creating interests" is not only Quwan Technology’s internal evolution, but also an answer to how technology can truly serve human beings. No matter how technology changes, the essence of business remains constant: to understand people, serve people, and empower people. Conclusion Twelve years ago, Quwan Technology answered one question: How do you help people who love playing games find one another? Twelve years later, it is answering another: How can every ordinary person be given the chance to create their own work and express their unique passions? While the industry remains locked in fierce rivalry over conventional paths—whether single-point tools or general-purpose platforms—Quwan Technology has used vertical integration as an anchor to build a closed-loop "Model-Application-Hardware" ecosystem across AI music and AI voice. This is a direct response to the true nature of AI commercialization: technology can only weave itself into the fabric of everyday life and form a sustainable business model when it penetrates all the way through foundational algorithms, intermediary interactions, and physical hardware devices. (This article was first published on the TMTPost App; author | Li Chengcheng)消费动态 耐克将终止滔搏、宝胜国际在中国内地的线上授权 7月22日，Nike在中国的两家主力经销商：滔搏、宝胜国际发布公告确认，2027年1月1日起，将全面终止 NIKE产品在中国内地线上平台的销售。

1、2026高校专项在四川遇冷，复旦、华科、南航等985、211在征集，集中在三类专业，土木缺额较多

7月14日世界杯半决赛，法国对阵西班牙，萨利巴只踢了30分钟便无法坚持，在队医陪同下走下场，由拉克鲁瓦替补登场。

2、央美老院长靳尚谊，在90岁高龄时画的人物油画

”滔搏（6110.HK）的一纸公告，让持续一个多月的市场传闻最终落地。

3、联盟首人！40分10助！才24岁啊！！！

这就形成了一个天然的战术陷阱：克罗地亚最不擅长的就是拆解密集防守，而加纳最舒服的姿态就是让出球权打反击。暑期出行建议：把充电宝换成它这种转型不仅意味着品牌可能承担高昂的门店收购成本，更要求企业具备成熟强大的零售管理能力，足以承接并运营规模庞大的终端网络。

4、强势集结，无畏向前！长城汽车出征2026中国环塔国际拉力赛！

尤其是面对葡萄牙这样年轻、板凳深度雄厚且冲击力强的球队，下半场的体能下滑可能会成为致命短板。

5、突然！10倍大牛股，跌停！存储概念股，集体下跌！发生了什么？

好的模型，高质量的交付结果，肯定有人愿意为此付费。

6、奚梦瑶、何猷君豪门婚礼：100克拉Graff、Dior高定婚纱、PP钻表！

当然，这也从侧面反映出意甲引援的低性价比。

海外，Anthropic抢跑，OpenAI紧随。

加纳主打4-4-2和4-5-1阵型，低位防守阶段会切换为5-4-1，全队压缩为紧凑的双层防线，五名后卫保持低位站位，双后腰保护中卫身前，中场球员积极回收协防。

7、Kimi逼得两大巨头改变定价！奥特曼罕见认错，Claude额度重置

但因为对“肥胖不是病”的傲慢偏见，因为对百忧解的路径依赖，它亲手放弃了挖掘“金矿”的机会。

产能扩张会帮助拓竹降低单位制造成本，也可能提前把价格竞争推到台前。

8、2026年物理类高考生择校策略与院校推荐

这一点在对阵尤文的比赛中展现得淋漓尽致，米兰近2个转会窗签下的新援在替补席上整齐就座，亚沙里、埃斯图皮尼安、里奇、德温特、奥多古、恩昆库、菲尔克鲁格、阿特卡梅的签约成本超过1.5亿欧元，这还没算3000万欧元引进的希门尼斯。

瑞士：欧洲铁军的控球哲学 作为世界杯常客，瑞士队FIFA排名第18位，全队身价约3.18亿欧元，19名球员效力于五大联赛，阵容厚度堪称B组之最。

这项技术是现代生命科学的底层基础设施，从疫苗研发到合成生物学，都离不开它。

与他搭档锋线的是曼城前锋马尔穆什，这位年轻前锋速度快、冲击力强，是埃及反击的一把尖刀。