善良的保险公司销售员陈文（黄渤 饰）在广场邂逅了一个疯疯癫癫的女孩，伊藤谁知在去精神病院的路上女孩化身成清秀美丽的佳人。虽然惹得一堆麻烦上身，伊藤不过陈文次日还是应约与这个叫做沈露（江一燕 饰）的女孩见面。沈露要求陈文做他的假装情侣，而陈文也欣然接受。在接下来的日子里，陈文变成一个随叫随到的小仆人，他按照沈露的要求做着各种各样难为情却又好玩的事情，两人度过了一段难忘的美好时光。在此期间，陈文慢慢喜欢上了这个古灵精怪的女孩，沈露的心中似乎也经历着某种矛盾纠葛。某一天，沈露突然音讯全无，再见面时她却提出结束和陈文这段假装情侣的游戏……
回复 :Timed with the 2020 women's suffrage centennial, American Masters - Unladylike2020: The Changemakers takes a look at women whose courage and tenacity 100 years ago shaped the political life and future of this nation. Their accomplishments were instrumental in accomplishing voting rights for women -- but also in improving the quality of life for all citizens. This hour-long PBS American Masters animated documentary film will present profiles of five little-known women trailblazers who were active in government, civil rights, and citizenship rights, behaving in ways that placed them outside the mainstream of expected behaviors for 'ladies' at the turn of the 20th century. They include: Martha Hughes Cannon, the country's first female state senator; Jovita Idar, a journalist, and president of one of the first Mexican American women's civil rights organizations; Jeannette Rankin, the first woman elected to the U.S. Congress; Mary Church Terrell, a leader in the anti-lynching movement and a founder of the NAACP; and Zitkála-Sá, aka Gertrude Simmons Bonnin, who lobbied for U.S. citizenship, voting rights and sovereignty for American Indians a century ago.
川与晨
回复 :该片改编自阿莱克丝·弗林创作于2007年的同名小说，用惊悚、哥特的外衣包装一段美女与野兽的传奇故事。故事发生在纽约曼哈顿，英俊人品却很差的富家公子Kyle（亚历克斯·帕蒂弗 Alex Pettyfer 饰）为了嘲弄同学Kendra（玛丽-凯特·奥尔森 Mary- Kate Olsen 饰），把她邀请到自己聚会让她出丑。备受侮辱的Kendra当即给他下了恶咒，把他变成了人见人厌的“怪物野兽”，只有当一个女孩真正发自内心爱上这个他，咒语才会解除。Kyle的父亲见到儿子变成这样冷酷地把他赶到布鲁克林的宅子里软禁了起来，只给他留了衷心的管家和双目失明的家庭教师。正当Kyle认为自己永远也无法解除咒语之际，老天爷机缘巧合让他的同学Linda（瓦妮莎·哈金斯 Vanessa Hudgens 饰）住进了他家。Linda会成为Kyle的真爱帮他摆脱诅咒吗？
回复 :Exploring the fallout of MIT Media Lab researcher Joy Buolamwini’s startling discovery that facial recognition does not see dark-skinned faces accurately, and her journey to push for the first-ever legislation in the U.S. to govern against bias in the algorithms that impact us all.
