企业级匿名分享应用 Memo：为员工之间坦诚交流架起桥梁
在过去的一年，我们看到大量匿名应用在手机上纷纷出现，允许用户与附近的人或是社交圈子里的人分享信息。但到目前为止，其中大多数匿名应用都专注于消费者市场。
一款名为 Memo 的新应用希望可以从企业级市场分得一杯羹，让公司员工可以与同事匿名、私下分享信息。
Memo 由纽约市一家名为 Collectively 的公司开发，该公司寻求以全新的方式“让工作变得更具人性化”。Memo 背后的创意与其他众多匿名分享应用的创意一样，即只要不让用户在帖子中暴露自己的身份，他们会更为坦诚地分享在实名状况下不敢公开的事情。
为了保证用户确实在某家公司工作，Memo 要求他们在注册时必须提供公司的电子邮箱地址，或是通过 LinkedIn 来验证他们的雇员身份。在身份验证步骤完成以后，Memo 会向用户提供唯一识别代码，但除此之外，不会保存其他任何身份信息。
一旦上述步骤全部完成，用户可以在公司内网与其他员工在私下交流。他们也可以与其他用户公开分享信息，但必须由 任职单位“ 验明正身”。
Collectively 首席执行官莱恩·延森（Ryan Janssen）表示，Memo 的目标是让公司的员工之间进行更坦诚的交流。他认为，不少大公司的高管经常不与普通员工接触。
延森在接受我电话采访时说：“一些企业之所以陷入困境，是因为他们不倾听员工的声音。”但他也暗示，员工们也不敢分享他们对发生在公司内一些事情的看法。
延森说：“管理层具有双重角色…一方面，他们被认为应该为公司内的交流提供便利，但另一方面，他们还决定着员工们的命运。这两种角色恰恰存在着矛盾。”
为了测试这种假设，Collectively 去年秋天首先面向惠普、IBM、亚马逊和花旗集团等大公司的员工推出 Memo。该应用被数千名员工下载到手机，当作私密移动留言板在这些公司中使用，如今 Memo 已经完全开放，所有人都能下载。
Memo 没有权限访问在这些私密留言板上进行的任何对话。Collectively 希望采用的商业模式是，推出一系列管理层可以使用的工具，包括分析工具、情绪分析工具，以及能对员工之间分享的消息作出回复的解决方案。
即便如此，有些公司仍然对员工在 Memo 上面匿名分享的事情感到不满。延森说，已有两家员工使用 Memo 的公司向 Collectively 发来“停止通知函”（cease-and-desist order），另外该公司还收到了其他多家企业发来的“措辞强烈”的电子邮件。
此外，延森告诉我，还有三家公司的员工“收到了一份备忘录，警告他们不要使用 Memo，这种做法真是具有讽刺性”。延森表示，他并未看到这些备忘录，只是通过 Memo 的信息反馈栏听说的。
有些公司还试图通过拦截身份验证电子邮件或是发自员工收件箱的邀请函，不让本公司员工使用 Memo。不过，延森认为企业的这种反应其实是件好事。在收到这种电子邮件以后，延森可以与一些公司坐下来谈一谈，找到更好的合作办法，同时研究 Collectively 应该推出哪些工具，帮助这些企业对员工在 Memo 中反映的事情作出回应。
虽然 Memo 迈出了不错的第一步，但很显然，在企业接受了有关员工在公司内部匿名分享信息的创意之前，Memo 还有很长的路要走。
Memo Brings Anonymous Group Sharing To The Enterprise
Over the last year, we’ve seen a bunch of anonymous (or anonymish) apps crop up on mobile phones, allowing users to share messages with people nearby or those in their social circles. To date, though, most of those apps have been focused on the consumer market.
A new app called Memo hopes to capture some of the enterprise market, enabling employees to share anonymously and privately with their coworkers.
Memo was created by a New York-based group called Collectively, which is looking for new ways to “help make work more human.” The theory behind Memo, like that behind many other anonymous sharing apps, is that by removing a user’s identity from a post they would be much more honest with the things they chose to post.
In order to ensure users work at a certain organization, Memo requires them to sign up with a company email address or verify their employment by connecting through LinkedIn. After that verification takes place, Memo provides users with a unique user ID but doesn’t save any other identifiable information.
Once that’s all done, users can share privately with other employees within their company’s network. They can also share publicly to any other users, but they are identified only by the company they work for.
For CEO Ryan Janssen, Memo’s goal is to open up more honest communication within an organization. All too often, he believes, senior management in many big companies is out of touch with the average worker.
“Companies are suffering because they aren’t listening to their employees,” Janssen told me in a phone interview. But he suggests employees are afraid to share what they really think about what’s happening in their organizations.
“Managers have this bifurcated role… On the one hand they are supposed to facilitate communication throughout the company, but they also determine employees’ futures. Those roles are in opposition to each other,” Janssen said.
To test out this hypothesis, the company made Memo available to employees within organizations like HP, IBM, Amazon, and Citigroup last fall. The app was downloaded by thousands of employees and used as a private mobile message board in those companies, and now it’s being opened up so that anyone can download it.
Memo doesn’t have access to any of the conversations that happen within those private boards. The business model it hopes to employ is to roll out tools that management can use that could include analytics tools, sentiment analysis, and ways to respond to messages that employees share.
That said, some companies aren’t happy about the things their employees have been sharing anonymously on Memo. Janssen says he’s received two cease-and-desist orders from companies with employees on Memo and some “strongly worded” emails from a few other organizations.
In addition, he told me employees at three other companies “received a memo not to use Memo, which is a little ironic.” Janssen says he hasn’t actually seen those memos, just heard about them through the app’s feedback form.
While some companies have tried to shut down use of Memo by blocking verification emails or email invites from hitting employee inboxes, Janssen thinks the backlash is actually a good thing. As a result of the emails he’s received, Janssen has been able to set up meetings with a few companies to figure out how he can better work with them and which tools he could implement to help them respond to employee feedback in the app.
It’s a good first step, but there’s obviously a long road ahead before companies get comfortable with the idea of anonymous sharing in the enterprise.
来源:techcrunch
Facebook宣布开源深度学习人工智能工具[摘要]Facebook的人工智能研究团队今天宣布，将开源其深度学习人工智能工具。
Facebook的人工智能研究团队今天宣布，将开源其深度学习人工智能工具。
Facebook将通过Torch库发布这一软件。Torch是一个协助机器学习技术开发的开源环境，被学术界，以及谷歌、Twitter和英特尔等公司在研究中广泛使用。
Facebook表示，相对于Torch中的默认软件，其深度学习模块的执行速度要更快。这将帮助研究人员在更短的时间内开发规模更大的神经网络。
Facebook希望，分享这一工具将推动整个深度学习研究领域的发展。（李玮）
Facebook open-sources its deep-learning AI tools
Facebook is sharing some of its technology. The company’s artificial intelligence research team today announced that it is open sourcing its deep-learning AI tools.
The software will be available on the Torch library, which serves as an open-source environment for machine learning development. Torch is widely used for research in academia, as well as by companies like Google, Twitter and Intel.
Facebook claims its deep-learning modules are significantly quicker than the default ones available through Torch, and allow the company to work on larger neural networks in less time.
Notable improvements include a 23.5x speed-up over publicly available convolutional layer codes, and the ability to parallelize neural networks training over GPU cards.
The company hopes sharing its tools will help optimize progress across the entire deep-learning research landscape.
来源：TNW
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