Adobe AIR第一单:Seesmic买下Twhirl

Seesmic收购Twhirl

AIR平台出来有一段时间了,目前的情况看,个人觉得很受web开发者喜欢,界面绚丽,编程模式和通用的web编程模式完全兼容。Twhirl是基于AIR平台的一个国外非常流行的微博客(类似于饭否)的客户端。大约有7%的Twitter信息用此软件发布。不久前该软件被Seesmic公司收购,可谓AIR平台软件第一单。这是Seesmic公司发表的购买Twhirl的二十个理由。没想这也被GFWed了,晕,原文拷贝至此,请下看:

As TechCrunch just announced, Seesmic just acquired Twhirl. And here are 20 ways it will benefit the Seesmic community

-Staying in touch with your friends using microblogging is much easier using a client than through your browser
-Thwirl is the
#1 and coolest Twitter client with more than 100,000 downloads and 7% of all tweets posted per day
-Thousands of new users download Twhirl daily
-Twhirl works on Mac AND PC, soon on Linux too
-Twhirl lets you easily use all the advanced messaging options of Twitter (replies, direct messages)
-Twhirl added very cool features such as search and url shortening in a second
-Twhirl allows you to have multiple Twitter accounts opened simultaneously
-Twhirl not only posts on Twitter but also on Pownce and Jaiku, with more services coming soon
-Seesmic and Twhirl have been created exactly the same way, by listening to their communities and adding new features according to their popularity
-Twhirl has
amazing feedback from its users and press coverage: Thwirl was just on Fox News
-We got in touch entirely through using Twitter and Twhirl... how cool is that? Okay, we also used Skype a bit to close the deal

 

Marco Kaiser, who created Twhirl

-most of Seesmic team and investors constantly use Twhirl, made things easy!
-Marco was already in the process of adding Seesmic support to Twhirl. That is how we got together and thought about him joining in, not the other way round
-Adding video to Twhirl will be a plus to the Twhirl community. It will remain optional -- we won't break it!
-Twhirl is free and will remain free
-Marco has the same international vision, already supporting english, german, spanish and italian (hey where is french!)
-With Twhirl being based in Germany, Seesmic now has a presence there which will help with the German version and community
-Marco will have more means to improve Twhirl as he will join Seesmic full-time and will be able to utilize the Seesmic's support and infrastructure
-We are only at the beginning of microblogging, the space is very exciting and new
-Marco Kaiser is super cool and it is all about people

update: thank you all for writing about this (in no particular order and not exhaustive look here and here for more) 

Marshall Kirkpatrick / ReadWriteWeb: Seesmic + Twhirl is a Vision of the Web's Future (Marshall, I love your title!)
Chris Morrison / VentureBeat:
Seesmic jilts the browser to take a twirl with Twhirl
Rafe Needleman / Webware.com:
Video chat startup Seesmic acquires Twitter client Twhirl

Liz Gannes / NewTeeVee: Seesmic Acquires Desktop Client

Ross Mayfield / Ross Mayfield's Weblog: Twhirling Seemic's Underweb
Staci D. Kramer / paidContent.org:
Seesmic Acquires Twitter Desktop Client Twhirl
Brian Solis / bub.blicio.us:
Seesmic Sets Its Sights on Twhirl
John Musser / ProgrammableWeb:
Seesmic Acquires Twitter Mashup Twhirl
Kristen Nicole / Mashable!:
Seesmic Acquires Twhirl, for Desktop Video Microblogging
Frederic / The Last Podcast:
Seesmic buys Twhirl

Ouriel Ohayon / TechCrunch France: Seesmic acquiert Twhirl

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内容概要:本文介绍了基于贝叶斯优化的CNN-LSTM混合神经网络在时间序列预测中的应用,并提供了完整的Matlab代码实现。该模型结合了卷积神经网络(CNN)在特征提取方面的优势与长短期记忆网络(LSTM)在处理时序依赖问题上的强大能力,形成一种高效的混合预测架构。通过贝叶斯优化算法自动调参,提升了模型的预测精度与泛化能力,适用于风电、光伏、负荷、交通流等多种复杂非线性系统的预测任务。文中还展示了模型训练流程、参数优化机制及实际预测效果分析,突出其在科研与工程应用中的实用性。; 适合人群:具备一定机器学习基基于贝叶斯优化CNN-LSTM混合神经网络预测(Matlab代码实现)础和Matlab编程经验的高校研究生、科研人员及从事预测建模的工程技术人员,尤其适合关注深度学习与智能优化算法结合应用的研究者。; 使用场景及目标:①解决各类时间序列预测问题,如能源出力预测、电力负荷预测、环境数据预测等;②学习如何将CNN-LSTM模型与贝叶斯优化相结合,提升模型性能;③掌握Matlab环境下深度学习模型搭建与超参数自动优化的技术路线。; 阅读建议:建议读者结合提供的Matlab代码进行实践操作,重点关注贝叶斯优化模块与混合神经网络结构的设计逻辑,通过调整数据集和参数加深对模型工作机制的理解,同时可将其框架迁移至其他预测场景中验证效果。
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