Technology that connects computers to telephones has developed very fast in the last ten years. This is clear in the development of the fax. A traditional fax can include many documents and is simple to send. It is rather like a copier combined with a telephone. First, you insert a document into the fax machine, enter the fax number and then turn on the machine. If it connects, the sending fax machine reads the document and sends it to the receiving fax machine. At the same time, the receiving machine receives the document and then prints it.

But technology never stays still. New technology like PC fax programs and LAN fax servers (局域网传真服务器)have recently been introduced to improve fax communications. The latest improvement is the IP fax which uses Internet Protocol(因特网协议)to send faxes.

　　There are two basic ways of sending information using the IP fax system: store-and-forward or real-time. Store-and-forward ways of sending messages are widely used. In this mode, the entire document is sent to a network-based server that stores it and then sends it on to the receiving fax. Real-time IP faxing is closer to sending a fax in the traditional way. Real-time mode allows two fax machines to directly communicate and send the material more efficiently.

IP fax can send a fax document from one person to another. A fax machine or a computer can be used to send or receive the fax. IP fax also allows e-mail to be used to receive faxes. This   enables users to receive faxes anywhere at anytime as long as they have an Internet fax address.

Artificial Intelligence Develops an Ear for Birdsong

We can learn a lot from nature if we listen to it more — and scientists around the world are trying to do just that. From mountain peaks to ocean depths, biologists are planting audio recorders to eavesdrop (窃听) on the whistles and songs of whales, elephants, bats and especially birds. This summer, for example, over 2,000 electronic ears will record the sound scape of California’s Sierra Nevada mountain range. 【小题1】

“Audio data is a real treasure because it contains vast amounts of information,” says ecologist Connor Wood, a Cornell University postdoctoral researcher, who is leading the Sierra Nevada project. “We just need to think creatively about how to share and access that information.” 【小题2】 Fortunately the latest generation of machine-learning AI systems can process thousands of hours of data in less than a day.

Stefan Kahl, a machine-learning expert at Cornell’s Center for Conservation Bioacoustics and Chemnitz University of Technology in Germany, built BirdNET, one of the most popular avian-sound-recognition systems used today. Wood’s team will rely on BirdNET to analyze the Sierra Nevada recordings. 【小题3】 The neural network then teaches itself which features can be used to associate an input (in this case, a bird’s call) with a label (the bird’s identity).

【小题4】 Although they analyze audio much more quickly than humans, they still lag behind in filtering out overlapping sounds to home in on a signal of interest. Some researchers see this as the next problem for AI to tackle. Even the current imperfect versions, however, enable sweeping projects that would be far too time-consuming for humans to tackle alone. “As ecologists,” Wood says, “tools like BirdNET allow us to dream big.”

Working robots are typically big, simple and strong. They are large pre-programmed units working in dangerous and dull jobs. But the growing trend towards cooperative robots , or cobots ,which work in harmony with humans is changing robotic use worldwide.

The fact is that most industrial robots were not designed to do with unpredictable human environments.By cutting robots down to the desktop size and embedding（嵌入） them with sensors and AI , the next generation of cobots will feel our presence , learn from us and combine with us better. Lightweight and portable cobots can work in less space and share it with people rather than being caged off. Decreasing costs for robotic systems make them more affordable to small businesses , and their ease of setting up and programmability makes them simple to develop.

Although the cooperative robot is relatively novel , the initial concept was invented in 1996.Acobot patent was filed in 1997 , which detailed "an instrument and method for direct physical interaction between a person and a general-purpose operator controlled by a computer".The idea of robotic feedback（反馈） was also built-in so that cobots would redirect or control motions that originate with the operator through physical guidance.

The future of cobot working is likely to change as newer interfaces and ways of interacting are developed.Voice commands are bound to be a feature as natural language processing systems become more widespread.Robotic movements and interactions will be controlled using non-invasive brain control interfaces.Unplanned changes to production and safer interaction with humans will then require a step-change in robot learning.

Cobots will learn directly from human interaction or even from virtual simulations（模拟） that will help them adapt to real-world situations.Open robotics platforms , such as Carnegie Mellon University's LoCoBot or Elephant Robotics' Catbot , mean that programmers can share the skills they have developed via the cloud.Cobot carers , such as ElliQ , the companion robot , ceiling-mounted rail robots , or even IKEA' s robotic furniture , promise a nice future of cooperation.