1.4 Extending skills
translation: how well does it translate the ideas from one language to another? As you know, words and phrases can have different meanings depending on the type of text they are used in. Human translators will have a lot of experience with different types of text, so they can identify the correct meaning for the specific text. Machine translators may not be able to recognize the different types of texts, so the translation may sound strange or, in some cases, be totally wrong. Another disadvantage is the range of languages which machine translation can provide. Most machine translation software will support popular languages such as English, Spanish, Mandarin and Arabic, but less popular languages are not always supported. A final disadvantage for machine translation is that it does not do a good job with creative texts, such as novels or poems. These rely on a knowledge of the culture of a country, as well as its language. For this type of translation, a human translator is essential.
11 Lecture 2
However, the state of computing technology in the 1950s meant that it was difficult to construct machines which would pass the Turing test. Computers had small amounts of memory and storage, which made it difficult to provide the amount of data needed. Computers were also extremely expensive, and only the largest organizations could afford them. In 1955, the RAND Corporation in the United States funded a conference at which the term ‘artificial intelligence’ was used for the first time. While the conference did not achieve anything concrete, most people attending agreed that AI was possible and should continue to be researched. In the 1960s and 1970s, the development of AI
focused on using language processing to interact with people. Programs such as ELIZA, which was created in the mid-1960s, used pattern matching to give answers which seemed relevant. However, it only provided answers which were already chosen, and it did not generate any new knowledge. For this reason, it could not be considered as AI. Nevertheless, many users felt that they were communicating with a human. In the 1980s, AI was able to develop further because of increased government funding and the development of new algorithms. Government funding helped to develop ‘expert systems’, which took knowledge from a human expert and coded it as questions and answers. The computer could then answer questions in the same way the expert would have done. While this was very useful, it still gave answers which had been provided, so it was not AI. By the 1990s, government funding was declining
because AI developments had not been as successful as many had hoped. However, the speed and storage capacity of computers had grown rapidly, and they could now handle large amounts of data – both text data and, increasingly, audio data from speech. A major landmark occurred in 1997, when an IBM computer called Deep Blue defeated a world chess champion: Garry Kasparov. Another landmark around the same time was the availability of the first speech recognition program for commercial use: Dragon Dictates. The 2010s brought a number of major landmarks. One was the development of devices which could
understand quite complex spoken language. Examples were Siri (Apple’s voice-enabled search), and Alexa (Amazon’s voice-controlled virtual assistant). Another landmark came in 2017, when Google’s AlphaGo beat a world champion of Go. The computer had been trained by playing games of Go against itself and learning from its mistakes. Even though Go is thought to be the most difficult game for a computer to play, the computer still won. This was a true example of AI, as the computer was able to learn by itself and was not simply following instructions from a human. In contrast to the Mechanical Turk, where the human was inside the machine, this time, the machine was thinking for itself.
12 Lecture 3
After the planning phase, the next phase, requirement analysis, means finding out what the users want the software to do. For example, some questions the development team can ask are: Who will use the software? In other words: Who are the users? What will they want the software to do? What information will the system use as input and create as output? Depending on the method used, this phase can happen once – if the method used is the waterfall method – or a number of times – if the method is a more iterative one. Once the requirements are identified, the next
stage is to decide on the design for the software. The development team will decide on the structure of the software, which often means breaking it down into different sections. They will also decide which languages to use to write the code. In this phase, the initial designs for the interface for the system will be decided. The next phase of the SDLC is to develop or write
the software that has been designed. Usually, the code is written by teams of programmers. They will need to have clear guidelines to ensure that their code all fits together. Some methods, such as agile, encourage programmers to work closely together as they write the code. Testing is often done as the code is written by each programmer and when the code is shared with code written by other programmers. This means that any problems are fixed more quickly. However, more complex testing to make sure the software works as it is supposed to is done before the software reaches the final phase. The final phase is releasing the software to users.
The internet means that this can be done very quickly, because users from anywhere in the world can download the necessary files. Depending on the method, many of the phases can be repeated. Feedback from software users can be used to make improvements, both in terms of what the software can do and, also, in terms of the quality of the software.
13 Lecture 4
One strategy for improving quality was to create teams to check the quality of code in programs when they had been written. Quality assurance teams, known as QA teams, would create test plans and step-by-step checklists to test how well a program worked. Every time there was an update or change to the code, these would be rerun.
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