Watson had to listen to questions and give answers in a natural human language. However, it learned from million pages of structured and unstructured content that took up four terabytes of disk storage.
The man and the machine played a five-game tournament in Seoul. Lee Sedol won only the fourth game. In an experiment in , artificial intelligence was was tasked with detecting breast cancer. A neural network was trained to find signs of cancer using tens of thousands of mammographic images of the disease. This was a new and important development in breast cancer detection. Magenta is a Google Brain project, and its objective is to figure out whether machine learning can be used to create compelling art and music, and how we should go about it.
The team that created Magenta used TensorFlow, a Google machine learning library. In February in San Francisco, Google sold 29 paintings on a charity auction. In December , Google released the TensorFlow library to the public. Why did Google give out this powerful piece of software for free? According to prof. About 10 years ago, Google open-sourced the Android Operating System for smartphones.
After another few weeks, Facebook open sourced their own artificial intelligence library called Caffe2. He took a Linux repository all the source files and headers files , combined it into one giant document it was more than MB of code and trained the RNN with this code. Sample code generated by Artificial Intelligence. Literally overnight, the AI-generated code including functions and function decorations. It had parameters, variables, loops and correct indents.
Brackets were opened and later closed. It even had comments. The AI made some mistakes of course. In some instances, variables were not used. In others, variables which had not been declared earlier were used. But Karpathy was satisfied with the result. The project is available on GitHub.
It uses the Torch7 deep learning library. Here is the whole output file received by Karpathy. Microsoft and Cambridge University researchers have developed artificial intelligence that can write code and called it DeepCoder. The tool can write working code after searching through a huge code database. It then tries to make the best possible arrangement for the harvested code fragments and improves its efficiency over time. Engineers are in high demand and commanding high wages.
There are simply not enough software engineers available to fulfill the needs of companies looking to build applications and services. While it seems demand for software developers will be strong for the foreseeable future, how long will it be before these engineers are replaced by the very software that they are tasked to create? These developments do not bode well for the software developer. I can envision a not too distant future where sapient computer systems can take very general instructions either verbally or written and translate those into the applications or media assets that currently require a skilled technician to generate.
These systems would be self-sufficient, except perhaps for access to the energy that runs them. Predicting the timing of these events is difficult. As times changed, this aspect also changed.
Today, women get accorded equal treatment. Then came the 20th century and the invention of the telephone. The telephone needed no translation from any code. There was increasingly less need for telegraph operators as the telegraph was phased out. Jumping ahead a century from today, we find ourselves in the same sort of predicament. They are reaping the results of being highly skilled. The question begs, however, is it sustainable in a fast-changing world?
Being a programmer is different from being a telegraph operator, but the dynamics are the same. Programming needs a broad skill set, a sharp intellect, and a fluid and creative mind. Programmers today hold the same position telegraph operators held in the 18th century. There has been an explosion of software in recent times that can only get equaled by the rise of networked communication in the 18th century. There is an ever-growing demand for newer and better software that programmers have to keep up with.
The telegram had to be manually translated by humans to natural language. It is the same with code. Human beings have to write every line of source code, but it means the probability of programmers becoming obsolete is high. Software is becoming more and more sophisticated. The frameworks being developed mean the source codes being written by humans are becoming increasingly few.
Advanced programming languages have been developed, and compilers and interpreters have made it easier to program. As it is today, the software writing process is still being done by humans.
Who is to say what will happen in the next 20, 30 or 50 years? Technology is dynamic, and software changes and improvements are the order of the day. Moving with the changes is inevitable. Software is always getting upgraded.
What works today will not necessarily work tomorrow. It is a possibility that software will get developed in the future that will take over the human skill of writing code.
Who would have thought back then that the telegraph would become obsolete? It was all the rage at the time. Operators would never have imagined they would become redundant.
In technology , nothing stays the same for long. The age of human-assisted software development is dawning on us. That is, computers will be performing the majority of development and humans will simply assist their endeavors. In this new era, visionaries and testers reign supreme. The visionaries will be responsible for coming up with the grand plans. They will determine what problem needs to be solved. This boils down to describing expected output given an input. The testers will then write the tests that assert the problem is indeed solved.
That is, verifying the correct output was produced given an input. The computers are now responsible for transforming a given input into a desired output. At this point, you might be wondering how this miracle of automated software development will even be possible.
The answer is genetic programming.
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