Considering the Future of Processing Power

The vast majority of processors made today perform tasks as procedures. The processor looks at an instruction, performs the task specified by that instruction, and then moves onto the next instruction. It sounds like a simple way of doing things, and it is. Because a processor can perform the instructions incredibly fast—far faster than any human can even imagine—it could appear that the computer is thinking. What you’re seeing is a processor performing one instruction at a time, incredibly fast, and really clever programming. You truly aren’t seeing any sort of thought in the conventional (human) sense of the term. Even when using Artificial Intelligence (AI), the process is still a procedure that only simulates thought.

Most chips today have multiple cores. Some systems have multiple processors. The addition of cores and processors means that the system as a whole can perform more than one task at once—one task for each core or processor. However, the effect is still procedural in nature. An application can divide itself into parts and assign each core or processor a task, which allows the application to reach specific objectives faster, but the result is still a procedure.

The reason the previous two paragraphs are necessary is that even developers have started buying into their own clever programming and feel that application programming environments somehow work like magic. There is no magic involved, just incredibly fast processors guided by even more amazing programming. In order to gain a leap in the ability of processors to perform tasks, the world needs a new kind of processor, which is the topic of this post (finally). The kind of processor that holds the most promise right now is the neural processor. Interestingly enough, science fiction has already beat science fact to the punch by featuring neural processing in shows such as Star Trek and movies such as the Terminator.

Companies such as IBM are working to turn science fiction in to science fact. The first story I read on this topic was several years ago (see IBM creates learning, brain-like, synaptic CPU). This particular story points out three special features of neural processors. The first is that a neural processor relies on massive parallelism. Instead of having just four or eight or even sixteen tasks being performed at once, even a really simple neural processor has in excess of 256 tasks being done. The second is that the electronic equivalent of neurons in such a processor work cooperatively to perform tasks, so that the processing power of the chips is magnified. The third is that the chip actually remembers what it did last and forms patterns based on that memory. This third element is what really sets neural processing apart and makes it the kind of technology that is needed to advance to the next stage of computer technology.

In the three years since the original story was written, IBM (and other companies, such as Intel) have made some great forward progress. When you read IBM Develops a New Chip That Functions Like a Brain, you see that that the technology has indeed moved forward. The latest chip is actually able to react to external stimuli. It can understand, to an extremely limited extent, the changing patterns of light (for example) it receives. An action is no longer just a jumbo of pixels, but is recognized as being initiated by someone or something. The thing that amazes me about this chip is that the power consumption is so low. Most of the efforts so far seem to focus on mobile devices, which makes sense because these processors will eventually end up in devices such as robots.

The eventual goal of all this effort is a learning computer—one that can increase its knowledge based on the inputs it receives. This technology would change the role of a programmer from creating specific instructions to one of providing basic instructions and then providing the input needed for the computer to learn what it needs to know to perform specific tasks. In other words, every computer would have a completely customized set of learning experiences based on specific requirements for that computer. It’s an interesting idea and an amazing technology. Let me know your thoughts about neural processing at John@JohnMuellerBooks.com.

 

Author: John

John Mueller is a freelance author and technical editor. He has writing in his blood, having produced 99 books and over 600 articles to date. The topics range from networking to artificial intelligence and from database management to heads-down programming. Some of his current books include a Web security book, discussions of how to manage big data using data science, a Windows command -line reference, and a book that shows how to build your own custom PC. His technical editing skills have helped over more than 67 authors refine the content of their manuscripts. John has provided technical editing services to both Data Based Advisor and Coast Compute magazines. He has also contributed articles to magazines such as Software Quality Connection, DevSource, InformIT, SQL Server Professional, Visual C++ Developer, Hard Core Visual Basic, asp.netPRO, Software Test and Performance, and Visual Basic Developer. Be sure to read John’s blog at http://blog.johnmuellerbooks.com/.

When John isn’t working at the computer, you can find him outside in the garden, cutting wood, or generally enjoying nature. John also likes making wine and knitting. When not occupied with anything else, he makes glycerin soap and candles, which comes in handy for gift baskets. You can reach John on the Internet at John@JohnMuellerBooks.com. John is also setting up a website at http://www.johnmuellerbooks.com/. Feel free to take a look and make suggestions on how he can improve it.