Growing technology with unaddressed questions and scenarios

Technology is growing and changing at such a fast pace, that today’s development and concepts get old by tomorrow!. Code’s or machine’s ability to learn and response without being programmed has become utmost popular and is leading most of the daily process, where least human involvement is required now.

Focusing on the trend of data being generated from ample of processes on day to day basis in organization has lead Machine learning to emphasize more on the development part where programs can be developed to deal with new strains of data from the various processes.

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The pace at which the data is being generated from a small process or a bigger process is in equal demand for auto capture of the data from one end and should be analyzed by the system at front end with all possible scales and speculations for quicker decisions by the management.  Following this now the trend of the development of algorithms has made shift from writing “supervised algorithms” to unsupervised algorithm, where the supervised part of the algorithm gives better insights into the new data from past data and unsupervised part concludes from the old datasets.

Process Software should be backed by the statistical analysis and predictive analytics to make artificial intelligence and to automate the decisions making ability in process(es).

Though even if organizations and regulatory bodies make standard guidelines for electronic technologies where the ample of codes are being run to capture, store, clean, analyze, and present the result in fractions to the user, will again keep on changing and evolving with growing technology. This process would leave behind the QUESTIONS and SCENARIOS unaddressed!. Manual and Automated testing of the application would not be sufficient to make application stand with data set variation.

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Artificial Intelligence – challenging human minds with rational agents!

It has become challenging for humans to beat computer systems and logics formulated behind them. Developed by humans for the excellence of processes in day to day life and for the care of population.

There are four ways of approaching Artificial Intelligence:

  1. Thinking humanly – cognitive science
  2. Thinking rationally – logic
  3. Acting humanly – turing tesing
  4. Acting rationally – rational agent

Thinking or acting deals with thinking processes or behavior, while humanly or rationally means humanly or to do the right things.

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The AI approach has been taken to such a level where robots and software are communicating with human in their language. In fact the AI’s approach is to act rationally and to build rational agents, and these agents are nothing but the robots and software.

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Gestation of Artificial Intelligence (AI) was from 1943-1955, where the AI developed in a cogitative process. First work on AI was started by Warren McCulloch and Walter Pitts in 1943, where the duo developed and worked on artificial neuron model where the neurons where either on or off to function.

“How AI has become an Industry” and entire processes has been given a cobwebbed connection to increase the production and output by many folds. None of the major processes in industries are free from software applications and machines that are guided by codes.

Challenges to be handled in future:

Though this ever growing technology is helping each and every one of us and at the same time it is keeping humans away from the nature and that’s where the natural processes are evolving and leading to a world of so many unexpected disorders, health issues.

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Next Generation Sequencing (NGS)- breaking the human genome code

So far now, it has become possible to sequence anyone’s genome cheaper and quickly with the help of latest technologies. Researchers have started gaining much into discovering the meaning of individual genomes. Though still the sequencing has not come down to an affordable price but has been sponsored mostly by the stake holders of the research projects to get into the main stream of the genomics worlds. And it has been highlighted that the individual genome sequencing would help track the rare deformities and anomalies in the gene line of human and can be engineered to treat or suppress the genes responsible for the cause.

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Concerns over the repository of the genome sequences:

  • If the genome is sequenced, who should access this?
  • How securely the sequences can be stored away from snooping?
  • How the national database should be made?
  • Would it be easy to handle fastest growing data of sequences?
  • Would this be easy to make available centrally for right access?

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Technologies that is killing the password system!

Positioning human body as a recognition tool is the current leading way of identification at every ground now. Alphanumeric and other sort of randomly generated passwords are on the verge of losing ground now. How Apple started the use of fingerprint identification in gadgets, like that now every electronic gadget would let the initiation post biometric identification to avoid any interference.

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Increasing trend in the technology has made process easy and quite fast, no doubt but changes always comes with bunch of challenges that growing technology is facing in terms of maintaining data integrity, backup of the data, analysis of the data etc.

Cryptography does help in tackling the problem upto a great extent. If there is a way to encrypt data, there is always a way to decrypt the same using other platforms and code. This growing and multiplying technology has both pros and cons. Both ends need equal attention to manage the process.

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