Google’s computers OUTWIT their humans
Google no longer understands how its ‘deep learning’, decision-making computer systems have made themselves so good at recognising things in photos. This means that the Internet giant may need fewer experts in the future as it can instead rely on its semi-autonomous, semi-smart machines to solve problems all on their own.
Deep learning is attractive to Google because it can solve problems the company’s own researchers can’t, and it can let the company hire fewer inefficient human experts. And Google is known for hiring the best of the best.
By ceding advanced capabilities to its machines, Google can save on human headcount, better grow its systems to deal with a data deluge, and develop capabilities that have – so far – befuddled engineers.
The advertising giant has pioneered a similar approach of delegating certain decisions and decision-making selection systems with its cluster management tools which seem to behave like ‘living things’ in how they allocate workloads.
Given Google’s ambition to ‘organise the world’s information’, the fewer people it needs to employ, the better. By developing these ‘deep learning’ systems, Google needs to employ fewer human experts, says V.Quoc, a software engineer at Google.
Software robots are already taking over many of the BPO jobs and IT management and support jobs. Companies are increasingly deploying software that can learn about and adapt to its environment, allowing it to do work that used to be the exclusive domain of humans, from customer services to answering legal queries.
IPSoft, a New York based company, unveiled its disruptor autonomics and machine-learning technology, which allows nearly half of all incidents on computer networks to be resolved without human intervention, thus providing large cost savings for service providers. Incidentally, Infosys and Wipro were the frontrunners among Indian companies to forge an alliance with IPSoft. It’s predicted that the next $100 billion revenue of IT industry in India will come out of only 1 million employees (the current $100 billion came out of 3 million employees).
A lot of effort is being put by master software coders to create softwares, which can redesign their code when required, all by themselves. Once such softwares become ubiquitous, they would be able to redesign themselves and write code for other programmes without human intervention. IT workers face the same fate that their creations has caused to workers in other industries: redundancy.
There is hope only for those IT workers who use their knowledge and skills for innovative pursuits to create new services and offerings as most of the routine work will be done by the software robots (bots).
Gazing through the crystal ball
- The last two decades of the massive IT-led employment generation will be a thing of the past; don’t push your children into IT careers except by their own choice
- System software will do well as bigger and better softwares will continue to be build for cloud-based ‘auto-customsiable’ applications platforms
- Even the smallest of businesses/organisations will be critically IT-enabled; IT professionals will be in demand but more as business architects than technology architects because standard cloud-based application platforms will be become the norm within a decade