Machine learning is the application of artificial intelligence that enables systems to learn, adapt, and improve user experience by self-programming. Such systems do not require extra-programming to adapt to users’ behaviour; instead, the program/software identifies the users’ patterns and actions and adjusts to it.
Machine learning is being implemented in businesses around the globe. Still, most companies are holding back to implement the technology to avoid investment and fear of failed execution.
Many large firms, including banks, medical companies, automotive industries, are trying hard to mature their deep-learning modules and ensure aggressive implementation of data-driven self-learning programs/software in their facilities. Recent leaps in AI must be taken seriously by business leaders and top-level executives if they want to adapt to rapidly changing business canvas. Waiting for the technology to mature before implementation can be disastrous and will take businesses out of the competition.
According to a report published by McKinsey Global Institute, 45% of workplace tasks can be automated using present-day technology. And 80% of these tasks are attributable to machine learning.
Utilizing machine learning can help businesses reduce costs on daily tasks like resource and inventory management. The automotive industry is aggressively trying to create, refine, and implement AI models to bring self-driving cars on the road. Elon Musk’s Tesla is already making leaps, Ford group is actively pursuing self-driving cars, and the winner in this race will have a significant market share in the near future. It is highly likely that other players will struggle and eventually fade out if they fail to accept, adopt, and implement the new technologies.
Richard Sutton, a professor of computer science at the University of Alberta, said,
“Understanding human-level AI will be a profound scientific achievement (and economic boon) and may well happen by 2030 (25% chance), or by 2040 (50% chance)—or never (10% chance).”
The change is imminent, and those who will wait for technology to mature will suffer heavily both in terms of quality of service, workplace efficiency, and revenue in the long run.
Andrew Ng, a Computer scientist and a global leader in AI and Machine learning, said:
It isn’t easy to think of a major industry that AI will not transform. This includes healthcare, education, transportation, retail, communications, and agriculture. There are surprisingly clear paths for AI to make a big difference in all of these industries.
The human imagination only bounds the scope of AI in future use. Leading Industries across the globe are terraforming their workplace environment to accommodate machine learning tools. AI will not take away jobs, but it will augment employees to do their job in a better manner.
The oil and gas industry suffers significant losses in unexpected maintenance tasks—applying machine learning tools in preventive maintenance, machinery inspection, field services, quality control, etc. can help save billions.
Current big players in artificial intelligence and machine learning are Google, Apple, Facebook, IBM, Microsoft, and Amazon. In one way or other, we deal with the AI algorithms on a daily basis. If you use a smartphone, then you must have had an encounter with Google Assistant, Siri, and Alexa. These machine learning algorithms identify behaviour patterns, recognize speech and audio/visual data and mould their interactions as per the user’s behaviour.
Leading management and business consultants advise businesses to shift towards incorporating artificial intelligence in the workplace and business analytics.
AI tools are exceptionally efficient in activity tracking and monitoring. Facial recognition tools, coupled with a security system, can trigger alarms in case of hostile interventions.
Energy-efficient systems can recognize patterns to save energy, significantly reducing the energy bills of the company.
Many personal assistant tools are making their way to smart devices like phones, tablets, and PCs capable of assisting just via voice command and recognizing behavioural patterns of the users. These AI can track, monitor, and predict user activity based on the available data.
Social media platforms are incorporating AI algorithms to show relevant ads and recommendations. A more commonly known AI application in social media is the posts that appear in the news feed of social media platforms.
Auto-pilot in an aeroplane is a self-aware system capable of taking in-flight decisions and sharing the burden of the pilot by controlling non-critical functions. Similar trends are now emerging in self-driving cars that can incorporate GPS data, cloud data from nearby vehicles and sensors data to deliver smoother, safer and reliable drives.