Ram Krishna , DDG(FA) , TEC
Artificial general intelligence (AGI) is the intelligence of general purpose systems that could successfully perform any intellectual task that a human being can, and ultimately well beyond human general intelligence. Many interdisciplinary approaches to intelligence (e.g., cognitive science, computational intelligence, and decision making) tend to emphasize the need to consider additional traits such as imagination (taken as the ability to form mental images and concepts that were not programmed in) and autonomy.Ram Krishna, DDG (FA), TEC
Assuming that human scientific activity continues without major disruptions, artificial intelligence may become either the most positive transformation of our history or, as many fear, our most dangerous invention of all. AI research is on a steady path to develop a computer that has cognitive abilities equal to the human brain, most likely within three decades. From what most AI scientists predict, this invention may enable very rapid improvements toward something much more powerful – artificial super intelligence – an entity smarter than all of humanity combined. The first level of AI development is gradually appearing in the technology we use every day. With every coming year, these advancements will accelerate and the technology will become more complex, addictive, and ubiquitous. We will continue to outsource more and more kinds of mental work to computers, disrupting every part of our reality – the way we organize ourselves and our work, form communities, and experience the world.
The Exponential Growth
The exponential growth of technology, generally defined by the repeated doubling of computer power and evolution of various other supplementary technologies, such as cloud computing, machine learning, and cognitive computing, is collectively paving the growth of the market for AI. As a result of these technological changes, today's largest and fastest-growing companies' principal assets are no longer physical but instead digital, i.e., software, algorithms, and big data mined to offer ever-improving products and services. The larger impact of these three exponential forces – the cloud, artificial intelligence, and connected devices – on our society, economy, and digital marketing industry is far from clear. We are moving toward a world where data intelligence software will be able to predict our own future behavior and deepest desires, even before our conscious minds are aware. Now, with great power comes great responsibility, which is where user privacy and data security are paramount.
Road to Artificial General Intelligence
Building a computer as smart as human artificial intelligence, or AI, is a broad term for the advancement of intelligence in computers. There are three categories, or calibers, of AI development. These are:
Artificial narrow intelligence (ANI). Artificial narrow intelligence is the first intelligence caliber, AI that specializes in one area. There is AI that can beat the world chess champion in chess, but that is the only thing it does.
Artificial general intelligence (AGI). Artificial general intelligence is the second intelligence caliber. AI that reaches and then passes the intelligence level of a human, meaning it has the ability to "reason, plan, solve problems, think abstractly, comprehend complex ideas, learn quickly, and learn from experience."
Artificial super intelligence (ASI). Artificial super intelligence is the third intelligence caliber. AI that achieves a level of intelligence smarter than all of humanity combined–"ranging from just a little smarterto one trillion times smarter."
Artificial Intelligence Technologies
The market for artificial intelligence (AI) technologies is flourishing. Beyond the hype and heightened media attention, the numerous start-ups and the Internet giants racing to acquire them, there is a significant increase in investment and adoption by enterprises. Artificial Intelligence today includes a variety of technologies and tools – some time-tested, others relatively new. Detailed analysis of certain technologies needs to be considered while adopting to support human decision making:
- Natural language generation. Producing text from computer data. Currently used in customer service, report generation, and summarizing business intelligence insights.
- Speech recognition. Transcribe and transform human speech into format useful for computer applications. Currently used in interactive voice response systems and mobile applications.
- Virtual agents. "The current darling of the media," says Forrester (I believe they refer to my evolving relationships with Alexa), from simple chatbots to advanced systems that can network with humans. Currently used in customer service and support and as a smart home manager.
- Machine learning platforms. Providing algorithms, APIs, development and training toolkits, data, as well as computing power to design, train, and deploy models into applications, processes, and other machines. Currently used in a wide range of enterprise applications, mostly involving prediction or classification.
- AI-optimized hardware. Graphics processing units (GPUs) and appliances specifically designed and architected to efficiently run AI-oriented computational jobs. Currently primarily making a difference in deep learning applications.
- Decision management. Engines that insert rules and logic into AI systems and used for initial setup/training and ongoing maintenance and tuning. A mature technology, it is used in a wide variety of enterprise applications, assisting in or performing automated decision making.
- Deep learning platforms. A special type of machine learning consisting of artificial neural networks with multiple abstraction layers. Currently primarily used in pattern recognition and classification applications supported by very large data sets.
- Biometrics. Enable more natural interactions between humans and machines, including but not limited to image and touch recognition, speech, and body language. Currently used primarily in market research.
- Robotic process automation. Using scripts and other methods to automate human action to support efficient business processes. Currently used where it is too expensive or inefficient for humans to execute a task or a process
- Text analytics and NLP. Natural language processing (NLP) uses and supports text analytics by facilitating the understanding of sentence structure and meaning, sentiment, and intent through statistical and machine learning methods. Currently used in fraud detection and security, a wide range of automated assistants, and applications for mining unstructured data.
AI Functions and Applications
The AI function comprises of providing information, moving objects, communicating, planning, learning, and reasoning. A few of the various applications/jobs being handled are: intelligent robots, natural language generation, neural networks, gaming, smart home devices, virtual personal assistants, smart cars, chatbots, shopping with difference and locating cancer cells, etc.
India views AI as a critical element of national security strategy. Spurring AI-based innovation and establishing AI-ready infrastructure are thus necessary to prepare India's jobs and skills markets for an AI-based future and to secure its strategic interests. It is also required to view machine intelligence as a critical element of India's security strategy. We also need to identify public sector applications like detecting tax fraud, preventing subsidy leakage, and targeting beneficiaries, where current advances in AI could make a significant impact.
AI-based applications to date have been primarily in consumer goods. There is a need to adopt a policy to drive AI innovation, adaptation, and proliferation in sectors beyond consumer goods and information technology services. AI needs to be made a critical component in India as part of Make in India, Skill India, and Digital India programs by offering incentives for manufacturers, creating regional innovation clusters for manufacturing automation and robotics in partnership with universities and start-ups, incorporating market-based mechanisms for identifying the kind of skills that employers will value in the future, and promoting cloud infrastructure capacity building inside India.
The sequential system of education and work is outdated in today's economic environment as the nature of jobs shifts rapidly and skills become valuable and obsolete in a matter of years. There is a need to devise alternate models of education that would be better suited to an AI-powered economy of the future.
Witnessing the pace of the current digital revolution and the evolution of quantum computing, the AI in the foreseeable future will be more human-like, smarter, accurate, and faster. Even though the benefits of the improvised AI will be huge and unimaginable, stiff challenges regarding privacy and access to information cannot be ruled out. Robots with advanced AI features will affect the job security of a large number of people as professionals will be gradually replaced. Expertise in data mining/big data will be demanding, and educational institutions and big business houses will have to overhaul their workforce. Many organizations will put cyber security on par with other intelligence and defense priorities.