Will Artificial Intelligence Out-Perform Humans at Cognitive Tasks? - Xane AI
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Will Artificial Intelligence Out-Perform Humans at Cognitive Tasks?

Will Artificial Intelligence Out-Perform Humans at Cognitive Tasks?

Blog by Oluwasegun Oke

This question weighs more on whether today’s AI personalized and screen-based services are well adapted enough for a swift change in its overall application across super-improved algorithmic and robotic capacity developments. These areas are being understudied and few breakthroughs have been recorded through new waves of algorithms, interfaces, and platforms so far. For instance, machines are most likely to replace human beings in jobs that require fewer talents and skills, such as in self-driving cars, clothes sewing, and fast food cooking. 

We are therefore going to witness huge input usage and preprocessing AI systems development technology solutions, that will drive advanced economies of the world to the next phase of both domestic and industrial humanoid integration revolution, that is bound to significantly alter the way we perceive robots, and the impact this may bring to our social values, cultures, and legislation.

But since so much is at stake, based on current efforts being made to further develop more AI systems, especially through deep learning and neural technology, in order to make AI-solutions more reliable, and trustworthy, as they help in processing, planning, speech recognition, interphase applications, and interaction. 

While the booms of AI in the 1950s successfully put forward practicalities about newly developed chat software, and perception neural network software. This essentially culminated in AI research milestones, for scientists, who theorized on how AI was about to fully rescue advanced economic woes, that were imminent.

And led to the second AI boom in 1976-2006, to the third one in 2016. Now moving forward, BT training and Hopfield Neutral Network, inspired a unique roadmap, to substantiate speech recognition, speech translation, and Japan’s fifth-generation computer concept.

In the same way, ImageNet optimized its quota outputs in 2012, while Hilton created deep learning in 2006 when Al was in its third boom (2006 till date).

A Comparison of AI to Human Ability

AI basically deals with machine intelligence, integration of a variety of fields, such as neural networks, deep learning, IoT, reinforcement learning, etcetera. And analysis for further developments of superior natural language processors and machine algorithms, to be fully integrated, for greater efficiency and reduced man-hours, to secure the available space for cost-effective AI products and services.

Today, AI is able to translate languages, diagnose medical conditions accurately, compete at the master level in chess, self-drive vehicles, and write reports on sports events. But while it has been forecasted that 2060 will see AI take over from man in all fields of endeavors. It is uncertain how much more discoveries and proactiveness are lacking. Even though certain functions, such as legislation and policy-making may remain solely for humans. 

Research over the four decades has shown that cognitive tasks usually performed by humans, can be effectively out-performed by Artificial intelligence. And the pioneers of this discovery are convinced that the future belongs to AI technological breakthroughs, in order to slowly do away with human errors, especially with regards to assembly plants, media, entertainment, academia, among others. 

And in recent years, algorithms are now able to recognize images better than humans, widely acclaimed the cognitive task of vision. It is the main reason we have voice assistants, in Siri and Alexa. Using the existing four cognitive skills, which are strategic reasoning, natural language understanding, search, and learning. 

And since the human brain consists of 100 billion neurons and 10^14 synaptic connections, it is widely argued by philosophers and scientists that it may possess the answer to unraveling the next phase of artificial intelligence. And if all goes as planned in the end, AI would become an objectified brain that holds unparalleled power to creativity, emotion, and intelligence, which would lead man into a state of unprecedented cognitive capabilities. It would also usher in an era of low carbon emission and climate change elimination, as more back door technological innovations must have been swung open through newly optimized AI concepts. 

Can AI Really Out-performed Humans?

As more calls for a reduction in man-hours and corresponding increments in the quality of products and services, continually catch public attention, especially within diverse corporate entities. Being that humans still have the upper hand in terms of frantic efforts through research in psychology, neuroscience, and linguistics, thereby leaving behind a closing margin that machine intelligence is yet to learn and automate.

And given the scope of today’s AI knowledge, we have to ask pertinent questions, such as, can machine think, do they learn, and how can their cognitive skills become a match or even better than that of humans. For instance, AI develops into an array of learning algorithms that help business managers seek out prospects. And also develops new leads for teachers to adopt better models and follow a more comprehensible approach in their pursuit to impart knowledge to their students. AI is also widely known to be an instrument for exploring and mining primary areas of research, that has become a global phenomenon.

In order to form an idea of what the future Interaction between machines and humans portends, floods of science fiction movies have also been widely used to portray eras when machines became a dominant force in our society. It indeed further stresses the level to which humans were outsmarted and almost toppled from his highest authority position. Although computer scientists have been quick to dispel these claims as mere theories and further uphold humans as being indomitable, no matter how supreme the level of machine intelligence becomes. However, the closing arguments of critics are that of ethics and human consciousness. It erects a border fence across the subject matter, and extends a big blow against earlier notions of perfect machine intelligence, coming from years to come.

The Future of Human and AI Interaction

Thinking consists of aspects, when it comes to machine cognitive development. We have the first layer, which is language. Conscience is the second, and the outward reflection of control mechanisms is the third. For machines, information exchange simply means electrons movements, and relay of arrays of neurons, which have made AI keep closing up the gap, along with research milestones, from this 21st century. 

In all, developing major platforms that can be useful to various brands, while boosting demands, is a new way forward. And is inclusive in the imminent future of AI technological advancement. Because in the end, we hope to see the coevolution between mankind and intelligent machines. And unlike the negative coalitions portrayed in science fiction movies, we believe that the right AI boom can act as a catalyst to accelerate us into these beginnings, without surpassing humans’ intelligence, nor dominating or controlling our civilization.

Cognitive Computing

Unlike ordinary ones, cognitive computing can be said to be the integral force driving the future of AI, as we may later reflect on its myriads of advantages. It thrives on the previously acquired information, hence memorizing patterns, learning, and recalling for a variety of problem-solving purposes. In other words, improving human cognitive skills is based on this phenomenon, which evolved into existence, after the eras of tabular and programming computing. And with experts training, the cognitive computer can learn, adapt, analyze complex reasoning, and generate required assessments or results. 

Cognitive computing practically operates based on well-arranged decision-making algorithms that show evidence-based learning ability, coupled with the internal computation that enables it to process structured and unstructured data, gaining insights into different users across diverse industries.

It extracts context entities, such as personalities from business and social media data, and classifies different users according to certain qualities, which can be aligned with the needs of the organization. Say, for instance, to extract the best users who are willing to invest in such businesses, or better still, to increase conversions and grow the audience for a marketing campaign. Besides, cognitive computing comprises natural language understanding, human-computer interaction techniques, and machine learning. 

And due to its ability to study and simulate human understanding of the objective world, it amasses cognition and value discovery of information and data. It, therefore, possesses the ability to store, organize, manage and analyze big data for long-term complex tasks resolution objectives.