Are the intelligent systems taking the control of the Humans? What is a robot’s influence in the human world? Will the future influence be made by the intelligence system self?
There is so many questions in this contest.
Intelligent systems are all technologically advanced machines that perceive and respond to the world around them. Intelligent systems can take many forms, from automated vacuums such as the Roomba to facial recognition programs to Amazon’s personalized shopping suggestions, or in our Economy Use, with what kind of currency we in future will be able to use.
One way that such systems can perceive their environment is through vision. The study of how computers can understand and interpret visual information from static images and video sequences emerged in the late 1950s and early 1960s. It has since grown into a powerful technology that is central to the country’s industrial, commercial, and government sectors.
It started with the dos programming interface, with the first computer programs used in Commondore and Amiga, and since developed into more advanced systems with the upcoming of PC Computers.
Banks, Big Organizations and Governments have made researches through the years and people have been educated specifically to build these systems.
Currently this quickly was becoming a strong industry demand for people who understand intelligent systems technology and know how to apply it to real-world problems. Graduates in this area can work in academia, national and government labs, and industry companies such as Google, Microsoft, Intel, IBM.
In the field of building all these intelligent systems, we may focuses on how these systems interact with human users in changing and dynamic our physical and social environments.
Early robots possessed little autonomy in making decisions: they assumed a predictable world and perfumed the same action(s) repeatedly under the same conditions.
Today, a robot is considered to be an autonomous system that can sense the environment and can act in a physical world in order to achieve some goals.
Research in intelligent systems faces numerous challenges, many of which relate to representing a dynamic physical world computationally.
We can identify them in four factors.
- Uncertainty: Physical sensors/effectors provide limited, noisy and inaccurate information/action. Therefore, any actions the system takes may be incorrect both due to noise in the sensors and due to the limitations in executing those actions.
- Dynamic world: The physical world changes continuously, requiring that decisions be made at fast time scales to accommodate for the changes in the environment.
- Time-consuming computation: Searching for the optimal path to a goal requires extensive search through a very large state space, which is computationally expensive. The drawback of spending too much time on computation is that the world may change in the meantime, thus rendering the computed plan obsolete.
- Mapping: A lot of information is lost in the transformation from the 3D world to the 2D world. Computer vision must deal with challenges including changes in perspective, lighting and scale; background clutter or motion; and grouping items with intra/inter-class variation.
Today all these intelligent systems are build in near most of our world. The Intelligent systems are poised to fill a growing number of roles in today’s society, including, here a list of most important areas:
- Factory automation.
- Field and service robotics.
- Assistive robotics.
- Military applications.
- Medical care.
- Visual inspection.
- Character recognition
- Human identification using various biometric modalities (e.g. face, fingerprint, iris, hand)
- Visual surveillance
- Intelligent transportation
But still the machines haven’t taken over. Not yet at least. However, they are seeping their way into our lives, affecting how we live, work and entertain ourselves. From voice-powered personal assistants like Siri and Alexa, to more underlying and fundamental technologies such as behavioral algorithms, suggestive searches and autonomously-powered self-driving vehicles boasting powerful predictive capabilities, there are several examples and applications of artificial intellgience in use today.
However, the technology is still in its infancy. What many companies are calling A.I. today, aren’t necessarily so.
A true artificially-intelligent system is one that can learn on its own. We’re talking about neural networks from the likes of Google’s DeepMind, which can make connections and reach meanings without relying on pre-defined behavioral algorithms. True A.I. can improve on past iterations, getting smarter and more aware, allowing it to enhance its capabilities and its knowledge.
That type of A.I., the kind that we see in wonderful stories depicted on television through the likes of HBO’s powerful and moving series, Westworld, or Alex Garland’s, Ex Machina, are still way off. We’re not talking about that. At least not yet.
Today, we’re talking about the pseudo-A.I. technologies that are driving much of our voice and non-voice based interactions with the machines — the machine-learning phase of the Digital Age.
While companies like Apple, Facebook and Tesla rollout ground-breaking updates and revolutionary changes to how we interact with machine-learning technology, many of us are still clueless on just how A.I. is being used today by businesses both big and small.
How much of an effect will this technology have on our future lives and what other ways will it seep into day-to-day life?
The truth is that, whether or not true A.I. is out there or is actually a threat to our existence, there’s no stopping its evolution and its rise.
Humans have always fixated themselves on improving life across every spectrum, and the use of technology has become the vehicle for doing just that. And although the past 100 years have seen the most dramatic technological upheavals to life than in all of human history, the next 100 years is set to pave the way for a multi-generational leap forward.
This will be at the hands of artificial intelligence. A.I. will also become smarter, faster, more fluid and human-like thanks to the inevitable rise of quantum computing.
What happens after the first quantum computer goes online, making the rest of the world’s computing obsolete? How will existing architecture be protected from the threat that these quantum computers pose?
Through the intelligence systems developments and educated people in this are it have been more important than ever with protection. Protection of data and important informations.
Considering that the world lacks any formidable quantum resistant cryptography (QRC), how will a country like the United States or Russia protect its assets from rogue nations or bad actors that are hellbent on using quantum computers to hack the world’s most secretive and lucrative information.
Nigel Smart, founder of Dyadic Security and Vice President of the International Association of Cryptologic Research, a Professor of Cryptology at the University of Bristol and an ERC Advanced Grant holder, tells that quantum computers could be about 5 years out.
So with the New World of Intelligence Science very near, We have to make this in our Minds, and take steps to make Humans still be in the role factor of Our Humanity and World.
No political or religious influence can stop it, we can only take it within our life and use it in an intelligent way. 💕 That’s it. 😏