Tag Archives: Artificial Intelligence

Robots to the rescue!

The effect of tremors, storms, flooding is expanding, so the requirement for robots for all periods of a fiasco, from anticipation to reaction and recuperation, will increment also.M1

Quick advances in innovation are altering the jobs of airborne, earthly and oceanic automated frameworks in a fiasco alleviation, pursuit, and salvage (SAR) and rescue activities. Robots and automatons can be conveyed rapidly in regions regarded unreasonably dangerous for people and are utilized to manage rescuers, gather information, convey basic supplies or give correspondence administrations.

The principal detailed utilization of SAR robots was to investigate the destruction underneath the crumbled twin towers of the World Trade Center in New York after the September 2001 fear-based oppressor assaults. Up to now, in excess of 50 arrangements of debacle robots have been archived all through the world, as per the Texas-based Center for Robot‑Assisted Search and Rescue

New innovations being used or improvement for salvage automatons and robots incorporate methods for expanding survivor recognition. Sensors examine zones for pulses and breathing, multisensor tests react to scents or sounds and concoction sensors flag the nearness of gases.

Standards put safety firstM2

A significant part of the innovation utilized in automatons originates from product hardware created for purchaser fundamentals like cell phones. Automatons likewise require worldwide situating satellite (GPS) units, remote transmitters, flag processors and microelectromechanical frameworks (MEMS). The flight controller likewise gathers information from barometric weight and velocity sensors.

Perfect for separated and remote difficult to-get to zones. utilizing rambles is valuable not just when cataclysmic events make access via air, land, ocean or street troublesome, yet in addition in segregated districts that need available foundation. As of late, rambles have begun conveying restorative supplies in zones where discovering crisis social insurance is very troublesome. as of now just about a fourth of the world’s nations control the utilization of automatons. Their sending in a fiasco help activities presents difficulties including administrative issues, especially when choices are made on a specially appointed premise by neighborhood and national experts. Philanthropic alleviation offices additionally caution of the dangers of helping rambles being confused with the military airplane.

Over and submerged as well

Given that 80% of the total populace lives close to water, oceanic automated vehicles can likewise assume a significant job in catastrophe alleviation by assessing basic submerged framework, mapping harm and recognizing wellsprings of contamination to harbors and angling zones. In the Mediterranean, a battery‑powered automated gadget originally created for use by lifeguards to save swimmers has been adjusted to help salvage displaced people crossing the Aegean Sea from Turkey. This sea robot has a most extreme cruising rate of 35 km/h and can work as a buoyancy gadget for 4 individuals.

A robot working in a risky situation needs free power and sensors for explicit conditions. It might be cut off from its human administrator when correspondence signals are inconsistent. At the point when remote task guided by sensor information ends up outlandish, a salvage robot needs the capacity to settle on choices all alone, utilizing Artificial Intelligence or other man-made consciousness (AI) calculations.

Artificial Intelligence grows to help predict and characterize earthquakes!!!


With a developing abundance of seismic information and registering power available to them, seismologists are progressively swinging to a control called AI to all the more likely comprehend and foresee convoluted examples in tremor action. Recognize quake focuses, describe diverse sorts of seismic waves and recognize seismic action from different sorts of ground ” noise.”

Artificial Intelligence alludes to a lot of calculations and models that enable Computer’s to recognize and remove examples of data from vast informational indexes.

 AI strategies frequently find these examples from the information themselves, without reference to this present reality, physical instruments spoken to by the information. The strategies have been utilized effectively on issues, for example, computerized picture and discourse acknowledgment, among different applications.

More seismologists are utilizing the strategies, driven by “the expanding size of seismic informational collections, enhancements in computational power, new calculations and design and the accessibility of simple to-utilize open-source AI structures,”

A few scientists are utilizing a class of AI techniques called profound neural systems, which can become familiar with the perplexing connections between gigantic measures of information and their anticipated yield.

The unordinary idea of the developing number of seismic tremors brought about by oil wastewater transfer in the district makes it fundamental to anticipate ground movement for future quakes and to conceivably alleviate their effect.

AI methods could be utilized progressively sooner rather than later to save simple records of past seismic tremors. As the media on which this information are recorded steadily debases, seismologists are in a race against time to secure these significant records. AI strategies that can distinguish and order pictures can be utilized to catch this information in a financially savvy way

A few investigations use AI systems to find quake causes and to recognize little tremors from other seismic “Noise” in the earth.

Intelligent Social Robots Must Have a “Hypothesis of Mind”

Recognizing other minds is essential for intelligent social interaction

1So as to fabricate AI with human-like knowledge—AIs who can collaborate socially, who can work with us to accomplish objectives, we should initially make one essential element primarily missing from their present plan. This component is the thing that psychological researchers call a “hypothesis of a brain.”

The hypothesis of mind alludes to the capacity to characteristic mental states, for example, convictions, wants, objectives, and expectations to other people, and to comprehend that these states are unique in relation to one’s own. Computer’s furnished with a hypothesis of a brain would remember you as a cognizant specialist with your very own psychological universe, as opposed to something absolutely unthinking and lifeless.

A hypothesis of mind influences it conceivable to comprehend feelings, to surmise aims, and foresee conduct. The capacity to distinguish others’ brains is basic to human discernment and social connection; it enables us to construct and look after connections, conveys successfully, and work agreeably to accomplish shared objectives. Actually, look into has demonstrated that having a modern hypothesis of psyche might be a substantial piece of why people have psychological abilities that appear to be interminably more dominant than those of our hereditarily comparative primate relatives. This capacity is important to the point that when it is upset, as we find now and again of chemical imbalance, fundamental mental capacities like language learning and creative ability become disabled.

2Perceiving different personalities comes easily for people, yet it is no simple assignment for a PC. We frequently overlook that minds are not straightforwardly discernible and are, equitably, undetectable. “In the event that you could explode the cerebrum to the measure of a plant and stroll about inside, you would not discover cognizance.” It is a to some degree impossible to miss the reality of nature that awareness—in spite of the clearness and clarity of our first-individual tangible experience—is an immaterial reflection whose whole presence must be construed.

While these fundamental meaningful gestures and others, for example, pointing signals and head gestures are basic to the establishment of a hypothesis of the brain, similarly critical is the capacity to perceive essential enthusiastic articulations. Not exclusively are such articulations direct markers of another’s an enthusiastic state, yet when they are joined with look data, the outcome can be very uncovering. It is possible that a perceptive robot could make a psychological model of a human after some time—including data about their wants, aversions, and fears—in the event that it consistently inventories the feelings being communicated when somebody’s look is aimed at specific items, scenes, or other individuals.

Society could benefit greatly from this technology

Space Weather in the Machine Learning Era?

Machine Learning is expected to play an increasingly important role in scientific fields where data are pivotal.

rob1Machine Learning is universal in current life—it’s the motor driving innovations like informal communities, extortion location, content interpretation, and discourse acknowledgment. Extensively, ML is a part of man-made brainpower that bargains with planning calculations that “gain from information.” The errands handled by ML calculations are generally partitioned into three classes: arrangement (doling out a datum to a given class or classification), relapse (foreseeing a consistent incentive for a discernible), and dimensionality decrease (discovering connections among factors).

ML is especially engaging when an informational collection is very dimensional—henceforth difficult to process with customary factual techniques—or is complex to the point that human specialists have restricted knowledge. Learning can either be “administered,” when the calculation filters through countless for which the appropriate response is known, or “unsupervised,” when the calculation gathers examples and connections fundamental the informational collection. The present ML renaissance came about because of the mix of huge informational indexes—which are getting altogether greater after some time—and all the more dominant PCs, which can analyze these large data sets.rob2

Many in the space science network envision that ML will profoundly affect heliospheric material science soon. Space missions in a previous couple of decades have returned a lot of information including remote, in situ, and ground-based perceptions. Space material science and space climate offer a gigantic chance to utilize ML strategies that can unravel very dimensional information and identify designs and causal connections in complex nonlinear frameworks. To use these strategies to their fullest degree, be that as it may, space physicists should be comfortable with the language and devices of ML. Along these lines, a requirement for interdisciplinary joint efforts has risen.

The accompanying open difficulties were tended to by the participants:

understanding causality and reducing dimensionality in space information (remote, in situ, and ground-based).

managing expansive irregular characteristics in space climate information (e.g., occasions and nonevents) to prepare to estimate models.

creating expansive inventories of occasions with ML calculations.

To cultivate advantageous interaction and cross-treatment crosswise over orders, a workshop united scientist from space climate, space material science, software engineering, data science, Machine Learning, and information mining.

Robot-Assisted Therapy for Autistic Children

4Social semi-humanoid robots are rapidly gaining ground in the education and health care industry. The rapid advancement of artificial intelligence (AI) along with new developments in robotics have resulted in the creation of super-friendly semi-humanoid robots that are perfect for helping the elderly and children alike in countless therapy and rehabilitation settings. Robot-assisted therapy is a type of therapy that helps increase traditional human therapy and is considered a game changer. In recent years, robot-assisted therapy with children suffering from autistic spectrum disorder (ASD) has been extremely successful. This has opened an area within robotics that promises to make a difference in the future of health and education. Artificial Intelligence (AI) in combination with advanced robotics can now be used as an educational and therapeutic tool to stimulate cognition, mental health and also to help the elderly in rehabilitation centres.

There is no cure for autism. However, scientific studies suggest that intensive therapies at an early stage of a child’s development produce lasting and significant improvements in a child’s ability to adapt and thrive in social situations.

Robot therapy:

QTrobot is a semi-humanoid social robot developed by a company, to increase the efficiency of autism therapy by attracting the attention of children in order to teach them new life skills.

Milo is a humanoid robot designed to be used as a tool in therapy for autistic children. Milo seems to be interesting and accessible for students with ASD, helping them to adjust emotions, learn to express empathy, learn about social situations and how to better integrate with them. Milo can walk, talk and model human facial expressions. So, every autistic child can be successful with a little support and the help of a hugging machine or a friendly robot.

Data Science

How do we relate Data Science, Artificial Intelligence, Machine Learning & Deep Learning with each other?




It is an interdisciplinary field about processes and systems to extract knowledge or insights from data in various forms. This means that data science helps AI to come out of the problems by linking related kind of data for future use. Basically, information pools faster and more efficiently. They play active roles in the design and implementation work of four related areas:

  • Data architecture
  • Data acquisition
  • Data analysis
  • Data archiving



In the present, AI is complex and effective but is nowhere equal to human intelligence. Humans use the data present around them and the data accumulated in the past to figure out anything and everything. However, AIs don’t have that ability just yet.

Artificial intelligence is turning up to every industry, but we must understand its limits. The principle limitation of AI is that it learns from the data. There is no other way in which knowledge can be integrated. That means any deception in the data will be reflected in the results. And any additional layers of prediction or analysis must be added separately.


Machine Learning

Machine learning is an application of artificial intelligence (AI) that provides systems ability to automatically learn and improve from experience without being exclusively programmed. It focuses on the development of computer programs that can access data and use it to learn for themselves.

The process of learning begins with observations or data, such as examples, direct experience, or instruction, to look for patterns in data and make better decisions in the future based on the examples that we provide. Machine learning methods

  • Supervised machine learning algorithms
  • unsupervised machine learning algorithms
  • Semi-supervised machine learning algorithms
  • Reinforcement machine learning algorithms


Deep Learning

It is a latest technology behind driverless cars, which enables them to recognize a stop sign, or to make difference between a pedestrian from a lamppost. Models are trained by using a large set of collected data and neural network architectures


Artificial intelligence is a huge term with applications ranging from robotics to text analysis. It is still a technology under evolution and there are dispute of whether we should be aiming for high-level AI or not. Machine learning is a subset of AI that focuses on a definite range of activities.

Big Data 2018

The future of Artificial Intelligence in 6 ways

Technology moves at rapid speed, and we now have more power with us than we had in our homes in the 1990s. Artificial intelligence (AI) has been an interesting concept of science fiction for decades, but many researchers think we’re finally getting close to making AI a reality. NPR notes that in the past few years, scientists have made development in “machine learning,” using neural networks.

This is a type of “deep learning” that allows machines to process information for themselves on a very refined level, allowing them to perform difficult functions like facial recognition. Below are the 6 ways of AI which highly impacts on future

 Automated Transportation

We’re already seeing the beginnings of self-driving cars, though the vehicles are currently required to have a driver present at the wheel for safety. Inspite of these advance in developments, the technology isn’t perfect yet, and it will take a while for public acceptance to bring automated cars into widespread use. Google began testing a self-driving car in 2012, and since then, the U.S.

Cyborg Technology

One of the main circumspection of being human is simply our own bodies—and brains. AI gives the most impact on people with amputated limbs, as the brain will be able to communicate with a robotic limb to give the patient more control. This kind of cyborg technology would automatically reduce the limitations that amputees deal with on a daily basis.

Taking over dangerous jobs

Robots are already taking over some of the most difficult jobs available, including bomb defusing. These robots aren’t quite robots yet, according to the BBC. They are technically drones, being used as the physical counterpart for defusing bombs, but requires a human to control them, rather than using AI. Whatever their allocation, they have saved thousands of lives by taking over one of the most dangerous jobs in the world.

Solving climate change

Solving climate change might looks like a tall order from a robot, according to the development machines have more access to data than one person ever could—storing a mind-boggling number of statistics. Using big data, AI will identify the development and use that technology to solve the difficult problems.

Robot as friends

At this time, most of the robots are still emotionless and it’s hard to imagine a robot you could relate to. However, a company in Japan which has taken the advancement big steps towards a robot companion—which who can understand and feel emotions. Introduced in 2014, the Robot companion which is named as “Pepper” was sold in 2015, with all 1,000 initial units selling out within a minute. The robot was specifically programmed to read human emotions, develop its own emotions. Pepper goes on sale in the U.S. in 2016, and more sophisticated friendly robots are sure to follow.

Improved elder care

Although we don’t know the exact future, it is quite conspicuous that relating with AI will soon become an everyday activity. These interactions will apparently help our society evolve, particularly in regards to automated transportation, cyborgs, handling dangerous duties, solving climate change, and improving the care of our elders.