Farmers’ interest in cutting-edge technology has generated a market for agricultural robots and drones worth $23.06 billion by 2028. In open fields and greenhouses, robots can already perform a range of tasks. From weeding and harvesting to sampling and spraying, advanced technology help farmers cultivate healthy crops in a financially and environmentally sustainable manner. While we are only at the beginning of this trend, there are already numerous examples of how agricultural robots might affect food production.

A Tertile robot that makes weeding easier than ever

In many homes, there are food and flower gardens. While this activity is fun and offers nutritious food, it is also a constant battle to eliminate weeds that deprive plants of water and nutrients. Weeding can be time-consuming and difficult, which is why Franklin Robotics, a technology company, has come up with a solution. Tertill, a 1.1-kg heavy robot from this American startup, trims itself as it walks about the garden. The four-wheeled device uses sensors to locate its target and a nylon thread on its underside to pull weeds out.

The robot’s solar panel can charge its battery when it is exposed to direct sunlight. The device can also be charged using a USB cord. To keep Tertill from fleeing and allowing it to patrol in a set area, the robot’s owners must enclose their garden with at least a five-centimeter-high wall. Although the machine is weather-resistant, rocks, mud, and uneven terrain might slow it down. Franklin Robotics has also developed a smartphone app that allows clients to monitor the robot’s activities as well as the weather in the garden.

Smart core to check soil samples

Crop production in large open fields faces unique challenges. Farmers must study soil samples to determine the number of nutrients required in certain field areas. Using the proper amount of nutrients can increase yields, cut costs, and minimize surface and groundwater pollution. Using too many or too few chemicals, on the other hand, may have a negative impact on agricultural productivity. Farmers often collect soil samples by hand, which is a time-consuming and error-prone procedure despite the necessity of the process.

Troy Fiechter and Drew Schumacher, both Purdue University graduates, have developed a superior soil analysis method. The duo developed SmartCore, an autonomous robot that navigates fields and collects samples from specific locations. Obstacle detection algorithms and GPS lead the equipment to take samples from the same region each year, allowing farmers to track the changes in their soil. After the sample is taken, SmartCore transports it to the edge of the field for shipment to a lab.

Swarm robots to plant seeds

The robots use satellite navigation to transmit their exact location, which helps operators optimize planting operations. Controlling and optimizing the machines is the responsibility of the OptiVisor algorithm. Fendt’s field robotic system is energy efficient due to its low weight and low-maintenance engine. The grid, farmers’ biogas facilities, wind energy, or fuel cells can all be used to charge the battery. As one of the pioneers in the development of farming tractors in the early twentieth century, Fendt believes that its latest technology solutions may help agriculture take the next big step forward.

The robots send their exact location via satellite navigation, which aids operators in optimizing planting operations. The OptiVisor algorithm is in charge of controlling and optimizing the machines. Because of its low weight and low-maintenance engine, Fendt’s field robotic system is energy efficient. The battery can be charged using the grid, farmers’ biogas facilities, wind energy, or fuel cells. Fendt believes that its latest technology solutions can assist agriculture to take the next significant stride ahead, as one of the pioneers in the creation of farming tractors in the early twentieth century.

Mamut robots to spot plant diseases

Experiments are also being conducted by Cambridge Consultants, a subsidiary of the French engineering firm Altran. The high-tech company is working on Mamut, an AI-powered autonomous robot that uses a stereo camera, an AI system, lidar, and a compass to map and navigate a natural area. Inspection sensors and six 360-degree cameras, one of which is a multispectral imaging camera, are included in the device. Mamut wanders around farm fields, gathering visual data and creating maps to aid farmers in spotting diseases, estimating crop yields, and selecting the best harvesting time. Unlike drones, the robot goes beneath the plants to get more detailed information.

Cambridge Consultants is still training the AI to monitor crops, which is a difficult task. The robot travels around 24 kilometers in eight hours, during which time the developers evaluate functions including collision avoidance, route planning, and route following. Although high-value crop growers expressed the most interest, the company thinks that the Robotics-as-a-Service commercial model will allow the product to reach a larger market. Farmers would only pay for a one-time service, and the technology supplier would own the robot. This allows consumers to adjust their robot usage based on their current needs and cost constraints.

Naio technologies robots

Naio Technologies has a number of robots that can not only operate as the ideal farm laborer, but also conserve and protect the environment.
The robots are capable of weeding, hoeing, and harvesting assistance. “We aim to provide access to the latest technologies to all partners in the agriculture industry, to help grow healthier, more abundant, and ecologically friendly crops,” the team says.

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Global Artificial Intelligence Summit & Awards

If you or your organization is building cutting-edge AI solutions to adapt to a world driven by technology, Please nominate yourself/or your company for GAISA AWARDS 2022.

Please follow the below-given link to nominate:https://gaisa.in/award

All further details regarding the event will be updated on the official website of Gaisa 2022. Please Visit: https://gaisa.in/

The post Top AI devices for agriculture lands appeared first on AICRA.

How is the Mobility Landscape Changing?

Mobility technology is a driving force in making transportation more user-friendly and accessible. Smart mobility is propelling city economic growth, improving logistics supply chains, increasing labor market accessibility, and opening up new markets for businesses.

Smart mobility technologies such as shared bikes and e-scooters are changing the urban mobility ecosystem, and cities are responding by building dedicated lanes and improved transportation systems.

Why is AI Important to Mobility?

Smart cities all over the world strive to provide more efficient and environmentally friendly transportation options. Transportation options such as Connected Autonomous Vehicles (CAV) and drone deliveries will soon dominate the mobility landscape. Because of the constant increase in traffic, traffic-induced noise and pollution, and the limited availability of space in urban areas, the way people and goods move will have to change dramatically.

Machine learning, artificial intelligence, and data analytics are used by organizations to identify, predict, and solve mobility challenges. Companies and cities can use artificial intelligence technology to transition to autonomous mobility — highly personalized and environmentally friendly systems.

Eight Ways AI is Impacting Mobility

Here are the top eight ways in which AI is changing mobility.

1. Smart Grid Management

Electric cars need to charge their batteries now and then. But many people don’t know that they can also resell the power stored in electric cars’ batteries back to the electrical grid. AI can predict the best times to charge your electric vehicle and when to use it for Vehicle-to-Grid (V2G) “un-charging.” Smart grid management enables drivers to reduce costs and increases the efficiency and stability of the entire grid.

2. Transportation Systems

Mobility-as-a-Service (MaaS) enables users to quickly plan trips using different means of transportation. With MaaS, commuters can book, manage, and pay for rides using personal devices like smartphones or other connected devices.

When powered by AI, MaaS systems gain significant benefits, like fully autonomous driving and smart tracking. Additionally, MaaS with AI-based controllers can optimize, monitor, and coordinate autonomous car fleets while offering great options to individual users.

AI-based MaaS can also be applied to ride-sharing, enabling users to share autonomous cars across an optimized route in a much cheaper and safe way. Ride-sharing users can also get a greater social experience when riding with people of similar interests. This can change traditional transportation networks and transform the way people commute.

3. Driver Tracking

A driving monitoring system uses cameras to monitor the alertness of the driver. The system detects the driver and assesses his or her level of concentration. When a driver is distracted, the system alerts them. Drivers can use AI-based systems to customize vehicle settings such as seat position, temperature, and mirrors.

This technology is based on AI algorithms that monitor head position, eye openness, and other alertness indicators. If necessary, the system alerts the driver to refocus or take a break. Posture management allows for the most effective deployment of airbags in the event of an accident.

4.Self-Driving Vehicles

Despite public skepticism, driverless vehicles are slowly but steadily making their way into the transportation sector. While the majority of self-driving vehicle companies are still running pilot projects to ensure passenger safety, some have already deployed vehicles on public roads. As this technology advances, self-driving vehicles may gain widespread acceptance and become the norm for consumers.

Computer vision and deep learning systems are the brains of a self-driving car. These systems are responsible for processing and giving context to all the information that comes from the sensors. A self-driving car’s data is coming from multiple different sources like cameras, radar, and Light Detection and Ranging (LiDAR). Computer vision systems need to process data from all these different sources. As a result, environment information gathering becomes a very comprehensive task.

5.Traffic Management

Every day, people face traffic congestion issues. AI has matured to the point that it can now solve this problem. Cameras and sensors are embedded throughout roads to collect traffic data. These details are sent to cloud-based big data analytics and AI-based systems. These big data tools perform an analysis to identify traffic patterns and predict congestion.

Drivers can also use AI to improve road safety and reduce wait times. Important traffic information such as accidents, road closures, and the shortest routes to a destination can assist drivers in traveling without encountering traffic congestion.

6.Manufacturing

AI is also changing the way cars are built. For example, Kia recently introduced the Hyundai Vest Exoskeleton (H-VEX) wearable robot. The robot is used to improve car assembly lines as well as to protect factory workers.

Another example is Automated Guided Vehicles (AVGs), which are designed to transport materials without the use of humans. Welding and painting robots powered by AI can detect manufacturing flaws and adjust their processes accordingly. These AI-powered robots make automobile manufacturing safer, more efficient, and less expensive.

7.Insurtech

Technology applications in insurance, also known as insurtech apps enable drivers to file their damage assessments after an accident and driver risk assessments based on risk factors filtered out of big data.

8.Smart Cities

AI-based systems have a huge impact on the way cities expand and grow. For instance, autonomous vehicles can initiate a de-urbanization trend. Autonomous vehicles offer a cheaper, faster, and safer way to commute. People can live outside of cities and use self-driving cars to get to work quickly. And since they aren’t driving, they can be fully productive during the ride, using commute time to continue working while the AI drives the vehicle

Conclusion

The transportation industry is ever-changing. Artificial intelligence and machine learning are already reshaping the automotive industry. AI-based systems aid in the reduction of traffic accidents and fatalities, the reduction of manufacturing costs, and the improvement of service levels. On the other hand, when businesses fail to adapt and follow the new trend, AI-based automation and systems can result in technological unemployment.

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Global Artificial Intelligence Summit & Awards

If you or your organization is building cutting-edge AI solutions to adapt to a world driven by technology, Please nominate yourself/or your company for GAISA AWARDS 2022.

Please follow the below-given link to nominate:https://gaisa.in/award

All further details regarding the event will be updated on the official website of Gaisa 2022. Please Visit: https://gaisa.in/

The post How AI is Changing the Mobility Landscape appeared first on AICRA.

The fear of robots replacing humans in job roles is unnecessary. Automation has very less effect on job roles that involve managing people, applying expertise, and social interactions, where machines are unable to match human performance at least for now. There are also some jobs (Mostly jobs in unpredictable environments) that are technically difficult to automate.

People see how automation is replacing humans from different job roles but one important thing that they don’t notice is the new jobs created by automation and new technologies. According to experts, we might see a spur of job creation by 2030.

Globally, we estimate that 250 million to 280 million new jobs could be created from the impact of rising incomes on consumer goods alone, with up to an additional 50 million to 85 million jobs generated from higher health and education spending.

Article: Jobs lost, jobs gained: What the future of work will mean for jobs, skills, and wages from www.mckinsey.com

The investments made in technologies like artificial intelligence are expected to gain by 50 % by 2030, this will create 20 to 30 million jobs globally.

Automation will transform the world and workplace but it is not going to cause any harm to the workforce until and unless employees are ready to adapt to the new scenario and update themselves with new skills required to go hand in hand with automation and technology.

Will there be enough work in the future?

Sufficient economic growth, technological innovations, and investments are enough to create new jobs in the future.

Benefits of automation in workplaces

• Improved safety and security: With automation robots are taking over hazardous jobs such as jobs involving blades, welding, chemical exposure, and more. It’s obvious why human error can have huge consequences in this setting, especially after workers have been on the line for long hours. Automation also reduces human errors in office settings by accurately monitoring unusual cyber activities.
• Product/Service quality: One of the most significant advantages of automation is the elimination of weariness. Furthermore, robots do not require restroom breaks or sick days. They can produce the same thing in the same way for as long as you want, with almost little fluctuation in quality. In an office setting, automation also provides higher product quality. Automation personal assistance can plan for your office meetings and also remind you about your hospital appointment.
• Higher profits: Automation has the potential to create higher profits by accelerating business growth. For example, while the development of ATMs may have reduced bank teller jobs, the number of branches expanded since ATMs made it cheaper to operate each branch. As a result of the capacity to service more clients over long hours at a lower cost, bank teller employment grew overall.
• More value to employees: By automating aspects of your business, you may provide your employees more value and make them more productive. Furthermore, it will most likely lead to more interesting work.
• Freedom from boredom: Automation allows human employees to focus on more critical jobs band free them from busy and repetitive works.

Conclusive thoughts

Automation in the workplace has huge benefits for everyone. It expedites time-consuming activities, enhancing the candidate and employee experience. This boosts revenue, productivity, and the employer brand. While some people are concerned that AI, automation, and robots will take their jobs away, the facts.

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Global Artificial Intelligence Summit & Awards 2022

f you or your organization is building cutting-edge AI solutions to adapt to a world driven by technology, Please nominate yourself/or your company for GAISA AWARDS 2022.

Please follow the below-given link to nominate:https://gaisa.in/award

All further details regarding the event will be updated on the official website of Gaisa 2022. Please Visit: https://gaisa.in/

The post How Artificial Intelligence Transforming Work Places? appeared first on AICRA.

 We are living in an era of social media with an active population of 3.81 billion. Social media has become the favorite baby of many business sectors since it provides a great way to find new clients or nurture their relationships with existing ones. Social media platforms like Facebook, Instagram, etc. are dealing with an unimaginable amount of data that is increasing exponentially with each passing year. 

The analysis and management of bulk data consisting of social media spaces are done through the incorporation of Artificial intelligence and several other technologies. 

As we all know, AI makes a machine think and act accordingly.AI & machine learning together helps various social media platforms make sense of the user-generated data. Ai empowered analysis of voluminous data helps companies to perceive what’s trending, different hashtags, and patterns. Using various algorithms, AI can detect unstructured user comments and thereby offer a customized experience and concede crisis. For example, Facebook with the help of AI grasps the likes & interests of users to serve content accordingly.

Artificial intelligence has great relevance in social media networks. It creates better and more efficient ways for marketing. The influence of AI in social media automates some of the labor-intensive tasks and makes them more focused on higher-value tasks. 

Ai can also dramatically enhance the revenue from your social media investments giving you an insight into effective posts, relevant audiences, and the channels that work best for you.

Let’s now go through some of the Use cases of Ai in social media marketing

• Content creation & Management

Ai helps us to produce and distribute effective sharable content. Ai tool analyses past experiences and learn what works in each channel. It develops the right message at the right time according to the interested audience.

• Social media insights

Several AI-powered tools are used to measure and improve brand equity, detect consumer trends, and understand target audiences. It also recommends what to post and when to post after learning about successfully implemented strategies by others.

• Advertising

Ai tools can literally create effective ads optimized for clicks and conversions.AI can also analyze PPC advertising across Facebook and Instagram, then offers recommendations to improve performance based on data.

• Ai powered chatbots

Businesses use Ai-powered chatbots to answer customer queries. These chatbots can effectively proceed with conversations with consumers and provide them with the required answers.

• Increased security

Artificial intelligence is also used to ensure the security of user data by adding features like user authentication, pattern detection, fraud prevention, etc.

Artificial intelligence is here to stay forever. Ai has a great impact on social media networks. Social media is the biggest virtual market in the future and AI helps it to improve in every possible way. 

The post Rising Influence of AI on social media platforms appeared first on AICRA.

AI has contributed a lot to the world for 3 decades. It is now innovating gracefully with widespread sub-technologies and applications. From biometrics and computer vision to smart devices and self-driving cars, emerging trends are fuelling the AI craze. 

Ai seems promising in 2022 with some awe-inspiring technologies.

Promising AI Technologies

The topper of the list is AI Optimized Hardware exclusively used to execute AI-oriented tasks specifically. They have an advanced central processing unit alongside improved graphics. Portable AI-optimized silicon chips are one example, which can be inserted into any device to acquire information. Some industry big names such as Alleviate, Google, and Cray are focused on generating AI-optimized hardware solutions.

Biometrics stands as the source of interaction between humans and machines.  It is known as a futuristic technology that includes face recognition, touch recognition, Iris recognition, DNA matching, Retina recognition, voice recognition, etc. Biometrics authenticates a person based on unique, specific, and verifiable data. 

Computer vision is another subfield of artificial intelligence that is capable of exceptionally exceeding human visual abilities in many areas. it trains machines to understand and interact with the visual world. This technology is used in machines to identify and classify objects in images, videos, and deep learning models precisely.

As technology occupies every hook and corner of our life, each one of us is largely exploited by it. Smart devices are stealing all our attention nowadays, Examples are smart security cameras, smart speakers, smart watches, smart keychains, etc. Text analytics along with NLP brings stunning changes to the technology world in 2022. Text analytics is used for identifying the structure, meaning, sentiments & intent of a sentence through machine learning.

The technologies used behind cyber defense are mostly the subfields of AI. It uses a computer defense mechanism to detect & prevent data theft. Researches are ongoing for developing AI-empowered machines that can carry out the content creation process. Whether it is making videos, images, ads, blogs, white papers, or news stories. 

Peer-to-peer network connections are gaining much popularity in 2022 due to the security it provides while sharing data. It integrates different systems and computers for the process instead of transmitting data via a server. It also comes with the ability to solve critical problems.

The world is eagerly looking at every small technical achievement of this year. 

One of the greatest news coming on our way is about self-driving cars, It has been a long dream for us. Ai-powered self-driving cars will be efficient in avoiding collisions. Besides, the car is powered by sensors that aides in mapping out the immediate environment of the vehicle.

AI had demonstrated huge potential for many years. The increased use of AI-empowered models in 2022 can be considered a technological breakthrough in every aspect.

Ai is a game changer..!

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Global Artificial Intelligence Summit & Awards 2022

If you or your organization is building cutting-edge AI solutions to adapt to a world driven by technology, Please nominate yourself/or your company for GAISA AWARDS 2022.

Please follow the below-given link to nominate:https://gaisa.in/award

All further details regarding the event will be updated on the official website of Gaisa 2022. Please Visit: https://gaisa.in/

The post Promising AI Technologies In 2022 appeared first on AICRA.

An article from IBM says, AI’s capability to analyze massive quantities of data with lightning speed means security threats can be detected in real time, or even predicted based on risk modeling. As AI reaches new frontiers, there must be a framework for ensuring AI is accurate and ethical.

On the other hand, experts observed that Ai can be resource-intensive so, the technology implementation is not practical in many applications. for the time being, let’s ignore this fact and think about the giant investments flowing through the cybersecurity community to develop AI-empowered tools. Researchers suggest Use of artificial intelligence with this kind of investment may have a lot to offer in the cybersecurity sector.

AI empowered security measures in modern-day businesses

Every modern business incorporates high-level security measures for keeping their data safe from hackers.AI empowered security measures are designed to work around the clock and it only requires milliseconds to identify & respond to the occurrence of cyber-attacks.

Capgemini research institute analyzed the role of cybersecurity, and their report says that “building up cybersecurity defenses with AI is imperative for Business organizations. This is, in part, because the survey’s respondents (850 executives from cybersecurity, IT information security, and IT operations across 10 countries) believe that AI tools are necessary for cybersecurity.”

After all, hackers are already using the technology to perform cyberattacks. Artificial intelligence will open new doors to enhance the existing cybersecurity solutions and it can be a boon to organizations.

Integration of AI in cyber security systems

Integration of AI in existing cybersecurity systems requires planning, training, and groundwork preparation. Once it is done, you can create more accurate, biometric-based login techniques, detect threats and malicious activities with the assistance of predictive analysis, enhance learning and analysis through natural language processing, Securing conditional authentication and access, and many more.

Big companies like CrowdStrike, FireEye, and Fortinet are already using Ai tools for their digital security.

Ai technologies show significant growth in the cybersecurity sector, but Just like AI tools help to accurately identify and stop cyberattacks, the AI systems can also be used by hackers to launch more sophisticated attacks. Adversarial AI is a term used to define the development and use of AI for illegal purposes like hacking. The famous software company, Accenture identified adversarial AI when their system started weirdly misinterpreting inputs. Intentionally modified inputs can trick the system into misidentifying or misclassifying objects.

In a Nutshell

Ai vulnerabilities are a feast to hackers but still, the positive side of the technology outweighs the negative.AI provides much-needed analysis and threat identification that can be acted upon by cybersecurity professionals to reduce breach risk and improve security posture. An abundance of Ai powered cybersecurity tools are waiting for us in the future. Let’s build powerful human-machine partnerships that push the boundaries of cybersecurity.

Global Artificial Intelligence Summit & Awards 2022

If you or your organization is building cutting-edge AI solutions to adapt to a world driven by technology, Please nominate yourself/or your company for GAISA AWARDS 2022.

Please follow the below-given link to nominate:https://gaisa.in/award

All further details regarding the event will be updated on the official website of Gaisa 2022. Please Visit: https://gaisa.in/

The post AI in cybersecurity: Boon or bane appeared first on AICRA.

Since the community of AI experts and enthusiasts is now greater than ever, the need for knowledge exchange is natural, even during a pandemic.

Below are a few options for exploring the AI space through the eyes of leading scientists and engineers. These conferences take place on various dates around the world; choose the one that works best for you.

Global Artificial Intelligence Summit & Awards 2022

Dates: October 6th & 7th

Location: New Delhi, India

GAISA-Global Artificial Intelligence Summit & Awards series organized by the All India Council for Robotics & Automation hosts the 3rd edition on the 06th & 07th of October 2022, focused on the prominence of AI in human lives & business industries. The event will bring together some of the world’s leading decision-makers, technologists, innovators, and investors. It will offer you a unique platform to explore how AI can transform current technologies, which can later help in developing a better future.

SIGGRAPH

Dates: August 8-11

Location: Vancouver, Canada, and online

This is a combination of conference and exhibition activities focused on production & animation, arts & design, gaming & interactive, education, and the latest technologies in computer graphics and interactive techniques. The event is organized by ACM SIGGRAPH in Northern America and dates back to 1974. Since 2008, the annual SIGGRAPH conference has also been held in Asia.

ICPR (International Conference on Pattern Recognition)

Dates: August 21-25

Location: Montreal, Canada, and online

This conference is organized by IAPR (the International Association of Pattern Recognition). Here, experts from the niches of image, sound, speech, and pattern recognition as well as computer vision and machine intelligence could unite to upgrade their skills and knowledge.

IntelliSys

Dates: September 1-2

Location: Amsterdam, the Netherlands, and online

This conference aims at gathering scientists and practitioners from more than 50 countries in the fields of intelligent systems and artificial intelligence. The event’s goal is to discuss the AI impact on day-to-day operations and exchange research and development results.IntelliSys is divided into four tracks dedicated to artificial intelligence, machine learning, robotics, and ambient intelligence. The program includes expert talks, lectures provided by scientists, presentations, and collaborative sessions.

IEEE ICIP (International Conference in Image Processing)

Dates: October 16-19

Location: Bordeaux, France

This is the 29th ICIP conference, which is considered to be the largest in the area of image & video processing and computer vision. Attendees will have a chance to participate in tutorials and special & industry sessions, visit the forum’s exhibition, and reach out to the leading experts and researchers.

ECCV (European Conference on Computer Vision)

Dates: 24-28 October

Location: Tel-Aviv, Israel (online and hybrid options are being considered)

ECCV was first organized in 2010 and now takes place every two years, alternating with ICCV. Like other leading computer vision conferences (ICCV and CVPR), this one comprises the main technical program (up to three days) with tutorials and workshops on the first and last days.

Conclusion

The AI industry continues to expand and penetrate numerous industries, including finance, healthcare, education, and agriculture. The conferences listed above are only the tip of a much larger iceberg. To reshape and optimise traditional operations, the business and academic communities have formed strong alliances.

The post Top AI Conferences in 2022 appeared first on AICRA.

One of the numerous concerns raised by AI is the risk of eliminating a major chunk of the human workforce by replacing the need for manual labor. However, it will also free humans from tiresome, repetitive duties, letting them focus on more difficult and lucrative projects or simply take some much-needed time off.

According to McKinsey research, depending on the adoption scenario, automation may displace between 400 and 800 million jobs by 2030, necessitating the relocation of up to 375 million people.

These data can cause people to be concerned about the future. However, history suggests that this is not the case; there is no doubt that some industries will be altered to the point where they will no longer require human labor, resulting in job redefinition and business process transformation. For example, many health difficulties may be efficiently automated, allowing doctors to focus on other critical matters that require their attention. In terms of totally replacing humans, human labor is and will remain necessary for the foreseeable future.

Though the potential of AI is infinite, it is also constrained. While it is obvious that AI will rule the professional world on a variety of levels. However, no matter how smart AI becomes, it will never be able to mimic human awareness, which supports humans’ position at the top of the food chain.

Until now, we’ve been discussing employment that can be taken away as technology progresses, but the human parts of work cannot be replaced. Let’s concentrate on something they can’t accomplish. Some occupations are only capable of being performed by people.

There are jobs that require creation, conceptualization, complex strategic planning, and dealing with unknown spaces and feelings or emotional interactions that are way beyond the expertise of an AI as of now. Let’s now talk about certain skills that are irreplaceable till the human race exist.

1. Empathy : is unique to humans: While some may argue that animals exhibit empathy, they are not the ones taking over occupations. Humans, unlike programmed software designed to provide a specific outcome, can experience emotions. The personal affinity between a person and an organization is the cornerstone of a professional connection, which may appear paradoxical. To create trust and human connection, humans want a personal connection that extends beyond the professional realm, which bot technology absolutely lacks.

2. Emotional Intelligence: While accurate, the AI is not intuitive or culturally sensitive, as these are human characteristics. No matter how precisely it is programmed to perform a task, it lacks the human ability to adjust to the algorithm of human intelligence. For example, reading into a situation or another person’s face. It lacks emotional intelligence, which allows humans to recognize and handle interactions that need emotional communication. During your customer service, a human interaction to read and grasp the situation is always preferable to an automated computer that cannot operate or aid beyond the programming.

3. Creativity: A benefit of being human: Artificial intelligence (AI) can improve productivity and efficiency by eliminating errors and repetition and replacing manual tasks with clever automated solutions, but it cannot comprehend human psychology. Furthermore, as the world becomes more AI-enabled, people will be able to take on more novel tasks.

4. Problem-solving outside of a code: Humans may deal with unforeseen uncertainty by analyzing the circumstance; for example, by using critical thinking in difficult scenarios and employing inventive approaches. Unlike people, which can work in a range of environments and circumstances, AI-powered devices cannot act beyond their function, which may be far in the future but not in the near future.

There is little question that artificial intelligence will not drive the future. Humans must be creative, analytical, and contextually aware in order for AI to work. The reason for this is simple: humans will continue to deliver value that machines cannot.

The post 4 skills that won’t be replaced by AI appeared first on AICRA.

Current AI trends are nothing short of remarkable. Every day, we hear about systems and machines performing tasks that, until recently, we thought were solely and permanently reserved for humans: making medical diagnoses, drafting legal documents, designing buildings, and even composing music.

Our concern here is with something even more startling: the prospect of high-level machine intelligence systems outperforming humans in almost every task. This is not a work of science fiction. According to a recent survey, the median estimate among leading computer scientists was that this technology would be available within 45 years.

Importantly, the survey revealed significant disagreement. Some believe that high-level machine intelligence will arrive much sooner, while others believe it will arrive much later, if at all. Such divergences of opinion abound in recent AI literature, ranging from popular commentary to more expert analysis.

Regardless of these opposing viewpoints, one thing is certain: if we believe this type of outcome is possible, it should demand our attention. Continued advancement in these technologies could have extremely disruptive consequences, exacerbating recent trends in inequality, undermining work as a force for social integration, and undermining a source of purpose and fulfillment for many people.

Six AI scenarios that could build a positive future

One of the most major obstacles to action is that there is currently no agreement on what future we should aim for, possibly because there is little discussion about what might be desirable. This lack of vision is a problem because, if high-level machine intelligence does arrive, we risk being overwhelmed by unprecedented technological change and unstoppable economic forces. This would be a huge missed opportunity.

As a result, workshop attendees and interviewees, ranging from science-fiction writers to economists and AI experts, attempted to articulate positive visions of a future in which Artificial Intelligence can do the majority of what we currently call work.

These scenarios represent possible human trajectories. However, none of them are unambiguously achievable or desirable. While there are elements of significant agreement and consensus among the visions, there are also revealing clashes.

1. Shared economic prosperity
The economic benefits of technological progress are widely shared around the world. The global economy is 10 times larger because AI has massively boosted productivity. Humans can do more and achieve more by sharing this prosperity. This vision could be pursued by adopting various interventions, from introducing a global tax regime to improving insurance against unemployment.

2. Realigned companies
Large companies focus on developing AI that benefits humanity, and they do so without holding excessive economic or political power. This could be pursued by changing corporate ownership structures and updating antitrust policies.

3. Flexible labour markets
Human creativity and hands-on support give people time to find new roles. People adapt to technological change and find work in newly created professions. Policies would focus on improving educational and retraining opportunities, as well as strengthening social safety nets for those who would otherwise be worse off due to automation.

4. Human-centric AI
Society decides against excessive automation. Business leaders, computer scientists, and policymakers choose to develop technologies that increase rather than decrease the demand for workers. Incentives to develop human-centric AI would be strengthened and automation taxed where necessary.

5. Fulfilling jobs
New jobs are more fulfilling than those that came before. Machines handle unsafe and boring tasks, while humans move into more productive, fulfilling, and flexible jobs with greater human interaction. Policies to achieve this include strengthening labour unions and increasing worker involvement on corporate boards.

6. Civic empowerment and human flourishing
In a world with less need to work and basic needs met by UBI, well-being increasingly comes from meaningful unpaid activities. People can engage in exploration, self-improvement, volunteering or whatever else they find satisfying. Greater social engagement would be supported.

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• Programming
  A data scientist will be skilled in one or more programming languages, such as R, Python, SAS, Hadoop, and so on. It is not just about writing code, but also about becoming acquainted with multiple programming environments for data analysis. With the area of data science seeing unprecedented attention and importance in organizations worldwide, a grasp of programming languages and the capacity to adapt to evolving technologies are critical to a data scientist’s success. Any reluctance to use programming tools might be a deal-breaker for a corporation that relies on your expertise to boost its business growth.
• Quantitative Analysis
  This is the essence of the job of a data scientist. A data scientist’s profile includes having a calculated and visceral awareness of a complicated environment and its behavior, munging data that is messy and difficult to deal with, and generating prototypes and models to test hypotheses. Machine learning — supervised and unsupervised learning algorithms, time-series forecasting, data-reduction techniques, neural networks, and so on – are all must-know ideas.
• Math and stats knowledge
  Without statistics, a data scientist and an organization’s future are at risk. Without math and statistics, it will be hard to generate hypotheses based on how a system would respond to changes, make statistically significant assumptions about data variances, define metrics to lay out objectives and measure progress, and draw reliable conclusions from the dataset. Writing code or properly employing functions will also be difficult if a solid basis in arithmetic and statistics is lacking.
• Visualization Skills
  It is well known that humans absorb information more quickly in the form of visuals than in words or figures. Working knowledge of data visualization technologies such as Tableau, Qlikview, Plotly, or Sisense will ensure that a data scientist can confidently convey insights to both a technical and non-technical audience, persuading them of the business value their insights can provide. A data scientist’s success may be determined by familiarising oneself with the concepts of visualizing and presenting attractive data to stakeholders.
• Multivariate Analysis and Linear Algebra
  It may or may not be expressly asked in an interview, but a data scientist may have to design their implementation models in-house at some time. This is especially true when data-driven solutions might result in transformational improvements for the firm. Data science is a relatively recent field with no fixed job definitions. When building out-of-the-box models, a working grasp of linear algebra and multivariable calculus might be useful. In addition, an interviewer may surprise you with a calculus question. A self-assured data scientist will advise them to go for it!

Conclusion
Whether you are an employer or a recruiter, this list of successful data scientists’ skills and qualities can help you find the best candidates. When making your next recruitment, search for applicants that have a solid combination of data intuition, statistical thinking abilities, a “hacker’s spirit,” and a fair dosage of creativity, in addition to technical talents. Data scientists with these qualities will undoubtedly help your organization develop and prosper.

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