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4or example, Amnesty International launched a structured initiative on Artificial Intelligence and Human Rights in 2017, while the New F York-based Data & Society Research Institute hosted a workshop on Artificial Intelligence and Human Rights in April, 2018. Artificial intelligence today is properly known as narrow AI (or weak AI), in that it is designed to perform a narrow task (e.g. Only facial recognition or only internet searches or only driving a car). Future of Artificial Intelligence - AI introduction, future scope of AI, career in AI, risks and benefits of AI, AI applications and examples, jobs in AI.

Today’s factories are easy to envision as futuristic-seeming hives of automation, where industrial robots mimic the movements and, seemingly, the intentionality of human workers.

Other future AI applications. Smart power grids: electric power flows both ways and is distributed dynamically according to changing demand. Security and military: Bomb diffusing robots, unmanned vehicles, “soldier” robots. Robot firefighters. AI Travel Agents.Astn AIatnuocc. AI Cashiers. AI Football Coaches. Avneet Pannu, M. Tech Student Department of Computer Science & Engineering DAV Institute of Engineering and Technology, Jalandhar India. Abstract: In the future, intelligent machines will replace or enhance human capabilities in many areas. Artificial intelligence is the intelligence exhibited by machines or software. The previous report, Preparing for the Future of Artificial Intelligence, discusses workforce needs, including the strong case for increasing diversity, and lays out a detailed plan for AI. Artificial intelligence (AI) has the potential to live up to its promise of mimicking the perception, reasoning, learning, and problem solving of the human mind (Exhibit 1). In this evolution, insurance will shift from its current state of “detect and repair” to “predict and prevent,” transforming every aspect of the industry in the process.

Today’s robots are not only working faster and more reliably than their human counterparts but also performing tasks beyond human capability altogether, such as microscopically precise assembly. But many of those robots are dumber than they look. That is, they may be more dexterous than humans, but they are programmed to perform a limited range of tasks. Many robots can’t safely work in close proximity to humans and literally have to be caged or regulated in ways that safeguard human coworkers.

Artificial intelligence (AI) is just now finding its niche in manufacturing, as the technology matures and costs drop—and as manufacturers discover applications for which AI algorithms can make complex decisions. And as it becomes ubiquitous, the future of artificial intelligence in manufacturing is already becoming feasible in emerging markets; showcasing better sensory capabilities; and, off the factory floor, predicting what will be needed and when.

1. The Rise of AI in New Manufacturing Markets

In manufacturing, capital investments are high and profit margins are often thin. Those conditions helped to drive a lot of manufacturing to low-wage countries, where the human-resource costs have been so low that the capital investment in AI and related automation was hard to justify. But rising living standards and wages in places like India have made AI an easier sell. In fact, China is already making significant investments in AI for manufacturing and e-commerce.

And just as US workers have lamented loss of jobs to automation, the same is now happening in Chinese factories. Although many workers will be replaced by robots in the short term, the end game will be to retrain those workers to perform higher-level design, programming, or maintenance tasks. The real driver, however, will be to develop applications for AI in manufacturing that don’t just automate tasks, but make entirely new business processes feasible—for example, custom configuration of products to individual customer requirements.

2. Better Machine Senses Mean Safer Workplaces

AI has its roots in the 1950s but only found broad acceptance with the development of machine-learning algorithms that could be loosed on a body of data to discover meaningful patterns—without deliberate programming. “Without flexible algorithms, computers can only do what we tell them,” says Michael Mendelson, a curriculum developer at the NVIDIA Deep Learning Institute. “Many tasks, especially those involving perception, can’t be translated into rule-based instructions. In a manufacturing context, some of the more immediately interesting applications will involve perception.” This would make factory robots more capable and better able to interact with—and take instructions from—humans.

Machine vision is one of these applications. Devising cameras many times more sensitive than the human eye has been the easy part. What AI adds is the increasingly useful ability to make sense of the images. Landing.ai, a startup formed by Silicon Valley veteran Andrew Ng, focuses on manufacturing problems such as precise quality analysis. It has developed machine-vision tools to find microscopic defects in products such as circuit boards at resolutions well beyond human vision, using a machine-learning algorithm trained on remarkably small volumes of sample images.

That’s a microlevel challenge. A macrolevel problem is training a robot to sense what is going on around it so that it can avoid disruptions or danger. This is analogous to the self-driving-vehicle problem, which is nearing real-world adoption. There is a likely role in factories for smart, self-driving forklifts and conveyors to move materials and finished goods around.

Robots often are stationary but are still at risk of crashing into things, or people, wandering into their workspaces. Machine vision or motion sensors can cause robots to stop what they are doing if there is a potential obstruction. But there is increasing demand for truly collaborative robots—“cobots”—that can work productively with human colleagues. AI is enabling them to take instructions from humans, including novel instructions not anticipated in the robot’s original programming. For this, robots and humans need a common language, which could increasingly be plain speech. This concept already has been demonstrated at the University of Rochester and at MIT.

“As humans, we’ve got millennia of practice explaining things to each other verbally while written word is a much newer, and often clunkier, technology,” Mendelson says. “Talking to robots allows us to communicate concepts that we might not be able to as clearly with text.”

3. AI In the Manufacturing Supply Chain—and Beyond

AI certainly is making robots more capable and easier for humans to collaborate with. But it will have an impact in areas that have nothing to do with robotics. In the supply chain, for example, algorithms can perceive patterns of demand for products across time, geographic markets, and socioeconomic segments while accounting for macroeconomic cycles, political developments, and even weather patterns. The output can be a projection of market demand, which in turn could drive raw material sourcing, human staffing, financing decisions, inventory, maintenance of equipment, and energy consumption.

In manufacturing, AI is also increasingly important in predictive maintenance for equipment, with sensors tracking operating conditions and performance of factory tooling, learning to predict breakdowns and malfunctions, and taking or recommending preemptive actions. “In other industries, this is already straightforward,” says Som Shahapurkar, director of machine learning at FICO, which has been commercializing AI for more than 40 years. “The application has spread across domains, from generating sophisticated consumer email alerts to automobile owners to failure prediction in ‘blades’ in server farms at Facebook and Google.”

Much of the data will come from sensors embedded in the processing equipment not only at the factory but also at suppliers’ facilities, tracking parts inventories and other front-end inputs and monitoring product-quality issues at distributor locations or retail outlets.

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AI can, in fact, provide clues to help manufacturers predict demand before they build products to fill the pipeline. In 2010, informatics professor Johan Bollen and colleagues at Indiana University demonstrated that algorithms could read and interpret sentiment in Twitter feeds precisely enough to accurately predict stock-market movements. Similar sentiment analyses could be used to project demand for products or even specific brands, Bollen says, especially now that consumers are transmitting their sentiments daily by chatting with household AI assistants from Google and Amazon. Much of Bollen’s recent work has been focused on social-media influence on political opinions, but he has studied consumer behavior, as well.

Still, AI’s proponents assert that the technology is only an evolutionary form of automation, an inevitable outcome of the Fourth Industrial Revolution. In the future, AI may be effective at making things, making them better, and making them cheaper. But there is no substitute for human ingenuity in dealing with the unexpected changes in tastes and demands—or in deciding whether to make things at all.

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1. Objective

In this article, we will study the future of Artificial Intelligence to learn the scope and career opportunities of AI in real industry. We will start with AI introduction, AI applications, examples, AI careers, and job profiles in AI. Moreover, will see practical examples for better understanding.

2. Introduction to Artificial Intelligence

“The science and engineering of making intelligent machines, especially intelligent computer programs.”

Intelligence distinguishes us from everything in the world, as we have the ability to understand and apply knowledge. We can also improve skills that play a significant role in our evolution.

We can define Artificial Intelligence as an area of computer science. Further, they deal with the ways in which computers can be made. They are made to perform cognitive functions ascribed to humans.

3. Benefits of Artificial Intelligence

a. Error Reduction

We use artificial intelligence in most cases as this helps us in reducing risks. Also, it increases the chance of reaching accuracy with the greater degree of precision.

b. Difficult Exploration

In mining and other fuel exploration processes, we use artificial intelligence and the science of robotics. Moreover, we use complex machines for exploring the ocean. Hence, overcoming the ocean limitation.

4. Risks of Artificial Intelligence

a. High Costs

Its creation requires huge costs as they are very complex machines. Also, repair and maintenance require huge costs.

b. No Replicating Humans

Intelligence is believed to be a gift of nature, and an ethical argument will continue on whether the human intelligence is to be replicated or not.

5. Artificial Intelligence Applications and Examples

a. Virtual Personal Assistants

In this, a huge amount of data is collected from a variety of sources to learn about users. Also, one needs to be more effective in helping them organize and track their information.

b. Video Games

Basically, we have used AI since the very first video games.

c. Siri

Machine Learning technology is used by Siri users. Also, they use it to get understand natural language questions and requests.

d. Tesla

Tesla is something you are missing if you are a car geek. Also, this is one of the best automobiles available until now.

Preparing For The Future Of Artificial Intellige…

6. Educational Requirements for Careers in Artificial Intelligence

• Various levels of math, including probability, statistics, algebra, calculus, logic, and algorithms.
• Bayesian networking or graphical modeling, including neural nets.
• Physics, engineering, and robotics.
• Computer science, programming languages, and coding.
• Cognitive science theory.

7. Artificial Intelligence Career Domains

A career in this can be realized within a variety of settings including:

• private companies
• public organizations
• education
• the arts
• healthcare facilities
• government agencies and
• the military.

8. Roles in AI Career

• Software analysts and developers.
• Computer scientists and computer engineers.
• Algorithm specialists.
• Research scientists and engineering consultants.
• Mechanical engineers and maintenance technicians.
• Manufacturing and electrical engineers.
• Surgical technicians working with robotic tools.
• Military and aviation electricians working with flight simulators, drones, and armaments.

9. Future of Artificial Intelligence

Artificial Intelligence is used by one another after the company for its benefits. Also, it’s a fact that artificial intelligence is reached in our day-to-day life at breakneck speed.

On the basis of this information arises a new question:

Is it possible that artificial Intelligence outperforms human performance?

If yes, then does it happen and how much does it take?

Only when Artificial Intelligence is able to do a job better than humans.

According to the Survey Results:

Machines are predicted to be better than humans in translating languages, running a truck, working in the retail sector, and can completely outperform humans by 2060.

As a result, MI researchers believe that AI will become better than humans in the next 40-year time frame.

• To build AI smarter, companies have already acquired around 34 AI startups. It was acquired in the first quarter of 2017. These companies are reinforcing their leads in the world of artificial intelligence.
• In every sphere of life, AI is present. We use AI to organize big data into different patterns and structures. Also, patterns help in a neural network, machine learning, and data analytics.
• From the 80s to now, artificial intelligence is now part of our everyday lives, it’s very hard to believe. Moreover, it is becoming more intelligent and accepted every day and there are many opportunities for businesses.

A Few Steps to Ensure the Business Stays Relevant to the AI Revolution:

a. A Finger on the Pulse

Maybe the time is not right for your business to harness the value of AI. However, that doesn’t mean you should stop keeping up like others that are using AI. Reading IT journal trade is a good place to start. Start focusing on how businesses are leveraging AI.

b. Piggyback on the Innovators

To implement AI, there are so many resources present from an industry that will help you.

For example:

Google has developed a machine learning system, TensorFlow. That has been released as an open-source software.

c. Brainstorm Potential Uses With Your Team

Teams must be engaged and encouraging in the areas of business, and AI could be deployed.>d. Start Small and Focus on Creating Real Value

It’s not mandatory to move forward for the sake only. Rather, it’s necessary to focus on objectives and start finding a best solution for it. Moreover, mean finding the specific process to run AI pilot. Also, see how it goes, learn and build from there.

e. Prepare the Ground

Before, to maximize the value of AI, its good to ensure your current process i.e. working in the best possible way.

f. Collaborate

To collaborate with a non-competing business. That is further down the road in terms of programming and enabling AI. AI has the potential to transform businesses. That is how a business moves and takes ups and down.

For Example:

Like movies, where humans stop, machines used to perform, as it requires steps and trials.

g. Cyborg Technology

Basically, it’s the biggest limitation in the human being. i.e its own bodies and brains. Its seen that we will argue with ourselves. As a result, Cyborg technology is added for our convenience. Moreover, this technology reduces the limitations. Also, we will deal with it on a daily basis.

h. Taking Over Dangerous Jobs

In bomb defusing, robots are used to save thousands of lives. They are technically drones. that require humans to control them. Over the years, as technology improves, we will need AI integration to help these machines.

i. Solving Climate Change

This might seem like a tall order from a robot. But one says that:

'Machines have more access to data than one person ever could — storing a mind-boggling number of statistics. We can use big data so that AI could one day identify trends. Also, it comes with the use that information to come up with solutions to the world’s biggest problems.'

10. Jobs in Artificial Intelligence

• Computational philosopher: to ensure human-aligned ethics are embedded in AI algorithms
• Robot personality designer
• Robot obedience trainer
• Autonomous vehicle infrastructure designer: new road and traffic signs to be read by a computer
• Algorithm trainers include the growing army of so-called “click workers.” That helps algorithms learn to recognize images or analyze sentiment, for instance.

11. Conclusion

We have studied the future of Artificial Intelligence and learned the future of Artificial Intelligence from every future perspective. We have also learned practical applications that will help you understand in a better way. Furthermore, if you have any questions, feel free to ask in the comment section.

Future Ai In The Military

Published at DZone with permission of Shailna Patidar . See the original article here.

Future Of Artificial Intelligence Pdf

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