Archive for the ‘Artificial Intelligence’ Category

A.I. Artificial Intelligence (2001) – IMDb

Nominated for 2 Oscars. Another 17 wins & 68 nominations. See more awards Learn more More Like This

Drama | Sci-Fi

Roy Neary, an electric lineman, watches how his quiet and ordinary daily life turns upside down after a close encounter with a UFO.

Director:Steven Spielberg

Stars:Richard Dreyfuss,Franois Truffaut,Teri Garr

Comedy | Drama | Sci-Fi

An android endeavors to become human as he gradually acquires emotions.

Director:Chris Columbus

Stars:Robin Williams,Embeth Davidtz,Sam Neill

Biography | Drama | History

In 1839, the revolt of Mende captives aboard a Spanish owned ship causes a major controversy in the United States when the ship is captured off the coast of Long Island. The courts must decide whether the Mende are slaves or legally free.

Director:Steven Spielberg

Stars:Djimon Hounsou,Matthew McConaughey,Anthony Hopkins

Drama | Mystery | Sci-Fi

Dr. Ellie Arroway, after years of searching, finds conclusive radio proof of extraterrestrial intelligence, sending plans for a mysterious machine.

Director:Robert Zemeckis

Stars:Jodie Foster,Matthew McConaughey,Tom Skerritt

Action | Crime | Mystery

In a future where a special police unit is able to arrest murderers before they commit their crimes, an officer from that unit is himself accused of a future murder.

Director:Steven Spielberg

Stars:Tom Cruise,Colin Farrell,Samantha Morton

Action | Drama | History

Based on the true story of the Black September aftermath, about the five men chosen to eliminate the ones responsible for that fateful day.

Director:Steven Spielberg

Stars:Eric Bana,Daniel Craig,Marie-Jose Croze

Adventure | Sci-Fi | Thriller

As Earth is invaded by alien tripod fighting machines, one family fights for survival in this sci-fi action film.

Director:Steven Spielberg

Stars:Tom Cruise,Dakota Fanning,Tim Robbins

Action | Drama | History

A young English boy struggles to survive under Japanese occupation during World War II.

Director:Steven Spielberg

Stars:Christian Bale,John Malkovich,Miranda Richardson

Drama

A black Southern woman struggles to find her identity after suffering abuse from her father and others over four decades.

Director:Steven Spielberg

Stars:Danny Glover,Whoopi Goldberg,Oprah Winfrey

Action | Adventure | Drama

Young Albert enlists to serve in World War I after his beloved horse is sold to the cavalry. Albert's hopeful journey takes him out of England and to the front lines as the war rages on.

Director:Steven Spielberg

Stars:Jeremy Irvine,Emily Watson,David Thewlis

Drama | Sci-Fi | Thriller

A genetically inferior man assumes the identity of a superior one in order to pursue his lifelong dream of space travel.

Director:Andrew Niccol

Stars:Ethan Hawke,Uma Thurman,Jude Law

Comedy | Drama | Romance

An Eastern European tourist unexpectedly finds himself stranded in JFK airport, and must take up temporary residence there.

Director:Steven Spielberg

Stars:Tom Hanks,Catherine Zeta-Jones,Chi McBride

In the not-so-far future the polar ice caps have melted and the resulting rise of the ocean waters has drowned all the coastal cities of the world. Withdrawn to the interior of the continents, the human race keeps advancing, reaching the point of creating realistic robots (called mechas) to serve them. One of the mecha-producing companies builds David, an artificial kid which is the first to have real feelings, especially a never-ending love for his "mother", Monica. Monica is the woman who adopted him as a substitute for her real son, who remains in cryo-stasis, stricken by an incurable disease. David is living happily with Monica and her husband, but when their real son returns home after a cure is discovered, his life changes dramatically. Written byChris Makrozahopoulos

Budget:$100,000,000 (estimated)

Opening Weekend USA: $29,352,630,1 July 2001

Gross USA: $78,616,689

Cumulative Worldwide Gross: $235,926,552

Runtime: 146 min

Aspect Ratio: 1.85 : 1

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A.I. Artificial Intelligence (2001) - IMDb

Artificial Intelligence in Human Resource Management

While, in the past, artificial intelligence may have been thought to be a product of science fiction, most professionals today understand that the adoption of smart technology is actively changing workplaces. There are applications of AI throughout nearly every profession and industry, and human resources careers are no exception.

A recent survey conducted by Oracle and Future Workplace found that human resources professionals believe AI can present opportunities for mastering new skills and gaining more free time, allowing HR professionals to expand their current roles in order to be more strategic within their organization.

Among HR leaders who participated in the survey, however, 81 percent said that they find it challenging to keep up with the pace of technological changes at work. As such, it is more important now than ever before for human resources professionals to understand the ways in which AI is reshaping the industry.

Read on to explore what artificial intelligence entails, how it is applied to the world of human resources management, and how HR professionals can prepare for the future of the field today.

At a high level, artificial intelligence (AI) is a technology that allows computers to learn from and make or recommend actions based on previously collected data. In terms of human resources management, artificial intelligence can be applied in many different ways to streamline processes and improve efficiency.

Uwe Hohgrawe, lead faculty for Northeasterns Master of Professional Studies in Analytics program explains that we as humans see the information in front of us and use our intelligence to draw conclusions. Machines are not intelligent, but we can make them appear intelligent by feeding them the right information and technology.

Learn More: AI & Other Trends Defining the HRM Industry

While organizations are adopting AI into their human resources processes at varying rates, it is clear to see that the technology will have a lasting impact on the field as it becomes more widely accepted. For this reason, it is important that HR professionals prepare themselves for these changes by understanding what the technology is and how it is applied across various functions.

Learn more about earning an advanced degree in Human Resources Management

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Among the numerous applications of AI in the human resources sector, some of the first changes HR professionals should expect to see involve recruitment and onboarding, employee experience, process improvement, and the automation of administrative tasks.

While many organizations are already beginning to integrate AI technology into their recruiting efforts, the vast majority of organizations are not. In fact, Deloittes 2019 Global Human Capital Trends survey found that only 6 percent of respondents believed that they had the best-in-class recruitment processes in technology, while 81 percent believed their organizations processes were standard or below standard. For this reason, there are tremendous opportunities for professionals to adapt their processes and reap the benefits of using this advanced technology.

During the recruitment process, AI can be used to the benefit of not only the hiring organization but its job applicants, as well. For example, AI technology can streamline application processes by designing more user-friendly forms that a job applicant is more likely to complete, effectively reducing the number of abandoned applications.

While this approach has made the role of the human resources department in recruitment much easier, artificial intelligence also allows for simpler and more meaningful applications on the candidates end, which has been shown to improve application completion rates.

Additionally, AI has played an important role in candidate rediscovery. By maintaining a database of past applicants, AI technology can analyze the existing pool of applicants and identify those that would be a good fit for new roles as they open up. Rather than expending time and resources searching for fresh talent, HR professionals can use this technology to identify qualified employees more quickly and easily than ever before.

Once hiring managers have found the best fit for their open positions, the onboarding process begins. With the help of AI, this process doesnt have to be restricted to standard business hoursa huge improvement over onboarding processes of the past.

Instead, AI technology allows new hires to utilize human resources support at any time of day and in any location through the use of chatbots and remote support applications. This change not only provides employees with the ability to go through the onboarding process at their own pace, but also reduces the administrative burden and typically results in faster integration.

In addition to improvements to the recruitment process, HR professionals can also utilize artificial intelligence to boost internal mobility and employee retention.

Through personalized feedback surveys and employee recognition systems, human resources departments can gauge employee engagement and job satisfaction more accurately today than ever before. This is incredibly beneficial considering how important it is to understand the overall needs of employees, however there are several key organizational benefits to having this information, as well.

According to a recent report from the Human Resources Professional Association, some AI software can evaluate key indicators of employee success in order to identify those that should be promoted, thus driving internal mobility. Doing so has the potential to significantly reduce talent acquisition costs and bolster employee retention rates.

This technology is not limited to identifying opportunities to promote from within, however; it can also predict who on a team is most likely to quit. Having this knowledge as soon as possible allows HR professionals to deploy retention efforts before its too late, which can strategically reduce employee attrition.

One of the key benefits of leveraging artificial intelligence in various human resources processes is actually the same as it is in other disciplines and industries: Automating low value, easily repeatable administrative tasks gives HR professionals more time to contribute to strategic planning at the organizational level. This, in turn, enables the HR department to become a strategic business partner within their organizations.

Smart technologies can automate processes such as the administration of benefits, pre-screening candidates, scheduling interviews, and more. Although each of these functions is important to the overall success of an organization, carrying out the tasks involved in such processes is generally time-consuming, and the burden of these duties often means that HR professionals have less time to contribute to serving their employees in more impactful ways.

Deploying AI software to automate administrative tasks can ease this burden. For instance, a study by Eightfold found that HR personnel who utilized AI software performed administrative tasks 19 percent more effectively than departments that do not use such technology. With the time that is saved, HR professionals can devote more energy to strategic planning at the organizational level.

While it is clear that artificial intelligence will continue to positively shape the field of human resources management in the coming years, HR professionals should also be aware of the challenges that they might face.

The most common concerns that HR leaders have focus primarily on making AI simpler and safer to use. In fact, the most common factor preventing people from using AI at work are security and privacy concerns. Additionally, 31 percent of respondents in Oracles survey expressed that they would rather interact with a human in the workplace than a machine. Moving forward, HR professionals will need to be prepared to address these concerns by staying on top of trends and technology as they evolve and change.

People will need to be aware of ethical and privacy questions when using this technology, Hohgrowe says. In human resources, [AI] can involve using sensitive information to create sensitive insights.

For instance, employees want their organizations to respect their personal data and ask for permission before using such technology to gather information about them. However organizations also want to feel protected from data breaches, and HR professionals must take the appropriate security measures into account.

To prepare for the future of human resources management, professionals should take the necessary steps to learn about current trends in the field, as well as lay a strong foundation of HR knowledge that they can build upon as the profession evolves.

Staying up to date with industry publications and networking with leaders in the field is a great way to stay abreast of current trends like the rapid adoption of artificial intelligence technologies. Building your foundational knowledge of key human resource management theories, strategy, and ethics, on the other hand, is best achieved through higher education.

Although there are many certifications and courses available that focus on specific HR topics, earning an advanced degree like a Master of Science in Human Resources Management provides students with a more holistic approach to understanding the connection between an organization and its people.

At Northeastern, we highlight the importance of three literacies: data literacy, technological literacy, and humanic literacy. That combination is one of the areas where I believe we will pave the way in the future, Hohgrawe says. This also allows us to explore augmented artificial intelligence in a way that appreciates the relationship between human, machine, and data.

Students looking to specialize in AI also have the opportunity to declare a concentration in artificial intelligence within Northeasterns human resource management program. Those who specialize in this specific aspect of the industry will study topics such as human resources information processing, advanced analytical utilization, and AI communication and visualization. Similarly, those who seek a more technical masters degree might consider a Northeasterns Master of Professional Studies in Enterprise Intelligence, which also includes a concentration in AI for human resources.

No matter each students specific path, however, those who choose to study at Northeastern will have the unique chance to learn from practitioners with advanced knowledge and experience in the field. Many of Northeasterns faculty have previously or are currently working in the human resources management field, enabling them to bring a unique perspective to the classroom and educate students on the real-world challenges that HR professionals face today.

Between the world-class faculty members and the multitude of experiential learning opportunities provided during the pursuit of a masters degree, aspiring HR professionals will graduate from Northeasterns program with the unique combination of experience and expertise needed to land a lucrative role in this growing field.

Interested in advancing your career in HR? Explore Northeasterns Master of Science in Human Resources Management program and consider taking the next step toward a career in this in-demand industry.

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Artificial Intelligence in Human Resource Management

What is AI? Artificial Intelligence Tutorial for Beginners

What is AI?

A machine with the ability to perform cognitive functions such as perceiving, learning, reasoning and solve problems are deemed to hold an artificial intelligence.

Artificial intelligence exists when a machine has cognitive ability. The benchmark for AI is the human level concerning reasoning, speech, and vision.

In this basic tutorial, you will learn-

Nowadays, AI is used in almost all industries, giving a technological edge to all companies integrating AI at scale. According to McKinsey, AI has the potential to create 600 billions of dollars of value in retail, bring 50 percent more incremental value in banking compared with other analytics techniques. In transport and logistic, the potential revenue jump is 89 percent more.

Concretely, if an organization uses AI for its marketing team, it can automate mundane and repetitive tasks, allowing the sales representative to focus on tasks like relationship building, lead nurturing, etc. A company name Gong provides a conversation intelligence service. Each time a Sales Representative make a phone call, the machine records transcribes and analyzes the chat. The VP can use AI analytics and recommendation to formulate a winning strategy.

In a nutshell, AI provides a cutting-edge technology to deal with complex data which is impossible to handle by a human being. AI automates redundant jobs allowing a worker to focus on the high level, value-added tasks. When AI is implemented at scale, it leads to cost reduction and revenue increase.

Artificial intelligence is a buzzword today, although this term is not new. In 1956, a group of avant-garde experts from different backgrounds decided to organize a summer research project on AI. Four bright minds led the project; John McCarthy (Dartmouth College), Marvin Minsky (Harvard University), Nathaniel Rochester (IBM), and Claude Shannon (Bell Telephone Laboratories).

The primary purpose of the research project was to tackle "every aspect of learning or any other feature of intelligence that can in principle be so precisely described, that a machine can be made to simulate it."

The proposal of the summits included

It led to the idea that intelligent computers can be created. A new era began, full of hope - Artificial intelligence.

Artificial intelligence can be divided into three subfields:

Machine learning is the art of study of algorithms that learn from examples and experiences.

Machine learning is based on the idea that there exist some patterns in the data that were identified and used for future predictions.

The difference from hardcoding rules is that the machine learns on its own to find such rules.

Deep learning is a sub-field of machine learning. Deep learning does not mean the machine learns more in-depth knowledge; it means the machine uses different layers to learn from the data. The depth of the model is represented by the number of layers in the model. For instance, Google LeNet model for image recognition counts 22 layers.

In deep learning, the learning phase is done through a neural network. A neural network is an architecture where the layers are stacked on top of each other.

Most of our smartphone, daily device or even the internet uses Artificial intelligence. Very often, AI and machine learning are used interchangeably by big companies that want to announce their latest innovation. However, Machine learning and AI are different in some ways.

AI- artificial intelligence- is the science of training machines to perform human tasks. The term was invented in the 1950s when scientists began exploring how computers could solve problems on their own.

Artificial Intelligence is a computer that is given human-like properties. Take our brain; it works effortlessly and seamlessly to calculate the world around us. Artificial Intelligence is the concept that a computer can do the same. It can be said that AI is the large science that mimics human aptitudes.

Machine learning is a distinct subset of AI that trains a machine how to learn. Machine learning models look for patterns in data and try to conclude. In a nutshell, the machine does not need to be explicitly programmed by people. The programmers give some examples, and the computer is going to learn what to do from those samples.

AI has broad applications-

AI is used in all the industries, from marketing to supply chain, finance, food-processing sector. According to a McKinsey survey, financial services and high tech communication are leading the AI fields.

A neural network has been out since the nineties with the seminal paper of Yann LeCun. However, it started to become famous around the year 2012. Explained by three critical factors for its popularity are:

Machine learning is an experimental field, meaning it needs to have data to test new ideas or approaches. With the boom of the internet, data became more easily accessible. Besides, giant companies like NVIDIA and AMD have developed high-performance graphics chips for the gaming market.

Hardware

In the last twenty years, the power of the CPU has exploded, allowing the user to train a small deep-learning model on any laptop. However, to process a deep-learning model for computer vision or deep learning, you need a more powerful machine. Thanks to the investment of NVIDIA and AMD, a new generation of GPU (graphical processing unit) are available. These chips allow parallel computations. It means the machine can separate the computations over several GPU to speed up the calculations.

For instance, with an NVIDIA TITAN X, it takes two days to train a model called ImageNet against weeks for a traditional CPU. Besides, big companies use clusters of GPU to train deep learning model with the NVIDIA Tesla K80 because it helps to reduce the data center cost and provide better performances.

Data

Deep learning is the structure of the model, and the data is the fluid to make it alive. Data powers the artificial intelligence. Without data, nothing can be done. Latest Technologies have pushed the boundaries of data storage. It is easier than ever to store a high amount of data in a data center.

Internet revolution makes data collection and distribution available to feed machine learning algorithm. If you are familiar with Flickr, Instagram or any other app with images, you can guess their AI potential. There are millions of pictures with tags available on these websites. Those pictures can be used to train a neural network model to recognize an object on the picture without the need to manually collect and label the data.

Artificial Intelligence combined with data is the new gold. Data is a unique competitive advantage that no firm should neglect. AI provides the best answers from your data. When all the firms can have the same technologies, the one with data will have a competitive advantage over the other. To give an idea, the world creates about 2.2 exabytes, or 2.2 billion gigabytes, every day.

A company needs exceptionally diverse data sources to be able to find the patterns and learn and in a substantial volume.

Algorithm

Hardware is more powerful than ever, data is easily accessible, but one thing that makes the neural network more reliable is the development of more accurate algorithms. Primary neural networks are a simple multiplication matrix without in-depth statistical properties. Since 2010, remarkable discoveries have been made to improve the neural network

Artificial intelligence uses a progressive learning algorithm to let the data do the programming. It means, the computer can teach itself how to perform different tasks, like finding anomalies, become a chatbot.

Summary

Artificial intelligence and machine learning are two confusing terms. Artificial intelligence is the science of training machine to imitate or reproduce human task. A scientist can use different methods to train a machine. At the beginning of the AI's ages, programmers wrote hard-coded programs, that is, type every logical possibility the machine can face and how to respond. When a system grows complex, it becomes difficult to manage the rules. To overcome this issue, the machine can use data to learn how to take care of all the situations from a given environment.

The most important features to have a powerful AI is to have enough data with considerable heterogeneity. For example, a machine can learn different languages as long as it has enough words to learn from.

AI is the new cutting-edge technology. Ventures capitalist are investing billions of dollars in startups or AI project. McKinsey estimates AI can boost every industry by at least a double-digit growth rate.

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What is AI? Artificial Intelligence Tutorial for Beginners

What Skills Do I Need to Get a Job in Artificial Intelligence?

Automation, robotics and the use of sophisticated computer software and programs characterize a career in artificial intelligence (AI). Candidates interested in pursuing jobs in this field require specific education based on foundations of math, technology, logic, and engineering perspectives. Written and verbal communication skills are also important to convey how AI tools and services are effectively employed within industry settings. To acquire these skills, those with an interest in an AI career should investigate the various career choices available within the field.

The most successful AI professionals often share common characteristics that enable them to succeed and advance in their careers. Working with artificial intelligence requires an analytical thought process and the ability to solve problems with cost-effective, efficient solutions. It also requires foresight about technological innovations that translate to state-of-the-art programs that allow businesses to remain competitive. Additionally, AI specialists need technical skills to design, maintain and repair technology and software programs. Finally, AI professionals must learn how to translate highly technical information in ways that others can understand in order to carry out their jobs. This requires good communication and the ability to work with colleagues on a team.

Basic computer technology and math backgrounds form the backbone of most artificial intelligence programs. Entry level positions require at least a bachelors degree while positions entailing supervision, leadership or administrative roles frequently require masters or doctoral degrees. Typical coursework involves study of:

Candidates can find degree programs that offer specific majors in AI or pursue an AI specialization from within majors such as computer science, health informatics, graphic design, information technology or engineering.

A career in artificial intelligence can be realized within a variety of settings including private companies, public organizations, education, the arts, healthcare facilities, government agencies and the military. Some positions may require security clearance prior to hiring depending on the sensitivity of information employees may be expected to handle. Examples of specific jobs held by AI professionals include:

From its inception in the 1950s through the present day, artificial intelligence continues to advance and improve the quality of life across multiple industry settings. As a result, those with the skills to translate digital bits of information into meaningful human experiences will find a career in artificial intelligence to be sustaining and rewarding.

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What Skills Do I Need to Get a Job in Artificial Intelligence?

Artificial Intelligence Graduate Certificate | Stanford Online

Overview

"Artificial intelligence is the new electricity."

- Andrew Ng, Stanford Adjunct Professor

Take advantage of the opportunity to virtually step into the classrooms of Stanford professors like Andrew Ng who are leading the Artificial Intelligence revolution.

Classes in the Artificial Intelligence Graduate Certificate provide the foundation and advanced skills in the principles and technologies that underlie AI including logic, knowledge representation, probabilistic models, and machine learning. Students can pursue topics in depth, with courses available in areas such as robotics, vision, and natural language processing.

Prepare for advanced Artificial Intelligence curriculum and earn graduate credit by taking these recommended courses; these courses willnot count towards the Artificial Intelligence graduate certificate. We highly recommend taking CS109 Introduction to Probability for Computer Scientists, or STATS116 Theory of Probability.

The certificate is designed to be completed in nine months, but you may take up to three years to complete it. Courses are available during Autumn, Winter, and Spring quarters:

Note: Course offerings may be subject to change. You do not need to enroll in the certificate to take the courses. You may enroll in any courses if you meet its prerequisites.

Software engineers interested in artificial intelligence. The fast-paced, academically rigorous classes that are part of this certificate are appropriate for applicants who can demonstrate mastery of the prerequisite subject matter including statistics and probability, linear algebra and calculus. Students should also have significant programming experience in Java, C++, Python or similar languages.

As demand for AI courses is high and seats are limited, applications are subject to additional review. Applicants will be notified once the application review process is complete and a decision has been made.

To pursue a graduate certificate you need to apply.

Tuition is based on the number of units you take. See Graduate Course Tuition on our Tuition & Fees page for more information.

1-2 years average3 years maximum to complete

Submit an inquiry to receive more information.

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Artificial Intelligence Graduate Certificate | Stanford Online