Category Archives: Artificial Intelligence

Artificial Intelligence, commonly abbreviated as AI, has a popular connotation within Scratch relating to a computerized mind that consists entirely of programming code.

Its usage in Scratch, albeit somewhat misleading, is most common in projects in which a user can play a game against the computer.

Most projects that use AI use special techniques, such as using variables to store different values. Those values may be previous locations, user input, and so on. They help to calculate different actions that allow the computer to make a good challenge to the player and succeed in its task.

A practical and optimal AI system will use recursion[citation needed] to try to adapt to the circumstances itself. Given (for a game):

A recursive function to return the best move for a player given a board and which player can be written under the following logic:

See the article on game trees for more on recursive functions and their use in constructing AI.

There is also another class of AI that depends solely upon only one of the factors. Such AI are a lot simpler and, in many cases, effective. However, they have not fulfilled the true requirements of an AI. For example, in the project Agent White, the AI moves along a given path and only tries to shoot at you. In this AI, only the user's position matters to the AI; it will rotate so that its gun turns towards the user. In the project Broomsticks, the AI only changes its position with respect to the ball.

AI which can take external stimulus and decide upon the best way to use it is called a learning AI, or an AI that uses something called machine learning. Neural networks are also commonly used for learning AIs. A learning AI is able to learn off of its present and past experiences. One popular way of making a learning AI is by using a neural network. Another is by making a list of things and creating a list of things for every reply (which can be done in Scratch, although with some difficulty as 2D arrays are not easily implemented).

Another type of AI is used in a remix of Agent White found here. In this remix, the AI picks a random path and follows it. It uses Math and future x and y positions based on the current position of a character which you control. Then it slowly moves toward that new position until it either reaches its destination or hits a wall. In this case, instead of Artificial Intelligence, it is more of Artificial Random because it never uses intelligence other than running into walls.

One of the biggest limitations AI has been facing is speed. Scratch is a rather slow programming language; hence most AIs on Scratch are slow because their scripts are too long.

Complications also have been a major problem for AI as all AI programs are very large and complicated, thus the scripts may become long and too laggy to make without crashing Scratch. For example, a simple game of Tic-Tac-Toe with AI will have a script running into multiple pages due to many conditions in if blocks, and sometimes an attempt to speed it up will be made by making it Single Frame.

The complicated script also makes remixing a problem. Because of all this, most AI projects have no improvements, causing the AI to remain glitchy. AIs may make mistakes that are easily avoidable by users, and most mistakes like these are hilariously known as artificial stupidity.

These projects have been using AI in the truest sense possible practically:

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Artificial Intelligence - Scratch Wiki

For the last 70 years science fiction writers and Hollywood movie directors have explored the place of robots and artificial intelligence (AI) in the future of humankind. But automated technologies with greater than human intelligence were first conceptualized in the imaginations of people in ancient societies and were woven into their folkloric systems, according to a highly-original new book.

TitledGods and Robots: Myths, Machines, and Ancient Dreams of Technology , the author, Dr Adrienne Mayor of Stanford University is, according to the university website, an independent folklorist/historian of science investigating natural knowledge contained in pre-scientific myths and oral traditions. In a nutshell, Dr Mayor can be described as a force of mythological and folkloric understanding and her previous works have been featured on NPR, BBC, History Channel, Smithsonian and National Geographic. Now, this new book offers readers comparisons between the legendary figures of ancient myths and the AI driven robots of today which are building tomorrows world.

Vulcan (Hephaestus). Engraving by E. Jeaurat, 1716. ( CC BY 4.0 )

While the corridors of universities and academic institutions are teaming with thousands of professors skilled with powerful oratory abilities in classic teaching environments, Dr Mayor has a quality that must be a thing of great envy with her peer group, that rare skill of original storytelling in written academic form. Not only does her book carefully analyze classic myths in an easy to digest way for the lay-reader, but all the way her methodology and observational stances adhere to the scientific method of investigation. However, where so many academic writers deliver dry base facts and figures with no context in the real world, Dr Mayor subtly prompts readers to project the archetypal messages in timeworn stories into our modern zeitgeist, as we build a new world with AI at the fore.

Medeia and Talus by Sybil Tawse. ( Public Domain )

According to a report about the new book in The Daily Mail , Dr Mayor said ancient people envisioned many of the technology trends we grapple with today including killer androids, driverless technology, GPS and AI-powered helper robots. Illustrating her hypothesis, the creations of Hephaestus, the god of metalworking and an invention in Homers Iliad , were predictions of the rise of humanoid robots. An article about Mayors research in Greek Reporter said AI-powered helper robots andkiller androids, according to Dr Mayor, appear in tales about Jason and the Argonauts, Medea, Daedalus and Prometheus and also the 'bronze killer-robot' Taloswho guarded the island of Crete. Furthermore, the legendary Pandora, who Dr Mayor describes as a 'wicked AI fembot like the replicant in the blockbuster movie Blade Runner, had been programmed to release eternal suffering upon humanity and Though the Greeks did not know how technology would work, they could foreshadow its rise in society, said Mayor.

Pandora trying to close the box that she had opened out of curiosity. ( Public Domain )

A book review on Science Mag , by Sarah Olson, softly criticized Dr Mayor saying Despite her extensive knowledge of ancient mythology, Mayor does little to demonstrate an understanding of modern AI, neural networks, and machine learning; the chatbots are among only a handful of examples of modern technology she explores. While Olsons observation is valid, looking at it another way, isnt this actually a veiled credit to the author? So often modern authors, especially scientific writers, speculate into complicated fields with their core understanding which dilutes the heart of their research. Contrary to this, it would appear Dr Mayor realized her speculations into future technologies including AI would only ever be speculations and rather than opening herself up to the scathing reviews of silicone valley tech geeks, she loyally focused her research on her specialist subject, which is quite clearly classical mythology.

The Science Mag article also criticized Mayor for not having added a few sentences to explain the difference between, say, machine learning and AI, which the reviewer claims makes it difficult for readers to identify the books intended audience. Again, this is possibly another credit to the author. Heres why. In our hyper-commercialized world seldom do authors write honest books simply because they believe a story needs to be written. Because Dr Mayor's book was not written for a defined audience it will be remembered as a brave scientific sentinel that will undoubtedly find or make its readership, organically, over time.

When you read this book, the ultimate takeaway is that the observations are un-skewed and non-sensationalized, neither are they dumbed down to fit into a publishers or predetermined audience. And when a book delivers more suggestions and questions than answers, like this one, it immediately becomes a refreshingly non-egotistical trip through classic mythology. What is more, the author has left sufficient space for readers to indulge in their own ideas and conclusions based on their understanding of technology. Thus, what has actually been published is more than a book, and the work marks a new generation of psychologically interactive mythological learning. You finish the story Dr Mayor began.

An article about Dr Mayors book on News said the author is urging leading tech bosses to closely analyze the stories and characters of Greek mythology as we close in on a future dominated by automated technologies. Gods and Robots offers optimistic insights with cautionary twists while warning of the potential risks of uncontrolled future technologies, and it is clear that Dr Mayor believes herself that AI might one day deliver the mythological worlds our ancient ancestors imagined and immortalized in their folk stories.

Top image: Was artificial intelligence predicted by the Greeks? Source: pict rider via Fotolia

By Ashley Cowie

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High-Technology Discovered in Classical Mythology Reveals ...

MUMBAI | NEW DELHI: Artificial intelligence (AI) is the buzz in the jobs bazaar as machine learning and the Internet of Things (IoT) increasingly influence business strategies and analytics. Human resource and search experts estimate a 50-60% higher demand for AI and robotics professionals in 2018 even as machines take over repetitive manual work.

Machines are taking over repetitive tasks. Robotics, AI, big data and analytics will be competencies that will be in great demand, said Shakun Khanna, senior director at Oracle for the Asia-Pacific region.

Organisations are being pushed to become even more efficient as jobs turn predictable, said Rishabh Kaul, cofounder of recruitment startup Belong, which helps clients search for and hire AI professionals. There is a significant increase in the adoption of AI and automation across enterprises, leading to a skyrocketing of demand for professionals in these fields, he said.

Jobs in the IoT ecosystem, have grown fourfold in the last three years, according to estimates by Belong. These are related to engagement technologies and data capture among other areas. Demand for professionals in the realm of data analysis, including data scientists, have grown by almost 76% in the past few years in AI.

The demand is at the entry level as well as middle to senior ranks across sectors such as business, financial services and insurance (BFSI), ecommerce, startups, business process outsourcing (BPO), information technology (IT), pharmaceuticals, healthcare and retail. Robotics is required by process-oriented companies for a better customer experience. It helps in cutting down cost and improves efficiency, said Thammaiah BN, managing director, Kelly Services India.

AI is helping companies to be in spaces so far not thought of. Organisations can accomplish new things, new products and services through AI.

Companies want to mine the data they have accumulated over the years, said Sinosh Panicker, partner, Hunt Partners. AI helps them predict and position their products better and push out new things, he said. However, theres an acute demand-supply mismatch for AI talent across industries, experts said. Candidates for AI roles related to natural language processing (NLP), deep learning, and machine learning are thin on the ground, according to the Belong Talent Supply Index. The ratio of the number of people to jobs in deep learning is 0.53, while for machine learning its 0.63 and for NLP its 0.71.

Only 4% of AI professionals in India have worked on cutting-edge technologies such as deep learning and neural networks, the key ingredients in building advanced AI-related solutions, said Kaul.

Roles in data science and data engineering (which are different facets of the AI family of skills) are at the intersection of math, statistics and programming, he said. This isnt typically taught at Indian colleges as part of formal learning.

A few academic institutions such as the Indian Institutes of Technology (IITs) in Kharagpur and Kanpur, the Indian Institute of Information Technology (IIIT) in Hyderabad and the Indian Institute of Science (IISc) in Bengaluru have specialised disciplines or centres for artificial intelligence and machine learning. In fact, according to our internal research, less than 2% of professionals who call themselves data scientists or data engineers have a PhD in AI-related technologies, said Kaul.

Such is the need for talent that it is prompting top business schools, including the Indian Institutes of Management (IIMs), to include AI and machine learning in their curriculum and expose students to the full ecosystem of IoT. The IIMs in Bangalore and Kozhikode and premier B-Schools like the SP Jain Institute of Management & Research (SPJIMR) are offering courses on AI, robotics and IoT that can be connected to business strategy to enhance performance, output and customer experience.

Some are learning skills through various other courses, including online ones. People who are keeping themselves abreast with new age technologies and have the right set of required skills under the same are in high demand, said ABC Consultants director Ratna Gupta.

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Its going to be a Happy New Year for Artificial ...

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Two of the most significant predictions for the new decade are that AI will become more pervasive, and the U.S. health-care system will need to evolve. AI can augment and improve the health-care system to serve more patients with fewer doctors.

However, health innovators need to be careful to design a system that enhances doctors capabilities, rather than replace them with technology and also to avoid reproducing human biases.

A recent study published in Nature (in collaboration with Google) reports that Google AI detects breast cancer better than human doctors. Babylon Health, the AI-based mobile primary care system implemented in the United Kingdom in 2013, is coming to the U.S.

Health-care is an industry in need of AI assistance due to a shortage of doctors and physician burnout.

Doctors in the U.S. are experiencing a burnout crisis. Nearly 45 percent of physicians report burnout, and the physician suicide rate is twice that of the general population. Research shows physicians experience burnout because of a poorly designed health care system that isnt intended to protect them or their patients.

Physician burnout has been linked to increased medical errors, unprofessional behavior, early retirement, depression, and racial bias.

In 2019 the Journal of the American Medical Association published a study of 3,392 second-year resident physicians who self-identified as non-Black and found that symptoms of burnout were associated with explicit and implicit racial biases.

A study from the Mayo clinic reported poorly designed electronic health records as a contributor to physician burnout.

Another major contributor to burnout is a shortage of physicians compared to the increased number and needs of patients that require care. The Association of American Medical Collegespredicts a shortageof 21,100 and 55,200 primary care physicians by 2032.

While a possible solution, AI systems can also cause problems. Increased medical error is a real potential consequence of poorly designed AI in medicine.

Medical error is the third leading cause of death in the U.S., attesting to both the need for improving the system but also the fragility of the system and consequences of poor design.

Eliminating the empathetic relationship is another potential consequence of poorly designed and integrated AI. Health care is built on a human-human link.

Humans desire and benefit from the problem-solving that comes from conversations. In clinics with electronic health records, physicians spend about 27 percent of their time on patient care and 52 percent time in the exam room interacting with the patient.

Replacing humans with technology inappropriately could lead to complacency from physicians and reduced engagement from patients.

AI could lead to new inequities and biases. Recent studies have shown that Black people are less likely to get proper treatment for lung cancer and adequate treatment for pain because of false beliefs about differences between Blacks and whites.

While some may conclude that AI would remove the biases that minorities receive by focusing on objective data, new research identifies inequities in AI systems.

A study published in Science in 2019 found that an algorithm used in U.S. hospitals systematically discriminated against Black patients by allocating less care to them.

Babylons AI-based chatbot sparked concerns as the chatbots safety has been reported; Babylon refutes these claims.

Many of the disruptive aspects of the AI system are unique to the National Health Service, which assigns patients to practitioners. With new funding and support, Babylon will enter the U.S. market. Health safety advocates need to be available to advocate for the unique needs of patients in the American health-care system.

For AI systems to work without harm, a greater understanding of what clinicians do and their current biases is needed. The goal of designing systems that preserves what clinicians do best without the risk of complacency is critical.

Both tech companies and health leadership are primarily comprised of white male staff that may not be trained to think about bias comprehensively. Diversifying the workforce of companies building AI systems and those innovating the health-care system is needed.

A recent report found that people of color and women are underrepresented in the AI field, as about 80 percent of AI professors are men, and people of color are only a fraction of staff at major tech companies.

Diversifying the pipeline of researchers is essential; equally important is building inclusive workplaces and communities that allow under-represented minority researchers to thrive.

Yes, well-designed AI in health-care systems can transform the health and well-being of members of society by allowing healthcare professionals to provide better quality care to more people and restoring balance to the people who dedicate their lives to providing care.

But the danger is that AI systems that pit humans against algorithms will likely introduce new biases and errors into the U.S. health-care system that will not only exacerbate health disparities but also make health care more dangerous for everyone.

Enid Montague, Ph.D. is an expert on human-centered automation in medicine, Associate Professor of Computing at DePaul University, Adjunct Associate Professor of General Internal Medicine at Northwestern University, and a Public Voices Fellow through The OpEd Project.

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Dangers of artificial intelligence in medicine | TheHill - The Hill

A couple of years ago, Vladimir Putin warned Russians that the country that led in technologies using artificial intelligence will dominate the globe. He was right to be worried. Russia is now a minor player, and the race seems now to be mainly between the United States and China. But dont count out the European Union just yet; the EU is still a fifth of the world economy, and it has underappreciated strengths. Technological leadership will require big digital investments, rapid business process innovation, and efficient tax and transfer systems. China appears to have the edge in the first, the U.S. in the second, and Western Europe in the third. One out of three wont do, and even two out three will not be enough; whoever does all three best will dominate the rest.

We are on the cusp of colossal changes. But you dont have to take Mr. Putins word for it, nor mine. This is what Erik Brynjolfsson, director of the MIT Initiative on the Digital Economy and a serious student of the effects of digital technologies, says:

This is a moment of choice and opportunity. It could be the best 10 years ahead of us that we have ever had in human history or one of the worst, because we have more power than we have ever had before.

To understand why this is a special time, we need to know how this wave of technologies is different from the ones that came before and how it is the same. We need to know what these technologies mean for people and businesses. And we need to know what governments can do and what theyve been doing. With my colleagues Wolfgang Fengler, Kenan Karaklah, and Ravtosh Bal, I have been trying to whittle the research of scholars such as David Autor, Erik Brynjolfsson, and Diego Comin down to its lessons for laymen. This blog utilizes the work to forecast trends during the next decade.

It is useful to think of technical change as having come in four waves since the 1800s, brought about by a sequence of general purpose technologies (GPTs). GPTs are best described by economists as changes that transform both household life and the ways in which firms conduct business. The four most important GPTs of the last two centuries were the steam engine, electric power, information technology (IT), and artificial intelligence (AI).

All these GPTs inspired complementary innovations and changes in business processes. The robust and most relevant facts about technological progress have to do with its pace, prerequisites, and problems:

Source: Comin and Mestieri (2017).

Putin is not the first Russian leader to understand the importance of breakthrough general purpose technologies. A hundred years ago, Vladimir Lenins Communist Party invented the Five-Year Plan to exploit electric power. Indeed, it wouldnt be an exaggeration to say that modern planning practices originated with Lenins plan for the electrification of the Soviet Union. To appreciate the importance of electrification, it is worth reading Lenins short Report on the Work of the Council of Peoples Commissars. Here are extracts from that speech, delivered in 1920 to stormy and prolonged applause:

You will hear the report of the State Electrification Commission, which was set up by the All-Russia Central Executive Committee of February 7, 1920.Communism is Soviet power plus the electrification of the whole country. We are weaker than capitalism, not only on the world scale, but also within the country. Only when the country has been electrified, and industry, agriculture and transport have been placed on the technical basis of modern large-scale industry, only then shall we be fully victorious. We have a plan which gives us estimates of materials and finances covering a long period, not less than a decade. We must fulfill this plan at all costs, and the period of its fulfillment must be reduced.

Today, the most serious practitioner of Soviet-style planning is the Chinese Communist Party. In 2015, it announced the $1.68 trillion Made in China 2025 plan, to do with artificial intelligence. The plan is to transform the Chinese economy and dominate global manufacturing by 2030. China has neither the entrepreneurial nimbleness of America nor the capable public finance systems of Western Europe, but it is putting a lot of money into digital dominance. The question is whether this will be enough.

The last two decades witnessed the rise of China as an economic power; the next 10 years will decide whether it will eventually become a superpower. For now, President Xis approach could be summed up much as Lenins strategy was in 1920: State capitalism is the Peoples Party plus artificial intelligence.

The story goes that in 2018, President Donald Trump complained to President Xi Jinping that Made in China 2025 was insulting to the U.S. because it aimed to make China the global leader in technology. Since then, there are no official references to it. No point taunting the worlds technology leader into doing more, the Chinese government reckons.

But the real advantage of the U.S. is that government exercises a lighter touch than in China or Europe, leading to shorter lags from invention to market and quicker adaptation by businesses so that productivity gains are realized more quickly than in competing countries. Notice the relatively rapid diffusion of computersavailable for use simultaneously in all rich economiesin the U.S., as compared with Canada, Japan, Germany, and France (Figure 3).

Sources: Historical Cross-Country Technology Adoption Dataset by Comin and Hobijn (2004) and the Maddison Project Database.

The regulatory, infrastructural, and cultural conditions that lead to quicker business process innovation require tight industry-academic linkages, a welcoming environment for high-skilled immigrants, sound product-market regulations, and sensible hiring and firing rules. These will be not easy for either China or Europe to institute, and the U.S. will have this edge for a while.

While the United States is quick to innovate, Western Europe is intrinsically more equal. Take a look at both the diffusion and penetration of internet use plotted in Figure 4. Europe played catch-up between 1990 and 2010, but internet usage has been more widespread in every European country since then. Greater income inequality in the U.S. surely has something to do with this, but it would be even more worrying if it were also due to more unequal opportunity. There is growing evidence that this is the case, and growing concerns that these gaps will quickly widen as AI-based technologies spread across the economy.

Source: World Banks World Development Indicators and the Maddison Project Database.

Since technological change will exacerbate inequality both of opportunities and outcomes, efficient redistribution will become more necessary during the next decade than it has been in the past. Europe would then have a big advantage: Market income inequality in all but five European countries is lower than the U.S. (Figure 5). After taxes and transfers, every European economy has a lower Gini coefficient than Americas.

Source: Causa and Hermansen (2018).

People who make long-term economic forecasts have a tendency to focus on strengths: China can mobilize a lot of money so it will become a superpower, the U.S. has a good climate for business so it will continue to dominate the world economy, and Europe is more egalitarian so itll get more bang for the buck. But perhaps we should look instead at the willingness of economies to remedy their shortcomings. China has to find ways to encourage entrepreneurship and address the massive disparities in education and wealth. Europe has to mobilize large amounts of money and make it easier for investors anywhere to bring inventions to the Single Market. The United States just has to quickly figure out ways to restore competition in tech, finance, health, and public education, so its redistribution systems are not strained.

So, whos most likely to succeed during the next decade? My money is on the United States. Productivity growth will pick up again as businesses take advantage of new technologies, consumers will take home big price and quality gains, and policy types will stop fretting about fears of secular stagnation. If enough of the tax burden is shifted from labor to capital, the incomes of middle-income households will keep pace. Expect the United States to call the shots for the rest of the century.

Read more:

Whoever leads in artificial intelligence in 2030 will rule the world until 2100 - Brookings Institution

The Pentagons nascent center devoted to artificial intelligence research and development wants to learn more about peoples perceptions of the budding technology.

According to a proposed information collection notice published in the Federal Register Thursday, the Defense Departments Joint Artificial Intelligence Center is funding a RAND Corporation-led study exploring civil-military views regarding AI and related technologies.

This data collection will help ensure [Defenses] ability to engage with leading private sector technology corporations and their employees, officials said in the notice.

As is standard with federal information collections, the Pentagon must engage public feedback on whether it is necessary before the study is conducted. Defense will accept comments until March 16 on that specific matter.

While details regarding the direct questions thatll be asked and how the study will inform future Defense efforts are largely absent from the notice, officials make it clear that they hope to hear from members of the software engineering, defense and aerospace communitiesas well as the general public. The notice forecasts that around 5,210 individuals are expected to respond.

The study will also conduct focus groups with members of the software engineering community and students from computer science programs, it said.

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What Do You Think About Artificial Intelligence? The Pentagon's AI Center Wants to Know. - Nextgov

TAMPA A tech company that works to develop artificial intelligence-enabled systems that learn and collaborate with humans is expanding to Tampa.

TheIncLab, based near Washington D.C., has opened an AI+X lab that is, artificial intelligence plus experience at the Undercroft, a tech development center and membership guild for companies focused on cybersecurity. Along with TheIncLab, the Undercroft provides work space for local offices of BlackHorse Solutions, Sharp Decisions, @Risk Technologies and Bull Horn Communications.

The Undercroft has offices in one of Ybor Citys most historic structures, the El Pasaje building on E Ninth Avenue. Built in 1886, it originally housed the Cherokee Club, a private retreat for for wealthy cigar-makers. The building, with arched porticos reminiscent of Centro Habana in Cuba, also hosted Jos Mart, Theodore Roosevelt and Winston Churchill before going on to become known variously as a bordello, a speak-easy, a casino, a jazzy nightclub and a low-rent hotel.

But when TheIncLab founder and chief executive officer Adriana Avakian describes what made Tampa an attractive place to expand, she talks less about its local color and more about its "burgeoning technology and cybersecurity industry and abundance of highly qualified talent.

"We spent a fair amount of time in the Tampa-St. Petersburg area in the past six months establishing key relationships and meeting with strategic partners to ensure the success of our expansion, she said in an announcement released through the Tampa Bay Economic Development Council.

Since its founding in 2015, TheIncLab has signed up clients from several branches of the U.S. Department of Defense as well as from Fortune 500 companies in the health care, aerospace, manufacturing, consumer electronics and technology spaces. Its services are tailored to help clients accelerate innovation, launch new products and services, open new markets and redefine customer relationships. The firm also has a lab in Nashville.

TheIncLab anticipates hiring 15 developers and engineers in the next 12 months and partnering with bay area universities to augment its staff with student interns. Before it decided on Tampa, it talked with University of South Florida administrators about the availability of talent and research expertise.

Artificial intelligence is one of the great frontiers in the innovation economy," USF College of Engineering professor Sudeep Sarkar, who chairs USFs department of computer science and is co-chair of the USF Institute for AI+X, said in a statement released through the Economic Development Council. With young companies, our students and our faculty working together, Tampa is growing to become a promising center of diverse skills and new perspectives that will shape AIs future.

TheIncLab was one of 10 tech companies selected out of 432 applications from across the U.S. to participate in Tampa Bay Waves TechDiversity program last summer, and is the second of the 10 to expand or move to the Tampa Bay area.

Like Drift, a business-to-business marketing tech company that last month opened a Tampa office with plans to hire up to 100 employees by 2021, TheIncLab is not receiving any state or local incentives to expand here, according to Economic Development Council spokeswoman Laura Fontanills.

See more here:

Artificial intelligence firm TheIncLab expands to Tampa - Tampa Bay Times

John McCarthy invented the term AI. Getty

John McCarthy was the son of a penniless Irish immigrant from Kerry and maybe the most important Irish American you never heard of. He died in 2011 aged 84.

He was an American computer scientist pioneer and inventor and is known as the father of artificial intelligence (AI) after playing the key role in the development of intelligent machines we now call computers. He won the Turing Prize, one step below the Nobel, in 1971.

He coined the term artificial intelligence for a 1955 Dartmouth College conference he chiefly organized which was the first-ever AI conference.

Decades later his work was critical for the creation of companies like Google as Sebastian Thrun, who currently leads the Google self-driving car project says.

"In my mind, Google is all about artificial intelligencewhat John McCarthy stood for matters, he said.

Read more: 5 discoveries and inventions you never knew were made by the Irish

McCarthy was the son of a union organizer, also John McCarthy, who had left the little fishing village of Cromane in Kerry in the early 1920s. First, he went to London.

He left home when he was 16 and went to London, selling a cow for the fare," his niece Mary Miller told the Irish Independent.

"He came back with a Jewish girl, Ida Glatt, from Lithuania, and they later got married. John Patrick spoke several languages and wrote regularly for The Kerryman before emigrating to Boston.

Both his parents were strong union and communist advocates, and his father found work as a union organizer in the depression in Los Angeles where John grew up. John Junior disavowed communism and became a convert to conservative Republicanism after Russia invaded Czechoslovakia in 1968.

McCarthy stated that his ultimate objective was to make a machine think exactly like a human and also be capable of abstract thought, solving problems and self-improvement.

Read more: Cornelius Ryan, the Irish D-Day reporter who re-invented journalism

That's still some years awayfive to 500 McCarthy once jokedbut AI, even in its current manifestation, has dramatically changed our world. (Isnt that right Alexa?)

Many of his colleagues thought he was nuts, but he persisted in his belief that "every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it."

He went on to invent Lisp, acknowledged as one of the world's most influential programming languages which became the standard AI program language and is still used today. Famed computer scientist Alan Kay called Lisp the "greatest single programming language ever designed."

McCarthy also played a major role in the development of time-sharing systems.

"Without time-sharing, you wouldn't have the modern internet," says Lester Earnest, who worked with McCarthy at the Massachusetts Institute of Technology and at the Stanford Artificial Intelligence Lab. (Today we know time-sharing as the cloud.)

He was deeply interested in his Irish heritage and stayed in the homes of relatives during visits to Ireland. In 1992 Trinity College awarded him an honorary doctorate and he gave a lecture entitled The Little Thoughts of Thinking Machines.

McCarthy passed away at age 84 in 2011. He was truly a man who changed the world.

John McCarthy invented the term AI. Getty

Original post:

This son of an Irish emigrant invented Artificial Intelligence and changed the world - IrishCentral

Updated: May 25, 2018:

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Recent Federal Government Action on Artificial Intelligence and Next Generation Technologies - JD Supra