Category Archives: Artificial Intelligence
World’s First ‘Living Machine’ Created Using Frog Cells and Artificial Intelligence – Livescience.com
What happens when you take cells from frog embryos and grow them into new organisms that were "evolved" by algorithms? You get something that researchers are calling the world's first "living machine."
Though the original stem cells came from frogs the African clawed frog, Xenopus laevis these so-called xenobots don't resemble any known amphibians. The tiny blobs measure only 0.04 inches (1 millimeter) wide and are made of living tissue that biologists assembled into bodies designed by computer models, according to a new study.
These mobile organisms can move independently and collectively, can self-heal wounds and survive for weeks at a time, and could potentially be used to transport medicines inside a patient's body, scientists recently reported.
Related: The 6 Strangest Robots Ever Created
"They're neither a traditional robot nor a known species of animal," study co-author Joshua Bongard, a computer scientist and robotics expert at the University of Vermont, said in a statement. "It's a new class of artifact: a living, programmable organism."
Algorithms shaped the evolution of the xenobots. They grew from skin and heart stem cells into tissue clumps of several hundred cells that moved in pulses generated by heart muscle tissue, said lead study author Sam Kriegman, a doctoral candidate studying evolutionary robotics in the University of Vermont's Department of Computer Science, in Burlington.
"There's no external control from a remote control or bioelectricity. This is an autonomous agent it's almost like a wind-up toy," Kriegman told Live Science.
Biologists fed a computer constraints for the autonomous xenobots, such as the maximum muscle power of their tissues, and how they might move through a watery environment. Then, the algorithm produced generations of the tiny organisms. The best-performing bots would "reproduce" inside the algorithm. And just as evolution works in the natural world, the least successful forms would be deleted by the computer program.
"Eventually, it was able to give us designs that actually were transferable to real cells. That was a breakthrough," Kriegman said.
The study authors then brought these designs to life, piecing stem cells together to form self-powered 3D shapes designed by the evolution algorithm. Skin cells held the xenobots together, and the beating of heart tissue in specific parts of their "bodies" propelled the 'bots through water in a petri dish for days, and even weeks at a stretch, without needing additional nutrients, according to the study. The 'bots were even able to repair significant damage, said Kriegman.
"We cut the living robot almost in half, and its cells automatically zippered its body back up," he said.
"We can imagine many useful applications of these living robots that other machines can't do," said study co-author Michael Levin, director of theCenter for Regenerative and Developmental Biologyat Tufts University in Massachusetts. These might include targeting toxic spills or radioactive contamination, collecting marine microplastics or even excavating plaque from human arteries, Levin said in a statement.
Creations that blur the line between robots and living organisms are popular subjects in science fiction; think of the killer machines in the "Terminator" movies or the replicants from the world of "Blade Runner." The prospect of so-called living robots and using technology to create living organisms understandably raises concerns for some, said Levin.
"That fear is not unreasonable," Levin said. "When we start to mess around with complex systems that we don't understand, we're going to get unintended consequences."
Nevertheless, building on simple organic forms like the xenobots could also lead to beneficial discoveries, he added.
"If humanity is going to survive into the future, we need to better understand how complex properties, somehow, emerge from simple rules," Levin said.
The findings were published online Jan. 13 in the journal Proceedings of the National Academy of Sciences.
Originally published on Live Science.
Asia Pacific Artificial Intelligence in Fashion Market to 2027 – Regional Analysis and Forecasts by Offerings; Deployment; Application; End-User…
The Asia Pacific artificial intelligence in fashion market accounted for US$ 55. 1 Mn in 2018 and is expected to grow at a CAGR of 39. 0% over the forecast period 2019-2027, to account for US$ 1015. 8 Mn in 2027.
New York, Jan. 15, 2020 (GLOBE NEWSWIRE) -- Reportlinker.com announces the release of the report "Asia Pacific Artificial Intelligence in Fashion Market to 2027 - Regional Analysis and Forecasts by Offerings; Deployment; Application; End-User Industry" - https://www.reportlinker.com/p05833586/?utm_source=GNW Real-time consumer behavior insights and increased operational efficiency are driving the adoption of artificial intelligence in fashion industry. Moreover, the availability of a large amount of data originating from different data sources is one of the key factors driving the growth of AI technology across the fashion industry. Artificial Intelligence has already disrupted several industries, including the retail and fashion industry. The fashion industry so far has been one of the primary adopters of the technology. The fashion retailers these days are leveraging several revolutionary technologies, including machine learning, like augmented reality (AR) and artificial intelligence (AI), to make seamless shopping experiences across the channels, from online models to brick and mortar stores. Fashion retailers are progressively moving towards the AI integration within their supply chain, where more focus is being on customer-facing AI initiatives. Further, an AI integrated search engine is expected to reshape the way fashion designers develop new product designs. Store operations and in-store services will also be greatly benefited from AI integration in the fashion industry.The artificial intelligence in fashion market is fragmented in nature due to the presence of several end-user industries, and the competitive dynamics in the market are anticipated to change during the coming years.In addition to this, various initiatives are undertaken by governmental bodies to accelerate the artificial intelligence in fashion market further.
The governments of various countries in this region are trying to attract FDIs in the technology sector with the increasing need for enhanced technology-related services.For instance, Chinas government relaxed the restrictions on new entries with an objective to encourage overseas and private capital to invest in its economy.
This factor is anticipated to drive the demand for artificial intelligence in fashion market in this region.The artificial intelligence in fashion market by deployment type is segmented into on-premise and cloud.During the forecast period of 2019 to 2027, the cloud-based segment is anticipated to be the largest contributor in artificial intelligence in fashion market.
The artificial intelligence in fashion market is experiencing a paradigm shift from traditional on-premise deployment to cloud-based deployments in the current scenario. This trend is predominantly driven by the presence of a new category of cloud-only solutions, which help in minimizing integration complexities and installation costs with quick setup.The overall artificial intelligence in fashion market size has been derived using both primary and secondary source.The research process begins with exhaustive secondary research using internal and external sources to obtain qualitative and quantitative information related to the artificial intelligence in fashion market.
It also provides an overview and forecast for the artificial intelligence in fashion market based on all the segmentation provided with respect to the Asia Pacifica region.Also, primary interviews were conducted with industry participants and commentators to validate data and analysis.
The participants who typically take part in such a process include industry expert such as VPs, business development managers, market intelligence managers, and national sales managers, and external consultants such as valuation experts, research analysts, and key opinion leaders specializing in the artificial intelligence in fashion market. Some of the players present in artificial intelligence in fashion market are Adobe Inc., Amazon Web Services, Inc., Catchoom Technologies S.L., Facebook, Inc., Google LLC, Huawei Technologies Co., Ltd., IBM Corporation, Microsoft Corporation, Oracle Corporation, and SAP SE among others.Read the full report: https://www.reportlinker.com/p05833586/?utm_source=GNW
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Companies Use Artificial Intelligence to Help With Hiring. Korean Consultants Teach You How to Beat It – Inc.
Artificial intelligence is supposed to free the hiring process from prejudices and biases. We can have a totally neutral system that evaluates candidates and selects the best possible one, regardless of race, gender, or any other characteristic.
It sounds fantastic, but it's been an abysmal failure in that matter. Artificial intelligence is only as good as the programmers, who, of course, are actual humans with flaws. Amazon, which, of course, has gobs of money to pour into development, had to scrap its A.I. recruiting process because the bot didn't like women.
HireVue faces pressure from rights groups over its hiring systems, which, according to TheWashington Post,
use video interviews to analyze hundreds of thousands of data points related to a person's speaking voice, word selection and facial movements. The system then creates a computer-generated estimate of the candidates' skills and behaviors, including their "willingness to learn" and "personal stability."
This model of gaming the system has been in place for as long as people have applied for jobs. There are thousands of articles on the internet that tell you how to answer standard interview questions ("Where do you see yourself in five years?") or extol the virtues of a firm handshake. This is really no different than the training these consultants give. Except, instead of trying to convince a human, you're trying to convince a machine.
And that makes this training so much more valuable. I can tell you "firm handshakes are important!" and then you interview with someone who prefers the dead-fish version of shaking hands and my advice harms instead of helps. Butif two companies use the same software, the information from these consultants will help you shine regardless of who the hiring manager is.
That's the goal, of course, to take the human biases out of interviews. But the biases still exist in A.I.--it's just that every job requires you to overcome the same preferences. Which means it will be easier to beat the system. Once the consultants figure out what the algorithms want, they can train you to respond the right way.
While it potentially levels the playing field, people who can afford training will do better in the interviews. Interviewers already discriminate on class, so this doesn't solve that problem at all.
Can artificial intelligence potentially make hiring better? Probably. But, as these consultants understand--anytime there is a system, there is a way to beat it. While humans are fallible, at least we all know they are. Artificial intelligence allows you to think the process is bias-free, but it's not. It just makes for consistent bias.
Published on: Jan 15, 2020
The opinions expressed here by Inc.com columnists are their own, not those of Inc.com.
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Companies Use Artificial Intelligence to Help With Hiring. Korean Consultants Teach You How to Beat It - Inc.
The future is intelligent: Harnessing the potential of artificial intelligence in Africa – Brookings Institution
The future is intelligent: By 2030, artificial intelligence (AI) will add $15.7 trillion to the global GDP, with $6.6 trillion projected to be from increased productivity and $9.1 trillion from consumption effects. Furthermore, augmentation, which allows people and AI to work together to enhance performance, will create $2.9 trillion of business value and 6.2 billion hours of worker productivity globally. In a world that is increasingly characterized by enhanced connectivity and where data is as pervasive as it is valuable, Africa has a unique opportunity to leverage new digital technologies to drive large-scale transformation and competitiveness. Africa cannot and should not be left behind.
There are 10 key enabling technologies that will drive Africas digital economy, including cybersecurity, cloud computing, big data analytics, blockchain, the Internet of Things, 3D printing, biotechnology, robotics, energy storage, and AI. AI in particular presents countless avenues for both the public and private sectors to optimize solutions to the most crucial problems facing the continent today, especially for struggling industries. For example, in health care, AI solutions can help scarce personnel and facilities do more with less by speeding initial processing, triage, diagnosis, and post-care follow up. Furthermore, AI-based pharmacogenomics applications, which focus on the likely response of an individual to therapeutic drugs based on certain genetic markers, can be used to tailor treatments. Considering the genetic diversity found on the African continent, it is highly likely that the application of these technologies in Africa will result in considerable advancement in medical treatment on a global level.
In agriculture, Abdoulaye Banir Diallo, co-founder and chief scientific officer of the AI startup My Intelligent Machines, is working with advanced algorithms and machine learning methods to leverage genomic precision in livestock production models. With genomic precision, it is possible to build intelligent breeding programs that minimize the ecological footprint, address changing consumer demands, and contribute to the well-being of people and animals alike through the selection of good genetic characteristics at an early stage of the livestock production process. These are just a few examples that illustrate the transformative potential of AI technology in Africa.
In a world that is increasingly characterized by enhanced connectivity and where data is as pervasive as it is valuable, Africa has a unique opportunity to leverage new digital technologies to drive large-scale transformation and competitiveness. Africa cannot and should not be left behind.
However, a number of structural challenges undermine rapid adoption and implementation of AI on the continent. Inadequate basic and digital infrastructure seriously erodes efforts to activate AI-powered solutions as it reduces crucial connectivity. (For more on strategies to improve Africas digital infrastructure, see the viewpoint on page 67 of the full report). A lack of flexible and dynamic regulatory systems also frustrates the growth of a digital ecosystem that favors AI technology, especially as tech leaders want to scale across borders. Furthermore, lack of relevant technical skills, particularly for young people, is a growing threat. This skills gap means that those who would have otherwise been at the forefront of building AI are left out, preventing the continent from harnessing the full potential of transformative technologies and industries.
Similarly, the lack of adequate investments in research and development is an important obstacle. Africa must develop innovative financial instruments and public-private partnerships to fund human capital development, including a focus on industrial research and innovation hubs that bridge the gap between higher education institutions and the private sector to ensure the transition of AI products from lab to market.
At the same time, we must be careful that priority sectors drive the AI strategy in Africa with accompanying productsnot the other way around. We believe the health care industry presents by far the most urgent need and promising market opportunity, and, as such, should be put at the top of the list for the continents decisionmakers. A large portion of the African population is still unable to access proper health care, with a low patient ratio of one physician per 5,000 patients, and there is almost no country with a fully integrated health management platform. AI could intervene directly to improve personalized health care and product development. Importantly, the health management platform precedes the leveraging of AI, so we must equally invest in cybersecurity, Big Data, cloud computing, and blockchain.
Artificial intelligence for Africa presents opportunities to put the continent at the forefront of the Fourth Industrial Revolution. Before Africa can lead this transformation, though, there are important steps that must be undertaken. First, the region needs to formulate a comprehensive continental blueprint to guide its AI strategy by involving key Pan-African institutions, academia, and the private and public sectors in its conception.
In addition, these stakeholders must also invest in creating a digital identity platform for all Africans with reliable data banks for AI to be a viable economic option. For this, it is imperative to leverage readily available local talent as a means to promote and democratize AI technology continent-wide. Finally, we must harmonize regulatory policies that encourage ethically built AI systems so as to guarantee a more inclusive economic development for Africa. With these important steps, the next decade for Africa will be intelligent.
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The future is intelligent: Harnessing the potential of artificial intelligence in Africa - Brookings Institution
Artificial Intelligence Expert Neil Sahota Says AI Will Have Major Impact On 2020 Elections And In Medicine – PRNewswire
LOS ANGELES, Jan. 15, 2020 /PRNewswire/ --Artificial intelligence, or AI, will play a significant role in the 2020 election campaign and may also lead to major breakthroughs in solving personal medical issues, according to futurist and AI expert Neil Sahota.
"I'm increasingly concerned about the impact of fake news, photo scams and other deceits designed to negatively influence voting this year," says Sahota, who works closely with the United Nations and other organizations to foster innovation and develop next generation products/solutions to be powered by AI. "We will see the effect of more AI tools generating fraudulent information and influencing voters. Thankfully, there will also be new tools to fight this kind of disinformation. What is certain is that machine vs machine battles will become more prevalent."
The author of the influential book Own the AI Revolution (McGraw Hill), Sahota is also an IBM Master Inventor, who led the IBM Watson Group and is a professor at the University of California/Irvine.
In addition to its potential impact on the election campaigns, Sahota predicts AI will be responsible for significant medical advances. "We will see more use of AI that will accelerate solutions for doctors, nurses, clinicians and researchers in providing personalized care," he said. "Each of us is genetically unique and there isn't a one-size fits all solution for us. But AI can solve this dilemma by providing personalized medicine based on a specific person's genomic sequence, lifestyle, medical history, environment and other differences. I think there will be great strides in these areas in the coming year."
"The election and medicine are only two areas where we will feel the impact of AI, which is coming into its own as an emerging technology," Sahota says. "We are likely to see it help combine tools such as block chain, virtual reality and artificial reality. For example, I envision a virtual reality courtroom where a law student interacts with an AI 'judge,' opposing counsel and jury. AI simulation is not only more 'real world' but has great variability, meaning each time the VR module is used, it's different. There's no memorization or 'cheat sheet' for the law student. It's a dynamic, highly interactive learning module and 2020 will start the wave of convergence: combining these technologies together.
About Neil Sahota: Neil Sahota is a futurist and leading expert on Artificial Intelligence (AI) and other next generation technologies. He is the author of Own the AI Revolution (McGraw Hill) and works with the United Nations on the AI for Good initiative. Sahota is also an IBM Master Inventor, former leader of the IBM Watson Group and professor at the University of California/Irvine. His work spans multiple industries, including legal services, healthcare, life sciences, retail, travel, transportation, energy, utilities, automotive, telecommunications, media, and government.
SOURCE Neil Sahota
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Artificial Intelligence Expert Neil Sahota Says AI Will Have Major Impact On 2020 Elections And In Medicine - PRNewswire
Artificial intelligence and the future of rep visits – – pharmaphorum
As access to healthcare professionals (HCPs) declines, the challenges facing sales representatives continue to increase: less time with HCPs, Sunshine Act restrictions, and integration of practices into larger health systems. It can be daunting.
Once, influence was based on interactions between reps and HCPs more than just about anything else. But today, influence is spread across a variety of touch points, many digital, which can be accessed by an HCP at any time and place. To reinforce their value, sales reps are expected to have deep knowledge of the market and their customers, so that they can tailor their interactions to the unique needs of each.
How can todays rep succeed? Its all about data.
Data gathered judiciously, digested accurately, analysed rapidly, and used wisely makes the sales force more efficient and productive. This concept is nothing new: it dates back to the beginnings of CRM in the 20th century.
But todays digital world offers new possibilities, enabling connections and predictions that yesterdays rep never even dreamed of.
What if reps could anticipate relevance?
By combining the best in industry expertise, brand strategy, CRM technology, and artificial intelligence (AI) and machine learning, reps can have the tools to make anticipated relevance possible.
At a recent Digital Health Coalition Midwest Summit, Intouch demonstrated examples of what this could look like for a brand, using their AI assistant, EVA, which is short for embedded virtual assistant.
How does it work?
EVA connects with Veeva to access a reps calendar of appointments to obtain information about where they need to go and who they need to see. Combined with marketing segmentation, EVA tells a sales rep the segmentation of todays calls. Data further informs the conversation with helpful facts like script-writing history, marketing plan, prior messages presented, and online activity, giving our rep a prediction of what their next best actions should be. These suggestions can be offered through the voice assistant, or sent by text or email for later reference, and can power the flow of the in-office detail. After the call, EVA can help a rep record a call quickly and easily in the CRM system.
An AI-powered ecosystem makes sure no pertinent data goes to waste. Whether its an email open, a website visit, a rep conversation, a script, or any other activity, the rep can quickly and easily understand what their HCP cares about and what information will be most helpful to their practice.
By anticipating relevance, the rep can provide an HCP with information thats useful to them, in the format, time, and place that helps them most. And EVA is able to use the most relevant assets efficiently and minimise the burden of administrative tasks. Time is used wisely on both sides, making it possible for the right information to help patients that much sooner.
Want to learn more about AI and modern pharma marketing? Download Intouchs comprehensive ebook.
Interested in learning how AI can work for your reps? Reach out to the Intouch team today.
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Artificial intelligence and the future of rep visits - - pharmaphorum
The G7 wants to regulate artificial intelligence. Should the US get on board? – News@Northeastern
With the introduction of new export controls on artificial intelligence software last week, the White House appealed to lawmakers, businesses, and European allies to avoid overregulation of artificial intelligence. It also maintained its refusal to participate in a project proposed by the Group of Seven leading economies, which seeks to establish shared principles and regulations on artificial intelligence, as the U.S. prepares to take over the presidency of the organization this year.
The U.S. has rejected working with other G-7 nations on the project, known as the Global Partnership on Artificial Intelligence, maintaining that the plan would be overly restrictive.
Kay Mathiesen is an associate professor of philosophy and religion in the College of Social Sciences and Humanities. Photo by Matthew Modoono/Northeastern University
Kay Mathiesen, an associate professor at Northeastern who focuses on information and computer ethics and justice, contends that the U.S.s refusal to cooperate with other nations on a united plan could come back to hurt its residents.
Advocates of the plan say it would help government leaders remain apprised of the development of the technology. The project, they say, could also help build consensus among the international community on limiting certain uses of artificial intelligence, especially in cases where its found to be controlling citizens or violating their privacy and autonomy.
U.S. leaders, including deputy chief technology officer Lynne Parker, counter that the proposal appears overly bureaucratic and could hinder the development of artificial intelligence at U.S. tech companies.
But Mathiesen says that many companies are already ahead of the curve in considering or implementing oversight mechanisms to guide the ethical development of their products. She says that its important to rein in the potentially harmful effects of artificial intelligence to ensure that the benefits of the technology are not overridden by the cost.
The idea that we should just not regulate at all or not even think about this, because maybe then we might limit ourselves, I think thats a pretty simplistic view, says Mathiesen, a professor of philosophy who studies political philosophy and ethics. Its not like the G-7 is going to have the power to all of a sudden impose regulations on U.S. industry. So that argument that merely by joining this [group] and beginning to think these things through, and do research on this, and develop [policy] recommendationsthat that by itself is going to put us behind on artificial intelligence doesnt hold a lot of water.
Mathiesen suggests that failing to work with other countries in addressing privacy issues stemming from the unchecked spread of artificial intelligence productssuch as facial recognitioncould result in consumer backlash, and thereby slow down the development of artificial intelligence in the U.S.
The technology is advancing incredibly rapidly and we want to make sure that were thinking ahead, and were building at the beginning protections for consumers before these things come out and its too late and we have to try to fix problems that we couldve prevented, she says.
The plan for the Global Partnership on Artificial Intelligence, which was introduced in December 2018, is to ensure that artificial intelligence projects are designed responsibly and transparently, in a way that prioritizes human values, such as privacy. The initiative received a major boost from Canada, which held the G-7s rotating presidency at the time, and was kept alive by France the following year. The U.S. will take over the presidency of the organization this year.
In addition to Canada and France, the other G-7 countries, including Germany, Italy, Japan, and the U.K., are on board with the project. The European Union, India, and New Zealand have also expressed interest. Mathiesen says that while she understands the concerns of some U.S. government officials about being out-competed, its important for the U.S. to be a participating member in this effort, especially while the technology is still in its nascent stages.
In a way, its better that the U.S. has buy-in at the beginning and is at the table to make these arguments about how do we balance concerns about things like privacy, security, and possible harm that could be produced by artificial intelligence? How do we balance that with also wanting to enable companies and inventors to create new things with artificial intelligence that can be economically and socially beneficial? she says.
Mathiesen suggested that failing to engage in these conversations with the wider international community could leave the U.S. trailing behind.
I think that the American citizens are going to suffer for that, just like they do now with the lack of data privacy, she says.
In conjunction with global professional services company Accenture, researchers at Northeasterns Ethics Institute last year produced a report that provided organizations a framework for creating ethics committees to help guide the development of smart machines.
For media inquiries, please contact Marirose Sartoretto at m.sartoretto@northeastern.edu or 617-373-5718.
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The G7 wants to regulate artificial intelligence. Should the US get on board? - News@Northeastern
Ancient Artificial Intelligence: The Mechanical Messiah and Other Automatons – Ancient Origins
It may not be long before Artificial Intelligence creates access to God via modern technology, however during the 19th century, a spiritualist by the name of John Murray Spear was inspired to build a Mechanical Messiah. Born on September 16, 1804, into a deeply religious family, John Murray Spear eventually became a member and minister of the Universalist Church. He forsook his ministry for spiritualism and was aided in his endeavor by illustrious technical advisors, the members of the Association of Electrizers: Thomas Jefferson (1743 - 1826), the third president of the United States; John Quincy Adams (1767 1848) an American statesman, diplomat, and lawyer who served as the sixth president of the United States; Benjamin Rush (1746 - 1813) a signer of the United States Declaration of Independence and a civic leader in Philadelphia, and Benjamin Franklin (1706 - 1790) a scientist, journalist, politician, inventor and one of the major protagonists of the American Revolution. This ambitious project had one flaw most of the technical team were deceased.
Three of the Electricizers: John Quincy Adams ( Public Domain ); Benjamin Rush by Charles Peale (1818) ( Public Domain )and Benjamin Franklin by Joseph Duplessis (1785) ( Public Domain)
The innovative Spear, under the influence of his first wife Sophronia, was intent on bettering the fate of this wretched humanity by providing it with all sorts of 'technical' information. With the guidance of his highly qualified technical team, Spear received instructions for realizing the unattainable perpetual death; a thinking machine; an electric ship and a global telepathic network. But his greatest achievement was a strange automaton, a curious device composed of electrical and mechanical parts that was to embody the 'New Motive Force', a technological 'Holy Spirit', a new 'Messiah' destined to awaken the whole of humanity from a demonic stupor. Spear believed he was spearheading a technological revolution (certainly not yet the Fourth) at a time when electricity was just beginning to enlighten the man in the street as to what 'miracles' human ingenuity was capable of.
John Murray Spear inventor of the Mechanical Messiah
The Mechanical Messiah was not born in a stable, nor warmed by the loving breath of an ox and a donkey, as the established Christian tradition would have one believe. No, this very strange, technological transformer between the Earth and Heaven, between the Immanent and the Transcendent was born in a laboratory at High Rock Cottage, Massachusetts.
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Dr Roberto Volterri is the author of 40 books including Gli Stregoni Della Scienza
Top Image : Thetis receiving the arms of Achilles from Hephaestus by Peter Paul Rubens (1630)
Museum Boijmans Van Beuningen ( Public Domain )
By Dr Roberto Volterri
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Ancient Artificial Intelligence: The Mechanical Messiah and Other Automatons - Ancient Origins
It’s 2020 Stop Confusing Cognitive Automation With Artificial Intelligence – Analytics India Magazine
Artificial intelligence has revolutionised every piece of technology it has touched. However, this augmentation for better or worse has also brought up a lot of confusion. With more and more AI application coming up in different fields, specifically in automation like Cognitive Automation, the conditions associated with it give the impression that the technology is artificially intelligent and seems to dilute the real meaning behind it. This poses a more significant problem as what qualifies as a mere application of AI can be called artificial intelligence.
When we talk about automation and AI, there is a lot of buzz around cognitive automation as it uses technology to mimic human behaviour and precisely the reason why some people call it as cognitive automation artificial intelligence.
Artificial Intelligence Vs Cognitive Automation
If one had to define artificial intelligence regarding computing, then it can be defined as the area of computer science that focuses on the creating intelligent machines that work and interact like humans with each other or with living beings. Some activities include speech recognition, learning, among others. When it comes to AI creating intelligent machines that work like humans is what one has to keep in mind from the definition. The creation process depicts the intelligence part of the device.
For example, AI in healthcare has had many applications over the years. Now, if a doctor wants to take the help of an AI, then during a particular procedure, intelligence comes into play when AI suggests which course of action to choose based on its analysis.
Intelligence, especially artificial intelligence, requires a lot of information to carry out its analysis about a process.
On the other hand, cognitive automation mimics quantitative human judgement or augments human intelligence. In short, cognitive automation imitates human thinking. If you look at the technologies in cognitive automation like natural language processing, image processing and contextual analysis all are more profound concepts of perceptions and judgements and are heavily influenced by AI.
If one looks at the cognitive applications, it becomes evident that the automation happens via hardcoded human-generated rules or through dense inputs.
According to Franois Chollet, creator of the neural network library, Keras, Automation is, at best, robustly handling known unknowns over known tasks, which is already incredibly difficult and resource-intensive in the real world whether engineering or data.
Therefore, when it comes to automation, it can only work if it is made aware of the unknowns. Working with the unknown entirely on itself will only result in the failure when it comes to automation. For instance, in the healthcare sector, doctors do take the help of AI for deciding the course of action based on the suggestions made by the intelligent system. However, when it comes to automation, this technology is only here to enhance the doctors practice and not independently run any analysis.
Cognitive automation learns through different unstructured data and connects to creating tags, annotations and other metadata. Cognitive automation tries to find similarities between items to specific processes. It seeks to identify the mentioned items in the process and then searches for similar ones in order to connect them.
To carry out a process by an automation system requires data. And, once enough information has been provided during the automation process, there is no requirement for humans to build an additional model to carry out the analysis further. As the new data set is provided, the automation makes more connections with the old one, which allows the cognitive automation systems to keep learning without any supervision and can continuously adjust to the new information.
Whereas for AI it carries out its analysis after been given a different data set at the expense of a massive amount of information which has been fed to the system. This information/data is more than the required data for cognitive automation.
In the current scenario, when one reads about the cognitive applications, the process and its workings might be similar to artificial intelligence, and thus creating confusion between the two. This happens because ultimately, cognitive automation is an application of artificial intelligence itself, which is just a little less intelligent. Cognitive automation doesnt deal with the unknowns of a process or the real-world problems, and it can only work through them if there is data fed to it in.
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It's 2020 Stop Confusing Cognitive Automation With Artificial Intelligence - Analytics India Magazine
Global Artificial Intelligence (AI) Market in Manufacturing Industry 2019-2023 | 31% CAGR Projection Through 2023 | Technavio – Business Wire
LONDON--(BUSINESS WIRE)--The global artificial intelligence (AI) market in manufacturing industry is expected to post a CAGR of around 31% during the period 2019-2023, according to the latest market research report by Technavio. Request a free sample report
Manufacturing companies are moving toward the implementation of Industry 4.0 standard to intensify automation to achieve higher operational efficiencies. This is increasing the adoption of a greater number of connected devices and technologies such as big data, ML, and IoT, which is resulting in the generation of high volumes of data. This, in turn, is compelling manufacturing firms to adopt AI-based solutions to extract insights from the data to improve the management of operations. Hence, the integration of industrial IoT and big data is crucial in driving the growth of the market.
To learn more about the global trends impacting the future of market research, download a free sample: https://www.technavio.com/talk-to-us?report=IRTNTR32119
As per Technavio, the increasing human-robot collaboration will have a positive impact on the market and contribute to its growth significantly over the forecast period. This research report also analyzes other important trends and market drivers that will affect market growth over 2019-2023.
Global Artificial Intelligence (AI) Market in Manufacturing Industry: Increasing Human-Robot Collaboration
Collaborative robots are designed to work in direct cooperation with humans in a well-defined workspace. They offer better productivity, reduced downtimes, and higher load capacity. Collaborative robots also improve safety in the manufacturing facility and prevent accidents and injury to humans. Moreover, they are affordable, highly adaptable, and are easy to install. Owing to such benefits, many organizations, including SMEs are increasingly adopting collaborative robot technologies. Over the next few years, the demand for collaborative robot technologies is expected to further increase with the development of better sensors and the integration of AI and ML algorithms.
Advances in AI related to intelligent business process and the increasing demand for generative designs will further boost market growth during the forecast period, says a senior analyst at Technavio.
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Global Artificial Intelligence (AI) Market in Manufacturing Industry: Segmentation Analysis
This market report segments the global artificial intelligence market in manufacturing industry by application (predictive maintenance and machine inspection, production planning, quality control, and others) and geography (APAC, Europe, MEA, North America, and South America).
The APAC region led the market in 2018, followed by North America, Europe, South America, and MEA respectively. During the forecast period, the APAC region is expected to maintain its dominance over the market. This is due to the growing adoption of smart technologies by manufacturing facilities in the region.
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Some of the key topics covered in the report include:
Market Landscape
Market Sizing
Five Forces Analysis
Market Segmentation
Customer Landscape
Geographical Segmentation
Market Drivers
Market Challenges
Market Trends
Vendor Landscape
Vendor Analysis
About Technavio
Technavio is a leading global technology research and advisory company. Their research and analysis focus on emerging market trends and provides actionable insights to help businesses identify market opportunities and develop effective strategies to optimize their market positions.
With over 500 specialized analysts, Technavios report library consists of more than 17,000 reports and counting, covering 800 technologies, spanning across 50 countries. Their client base consists of enterprises of all sizes, including more than 100 Fortune 500 companies. This growing client base relies on Technavios comprehensive coverage, extensive research, and actionable market insights to identify opportunities in existing and potential markets and assess their competitive positions within changing market scenarios.
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Global Artificial Intelligence (AI) Market in Manufacturing Industry 2019-2023 | 31% CAGR Projection Through 2023 | Technavio - Business Wire