Monthly Archives: September 2021

Artificial intelligence was once just a buzzword, but today its impact on our daily lives is far greater than ever before.

Let us imagine that you have decided to find an online casino available in your area with great bonuses. You type a query into Google and discover Tonybet. Why were we given this answer? Because the intelligence of the system is artificial intelligence, which makes decisions to improve your user experience based on your preferences and your online behavior.

Artificial Intelligence has a huge impact on many other industries as well.

In medicine, search, languages, automobiles, and, of course, advertising, artificial intelligence has driven innovation. Heres how we assess the impact of artificial intelligence on our daily lives.

In this sphere, AI memory is valued, as well as the ability to generate and compare vast amounts of information.

For several years now, everyone has heard about IBM Watson and DeepMind Health (a Google development) smart assistants that not only give advice to doctors but also figure out the genetic predisposition to pathologies. For example, IBM Watson already identifies and develops therapy plans for 13 types of malignant neoplasms: from cervical cancer to colon cancer.

Artificial intelligence even comes to the aid of patients. Telemedicine applications that collect data from fitness bracelets and other sensors, as well as questionnaires that establish the exact symptoms and diseases of patients, are becoming increasingly popular. For example, AI can recognize tuberculosis and disorders of internal organs, including the brain.

Some of the apps parse human speech and respond verbally, while others prefer written communication. The apps get the necessary information and then make recommendations on what to do next, or send the data to a therapist. The most popular intelligent assistants are Yours.MD and Ada, which can be downloaded from the App Store or Google Play.

Of particular importance are systems that can develop new medicines. According to Pfizers top manager, it takes an average of 12 years to develop and bring a new medicine to market. AI will make it possible to create the molecular structure and simulate the drug, which will increase its quality and reduce the time it takes to produce new drugs. Atomwise and Berg Health are pioneering supercomputers that solve this problem.

Large industrial companies in countries such as Japan, China, the US, Germany, and Switzerland are investing in new technologies. The trend today is toward fewer jobs involving intellectual labor and more computers.

Such jobs will suffer in the coming decades:

Robotization soon will also affect such professions as secretaries, cashiers, truck drivers, and waiters. An example of successful AI implementation was the H&H line plant. The technology, which tracks the gaze of workers, helped save 400 hours of training for trainees in 1 year and reduce the likelihood of accidents.

MIT Technology Review reported that Andrew Eun, a robotics and machine learning researcher, is developing a new project called Landing.AI. It aims to set up a manufacturing mechanism in factories and plants. His first partner is Foxconn, which manufactures Apple gadgets.

Soon, the field of education will be developing rapidly in two directions adaptive learning and proctoring.

Adaptive learning is designed to solve the problem of different performances of pupils and students. The fact is that one person learns material much faster and more successfully than another. Therefore, AI will monitor the level of knowledge of the student and adapt the order of blocks of courses to his abilities or inform the teacher how well the student has mastered the material. An example of such a system could be the Third Space Learning platform, which is currently under development.

Proctoring represents the control of pupils and students during the passing of control and examination tests. Whereas in the past, students were in the crosshairs of a webcam, now AI comes to the rescue. It monitors how often a student takes his or her eyes off the computer screen, whether he or she changes tabs on a browser, and whether there are no extra voices in the room. As soon as the AI notices an irregularity, it immediately alerts the human lecturer.

But can the machine replace an ordinary teacher? Rosa Lukin, a professor at University College London, denies it. It is worth finding a compromise, she says. After all, the goal is not to replace teachers with machines, but to improve education. The human teacher is certainly indispensable here.

The opinion that farming and livestock are backward and old-fashioned industries is a thing of the past. Today, the intensive growth of the global AI market in the agricultural industry is caused by the following factors: introduction of the data management system, automation of irrigation, increase in productivity of crops through the introduction of learning methods and increase in the number of people on the planet. At the same time, the growth of the AI market is limited by the high cost of collecting information about agricultural lands.

The widespread introduction of robotics in agriculture is represented by such developments:

Energias Market Research predicts that the AI market in the agricultural industry will grow by 24.3% by 2024. It will actively develop in the U.S. and the Asia-Pacific region. Agworld, Farmlogs, Cropx, Microsoft, AGCO, and others are among the central players in the smart agribusiness market.

The goal of implementing AI in this area is to fight traffic jams. Such systems are already working successfully in major cities in Europe, North America, and Asia.

Collecting information from traffic lights, analysis of traffic density, traffic accidents, weather data, and other factors that create traffic jams these are the functions of the computer. As a result, the intelligent system monitors the roads online, predicts what the traffic will be, and according to this, switches the traffic lights.

It monitors not only the traffic on the road, but also helps the drivers. For example, if necessary, the system calls for a tow truck. This solution will not be able to get rid of traffic jams completely, but it is quite possible to speed up the traffic by several times.

Probably, progress will be notified if we see widespread use of unmanned cars, which are vehicles that can move without human intervention. They are being developed by Google, AKTIV, Tesla Motors, and some others.

Of course, everyone has heard of the smart house, which in the future will be a typical example of AI. The largest manufacturers are Yamaha, Siemens, Abb, Beckhoff, and Legrand.

Such developments simplify human life to the maximum. For example, such a system will open the curtains in the morning, wake up the owners and make coffee. In the future, the functionality of the smart house will be expanded up to the fact that the closet will automatically steam clothes and the refrigerator will order food. Such a solution will optimize costs related to power, ventilation, heating, adjusting to a convenient schedule.

Vacuum cleaners that can not only do the cleaning but also move objects and charge themselves remain popular as well.

Another example of a domestic AI application is automated translators. While in the past machine translation left much to be desired, today the situation has changed dramatically. Google Translate demonstrates this: the algorithm is based on the fact that the computer perceives not individual words, but a complete sentence. It allows to obtain high-quality text, so soon, this method will become the basis for automatic translation.

Human-like androids are used not only for household chores but also for communication. Iron friend will not let you die of boredom, and sometimes it becomes a full member of the family. So, one lucky man in China managed to marry a robot. He turned out to be engineer Zheng Jiajia, who made his own bride.

Undoubtedly, the future of humanity is intertwined with robots, because every year more and more applications of artificial intelligence are developed. Most likely, it will surpass the abilities of humans, but at the same time greatly improve the quality of their lives. The main thing here is to find reasonable limits before AI learns to reproduce itself. According to Elon Musk, it is worth taking a proactive stance and already now limiting the use of AI, at least in the military industry.

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The Future Is Already Here: Areas Where Artificial Intelligence Is Already in Use and This Is Just the Beginning - Analytics Insight

Events over the past few years have revealed several human rights violations associated with increasing advances in artificial intelligence (AI).

Algorithms created to regulate speech online have censored speech ranging from religious content to sexual diversity. AI systems created to monitor illegal activities have been used to track and target human rights defenders. And algorithms have discriminated against Black people when they have been used to detect cancers or assess the flight risk of people accused of crimes. The list goes on.

As researchers studying the intersection between AI and social justice, weve been examining solutions developed to tackle AIs inequities. Our conclusion is that they leave much to be desired.

Some companies voluntarily adopt ethical frameworks that are difficult to implement and have little concrete effect. The reason is twofold. First, ethics are founded on values, not rights, and ethical values tend to differ across the spectrum. Second, these frameworks cannot be enforced, making it difficult for people to hold corporations accountable for any violations.

Even frameworks that are mandatory like Canadas Algorithmic Impact Assessment Tool act merely as guidelines supporting best practices. Ultimately, self-regulatory approaches do little more than delay the development and implementation of laws to regulate AIs uses.

And as illustrated with the European Unions recently proposed AI regulation, even attempts towards developing such laws have drawbacks. This bill assesses the scope of risk associated with various uses of AI and then subjects these technologies to obligations proportional to their proposed threats.

As non-profit digital rights organization Access Now has pointed out, however, this approach doesnt go far enough in protecting human rights. It permits companies to adopt AI technologies so long as their operational risks are low.

Just because operational risks are minimal doesnt mean that human rights risks are non-existent. At its core, this approach is anchored in inequality. It stems from an attitude that conceives of fundamental freedoms as negotiable.

So the question remains: why is it that such human rights violations are permitted by law? Although many countries possess charters that protect citizens individual liberties, those rights are protected against governmental intrusions alone. Companies developing AI systems arent obliged to respect our fundamental freedoms. This fact remains despite technologys growing presence in ways that have fundamentally changed the nature and quality of our rights.

Our current reality deprives us from exercising our agency to vindicate the rights infringed through our use of AI systems. As such, the access to justice dimension that human rights law serves becomes neutralised: A violation doesnt necessarily lead to reparations for the victims nor an assurance against future violations, unless mandated by law.

But even laws that are anchored in human rights often lead to similar results. Consider the European Unions General Data Protection Regulation, which allows users to control their personal data and obliges companies to respect those rights. Although an important step towards more acute data protection in cyberspace, this law hasnt had its desired effect. The reason is twofold.

First, the solutions favoured dont always permit users to concretely mobilize their human rights. Second, they dont empower users with an understanding of the value of safeguarding their personal information. Privacy rights are about much more than just having something to hide.

These approaches all attempt to mediate between both the subjective interests of citizens and those of industry. They try to protect human rights while ensuring that the laws adopted dont impede technological progress. But this balancing act often results in merely illusory protection, without offering concrete safeguards to citizens fundamental freedoms.

To achieve this, the solutions adopted must be adapted to the needs and interests of individuals, rather than assumptions of what those parameters might be. Any solution must also include citizen participation.

Legislative approaches seek only to regulate technologys negative side effects rather than address their ideological and societal biases. But addressing human rights violations triggered by technology after the fact isnt enough. Technological solutions must primarily be based on principles of social justice and human dignity rather than technological risks. They must be developed with an eye to human rights in order to ensure adequate protection.

One approach gaining traction is known as Human Rights By Design. Here, companies do not permit abuse or exploitation as part of their business model. Rather, they commit to designing tools, technologies, and services to respect human rights by default.

This approach aims to encourage AI developers to categorically consider human rights at every stage of development. It ensures that algorithms deployed in society will remedy rather than exacerbate societal inequalities. It takes the steps necessary to allow us to shape AI, and not the other way around.

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We need concrete protections from artificial intelligence threatening human rights - The Conversation CA

As part of a series of longitudinal studies on AI, the Stanford HAI has come out with the new AI100 report titled Gathering Strength, Gathering Storms: The One Hundred Year Study on Artificial Intelligence (AI100) 2021 Study Panel Report. The report evaluates AIs most significant concerns in the previous five years.

Much has been written on the state of artificial intelligence and its effects on society since the initial AI100 report. Despite this, AI100 is unusual in that it combines two crucial features.

First, it is authored by a study panel of key multidisciplinary scholars in the fieldexperts who have been creating artificial intelligence algorithms or studying their impact on society as their primary professional activity for many years. The authors are experts in the field of artificial intelligence and offer an insiders perspective. Second, it is a long-term study, with periodic reports from study panels anticipated every five years for at least a century.

As AI systems demonstrate greater utility in real-world applications, they have expanded their reach, raising the likelihood of misuse, overuse, and explicit abuse. As the capabilities of AI systems improve and they become more interwoven into society infrastructure, the consequences of losing meaningful control over them grow more alarming.

New research efforts aim to rethink the fields foundations to reduce the reliance of AI systems on explicit and often misspecified aims. A particularly evident concern is that AI might make it easier to develop computers capable of spying on humans and potentially killing them on a large scale.

However, there are numerous more significant and subtler concerns at the moment.

One can access the entire report here.

Nivash has a doctorate in Information Technology. He has worked as a Research Associate at a University and as a Development Engineer in the IT Industry. He is passionate about data science and machine learning.

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Dangers Of Artificial Intelligence: Insights from the AI100 2021 Study - Analytics India Magazine

Bosses at NHS Golden Jubilee Hospital in Clydebank, West Dunbartonshire, said patients there who need stents fitted in their heart arteries are the first in Scotland to have the procedure performed using guided AI technology.

During percutaneous coronary intervention (PCI) operations to treat coronary artery disease, stents are placed in narrowed coronary arteries to keep them open and maintain blood flow to the heart.

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Cardiologists at the hospital carry out planned PCIs using the new Ultreon 1.0 Software which merges the existing imaging technique of Optical Coherence Tomography (OCT) which gives a view inside an artery with AI for better visualisation, enabling faster, more accurate decisions.

Using both tools together gives cardiologists a comprehensive view inside patients heart arteries, helping them to determine the best treatment for arterial calcification.

The software speeds up the operation, using infrared lasers and AI to measure how much of the artery is diseased and the size of stent required.

This helps ensure stents are more accurately fitted, leading to improved long term health for patients.

Consultant Interventional Cardiologist Dr Stuart Watkins said: As people get older they can develop hardening of the heart arteries due to calcification.

This makes treating the arteries difficult for cardiologists because calcium is very hard and it can limit the expansion of our stents.

Its very important to identify calcification in the heart arteries, which isnt always apparent from doing a basic coronary angiogram.

OCT gives us extremely detailed pictures within the arteries so that we can pick up calcification and determine the best treatment strategy before we put stents in.

Ultreon helps us quickly measure how much of the artery is diseased and what size of stent you have to put in, without taking too much time to do it.

One of the first patients treated with the new technology at the hospital was 85-year-old Chris Stevenson, originally from Duntocher, West Dunbartonshire, but now living in Larkhall, South Lanarkshire.

After suffering from heart problems from age 50, his condition worsened recently and he needed four stents fitted.

The retired mechanical engineer was awake for the three-hour procedure and hopes it will help him be more active.

He said: Ive been taking things quite slowly at the moment. My wife Betty wont even let me do my normal chores, but I feel fantastic.

Ive also had two knee replacements so I havent been able to do the hillwalking I love, but I would like to get back to just being able to go out and keep active, so hopefully this latest treatment will help me do that.

I know how hard the specialists worked for me, as well as all the staff who booked me in and cared for me on the ward. I cant praise them highly enough, they were amazing.

The hospitals medical director Dr Mark MacGregor said the technology is now on offer to patients across Scotland and provides the potential for significantly improved long-term outcomes.

He added: This new technology is an excellent advancement in treating coronary heart disease.

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Artificial Intelligence now used in life-saving operations for heart patients in Scotland - The Scotsman

Financial risk control and management is one of the most definitive early applications of AI in fintech. Image: Shutterstock

The AI apocalypse is here. Across industries, segments, walks of lifeone may not realise it but it is playing out large. Larger still is the opaque jargon and the hype around it. Not without basis though.

The race to reach the top has many participantsresearch institutes, top corporates, educational institutions, and even states around the world. Artificial intelligence-powered fintech startups are registering exponential growth and so is the venture capital funding for them. Adapting quickly to embrace digital and become an active part of the ecosystem is essential. Network-enabled co-creation is at the heart of the new digital transformation.

AI and fintechAI promises to completely transform everythingsome things more than others. The BFSI space has already seen the sheer efficiency of AI to process massive data logs and deliver masterful insights through pattern recognition. AI has made a huge difference in the world of payments and financial services which is plagued with incidences of identity fraud and imposter scams.

With the need to deliver better experiences and customer conveniences, AI enables better and faster fraud detection in a hyper-digitised world where PII (Personally Identifiable Information) is available for a few hundred dollars on the dark web. Advanced risk monitoring and fraud detection enables prediction and detection in real-time and not post factum.

From barter to paper currency to plastic money to contactless cards, the world of payments has come a long way. AI promises to usher in a new world of frictionless and seamless payments where the ubiquitous modern POS of today will look archaic. Amazons experiments to do away with the retail checkout queue are a good example.

AI and investingAI-powered robo-advisors are the 'in' thing what with their ability to go beyond mere algorithm power to considering far more complex parameters including a range of factors from tax-loss harvesting to financial planning.

The applications of AI include predicting consumer behaviour and enabling effective buying of hyper-relevant and personalised products, to offer tremendous opportunities to marketers of financial services.

Digitisation and decentralisation are at the core of powering the fintech revolution, enabled by AI. Besides AI, there is blockchain, robotic process automation, and data analytics which constitute other prominent technologies impacting fintech.

The structuring, delivery, and consumption of financial services have all been disrupted, courtesy AI, while the new technologies lend an umbrella branding to the fintech transformation. To capitalise on the opportunities being unleashed, it is imperative develop an enterprise-wide strategy and apply AI to revenue and customer engagement opportunities.

Financial risk control and management are the most definitive early applications of AI in fintech. It is helping restore trust in the financial systems and bringing inclusion with digital finance, bridging the gap between the hitherto unbanked and the banked. The pandemic has further hastened the pace at which AI adoption in fintech is becoming the norm.

The fintech market storyMordor intelligence predicts the AI fintech market at a projected $22-plus billion, growing at a CAGR of 23 percent by the year 2025. The top finance leaders around the world acknowledge the role of technologies led by blockchain and AI. The global fintech market has a predominant penetration in the APAC and Americas with the APAC market forecasted to be the fastest-growing region.

The frontrunners amongst Indian fintech companies using AI include Razorpay (AI-powered system Third Watch helps address fraud issues); INDmoney (AI-driven financial advisory); CogNext (regulatory tech company using AI through automated tech platform, Platform X); Capital Float; Credit Mate; Lending Kart, and Mswipe.

Industrial revolution 4.0 will see a fusion of technologies across physical, digital and biological spaces, and will allow reinventing the firm around data, connectivity, analytics and AI, which removes traditional limitations of scale, scope and learning.

The writer is an executive-in-residence at the Anderson School of Management, UCLA besides being a global CEO coach and C-Suite Advisor.

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How AI Is Transforming The World Of Finance - Forbes India

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The globalIoT in Agriculture Marketsize is expected to reach USD 30.8 billion by 2028, registering a CAGR of 10.6% over the forecast period, according to the latest report by Reports and Data.Major factors driving market revenue growth are the growing demand for agricultural output, increasing penetration of Internet of Things (IoT) & Artificial Intelligence (AI) technologies in the farming sector, and increasing government support for adoption of latest agricultural technologies along with growing focus on livestock monitoring to enhance efficiency in farming.

Internet of Things plays a critical role in increasing agricultural productivity. IoT technologies can solve agricultural problems and maximise the quantity and quality of agricultural production by linking farms via a shared network and providing them with information sharing, storage, and review options. In agriculture, the Internet of Things (IoT) is combined with advanced technological tools, equipment, and solutions to increase operational performance and minimise energy waste. In IoT-based smart farming, a system is designed to monitor crop field and automate irrigation system using sensors such as light, temperature, and humidity.

Some of the prominent companies in the market include Deere & Company, Trimble, Raven Industries, AGCO Corporation (AGCO), AgJunction Inc. (AgJunction), DeLaval, GEA Farm Technology, Lely, Antelliq, AG Leader Technology (AG Leader), Tigercat, Ponsse, Komatsu Forest AB, Caterpillar, Treemetrics, Topcon Positioning Systems, and DICKEY-john Corporation.

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Market Overview:

Information and communication technology (ICT) encompass a wide range of communication networks as well as the technologies that support them. The information and communication technology (ICT) sector bring together manufacturing and service businesses whose products primarily perform or enable information processing and communication via electronic methods, including transmission and display. The ICT sector contributes to technical advancement, increased output, and increased productivity. Its impact can be measured in a variety of ways: directly, as a contributor to output, employment, or productivity growth; or indirectly, as a source of technical development influencing other sections of the economy.

The IoT in Agriculture market has been segmented into key regions of the world and offers an analysis of growth rate, market share, market size, current and emerging trends, production and consumption ratio, industrial chain analysis, demand and supply, import and export, revenue contribution, and presence of key players in each region. A country-wise analysis of the market is offered in the report to gain a better understanding of the regional spread and progress of the IoT in Agriculture market.

The study throws light on the IoT in Agriculture market mainly focusing on the growth factors and even the restraining factors. The restraining factors are also provided with the best solutions which also prove to be a counteract to the drawback and help increase the market demand. Applications, types, technology and many other segmentations are studied to give a depth of knowledge for further market investment. Key driving forces for IoT in Agriculture market is explained to help give an idea for a detailed analysis of this market.

The report also implements primary and secondary research techniques for gathering the most crucial pieces of professional information, and applies a number of industry-best techniques upon the data for projecting the future state of the global IoT in Agriculture market. Based on current market development, the report includes an analysis of how activities such as mergers and shapes the markets future.

Conclusively, all aspects of the IoT in Agriculture market are quantitatively as well qualitatively assessed to study the global as well as regional market comparatively. This market study presents critical information and factual data about the market providing an overall statistical study of this market on the basis of market drivers, limitations and its future prospects.

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