Category Archives: Artificial Intelligence

WEST FARGO, N.D. If a farmer didn't have to spray his entire field but could instead target weeds at their earliest stage and stop infestations before they start, the cost savings could be immense. Plus, consumers increasingly want less herbicides and other chemical applications applied to food crops, and agriculture continues to strive to be more environmentally friendly.

Dr. Rex Sun, an assistant professor in the department of Agriculture and Biosystems Engineering at North Dakota State University, and his team will have a new technology on display at the 2022 Big Iron Farm Show, Sept. 13-15 in West Fargo, that they think will accomplish those goals a remote control "weedbot" that uses artificial intelligence and robotics to perform site specific weed management.

The daily demonstrations at 1 p.m. will involve bringing real weeds from an NDSU greenhouse and showing how the robot identifies and eliminates them.

"Right now, the farmers are spraying weeds on the whole field, but we don't want to do that," Sun said. "So hopefully by using our precision agriculture technologies like robotics and AI, they can use this robot and identify the early stage and make that solution right on the spot so we don't have to spray the whole field."

The robot is in proof-of-concept stage, and there are improvements left to be made, Sun said, noting that a robot that uses mechanical means to eliminate weeds or systems that look for pests and disease are possible, too.

"This kind of platform, it can customize depending on what kind of applications the farming industry needs," he said.

While the robot is not autonomous, that is another possibility down the road, he said.

John Nowatzki, a retired agricultural machine systems specialist at NDSU who serves on the Big Iron Committee, said another demonstration will be a repeat from last year, with Titan Machinery and Raven Industries showing off their autonomous grain cart technologies . The demonstration will be west of the food court this year, because the space south of the racetrack used in the past is now a corn maze.

Hundreds of vendors also will be on hand at Big Iron, and many are preparing to show off new products or explain popular existing ones.

Nick Chiodo, marketing manager at Crary Industries, said Crary will have their Wind System on display for those who haven't seen it and experts to explain it. The system is an attachment for a soybean header that reduces shatter loss and feeds the combine more evenly through the blowing of high velocity air. Chiodo said the system can increase bushels per acres by as much as 5, with configurations that fit on most brand-name headers.

"Anywhere that grows soybeans, we're probably out there," he said.

They'll also have information and experts on their Revolution Ditcher, for use in cleaning out water ways, ditches or terraces. Chiodo said they'll have the "latest and greatest" on that in their booth.

Crary is planning a Dec. 15 event called Full Pod, which will feature famous farm YouTubers. For the cost of their ticket, attendees at that event will get dinner, a hooded sweatshirt, a grab bag and a chance to win door prizes, as well as opportunities to interact with the YouTubers and other farmers. Chiodo said anyone who has registered for the event can show their ticket at the booth and be entered to win a Grizzly cooler with the Full Pod log.

Big Iron is a must for Crary, Chiodo said. Crary is located close at hand to the fairgrounds.

"It's right across the street from us," he said. "It's our backyard."

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Big Iron Farm Show demonstration will show the potential of artificial intelligence and robotics in ag - Agweek

Stretched over 344,000 square kilometres, the Great Barrier Reef in Australia is the biggest coral reef system in the world and an important marine biodiversity hotspot. But, the natural wonder that can be seen from space is in poor health. Now, researchers are looking to leverage citizen science crowdsourcing and artificial intelligence to help plan conservation efforts better.

According to a study published in 2012, the Great Barrier Reef has lost over half its coral since 1985. Added to that, climate change has caused the reef to suffer from various bleaching events, or when the coral expels the algae living in its tissue due to the water being too warm. When coral reefs bleach, they are not yet dead. They can still recover if conditions improve, but it is estimated that it takes them up to 12 years.

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While conservation efforts are ongoing for the Great Barrier Reef, there is another issue. The sheer size of the reef system and the land that it occupies means that these efforts can only be focused on small sections. According to Andy Ridley, CEO and founder of Citizens of Great Barrier Reef, which conducts the Great Reef Census, researchers have only been able to monitor around five to ten per cent of the 3,000 individual reefs in the system in the past. This makes informed conservation decisions difficult.

The Great Reef Census helps solve this issue by using thousands of images captured by volunteers on dive boats, tourism vessels, yachts, fishing charters, and tug boats to survey images from the Reef. It then uses these images to understand the health of the reefs and to identify the locations where conservation efforts must be focused. As part of the project, researchers from the University of Queensland, Dell Technologies, and other organisations have partnered to leverage artificial intelligence and crowdsourcing to help understand the reef better. Two Great Reef censuses have already been conducted.

In the second census, the researchers first crowdsourced over 40,000 images of coral in the Great Barrier Reef from thousands of volunteers. Then, the challenge was tagging and identifying the coral species within the images to see which ones needed to be studied by marine biologists. Volunteers then tagged and identified various different coral species, which turned out to be a time-consuming process.

That is where the deep learning model developed by Dell Technologies came in. Using this data from the volunteers, Dell trained a deep learning model to analyse every pixel in an image to classify the reel and coral infrastructure.

The deep learning model first identifies which part of the image contains coral. And then, it is able to classify them if they belong to five selected species of coral. It is limited to five right now to maintain accuracy. This data, combined with the location data of the image can provide researchers with a snapshot of what kind of corals exist where. The researchers can then ascertain the health of the coral from selected images. They can then use this data to prioritise which reef must be conserved first, said Aruna Kolluru, chief technologist, Emerging Technology at Dell, to indianexpress.com over a video interaction.

This means that the deep learning model can take on the repetitive and tedious task of identifying and classifying the coral, freeing up volunteers for tasks that still require human input. These images can be analysed by marine biology experts if necessary based on this identification and classification. Currently, the model takes one minute to analyse an image.

According to Dells Kolluru, the deep learning model can further be improved to not only analyse images more accurately but to also be able to identify more species of coral. But for that, it needs to be trained on much larger numbers of images and data points.

For example, if you want to train a model to identify a car, you need to train it on many different kinds of images. It could be images of different parts of the car, like the tyres or the doors. It would also need to be trained on images of cars from different angles and with different lighting conditions. With all this data on how a car looks like in different images, it will better understand how to identify a car, explained Kolluru.

As the model develops further, researchers envision using it to protect other reef systems globally. We hope to expand the Census globally and build on the globally-available Allen coral atlas so that everyone can develop data on the most ecologically important reefs in their jurisdiction. The deep learning model will help standardise and support the ability of citizens to map the state of reefs worldwide, said Peter Mumby, a coral reef ecologist at the University of Queensland, to indianexpress.com over email. Mumby is part of the Great Reef Census team.

Ridley of Citizens of Great Barrier Reef told indianexpress.com that the third Great Reef Census will kick off in October. As the researchers develop the censuss methods, they are also ensuring these methods and technology are scalable and can be used to conduct similar research with other reef systems across the globe.

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Using citizen science and artificial intelligence to help conserve the Great Barrier Reef - The Indian Express

HOLLYWOOD, Fla.--(BUSINESS WIRE)--Great Speech, a pioneer and leader in virtual speech therapy, today announces patient matching Artificial Intelligence (AI) technology to optimize pairing patients with the most qualified speech therapists in our network for a patients specific condition. The AI technology considers multiple data points to create the best-indicated therapy/patient care partnership to provide more specialized care, more focused therapy and faster results in a shorter timeframe.

"We take pride in our ability to match each patient to the most qualified therapist with expertise in that specific diagnosis, says Avivit Ben-Aharon M.S. Ed, M.A. CCC-SLP, founder and clinical director, Great Speech. Drawing on our extensive network of more than 200 licensed speech therapists in 45 states, our technology identifies the therapist who has relevant specialty training, experience and distinct strengths to provide an optimal patient experience.

Each speech therapist in the Great Speech network has subspecialty training in particular aspects of a communication disorder. The AI technology platform works much like a primary care provider referring a patient to a specific medical specialist with expertise treating a particular condition.

AI is a valuable tool we now have to deliver the best care for our patients, explains Ben-Aharon. If a Medicare Advantage member with Parkinsons is learning to strengthen the muscles used for swallowing and speaking, they have a different need than a patient with Alzheimers disease who is working to manage memory deficits or teenagers who stutter and are working on improving the ability to express themselves.

AI is being rapidly adopted by healthcare leaders for efficient diagnosis and safer services. Great Speech patients benefit from more objective assessment and personalized therapy with AI assist. As an early adopter of treatment technology, Great Speech expects that AI will offer significant advantages for patients and help improve outcome in the future.

About Great Speech Inc.Great Speech Inc. is the pioneer and recognized leader in virtual speech therapy, and since 2014 has delivered convenient, specialized services to clients anytime, anywhere. Its innovative approach leverages technology to match credentialed therapists with children, adults and seniors who need and seek better speech communication. Proud recipient of the Womens Business Enterprise National Council (WBENC) certification. http://www.greatspeech.com

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Great Speech Develops Artificial Intelligence Platform to Refine Matching Process Between Patients and Most Qualified Speech Therapist - Business Wire

Chicago, Sept. 01, 2022 (GLOBE NEWSWIRE) -- Artificial Intelligence (AI) Robots Marketby Robot Type (Service, and Industrial), Technology (Machine Learning, Computer Vision, Context Awareness, and NPL), Offering, Application, and Geography (2021-2026)", Players profiled in this report are SoftBank (Japan), NVDIA (US), Intel (US), Microsoft (US), IBM (US), Hanson Robotics (China), Alphabet (US), Xilinx (US), ABB (Switzerland), Fanuc (Japan), Alphabet (US), Harman International (US), Kuka (Germany), Blue Frog Robotics (Paris).

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Browse in-depth TOC on Artificial Intelligence (AI) Robots Market178 - Tables81- Figures253 Pages

NVIDIA develops GPUs and delivers value to its consumers through PC, mobile, and cloud architectures. From focus on PC graphics, the company now emphasizes machine learning and various other AI technologies. NVIDIA addresses four large markets: gaming, visualization, data center, and automotive. NVIDIA has two reportable segments: Graphics and Compute & Networking. The Graphics segment includes GeForce GPUs for gaming and PCs, the GeForce NOW game-streaming service and related infrastructure, and solutions for gaming platforms; Quadro/NVIDIA RTX GPUs for enterprise design; GRID software for cloud-based visual and virtual computing; and automotive platforms for infotainment systems.

Intel provides computing, networking, data storage, and communication solutions worldwide. The company designs and develops key products and technologies that power the cloud and smart, connected world. Intel delivers computer, networking, and communication platforms to a broad set of customers, including OEMs, original design manufacturers (ODMs), cloud and communications service providers, and industrial, communications, and automotive equipment manufacturers. The company manufactures semiconductor chips, supplies the computing and communications industries with chips, boards, systems, and software that are integral in computers, servers, and networking and communications products.

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This research report categorizes the AI Robots market based on offering, robot type, technology, deployment mode, application and region.

AI Robots Market, by offering

AI Robots Market, by Robot Type

AI Robots Market, by Technology

AI Robots Market, by Deployment mode

AI Robots Market, by Application

Implementing automation technology and installing industrial robots throughout the production processes has helped industrial businesses enable human employees to dedicate more time to other demanding projects. This has improved quality, reduced risks for associates with dangerous tasks, and lowered the overall operational costs. As labor costs rise, automation technologies come as alternate options. Robots help complete monotonous tasks more quickly and consistently than humans.

With the adoption of technologies such as cloud computing, robots are now becoming networked. For instance, Ozobot & Evollve (US) offers Evo, which is equipped with OzoChat software for worldwide messaging between Evo robots. These networked robots can potentially be hacked, and their abilities can be adversely used. Also, global military & defense sector has started considering AI-based robots as a vital part of any military fleet.

AI-integrated robots are gaining traction with the increasing requirement of social robots to interact with humans and for assistance, among others. Assistant robots need to perform various tasks involving home security, patient care, companionship, and elderly assistance. Companies are now increasingly focusing on developing robots that are suitable for the entire family and excel in performing the abovementioned tasks.

Related Reports:

Artificial Intelligence in Manufacturing Market by Offering (Hardware, Software, and Services), Industry, Application, Technology (Machine Learning, Natural Language Processing, Context-aware Computing, Computer Vision), & Region (2022-2027)

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Artificial Intelligence (AI) Robots Market Projected to Reach worth $35.3 billion by 2026 Exclusive Report by MarketsandMarkets - GlobeNewswire

Monitoring and measuring forest ecosystems is a complex challenge because of an existing combination of softwares, collection systems and computing environments that require increasing amounts of energy to power. The University of Maines Wireless Sensor Networks (WiSe-Net) laboratory has developed a novel method of using artificial intelligence and machine learning to make monitoring soil moisture more energy and cost efficient one that could be used to make measuring more efficient across the broad forest ecosystems of Maine and beyond.

Soil moisture is an important variable in forested and agricultural ecosystems alike, particularly under the recent drought conditions of past Maine summers. Despite the robust soil moisture monitoring networks and large, freely available databases, the cost of commercial soil moisture sensors and the power that they use to run can be prohibitive for researchers, foresters, farmers and others tracking the health of the land.

Along with researchers at the University of New Hampshire and University of Vermont, UMaines WiSe-Net designed a wireless sensor network that uses artificial intelligence to learn how to be more power efficient in monitoring soil moisture and processing the data. The research was funded by a grant from the National Science Foundation.

AI can learn from the environment, predict the wireless link quality and incoming solar energy to efficiently use limited energy and make a robust low cost network run longer and more reliably, says Ali Abedi, principal investigator of the recent study and professor of electrical and computer engineering at the University of Maine.

The software learns over time how to make the best use of available network resources, which helps produce power efficient systems at a lower cost for large scale monitoring compared to the existing industry standards.

WiSe-Net also collaborated with Aaron Weiskittel, director of the Center for Research on Sustainable Forests, to ensure that all hardware and software research is informed by the science and tailored to the research needs.

Soil moisture is a primary driver of tree growth, but it changes rapidly, both daily as well as seasonally, Weiskittel says. We have lacked the ability to monitor effectively at scale. Historically, we used expensive sensors that collected at fixed intervals every minute, for example but were not very reliable. A cheaper and more robust sensor with wireless capabilities like this really opens the door for future applications for researchers and practitioners alike.

The study was published Aug. 9, 2022, in the Springers International Journal of Wireless Information Networks.

Although the system designed by the researchers focuses on soil moisture, the same methodology could be extended to other types of sensors, like ambient temperature, snow depth and more, as well as scaling up the networks with more sensor nodes.

Real-time monitoring of different variables requires different sampling rates and power levels. An AI agent can learn these and adjust the data collection and transmission frequency accordingly rather than sampling and sending every single data point, which is not as efficient, Abedi says.

Contact: Sam Schipani, samantha.schipani@maine.edu

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Artificial intelligence can be used to better monitor Maine's forests, UMaine study finds - UMaine News - University of Maine - University of Maine

The use of artificial intelligence by public bodies is to be monitored by Britains equality regulator for the first time to ensure technologies are not discriminating against people.

There is emerging evidence that bias built into algorithms can lead to less favourable treatment of people with protected characteristics such as race and sex.

The Equality and Human Rights Commission has made tackling discrimination in AI a major strand of its new three-year strategy.

It is today publishing new guidance to help organisations avoid breaches of equality law, including the public sector equality duty (PSED). The guidance gives practical examples of how AI systems may be causing discriminatory outcomes.

From October, the Commission will work with a cross-section of 30 local authorities and other public bodies in England and Scotland to understand how they are using AI to deliver essential services, such as benefits payments, amid concerns that automated systems are inappropriately flagging certain families as a fraud risk.

The EHRC is also exploring how best to use its powers to examine how organisations are using facial recognition technology, following concerns that the software may be disproportionately affecting people from ethnic minorities.

These interventions will improve how organisations use AI and encourage public bodies to take action to address any negative equality and human rights impacts.

Marcial Boo, chief executive of the EHRC, said:

While technology is often a force for good, there is evidence that some innovation, such as the use of artificial intelligence, can perpetuate bias and discrimination if poorly implemented.

Many organisations may not know they could be breaking equality law, and people may not know how AI is used to make decisions about them.

Its vital for organisations to understand these potential biases and to address any equality and human rights impacts.

As part of this, we are monitoring how public bodies use technology to make sure they are meeting their legal responsibilities, in line with our guidance published today. The EHRC is committed to working with partners across sectors to make sure technology benefits everyone, regardless of their background.

The monitoring projects will last several months and will report initial findings early next year.

The Artifical Intelligence in Public Services guidance advises organisations to consider how the PSED applies to automated processes, to be transparent about how the technology is used and to keep systems under constant review.

In the private sector, the EHRC is currently supporting a taxi driver in a race discrimination claim regarding Ubers use of facial recognition technology for identification purposes.

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Equality watchdog takes action to address discrimination in use of artificial intelligence - PoliticsHome

Published on: 08/31/2022 15:03 PM

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The Artificial Intelligence (AI) and Emerging Technologies (ET) Partnership Series will hold itsnext meeting,AI/ET Partnership Series #2: AI & Biotech, virtually and in person at the United States Patent and Trademark Office's (USPTO) Silicon Valley Regional Office on September 22, 2022 from 9:30 a.m. to noon PT. During this meeting, panelists from industry and the USPTO will explore various patent policy issues with respect to the biotech industry, including:

A full agenda with speakers will be posted prior to the event. This event is free and open to the public, so register early to attend in person or virtually.

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Save the date: Artificial Intelligence and Emerging Technologies Partnership meeting #2 on September 22 - United States Patent and Trademark Office

Until recently, coding involved repetitive tasks, and required knowledge of many minute details. These aspects of coding detracted from the truly creative work that developers enjoy, and they slowed developers down.

Now, artificial intelligencetechnology promises to eliminate much of that repetitive work, and developers are no longer thrown off task by having to search the web for those minute details.

The technology works similarly to auto-complete in word processing but writing code instead of plain language and completing whole functions at a time.

Among the latest offerings in AI-powered is Github's Copilot, an AI-powered pair programmer tool available to all developers for $10 a month or $100 per year.

The company claims Copilot can suggest complete methods, boilerplate code, whole unit tests, and even complex algorithms.

With AI-powered coding technology like Copilot, developers can work as before, but with greater speed and satisfaction, so its really easy to introduce, explains Oege De Moor, vice president of GitHub Next. It does help to be explicit in your instructions to the AI.

He explains that during the Copilot technical preview, GitHub heard from users that they were writing better and more precise explanations in code comments because the AI gives them better suggestions.

Users also write more tests because Copilot encourages developers to focus on the creative part of crafting good tests, De Moor explains. So, these users feel they write better code, hand in hand with Copilot.

He adds that it is, of course, important that users are made aware of the limitations of the technology.

Like all code, suggestions from AI assistants like Copilot need to be carefully tested, reviewed, and vetted, he says. We also continuously work to improve the quality of the suggestions made by the AI.

GitHub Copilot is built with Codex -- a descendent of GPT-3 -- which is trained on publicly available source code and natural language.

Because it was trained both on source code and natural language, you can write a comment in English, and then Codex will suggest the code that follows, De Moor explains. In fact, it can even write an entire function or class just given its description in English.

Tabnine CEO Dror Weiss says in the future, AI assistants will be able to review code for developers, create tests automatically, assist with debugging, and do clever automated maintenance operations on systems.

Eventually, every activity that can be automated, will be automated, he says.

From his perspective, a critical feature for organizations is the ability to integrate the specific best practices and code patterns for projects and organizations.

Using this kind of customized AI, organizations will benefit not just from acceleration but also from better consistency and quality of the code, he explains. Another benefit is reducing the time it takes for developers to become highly productive when joining a new project.

One major advantage of AI-assisted coding tools is context-aware code completion.

Microsoft's Visual Studio IntelliCode, for example, is a set of AI-assisted capabilities that enable developers to efficiently complete code with features like argument completion, code formatting, and style rule reference.

IntelliCode is trained on the code of thousands of highly rated open source projects on GitHub, and it uses context from the current code to make relevant recommendations.

Since launching IntelliCode, Microsoft has made updates such as whole-line code completions and refactoring and suggestions that enhance repeated edit experiences to save time for developers.

For organizations planning to implement a strategy involving AI coding assistants, Weiss says making a roadmap is key.

Organizations need to think strategically and have a vision of how they want to leverage AI, even as some essential functionality isn't yet available in any of the products in the market, he says.

He explains a logical first step toward implementing AI assistance would be identifying a specific group of developers and let them use AI based on pre-trained models that learned code patterns from publicly available code.

After a successful implementation, organizations can start rolling out to other groups. In parallel, they can tailor their AI assistance to their needs by creating custom AI models based on their code.

De Moor also points out developers spend much of their time on other tasks, and soon, those other tasks will also benefit from AI assistance.

Examples of these other tasks that are ripe for AI assistance are code review, testing, and refactoring.

Will this change the job of developers? Sure, but for the better, De Moor says. I do not foresee a future where Copilot produces anything useful without human input, but I do see unbridled human creativity, no longer bogged down by irrelevant detail.

He says programming is now about design (decomposing a large problem into smaller ones), and then specifying what the smaller blocks should do -- and the AI will fill in the details.

Weiss adds that as every company is becoming a software company, software development is every organization's most strategic and resource-constrained activity.

Companies are starting to meet the limits of how many developers they can get and getting smaller teams more productive is paramount -- even more so in a downturn as teams could be understaffed, he says. We believe that AI is the most effective way to make developers and teams more productive and will be the natural next step for every organization that has adopted basic DevOps and CI platforms.

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The Power of Artificial Intelligence Coding Assistance - InformationWeek

From Google Home to Alexa, the role of artificial intelligence (AI) seems to have grown over the years. It is now believed that AI will play a greater role when it comes crypto being traded. As a greater number of financial institutions start offering crypto-assets as wealth management offering, the roles of AI-supported trading will become more popular. There are over 4,000 cryptocurrencies and even the oldest coins show large fluctuations in their prices. Likewise, Bitcoin 30-day volatility index is twice the value from 2016 (as per data published on buybitcoinworldwide), Saurav Raaj, founder, director, Wize, a non-fungible token (NFT) infrastructure for businesses company, told FE Digital Currency.

As per industry observers, AI is used in intelligent trading systems for stock market prediction and currency price prediction. As per a report by IEEE Access, Generalised Autoregressive Conditional Heteroskedasticity (GARCH), is a time-series statistical model used for understanding volatility. AI is in the area of market sentiment analysis. Unlike traditional stocks, discussions among trading communities and social media reports, can drive trading decisions. AI with natural language processing (NLP) can analyse market and community sentiments and provide valuable insights to the traders, Raaj added.

Courtesy: IEEE Access, ResearchGate.

It is believed that trading decision is usually based on behavioural biases that cause them to act on an emotion which could lead to mistakes while processing information. AI-guided crypto trading is unlikely to get rid of emotional factors, it is likely to amplify that via machine learning. A deliberate fix in AI programmes to avoid trading at large corrections, and surges may help. Still, it is also likely to slow the usual stop-loss or take-profit exercise, Liquing Yu, Economic Intelligence Units (EIU) analyst on India, Indonesia, and Singapore, said.

Furthermore, industry experts noted that if properly implemented and trained, AI can help eliminate human bias. According to Vikram Pandya, director, Fintech, SP Jain, it definitely helps make scientific decisions backed by data and not by impulse.

According to Business Insider Report in June 2019, there are three areas where AI is used in banking, namely, conversational banking, anti-fraud detection, risk assessment, and credit underwriting. AI-based systems can help to process trading data which can assist traders to make better investment decisions. AI with machine learning (ML) can provide safeguards against such attacks and reduce damages in real-time. In extreme cases, it can be utilised to trigger circuit breakers and even stop trading, added Raaj.

Also Read: From centralisation to decentralisation; how blockchain-oriented fintech can benefit the financial sector

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From Google Home to Alexa, Artificial Intelligence to play large in trading of cryptocurrencies - The Financial Express

INNISFAIL, Australia (PRWEB) September 02, 2022

Mark C. Giffin announces his entry into the publishing scene with the release of Electronics One: Book 1 (published by Balboa Press AU), a fiction novel that delves into the emerging field of AI, its benefits and disadvantages.

Stephen Frost enjoys becoming a very rich man by being able to use AI. While working hard and inventing an AI doll as well as an electronic body armor and a fuel saving device, he meets his future wife Svetlana who had studied at a facility designed to train women into keeping a millionaire happy and contented. However, Stephen also realized there was a dark side that could come from all this.

Stephens ability in AI almost got Svetlana kidnapped. His own AI attacked the Pentagon, and then, someone else did the same. He knew it would only be a matter of time before someone designed a powerful AI that would be used for evil purposes. His wife, future children, the great American dream, and the safety of people in general were important to him. At the same time, he would want to keep up his research to produce new technologies to help humanity but there would be many challenges ahead.

Artificial intelligence is emerging as more and more real to people, with its pros and cons. The book puts forward possible advantages and threats relating to AI. It is a unique story with Stephen and his wife and artificial intelligence that has been the core of his life, Giffin says. When asked what he wants readers to take away from the book, he answers, Artificial intelligence is an exciting realm with dire consequences if used wrongly. By itself, artificial Intelligence should not go unchecked and out of control. For More details about the book, please visit https://www.balboapress.com/en-au/bookstore/bookdetails/841232-electronics-one

Electronics One: Book 1By Mark C. GiffinSoftcover | 6 x 9in | 200 pages | ISBN 9781982295110E-Book | 200 pages | ISBN 9781982295127Available at Amazon and Barnes & Noble

About the AuthorMark C. Giffin grew up in Queensland, Australia. He worked in the field of medical imaging while maintaining an interest in karate and cars. He became a black belt third dan and still teaches today. His cars include a four-wheel drive and a V8 sports sedan. Over the last 15 years, he has made a number of trips to the U.S. for up to three months, spending most of this time in Florida. He has also had an interest in emerging AI.

Balboa Press Australia is a division of Hay House, Inc., a leading provider in publishing products that specialise in self-help and the mind, body and spirit genre. Through an alliance with the worldwide self-publishing leader Author Solutions, LLC, authors benefit from the leadership of Hay House Publishing and the speed-to-market advantages of the Author Solutions self-publishing model. For more information or to start publishing today, visit balboapress.com.au or call 1-800-844-925.

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New fiction novel delves into the emerging field of artificial intelligence, its benefits and disadvantages - PR Web