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It is expected that by 2050, the Earths population will grow to 10 billion people or more. While it is possible that some limited new land can be brought under cultivation, it is clear that the worlds farmers will have to produce far more food with only scant increases of tillable land. Artificial Intelligence (AI) will be the farmers tool in achieving this goal.

As described in an article published by the University of Florida[1], farmers can now collect and analyze vast amounts of data about their crops. This includes weather patterns, soil health, and plant growth. Through the use of AI, modern farmers can improve their methods, making it possible to improve their crop yields, reduce waste and ultimately increase profitability.

As we face the daunting challenge of feeding a burgeoning global population, the role of AI in agriculture becomes increasingly pivotal. According to experts from the University of Florida:

"With the help of AI to optimize farming practices, farmers can improve their crop yields, reduce waste, and increase profitability. Accurate and timely data can make the difference between a successful or unsuccessful crop cycle, making it crucial for farmers to leverage technology and data to their advantage."

This insight highlights the critical role of AI in enhancing agricultural productivity and sustainability, essential for meeting the food demands of a growing population with limited arable land.

A critical challenge faced by farmers is sustainability. Forbes[2] reports that fully eleven percent of global emissions come from agriculture and that almost 40% of food produced in the US ends up being wasted. We also learn that just shy of two-thirds of the antibiotics used today are used to treat livestock that are ultimately intended to feed people and not to treat people and their illnesses directly. This is a direct cause of antibiotic resistance that is now emerging as a major factor in healthcare. Agricultural AI can go a long way towards alleviating these issues and more.

Agricultural artificial intelligence is a fast-evolving field, with significant new announcements out almost daily. Lets look at some of the AI generalities that also apply specifically to agricultural AI and also at some of whats even now available for todays farmers.

Machine learning is an essential part of AI, including agricultural AI. An article by MIT[3] quotes AI pioneer Arthur Samuel, defining machine learning as the field of study that gives computers the ability to learn without explicitly being programmed.

Traditional computer programming requires creating complete instructions for a computer to follow based on clearly defined inputs in order to accomplish a task. Machine learning, on the other hand, involves allowing computers to program themselves.

The first step is to garner a vast amount of data relevant to the need. In general, the inputs might be repair statistics, sensor data, or repair reports. The next step is to study the observed cause-and-effect relationships between the data elements in a dizzying array of combinations. Machine learning then puts the pieces together, and based on the patterns observed, it can predict future relationships with a high degree of reliability.

One of the things machine learning can do is to distinguish a tiny weed from a tiny plant.

TheLASERWEEDERscours a farmers land and employs AI to determine what each entity it encounters is a nascent crop plant or a weed. The machine, described as a mobile data center, can determine the difference between 40 crops and 80 types of weeds. If a weed is detected, a killer laser destroys the weed in milliseconds.

As described in a video fromCarbon Robotics [4], this AI-based device can take the drudgery out of farm work. NBC describes it as a killer robot with an AI brain, but its victims arent enemy combatants; rather, its targets are weeds!

LASERWEEDERvideo 2 min 3 seconds

The device, costing $1.2 million, can work 24 hours a day and can replace 30 farm workers who are becoming increasingly difficult to find and hire. In some ways, it can outperform human workers in that it finds immature weedlings that are too small for the workers to deal with.

Because the LASERWEEDER destroys weeds with lasers and not with pesticides, its a natural option for organic farmers. Its also reported that the data gleaned from the weed-killing process will be invaluable to farmers, providing them with real-world insights that will allow them to produce more food economically.

The LASERWEEDER, a brainchild of Carbon Robotics, is redefining weed control in agriculture. Here's the tech magic behind it:

High-Tech Vision and Precision: The LaserWeeder uses 42 high-resolution cameras combined with state-of-the-art computing to distinguish between crops and weeds in real-time. This isn't just a camera snapping pictures; it's a sophisticated AI system with deep-learning-based computer vision models that can tell a weed from a crop with sub-millimeter accuracy.

Laser Power: Armed with 30x 150W CO2 lasers, the LaserWeeder is ready to fire every 50 milliseconds. Imagine the precision and speed it's like having a sniper in the field, targeting only the bad guys (weeds, that is) and leaving the good guys (crops) untouched.

Environmental Benefits: This isn't just about zapping weeds. The LaserWeeder's method is a leap towards sustainable farming. By using lasers instead of chemicals, it leaves the soil microbiology undisturbed, unlike traditional tillage. This means healthier soil, healthier crops, and a happier environment. Plus, it's a boon for organic farming, offering an economical path to weed control without herbicides.

Efficiency and Cost-Effectiveness: Think about the labor and cost savings. The LaserWeeder can kill up to 200,000 weeds per hour and cover 2 acres per hour at 1mph. It works day or night, in all conditions, significantly cutting down the manual labor and the variable costs associated with traditional weed control methods.

In a nutshell, the LASERWEEDER is more than just a tool; it's a revolution in agricultural practices, aligning with the goals of increased efficiency, sustainability, and environmental responsibility.

The agricultural sector is facing a significant labor challenge, especially with the growing scarcity of willing workers. This is where AI and automation step in as game-changers.

Reducing Dependence on Manual Labor: AI-driven technologies, like the LASERWEEDER, are prime examples of how automation can significantly reduce the need for manual labor in farming. These technologies are capable of performing tasks that traditionally required a large workforce, such as weeding, harvesting, and monitoring crop health.

Enhancing Efficiency and Productivity: With AI, tasks are not only done faster but also with greater precision. For instance, AI-powered drones can monitor crop health over large areas within a fraction of the time it would take humans. This efficiency translates into higher productivity and, ultimately, better yields.

Addressing Labor Shortages: In regions where there is a shortage of agricultural workers, AI and automation provide a viable solution. Automated machinery and AI systems can operate around the clock, compensating for the lack of human labor and ensuring that agricultural operations do not suffer.

Shifting the Workforce Dynamics: As AI takes over more labor-intensive tasks, the role of the agricultural workforce is evolving. There's a growing need for skilled personnel to manage, maintain, and supervise these AI systems. This shift is creating new job opportunities that focus more on technology management rather than manual labor.

In essence, AI and automation are not just addressing the labor challenges in agriculture; they are transforming the very nature of farming work. By reducing the reliance on manual labor, these technologies are paving the way for a more efficient, sustainable, and productive agricultural sector.

As described by NVIDIA[5], Generative AI enables users to quickly generate new content based on a variety of inputs. Inputs and outputs to these models can include text, images, sounds, animation, 3D models, or other types of data. It works by identifying patterns and structures within existing data to generate new and original content.

The most famous example of Generative AI is, of course, ChatGPT.

As a start, farmers can use CHATgpt directly to get information. There are also specific platforms for agriculture. The Farmers Business Network[6] (FBM) describes a platform called, simply,NORM. The model concentrates on information of use to farmers. As described, examples of questions that can be asked are:

As detailed by Ambrook[7], NORM is built on OpenAIs GPT-3.5 model, and uses public data like weather reports, soil data, and product labels to answer ag-related questions. It also taps into FBNs exclusive agronomic data and assets from the USDAs National Agricultural Statistics Service.

Another example is farmer.Chat[8]. Thisvideoillustrates a farmer employing this Farmer.CHAT to get information about a problem area in his field.

Farmer.CHAT. by Gooey AI

The rest of the video illustrates the interactions between the farmer and farmer.CHAT, as the latter proposes solutions to the insect problem.

The potential of generative AI in agriculture is vast and varied. From tackling diseases to optimizing yields and revolutionizing crop breeding, AI is not just a tool but a transformative force in the agricultural sector. As technology evolves, we can expect even more innovative applications that will continue to reshape the future of farming.

Now, let's dive into how AI is not just a buzzword but a real game-changer on the farm. The folks at the University of Florida are onto something big here. They're talking about AI applications that are not just smart, but also kind to our planet:

Smart Watering Systems: Imagine a system that knows exactly when your crops are thirsty. That's what AI-driven irrigation is all about. It's like having a weatherman and a soil expert right in your field, ensuring every drop of water is used where it's needed most.

Predicting the Future of Crop Prices: Here's where AI flexes its economic muscles. By crunching numbers on climate trends and market shifts, AI helps farmers make savvy decisions. Less waste, more profit that's the kind of math farmers love.

Self-Driving Tractors? Yes, Please!: Deep learning is bringing the future to farms with autonomous tractors. These aren't your granddad's tractors they're high-tech beasts that know their way around a field, dodging obstacles and getting the job done with no coffee breaks.

Weed Zapping with Precision: Thanks to AI, we're seeing a revolution in weed control. Systems like John Deere's Blue River See & Spray are like snipers, taking out weeds with pinpoint accuracy. This means less herbicide on our food and in our environment. It's a win-win for farmers and Mother Nature.

Crop Disease Prediction:One of the most promising applications of generative AI is in the early detection and prediction of crop diseases. By analyzing vast datasets, including images of crop fields, weather patterns, and historical disease outbreaks, AI models can predict potential disease outbreaks before they become visible. This early warning system allows farmers to take preemptive actions, reducing the spread of disease and minimizing crop damage.

Yield Optimization:Generative AI is also playing a pivotal role in yield optimization. It can analyze data from various sources soil quality, weather conditions, crop health to generate recommendations for optimal planting, irrigation, and harvesting times. This not only maximizes yield but also ensures efficient use of resources.

Customized Crop Cultivation Plans:Another exciting application is the creation of customized crop cultivation plans. Generative AI can process data specific to a farmer's land, such as soil type, microclimate, and previous crop cycles, to generate tailored farming strategies. This personalized approach can significantly boost productivity and sustainability.

Enhancing Genetic Crop Improvement:In the field of genetic crop improvement, generative AI stands as a transformative force. It has the capability to simulate countless genetic combinations, enabling it to forecast traits that enhance crop resilience, nutritional value, and yield. This advanced approach significantly speeds up the breeding process, facilitating the creation of superior crop varieties more efficiently than conventional methods.

So, there you have it. AI in agriculture is more than just a fancy term it's making farming smarter, more sustainable, and, dare I say, cooler. It's not just about growing more food; it's about growing food the right way.

As described in an article posted by the University of Arkansas in The Arkansas Journal of Social Change and Public Service[9], 73% of the crop farmworker population in the United States are immigrant workers, and about 48% of hired crop farm workers have no work authorization.

The lack of willing workers, foreign, let alone US citizens, is a tremendous problem facing American agriculture. The answer is automation, and the 185-year-old John Deere company is jumping full steam into the AI revolution.

Simplifying agricultural automation is the fact that, like the factory floor, a farm is a work environment where everyone knows their job and both act and react in proscribed ways. This is entirely unlike the bedlam of busy city streets. So, while self-driving cars are going nowhere fast, the farm is a far more advantageous environment for driverless vehicles.

John Deeres autonomous 8R Farm Tractor.

As described in a report published by CNBC[10], John Deere has taken up the challenge presented by this opportunity in the form of its 8R Farm Tractor, which doesnt need a driver and instead relies on AI. Deere has curated hundreds of thousands of images from different farm locations and under various weather and lighting conditions so that with machine learning, the tractor can understand what its seeing and react accordingly.

No matter if youre a general or a farmer, you dont want to carpet bomb your opponent. If youre a general, you want to eliminate enemy soldiers, not civilians. If youre a farmer, you want to destroy weeds, not food crops.

Agricultural AI will make it easier to efficiently eliminate weeds, in some cases without any pesticides at all. In other cases, when pesticides cant be completely avoided, agricultural AI will make it possible to only hit the weeds and avoid the food crops.

This is important for two obvious reasons. The first is that pesticides cost money. The second is that the fewer pesticides that are used in the vicinity of food crops, the more money the farmer can get for his produce. And, of course, most agree that pesticide-free food is just plain healthier.

As the cost of AI comes down, and as more and more farmers worldwide have access to it, the world will enjoy better, cheaper and healthier foods. And let's not forget that by enabling more automated farming processes, Agricultural AI will mean that fewer farm workers will be stoop laborers, while more and more of them will emerge as machine operators, repair people and network technicians.

Perhaps the greatest modern breakthrough in agriculture was brought on by the tragic German scientist Fritz Haber, who pioneered a process to mass produce ammonia, which in turn can be used to produce artificial fertilizer. Before this development, the population of the world was less than two billion, and now it is four times that much, despite the ghastly toll of 20th century wars.

As much as we talk about the new industrial revolution, we may now acknowledge a new revolution in farming, brought on by artificial intelligence, but unlike the Haber Process, which uses vast amounts of energy and is extremely environmentally unfriendly, the AI revolution is essentially a clean revolution that will allow farmers to do more with less.

It will either reduce pesticide use or eliminate it entirely. It will advise farmers as to their best pathways into both increased profits and increased food yield. And it will allow the worlds rapidly declining cadre of farmers to feed a hungry world in a more sustainable manner.

Excerpt from:
Agricultural Artificial Intelligence: Because it's a Hungry World Out There - Electropages

Throughout history, some of the worlds greatest problems have also been businesses greatest opportunities.

Fast-forward to today, and makers of artificial intelligence systems are already moving to apply the intelligent computing innovations change-the-game potential for efficiency capture and process improvement across some of the most historically siloed and fragmented sectors like Americas vast and disjointed healthcare industry.

Alphabet-owned Google introduced Wednesday (Dec. 13) a new family of generative AI models fine-tuned for the healthcare industry, called MedLM.

Improving healthcare and medicine are among the most promising use cases for artificial intelligence, Google wrote in a blog post, noting that MedLM offers healthcare organizations two separate foundational models built on domain-specific data and designed to meet different operational and care-centered needs.

Healthcare organizations are exploring the use of AI for a range of applications, from basic tasks to complex workflows, per the blog post. Through piloting our tools with different organizations, weve learned the most effective model for a given task varies depending on the use case. For example, summarizing conversations might be best handled by one model, and searching through medications might be better handled by another.

The first MedLM model being offered is larger and designed for more complex workflows, while the second MedLM model is a medium model, which was purpose-built to be further fine-tuned depending on an organizations needs.

Healthcare is a giant sector with many segments and there exist different roles AI can play across the ecosystem that come weighted with different risks and different opportunities.

Beyond just the healthcare space, Googles approach of providing domain-specific models that can built out further with task-oriented training offers clues into how enterprise AI can be best monetized and scaled in the future.

Read also: Can Always-On AI Give Healthcare Providers a Helping Hand?

AI has been revolutionizing medicine over the last few decades, Forward CEO Adrian Aoun told PYMNTS in an interview posted this month. The problem is that it hasnt been doing it in the ways that we care about.

Things need to be built for a world of AI in order for that AI to work and scale, he added.

AI has been in the works for decades, about 75 years, and generative AIs prior, statistically predictive iterations have long been put to work optimizing healthcare insurance pricing and streamlining healthcare system operations with other algorithms humming in the background.

Many of the latest AI innovations are looking to bring AI interfaces into the foreground by helping doctors glean insights from healthcare data in real time and allowing users to find accurate clinical information more efficiently.

Despite the potential benefits of AI in healthcare, PYMNTS Intelligence found that 60% of adults remain uncomfortable with the idea of AI-driven healthcare decisions. Concerns range from biases in AI algorithms to fears that AI may lead to worse outcomes.

One of the threshold concerns is that the data sets being worked on for analytical purposes are not applicable to the individual in question, Tom ONeil, managing director at Berkeley Research Group and former chief compliance officer at Cigna, told PYMNTS in an interview posted in November. I think thats a big issue, and it is better to get out there and talk about it than to surround it with an aura of mystery.

Deploying generative AI across an area as critical as care delivery requires certain guardrails that have been made only voluntarily by domestic tech firms, with AI development in the U.S. taking place absent any binding policies.

Still, there exists an attractive and vast white space opportunity to supplement entrenched and manual healthcare processes with generative AI models that aid workers in completing their tasks.

See also: Healthcare Looks to AI for Potential Home Run Hit

As PYMNTS Karen Webster wrote at the beginning of the year, AIs greatest potential is in creating the knowledge base needed to equip the workforce any worker in any industry with the tools to deliver a consistent, high-quality level of service, quickly and at scale.

This is particularly true within healthcare, as tailoring AI solutions by industry is increasingly proving to be key to scalability.

Worldwide, very few people have access to doctors and the opportunity to have an AI doctor, even if they have just 30%, 50% of an average providers knowledge and capability, is still a massive value add, Beerud Sheth, CEO at conversational AI platform Gupshup, told PYMNTS in an interview posted in November.

Its not hard to imagine a future where healthcare systems might offer bespoke generative AI products for a range of ailments. Patients with a cold or flu would interact with a respiratory illness-trained AI, for example, while those with abrasions or cuts would be directed to an AI system trained to interact with pictures and images of the issue at hand.

Just as doctors are trained in their specialties, so too might the AI healthcare systems of tomorrow.

Still, as PYMNTS Intelligence found, there exists a growing urban-rural divide in access to and participation in digital healthcare services. This gap between access to care and the ability of care to be delivered will need to be addressed and ideally closed.

For all PYMNTS AI coverage, subscribe to the daily AI Newsletter.

See the original post:
Healthcare AI Models Highlight Role of Trained Point Solutions - PYMNTS.com

ROME (AP) Pope Francis on Thursday called for an international treaty to ensure artificial intelligence is developed and used ethically, arguing that the risks of technology lacking human values of compassion, mercy, morality and forgiveness are too great.

Francis added his voice to increasing calls for binding, global regulation of AI in his annual message for the World Day of Peace, which the Catholic Church celebrates each Jan. 1. The Vatican released the text of the message on Thursday.

For Francis, the appeal is somewhat personal: Earlier this year, an AI-generated image of him wearing a luxury white puffer jacket went viral, showing just how quickly realistic deepfake imagery can spread online.

The popes message was released just days after European Union negotiators secured provisional approval on the worlds first comprehensive AI rules that are expected to serve as a gold standard for governments considering their own regulation.

Francis acknowledged the promise AI offers and praised technological advances as a manifestation of the creativity of human intelligence, echoing the message the Vatican delivered at this years U.N. General Assembly where a host of world leaders raised the promise and perils of the technology.

But his new peace message went further and emphasized the grave, existential concerns that have been raised by ethicists and human rights advocates about the technology that promises to transform everyday life in ways that can disrupt everything from democratic elections to art.

Artificial intelligence may well represent the highest-stakes gamble of our future, said Cardinal Michael Czerny of the Vaticans development office, who introduced the message at a press conference Thursday. If it turns out badly, humanity is to blame.

The document insisted that the technological development and deployment of AI must keep foremost concerns about guaranteeing fundamental human rights, promoting peace and guarding against disinformation, discrimination and distortion.

Pope Francis leaves after an audience with sick people and Lourdes pilgrimage operators in the Paul VI Hall, at the Vatican, Thursday, Dec. 14, 2023. (AP Photo/Alessandra Tarantino) Pope Francis leaves after an audience with sick people and Lourdes pilgrimage operators in the Paul VI Hall, at the Vatican, Thursday, Dec. 14, 2023. (AP Photo/Alessandra Tarantino)

Francis greatest alarm was devoted to the use of AI in the armaments sector, which has been a frequent focus of the Jesuit pope who has called even traditional weapons makers merchants of death.

He noted that remote weapons systems had already led to a distancing from the immense tragedy of war and a lessened perception of the devastation caused by those weapons systems and the burden of responsibility for their use.

The unique capacity for moral judgment and ethical decision-making is more than a complex collection of algorithms, and that capacity cannot be reduced to programming a machine, he wrote.

He called for adequate, meaningful and consistent human oversight of Lethal Autonomous Weapons Systems (or LAWS), arguing that the world has no need for new technologies that merely end up promoting the folly of war.

On a more basic level, he warned about the profound repercussions on humanity of automated systems that rank citizens or categorize them. In addition to the threats to jobs around the world that can be done by robots, Francis noted that such technology could determine the reliability of an applicant for a mortgage, the right of a migrant to receive political asylum or the chance of reoffending by someone previously convicted of a crime.

Algorithms must not be allowed to determine how we understand human rights, to set aside the essential human values of compassion, mercy and forgiveness, or to eliminate the possibility of an individual changing and leaving his or her past behind, he wrote.

For Francis, the issue hits at some of his priorities as pope to denounce social injustices, advocate for migrants and minister to prisoners and those on the margins of society.

The popes message didnt delve into details of a possible binding treaty other than to say it must be negotiated at a global level, to both promote best practices and prevent harmful ones. Technology companies alone cannot be trusted to regulate themselves, he said.

He repurposed arguments he has used before to denounce multinationals that have ravaged Earths national resources and impoverished the Indigenous peoples who live off them.

Freedom and peaceful coexistence are threatened whenever human beings yield to the temptation to selfishness, self-interest, the desire for profit and the thirst for power, he wrote.

Barbara Caputo, professor at the Turin Polytechnic universitys Artificial Intelligence Hub, noted that there was already convergence on some fundamental ethical issues and definitions in both the EUs regulation and the executive order unveiled by U.S. President Joe Biden in October.

This is no small thing, she told the Vatican briefing. This means that whoever wants to produce artificial intelligence, there is a common regulatory base.

Original post:
Pope, once a victim of AI-generated imagery, calls for treaty to regulate artificial intelligence - WBRZ

SWISS International Airlines is to install a new digital boarding system on its aircraft, which will uses artificial intelligence to conduct a passenger count and make sure no stowaways have managed to sneak onboard.

The Zurich-based carrier has decided to adopt the system after a successful three-month trial conducted earlier this year. During the trial, the airline wanted to make sure that the AI model could work in various light conditions and detect a parent carrying an infant in their arms.

Unlike some airlines that rely on automated passenger reconciliation via boarding pass scanners, cabin crew at the Swiss flag carrier are still required to conduct a manual headcount of passengers using an old-fashioned clicker.

The new system makes that process obsolete, and SWISS says it expects the boarding process to be a lot quicker as a result.

Developed by Berlin-based tech startup Vion AI, the new passenger count system works with a camera installed at the boarding door, which monitors people coming and going from the plane.

A prototype of the system was only developed earlier this year, but during the trial conducted by SWISS, the airline found that it conducted passenger boarding counts reliably under a wide range of conditions.

Further work is, however, required to develop and refine the system and the airline doesnt expect to start installing the system across its fleet until later in 2024. Initially, the short-haul fleet will have the system fitted from the third quarter of 2024, while work to install the cameras on long-haul aircraft will begin in the final three months of 2024.

In the meantime, some aircraft will have the system installed as part of the ongoing development of the AI software but crew members will still be required to conduct manual passenger counts.

Addressing privacy concerns, SWISS says all data will be processed in full compliance with the strict European and Swiss data protection rules.

In adopting this AI-based solution for counting our passengers during boarding, were taking another major step forward into the digital future, commented Oliver Buchhofer, SWISSs Head of Operations.

The use of artificial intelligence will help make the boarding process faster and more efficient, Buchhofer continued. This in turn will reduce waiting times and give our guests a pleasanter travel experience. The new digital count will ease the workload on our cabin crews, too.

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Mateusz Maszczynski honed his skills as an international flight attendant at the most prominent airline in the Middle East and has been flying throughout the COVID-19 pandemic for a well-known European airline. Matt is passionate about the aviation industry and has become an expert in passenger experience and human-centric stories. Always keeping an ear close to the ground, Matt's industry insights, analysis and news coverage is frequently relied upon by some of the biggest names in journalism.

See original here:
SWISS International Airlines to Use Artificial Intelligence to Count Passengers With Special Cameras Installed at the ... - paddleyourownkanoo.com

Russian President Vladimir Putin appeared briefly lost for words on Thursday when confronted with an AI-generated version of himself.

The "double" took the opportunity to put a question to Putin about artificial intelligence during an annual news conference where dozens of callers from around the country were hooked up to the president by video link.

"Vladimir Vladimirovich, hello, I am a student at St Petersburg state university. I want to ask, is it true you have a lot of doubles?" the double asked, prompting laughter among the audience in the hall with Putin in Moscow.

"And also: How do you view the dangers that artificial intelligence and neural networks bring into our lives?"

The question prompted a rare hesitation from Putin, already in his fourth hour of taking questions at the marathon event.

"I see you may resemble me and speak with my voice. But I have thought about it and decided that only one person must be like me and speak with my voice, and that will be me," he said.

There has been recurrent speculation, particularly in Western media, that Putin has one or more body doubles to cover for him in some public appearances because of alleged health problems. The Kremlin had denied that and said the president's health is excellent.

Originally posted here:
Vladimir Putin lost for words as he confronts his AI 'double' - The Jerusalem Post