Copyright: news.mit.edu – “Need a Research Hypothesis? Ask AI.”

Crafting a unique and promising research hypothesis is a fundamental skill for any scientist. It can also be time consuming: New PhD candidates might spend the first year of their program trying to decide exactly what to explore in their experiments. What if artificial intelligence could help?

MIT researchers have created a way to autonomously generate and evaluate promising research hypotheses across fields, through human-AI collaboration. In a new paper, they describe how they used this framework to create evidence-driven hypotheses that align with unmet research needs in the field of biologically inspired materials.

Published Wednesday in Advanced Materials, the study was co-authored by Alireza Ghafarollahi, a postdoc in the Laboratory for Atomistic and Molecular Mechanics (LAMM), and Markus Buehler, the Jerry McAfee Professor in Engineering in MIT’s departments of Civil and Environmental Engineering and of Mechanical Engineering and director of LAMM.

The framework, which the researchers call SciAgents, consists of multiple AI agents, each with specific capabilities and access to data, that leverage “graph reasoning” methods, where AI models utilize a knowledge graph that organizes and defines relationships between diverse scientific concepts. The multi-agent approach mimics the way biological systems organize themselves as groups of elementary building blocks. Buehler notes that this “divide and conquer” principle is a prominent paradigm in biology at many levels, from materials to swarms of insects to civilizations — all examples where the total intelligence is much greater than the sum of individuals’ abilities.

“By using multiple AI agents, we’re trying to simulate the process by which communities of scientists make discoveries,” says Buehler. “At MIT, we do that by having a bunch of people with different backgrounds working together and bumping into each other at coffee shops or in MIT’s Infinite Corridor.”[…]

Read more: www.news.mit.edu

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Copyright: eurekalert.org – “Artificial Intelligence-Based Chatbot Created for Bioimage Analysis”

Scientists from Universidad Carlos III de Madrid (UC3M), together with a research team from Ericsson and the KTH Royal Institute of Technology in Sweden, have developed an artificial intelligence-based software programme that can search for information and make recommendations for biomedical image analysis. This innovation streamlines the work of individuals using large bioimage databases, including life sciences researchers, workflow developers, and biotech and pharmaceutical companies.

The new assistant, called the BioImage.IO Chatbot and introduced in the journal Nature Methods, was developed as a response to the issue of information overload faced by some researchers. “We realised that many scientists have to process large volumes of technical documentation, which can become a tedious and overwhelming task,” explains Caterina Fuster Barceló, a researcher in the Department of Bioengineering at UC3M and one of the study’s authors. “Our goal was to facilitate access to data information while providing a simple interface that allows scientists to focus their time on bioimage analysis rather than programming,” she adds.

The chatbot can be a very useful tool, enabling researchers to perform complex image analysis tasks in a simple and intuitive manner. For example, if a researcher needs to process microscopy images using segmentation models, the chatbot can help select and execute the appropriate model.

The assistant is based on extensive language models and employs a technique called Retrieval-Augmented Generation (RAG), which enables real-time access to databases. “The main advantage is that we do not train the model with specific information; instead, we extract it from up-to-date sources, minimising errors known as ‘hallucinations’, which are common inaccuracies in other AI models like ChatGPT,” adds Arrate Muñoz Barrutia, professor in the Department of Bioengineering at UC3M and another author of the study.[…]

Read more: www.eurekalert.org

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Copyright: cio.com – “Top 7 Generative AI Use Cases For Business”

The launch of ChatGPT in November 2022 set off a generative AI gold rush, with companies scrambling to adopt the technology and demonstrate innovation.

Many of the AI use cases entrenched in business today use older, more established forms of AI, such as machine learning, or don’t take advantage of the “generative” capabilities of AI to generate text, pictures, and other data. Legacy chatbots, product recommendation engines, and several other useful tools may rely only on earlier forms of AI.

Some industries such as biotech are finding ways to use gen AI, but many enterprises experimenting with the technology have found a limited number of use cases so far, says Kjell Carlsson, head of AI strategy at Domino Data Lab, provider of an enterprise AI platform. For many enterprises the return on investment for gen AI is elusive, he says.

“The reality for a lot of users is that they just don’t have enough [information] to make an AI strategy leveraging generative AI use cases, and they’re not going to get to enough value quickly,” he adds. “They have a couple of use cases that they’re pushing heavily on, but they are building up this portfolio of traditional machine learning and ‘predictive’ AI use cases as well.”

Many AI experts say the current use cases for generative AI are just the tip of the iceberg. More uses cases will present themselves as gen AIs get more powerful and users get more creative with their experiments.

However, a handful of gen AI use cases are already bubbling up. Here’s a look at the most popular and promising.[…]

Read more: www.cio.com

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The Billion-Dollar AI Investment Race – SwissCognitive AI Investment Radar

Our exploration begins with LG Group’s massive 74 billion-dollar pledge to AI development in South Korea, a move that heralds a future where technology drives growth and innovation. This ambitious investment underlines South Korea’s vision to become a global tech powerhouse.

Financial circles are buzzing about AI’s underestimated long-term economic impact. As OpenAI races towards a potential trillion-dollar valuation, the industry’s gaze shifts to AI’s transformative capabilities and its ability to redefine markets.

In Shanghai, a 13.8 billion-dollar fund aims to catapult startups in AI and biotech into the global arena, demonstrating China’s assertive push in tech innovation. Meanwhile, Cognition Labs seeks a $2 billion valuation for its AI code-writing tool, highlighting the increasing demand for AI-driven productivity enhancements.

Venture capital fervor mirrors this optimism, with nearly $100 million earmarked for AI startups by Superset, showcasing the sector’s potential for redefining technology’s future.

As we navigate through these groundbreaking developments and strategic investments, it’s evident that the journey of AI is not just about technology. It is also about shaping the future where innovation and human ambition converge, setting new frontiers for growth and possibilities.

Join the SwissCognitive AI Investment Radar and learn the latest news to stay updated in the fast-changing world of AI and Investments.

Previous SwissCognitive AI Investments Radar: Next-Gen AI Innovations And Investments.

Our article does not offer financial advice and should not be considered a recommendation to engage in any securities or products. Investments carry the risk of decreasing in value, and investors may potentially lose a portion or all of their investment. Past performance should not be relied upon as an indicator of future results.

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Andy Fitze, Co-Founder of SwissCognitive, World-Leading AI Network
Copyright: inside-it.ch – Andy’s AI Almanac: Technology Trilogy Engineer – die Köche der Zukunft

Let’s start from the beginning. We humans still believe that we understand non-linear processes. But in reality, we don’t. We can’t even get a bathtub halfway to a comfortable bathing temperature after the hundredth time. We are not made for things that we cannot grasp linearly. We are so overwhelmed by a simple weather forecast that we usually don’t even know what the weather is going to be like after reading the weather report. Intuition doesn’t want to enter our heads.

This leads me to 3 conclusions:

1. Things are complex, and we have simplified them so that we can understand and apply them. And that’s a good thing otherwise we’d all be overwhelmed. Anyone who goes skiing in winter, for example, knows this. There are the 3×3 rules of avalanche safety. That’s how it’s understood and it’s practical, but the reality is much more complex. So complex that we don’t understand it and can’t process it, especially not in the terrain at minus 20 degrees.
2. We deduce the future from experience, even and especially with highly volatile systems. We call this intuition, but what we mean is “competent behaviour in the face of complete cluelessness”. We tend to behave in this way when complexity is involved, perhaps in order to create a certain logic. For example, we believe that the next logical step after assisted driving is autonomous driving. In other words, we describe this change as “one step”. In reality, the technology is 1000 times more complex in this single step. When Steve Ballmer made fun of Apple in 2007, Microsoft sold millions of smartphones a year, and Apple none. Today, Apple sells that amount in one day.
3. We like to forget so badly we are practically world champions in it. Individual and social amnesia, so to speak. Before boarding the plane, we check our boarding pass to remember our seat number, but as soon as we get on the plane, we have forgotten everything.

And now we are surprised about AI, as if we had forgotten that calculators, Wikipedia, Google search, Excel, smartphones and even our kitchen stove have long surpassed us.

Wake up! With our experience, logic, and knowledge, we will hardly grasp technological developments, far less predict them.

We need to engage more intensively with technology. Much more!

What we see today with AI and its rapid development dazzles us. We are amazed, stunned and therefore blind to see what is coming.

My prognosis:

1. AI applied directly will boost productivity.
2. AI applied in technologies will define new markets.
3. AI merged with multiple technologies will change the foundations of our world.

We are already experiencing the first one today. The second one is also already advancing in the B2B sector. But the third one will be the most exciting. For example, the combination of AI, crypto, and blockchain will fundamentally change the trade of all assets in this world. And AI, biotech, and quantum will completely alter our understanding of ourselves, nature, and the healthcare industry.

For the first time in history, we will be able to answer complex questions with complex systems. I admit that I am very excited. This is beyond our current understanding.

Therefore, I suggest a new professional category: Technology Trilogy Engineer – chefs who understand how to rediscover technology recipes.

Original article: www.inside-it.ch

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SwissCognitive Guest Blogger: Jacques Ludik, Founder & CEO, Cortex Logic & Cortex Group – “The Evolving Swiss AI Ecosystem”

Switzerland stands as a beacon of innovation and a leader in the global AI arena. The country’s educational institutions, such as ETH Zurich and EPFL, are not just academic strongholds but are powerhouses of AI research with international reach and influence (Switzerland Global Enterprise, 2022). They provide a steady flow of highly skilled talent, feeding into a dense and flourishing ecosystem that nurtures both startups (Reinhard, 2023) and tech giants like Google and IBM (Steiger and Fitzer, 2023) and making it an invaluable partner on the global stage. (Switzerland Global Enterprise, 2022).

In the realm of AI, Zurich epitomizes this Swiss excellence. Home to ETH Zurich, one of the world’s leading universities, Zurich is a hotbed for AI research and development. The precision and accuracy inherent in Swiss culture resonate deeply with the needs of AI, drawing professionals to a city that promises not only professional success but also personal well-being. The forthcoming establishment of the AI Institute in Zurich is a testament to Switzerland’s appeal as a hub for cutting-edge technology and research (Boston Dynamics AI Institute, 2023). This expansion promises to further Switzerland’s capabilities in robotics and AI, integrating the intellectual rigor of academia with the dynamism of corporate R&D. The Institute aims to attract the best talent and contribute to the robust European ecosystem of innovation and technology.

Swiss innovation is globally recognized, with the nation consistently securing top positions in various innovation rankings. This innovative strength is bolstered by a business-friendly landscape with pragmatic regulations that encourage tech advancements while maintaining economic and political stability (European Commission, 2021). The synergistic relationship between business and academia in Switzerland is practically unique in Europe, creating a pragmatic cooperation that accelerates the translation of research into practical solutions (ZHAW, 2023).

Geneva stands as a testament to Switzerland’s commitment to global ethical standards in AI. As home to numerous international organizations, it is a pivotal city for establishing global standards that guide the ethical development and deployment of AI technologies (European Commission, 2021). International Geneva, hosting significant global AI activities, adds to Switzerland’s status as a leader in AI governance and the ethical implementation of AI technologies (U.S. News, 2023). This is a testament to Switzerland’s conducive environment for international organizations and their efforts in cognitive technologies.

Switzerland has emerged as a premier destination for AI innovation, distinguished by its combination of a solid educational foundation, economic stability, and quality of life. The country’s innovative prowess, evidenced by its top position as the most innovative country worldwide, is a result of its world-class educational institutions and a high quality of life that attracts global talent. Switzerland’s commitment to excellence is reflected in its thriving economy and its role as a benchmark of global innovation and sustainable growth. (WEF, 2023).

Switzerland’s political and economic stability, coupled with its business-friendly and pragmatic regulations, creates an environment conducive to growth and innovation. This is evidenced by successful AI applications across various sectors, including medical imaging and expense management, as demonstrated by companies like Incepto Medical and Jenji. (Switzerland Global Enterprise, d.u.).

Switzerland and Africa

Looking at potential collaborations with South Africa and the broader African continent, Switzerland’s strengths align well with the growing technological landscape of Africa. Some recent dynamics in the Africa AI Ecosystem along for a call to collaborate to democratize Human-centric AI. For example, the Machine Intelligence Institute of Africa (MIIA) aims to develop a collaborative impactful African AI Ecosystem in collaboration with a global partner network of excellence that helps to transform Africa and shape a better future for all in the Smart Technology Era. By engaging with Switzerland’s AI centers valuable insights and support can be provided to African AI ventures and organizations. The cross-pollination of ideas and resources between Switzerland and Africa can lead to mutual growth and the realization of a human-centric AI future.

Switzerland’s approach to innovation can inspire and align with Africa’s goals, from fostering talent and pioneering research to nurturing a dense and flourishing ecosystem that supports startups and established businesses alike. This alignment offers a promising foundation for business and governmental collaborations, further strengthening the AI bridge between Switzerland and Africa.

Switzerland’s Start-up Ecosystem

Celebrating this spirit of innovation, the TOP 100 Swiss Start-up Award exemplifies the dynamism of Switzerland’s start-up ecosystem. The event spotlights startups that contribute significantly to the job market and the economy, underscoring Switzerland’s role as a cradle of entrepreneurial success and a magnet for international investment. (Reinhards, 2023). The country’s start-up ecosystem has been a fertile ground for innovation, creating thousands of jobs and significant revenue. HAYA Therapeutics, Planted Foods, and Yokoy Group are among the success stories emerging from this vibrant landscape.

Western Switzerland, meanwhile, stands as a beacon of AI research, hosting esteemed institutions like the Idiap Research Institute and platforms like CAIM and TORCH, which contribute to the country’s stature in the global AI landscape. Switzerland’s agility in adapting to regulatory changes while fostering innovation makes it a prime location for AI companies and thought leaders.

In the vibrant landscape of European AI, Switzerland commands attention with its 67 AI startups. (Smart, 2022). Remarkably, the nation’s AI sector is amplified by the contributions of ETH Zurich, which stands out as a premier institution fostering AI founders. This educational powerhouse underpins the nation’s AI prowess, distinguishing it even among larger countries with more startups. Such educational and research institutions are pivotal in advancing Switzerland’s capabilities in the AI domain.

Switzerland’s commitment to world-class research and innovation

Switzerland’s commitment to research and innovation is deeply entrenched in its national ethos, with substantial investments in R&D that eclipse the spending percentages of many other developed countries. The nation’s research institutions, such as CERN, the Paul Scherrer Institute, and the Friedrich Miescher Institute, are renowned for their significant contributions to scientific knowledge, particularly in the fields of engineering and biotechnology. Such investments bolster the Swiss economy and cement its reputation as a global leader in innovation. (Swiss Confederation)

Switzerland’s accolade as the best country in the world by U.S. News & World Report for the sixth time speaks volumes about its global standing. With assessments based on power, cultural influence, and heritage among 87 countries, Switzerland’s ranking reflects its economic stability, safety, and low corruption levels. The nation’s reputation is further solidified by its educational quality and innovative spirit, as noted by Ambassador Jacques Pitteloud. The recognition of its climate initiatives and economic prudence, alongside its top rankings, positions Switzerland at the forefront of global leadership. Moreover, Switzerland’s consistent ranking in the World Competitiveness Ranking, particularly in infrastructure and government efficiency, underscores its formidable position in the global economy and its conducive environment for business and innovation.

Switzerland’s commitment to research and development has cemented its status as a world leader in innovation. The active promotion of innovation by government and academic institutions has fostered a dynamic ecosystem that continually drives progress. (U.S. News, 2023)

Lastly, Switzerland’s dedication to the Sustainable Development Goals (SDGs) showcases its commitment to global sustainability. Its collaborative efforts, such as those by the Swiss chocolate industry, and its economic achievements, underscore the nation’s proactive role in international efforts to address global challenges. (Wharton University of Pennsylvania, 2022).

In summary, Switzerland’s prowess in research and development is not only a pillar of its own economy but also contributes significantly to global technological advancements. Swiss universities and research institutions serve as fertile ground for the world’s best minds to tackle the foremost challenges in AI and robotics.

“The Evolving Swiss AI Ecosystem” by Jacques Ludik has been published originally on Digital First Magazine.

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Livia Spiesz, Head of Global Partnerships and Communications, SwissCognitive – “The AI Trajectory 2024 – Invest for Impact”

Venture Capitalism and AI: Seizing the Moment

In the past year, Artificial Intelligence (AI) redefined the scope of decision-making and operational efficiency and also revolutionized the capacity to solve complex challenges rapidly. This profound leap signifies the ushering of an era where AI underpins essential business strategies. Given the swift pace of AI innovation, venture capitalists (VCs) are increasingly drawn to its potential. Investment is not a matter of speculation but an imperative of the current landscape. The real question is no longer “Why invest in AI?” but “Can we afford not to?” Procrastination could mean forgoing the leadership in a wave of innovation that can transform society towards sustainable growth and resilience. Today’s investments are the seeds for tomorrow’s groundbreaking developments, casting a pivotal role in a revolutionized future.

AI Foundation Models: The Backbone of Tomorrow’s Technologies

At the center of AI’s rapid evolution are the foundational models, where leading LLM providers play a pivotal role. Consider NVIDIA, which started as a graphics processor manufacturer but has now become instrumental in AI infrastructure with its advanced GPU technologies. Current investments in this domain are reshaping how we perceive and interact with technology. When industry leaders articulate their visions, they do not merely set an organizational direction; they shape the global tech landscape. Their initiatives extend from optimizing search algorithms to driving comprehensive digital transformation projects, impacting lives across every longitude and latitude. These AI models aren’t just business – they’re the blueprints of worldwide digital advancement.

Revolutionizing Healthcare: Synergy of AI and Human Talent

AI in healthcare is not the future; it is revolutionizing patient care already today. AI-driven tools support doctors in swiftly diagnosing diseases, robotic arms perform intricate surgeries with meticulous precision, and intelligent systems analyze medical scans to catch signs of illness sooner than humans would do. AI is also personalizing patient treatment plans, managing hospital logistics to reduce wait times, and predicting patient outcomes for better resource allocation. Yet, alongside this AI-driven transformation is the irreplaceable value of human expertise. The real challenge, and opportunity, lies in harmonizing advanced tech with the nuances of human touch, intuition, and ethics. The synergy between cutting-edge technology and the depth of human skills presents a unique investment opportunity—one that promises returns in health, longevity, and quality of life.

STEM Evolution 2024: Redefining Science in the Age of AI and LLM

STEM (Science, Technology, Engineering, and Mathematics) fields are witnessing a renaissance as AI and LLM technologies redefine research paradigms. Leading academic institutions like MIT and Stanford are incorporating AI to amplify research, facilitating breakthroughs from synthetic biology to environmental sciences. The integration of LLM quickens data processing, refines hypothesis testing, and expands theoretical exploration, all at previously unimaginable velocities. This marks a pivotal moment for investors to contribute to a revolution that could unravel new scientific understandings and capabilities.

The Power of Collaboration: Uniting Minds, Industries, and Technologies

In a world characterized by its interconnectivity, collaboration emerges as the requirement of sustainable progress. Consider the collaboration between automotive giants and tech companies in creating autonomous vehicles, or pharmaceutical companies partnering with AI firms to expedite drug discovery. The magic happens when expertise from diverse fields converge, and silos break down. AI serves as the bridge to the future, but it’s human vision and collaboration that set the strong foundation and chart the path forward. In our pursuit of technological advancements, our greatest strength remains our ability to connect, share, and co-create.

Embarking on a Collaborative Voyage at The AI Trajectory 2024

The AI Trajectory 2024 is more than a conference; it’s a critical intersection where AI experts, industry leaders, and venture capitalists convene to shape the future. It’s a gathering grounded in real-world application and strategic foresight and offers a rare chance to engage with those at the forefront of AI innovation and investment. The discussions here are designed to cut through the noise, and focus on actionable insights that harmonize artificial and human intelligence to steer us into the future.

Join us at this conference and be part of a dialogue that shapes our collective tomorrow. As we map out the contours of a future enriched by AI, your participation is key to creating a vision that’s not only ambitious but also attainable and aligned with progressive growth.

Find the conference agenda and registration link HERE.
For two-click easy registration, click HERE.

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SwissCognitive Guest Blogger: Kashish Khan – “Top 10 AI Trends to Catapult the Global Agricultural Landscape in 2024”

In 2024, we can expect to see the following top 10 AI trends that will reshape the agricultural landscape worldwide.

This shift from traditional agriculture to advanced and modern precision agriculture provides for a suitable avenue to the agriculture industry to grow, providing lucrative opportunities for agritech companies and agribusinesses.

According to data insights from BIS Research, a market research company, the global precision agriculture market was valued at $7.89 billion in 2022 and is expected to reach $14.61 billion in 2027, following a CAGR of 13.12% during 2022-2027.

In 2024, we can expect to see the following top 10 AI trends that will reshape the agricultural landscape worldwide.

1. Autonomous Tractors and Farming Equipment

Autonomous tractors and farming equipment are set to become a game-changer in the agriculture industry. These self-driving machines will leverage AI and computer vision to perform tasks such as plowing, planting, and harvesting with utmost precision. By eliminating the need for human intervention, autonomous farming equipment will enhance productivity, reduce labor costs, and optimize resource utilization.

For instance, John Deere’s 8R, a fully autonomous tractor was revealed at CES 2022, which is equipped with GPS guidance, lidar, and advanced cameras.

Similarly, AgXeed Drive, an autonomous tractor equipped with GPS guidance, cameras, and radar was developed by AgXeed, a Dutch company.

Furthermore, Several companies have launched autonomous weeding robots, including FarmBot, EcoRobotix, and Naio Technologies. These robots use cameras and sensors to identify weeds and then remove them without the use of herbicides.

2. Big Data Analytics and Decision Support Systems

The abundance of data generated in agriculture can overwhelm farmers. However, AI-powered big data analytics and decision support systems will provide actionable insights, helping farmers make informed decisions. By analyzing various data points such as weather patterns, soil conditions, and crop health, these systems will optimize planting schedules, predict disease outbreaks, and recommend appropriate fertilization techniques.

In April 2023, an AI agricultural advisor named “Norm” was launched, marking a significant development in the field. Norm possesses the ability to rapidly provide crucial information, such as methods to combat specific pests, the most suitable seed varieties for specific soil types, and strategies for identifying and preventing cattle diseases.

3. Plant Health Sensors

Plant health sensors integrated with AI algorithms will enable farmers to monitor the well-being of crops in real-time. These sensors can detect diseases, nutrient deficiencies, and pest infestations early on, allowing for timely intervention. AI algorithms can process the data collected by these sensors, providing farmers with precise information on crop health and optimizing the use of pesticides and fertilizers.

In April 2023, Researchers at North Carolina State University developed a wearable electronic patch that can be placed on plant leaves to monitor the presence of pathogens and environmental stressors. The small patch incorporates sensors and electrodes to detect temperature, humidity, and moisture levels. In experiments with tomato plants, the patch successfully identified pathogenic infections and stressors. The researchers plan to make the patches wireless and test them in real-world conditions, aiming to assist growers in preventing crop problems and addressing food security challenges.

4. Agriculture Drones and Robots

Agriculture drones and robots equipped with AI capabilities will transform the way farmers manage their fields. Drones can survey large areas quickly, capturing high-resolution images of crops. AI algorithms can then analyze these images to identify areas requiring attention, such as water stress or weed infestations. Robots, on the other hand, can perform labor-intensive tasks like weeding or pruning with precision and efficiency, reducing the need for manual labor.

In June 2023, Precision AI, a Canadian startup, developed autonomous AI-powered drones for plant-level herbicide application. The drones aim to address the challenges faced by farmers in meeting food demand through intensive agricultural practices that result in environmental pollution. The technology offers real-time insights, data collection, and predictions for individual plant management, reducing water use, costs, and chemical excess while promoting soil health. Precision AI’s drones use edge computing to function without internet connectivity, providing near-instant weed identification. With $20 million in funding, the company plans to be operational by 2026 and expand into other applications such as insecticide reduction and fungicide optimization.

5. Farm Management Software

AI-powered farm management software will consolidate various aspects of farming, from inventory management to financial planning. These systems will integrate data from multiple sources, such as weather forecasts, market trends, and field conditions, to provide farmers with holistic insights into their operations. By streamlining workflows and optimizing resource allocation, farm management software will enhance productivity and profitability.

In March 2023, Bushel Inc., an independent software company launched Bushel Farm, a next-generation farm management software designed to reduce manual data entry for farmers and provide grain marketing insights. The software, built upon the company’s FarmLogs solution, offers a comprehensive feature set for mobile and desktop experiences while maintaining user-friendly design.

Moreover, Bushel will release an integration that enables farmers to automatically import their individual grain sales data into Bushel Farm, reducing the need for manual entry. This integration will provide valuable time savings for farmers and enhance the software’s capabilities. The software is available for both individual farms and commercial grain buyers/agribusinesses seeking to strengthen relationships and streamline grain marketing. Moreover, integrations with John Deere Operations Center and Climate FieldView® enhance data imports, and data privacy controls ensure authorized sharing.

6. Climate-Smart Technology

The agricultural industry is under increasing pressure to mitigate the effects of climate change. AI-driven climate-smart technology will aid in the development of sustainable farming practices. By analyzing historical climate data, AI algorithms can predict weather patterns and help farmers adapt their cultivation techniques accordingly. This will enable the industry to optimize water usage, reduce greenhouse gas emissions, and enhance overall resilience.

In May 2023, the University of Minnesota was granted $20 million over five years from the National Science Foundation (NSF) and the U.S. Department of Agriculture’s National Institute of Food and Agriculture (NIFA) to establish a National Artificial Intelligence Research Institute. The institute, known as AI-CLIMATE, aims to leverage artificial intelligence (AI) to develop climate-smart practices that simultaneously absorb and store carbon while promoting economic growth in the agriculture and forestry sectors.

7. Resiliency in Supply Chain

AI technology can bolster the resiliency of agricultural supply chains. By leveraging predictive analytics, machine learning, and data from multiple sources, AI systems can optimize logistics, inventory management, and demand forecasting. This will enable farmers to respond to market demands more effectively, reduce wastage, and ensure a steady supply of fresh produce.

In March 2023, Helios Artificial Intelligence, Inc. launched the open beta of its platform that detects agricultural supply chain disruptions in advance. The platform provides customized climate and economic risk insights for over 200 commodities in 180 countries, enabling agricultural importers to stay ahead of their competitors. Helios helps users predict supply availability, identify risks to yields, and provide valuable input for negotiation processes. Customers have already experienced transformative results, gaining actionable insights and proactively mitigating disruptions. The platform offers transparency into ESG, climate, economic, and political factors affecting suppliers.

8. Convergence with IoT

The convergence of AI with the Internet of Things (IoT) will amplify the transformative potential of agriculture. IoT devices, such as soil moisture sensors and smart irrigation systems, can collect vast amounts of data. AI algorithms can then process this data to automate and optimize irrigation, fertilizer application, and other farming operations. The integration of AI and IoT will enable farmers to achieve higher yields, conserve resources, and enhance sustainability.

In June 2023, Trilogy Networks, Veea, and Microclimates formed a partnership to offer an all-in-one agritech solution. Trilogy Networks, a leader in the agritech IoT-edge-cloud-platform market, aims to combine their technologies and platforms with Veea and Microclimates. The new Trilogy platform allows farmers and enterprises to collect, compute, and protect data at the edge, enhancing operational efficiency and reducing costs. Veea provides unified connectivity between the cloud, endpoints, edge, and devices. Microclimates specializes in smart climate-controlled environment management, enabling farmers to monitor and control temperature, humidity, CO2 levels, watering, and ambient light. Their platform supports thousands of sensors and provides 24/7 live monitoring.

9. AI Integration in Agriculture Biotechnology

AI is playing a pivotal role in advancing agricultural biotechnology. Genetic algorithms and machine learning techniques can accelerate the breeding process, helping develop crops with improved traits, such as disease resistance or higher yields. AI can also facilitate gene editing techniques, such as CRISPR, enabling precise and efficient modifications to plant genomes. These advancements will drive the development of resilient, high-performing crops.

For instance, in March 2023, InnerPlant and Mertec LLC joined forces to develop crops that can communicate biological stresses before they become visible to farmers. By integrating InnerPlant’s seed technology with Mertec’s soybean germplasm, the aim is to create crops that emit signals when they are under stress from pathogens, water deficiency, or nutrient deficiency. These signals, visible from satellites and tractors, provide early detection of problems weeks before they would be noticeable in the field

10. Precision Irrigation

Water scarcity is a significant challenge in agriculture, making precision irrigation a critical trend. AI algorithms can analyze data from various sources, including weather forecasts and soil moisture sensors, to optimize irrigation schedules. By delivering the right amount of water at the right time, precision irrigation enhances water-use efficiency, conserves resources, and minimizes environmental impact.

In April 2023, BASF and AGCO Corporation partnered to integrate and commercialize smart spraying technology on Fendt Rogator sprayers. Developed by Bosch BASF Smart Farming, this advanced solution allows precise herbicide application for effective weed control and cost optimization. Trials for the technology began in May 2021, showcasing its targeted spraying capabilities in various conditions, day, or night. The system saves herbicide through precise application, advanced sensors, automated sensitivity thresholds, and weed identification technology.

Conclusion

As we look forward to 2024, the global agricultural landscape is poised to undergo significant transformations driven by AI technology. Embracing the aforementioned advancements will empower farmers to overcome challenges, enhance productivity and profitability, and ensure a sustainable future for the agricultural sector.

About the Author:

Kashish Khan is a seasoned content writer with extensive experience in writing on various deep tech verticals concerning Artificial Intelligence and and IoT. She is affiliated with a reputed market research firm through which I receive critical insights into the industry.

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Copyright: news.mit.edu – “MIT Dcientists Build a System That Can Generate AI Models for Biology Research”

Is it possible to build machine-learning models without machine-learning expertise?

Jim Collins, the Termeer Professor of Medical Engineering and Science in the Department of Biological Engineering at MIT and the life sciences faculty lead at the Abdul Latif Jameel Clinic for Machine Learning in Health (Jameel Clinic), along with a number of colleagues decided to tackle this problem when facing a similar conundrum. An open-access paper on their proposed solution, called BioAutoMATED, was published on June 21 in Cell Systems.

Recruiting machine-learning researchers can be a time-consuming and financially costly process for science and engineering labs. Even with a machine-learning expert, selecting the appropriate model, formatting the dataset for the model, then fine-tuning it can dramatically change how the model performs, and takes a lot of work.

“In your machine-learning project, how much time will you typically spend on data preparation and transformation?” asks a 2022 Google course on the Foundations of Machine Learning (ML). The two choices offered are either “Less than half the project time” or “More than half the project time.” If you guessed the latter, you would be correct; Google states that it takes over 80 percent of project time to format the data, and that’s not even taking into account the time needed to frame the problem in machine-learning terms.

“It would take many weeks of effort to figure out the appropriate model for our dataset, and this is a really prohibitive step for a lot of folks that want to use machine learning or biology,” says Jacqueline Valeri, a fifth-year PhD student of biological engineering in Collins’s lab who is first co-author of the paper.

BioAutoMATED is an automated machine-learning system that can select and build an appropriate model for a given dataset and even take care of the laborious task of data preprocessing, whittling down a months-long process to just a few hours. Automated machine-learning (AutoML) systems are still in a relatively nascent stage of development, with current usage primarily focused on image and text recognition, but largely unused in subfields of biology, points out first co-author and Jameel Clinic postdoc Luis Soenksen PhD ’20.[…]

Read more: www.news.mit.edu

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Copyright: news.mit.edu – “Using AI, scientists find a drug that could combat drug-resistant infections”

Using an artificial intelligence algorithm, researchers at MIT and McMaster University have identified a new antibiotic that can kill a type of bacteria that is responsible for many drug-resistant infections.

If developed for use in patients, the drug could help to combat Acinetobacter baumannii, a species of bacteria that is often found in hospitals and can lead to pneumonia, meningitis, and other serious infections. The microbe is also a leading cause of infections in wounded soldiers in Iraq and Afghanistan.

“Acinetobacter can survive on hospital doorknobs and equipment for long periods of time, and it can take up antibiotic resistance genes from its environment. It’s really common now to find A. baumannii isolates that are resistant to nearly every antibiotic,” says Jonathan Stokes, a former MIT postdoc who is now an assistant professor of biochemistry and biomedical sciences at McMaster University.

The researchers identified the new drug from a library of nearly 7,000 potential drug compounds using a machine-learning model that they trained to evaluate whether a chemical compound will inhibit the growth of A. baumannii.

“This finding further supports the premise that AI can significantly accelerate and expand our search for novel antibiotics,” says James Collins, the Termeer Professor of Medical Engineering and Science in MIT’s Institute for Medical Engineering and Science (IMES) and Department of Biological Engineering. “I’m excited that this work shows that we can use AI to help combat problematic pathogens such as A. baumannii.”

Collins and Stokes are the senior authors of the new study, which appears today in Nature Chemical Biology. The paper’s lead authors are McMaster University graduate students Gary Liu and Denise Catacutan and recent McMaster graduate Khushi Rathod.[…]

Read more: www.news.mit.edu

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