Let’s unpack the latest news in AI:

AI reshapes corporate strategy from boardroom to supply chain
Countdown to 2025: The EU AI Act prepares to roll out
Could AI ease the burden of end-of-life decisions?
Robots get smarter with AI ‘brains’.
AI and IoT pioneering the next wave of smart investments
… and more!

Enjoy these insights and keep riding the wave of innovation!

Warmest regards,

The Team of SwissCognitive

Der Beitrag Robots Get Smarter With AI ‘Brains’. erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

Copyright: nature.com – “Using machine learning algorithms to enhance IoT system security”

The term “Internet of Things” (IoT) refers to a system of networked computing devices that may work and communicate with one another without direct human intervention. It is one of the most exciting areas of computing nowadays, with its applications in multiple sectors like cities, homes, wearable equipment, critical infrastructure, hospitals, and transportation. The security issues surrounding IoT devices increase as they expand.

To address these issues, this study presents a novel model for enhancing the security of IoT systems using machine learning (ML) classifiers. The proposed approach analyzes recent technologies, security, intelligent solutions, and vulnerabilities in ML IoT-based intelligent systems as an essential technology to improve IoT security. The study illustrates the benefits and limitations of applying ML in an IoT environment and provides a security model based on ML that manages autonomously the rising number of security issues related to the IoT domain.

The paper proposes an ML-based security model that autonomously handles the growing number of security issues associated with the IoT domain. This research made a significant contribution by developing a cyberattack detection solution for IoT devices using ML. The study used seven ML algorithms to identify the most accurate classifiers for their AI-based reaction agent’s implementation phase, which can identify attack activities and patterns in networks connected to the IoT.

The study used seven ML algorithms to identify the most accurate classifiers for their AI-based reaction agent’s implementation phase, which can identify attack activities and patterns in networks connected to the IoT. Compared to previous research, the proposed approach achieved a 99.9% accuracy, a 99.8% detection average, a 99.9 F1 score, and a perfect AUC score of 1.

It highlights that the proposed approach outperforms earlier machine learning-based models in terms of both execution speed and accuracy, and also illustrates that the suggested approach outperforms previous machine learning-based models in both execution time and accuracy.[…]

Read more: www.nature.com

Der Beitrag Using Machine Learning Algorithms To Enhance IoT System Security erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

Dalith Steiger and Andy Fitze, Co-Founder of SwissCognitive, World-Leading AI Network
Copyright: moneycab.com – “MWC24: Eine Revolution in der Welt der Technologie (MWC24: A revolution in the world of technology)”

Highlights and innovations at MWC24

MWC24 showcased an impressive array of innovations and technologies that are pushing the boundaries of connectivity. From the launch of new wearables with a fashionable design focus to comprehensive reports on the future of telecoms technology paving the way for new devices and technologies, MWC24 offered an insight into the industry’s most exciting developments. The variety of really good-looking products, such as the OPPO Air Glass 3 smart glasses, the Samsung Galaxy Ring, and the various Huawei fashion wearables, ranging from smart headphones to smartwatches, left visitors in awe. Companies are striving to develop really good-looking products.

Breaking through barriers: The campaign to bridge the usage gap

Discussions also focused on important topics such as closing the usage gap and promoting digital inclusion. The usage gap, which excludes millions of people worldwide from the benefits of the internet, remains a pressing challenge. The GSMA’s Breaking Barriers campaign aims to close this gap and ensure that everyone has access to the internet. Asisat Oshoala, the ambassador for this campaign, is committed to ensuring that the younger generation has access to the internet by using her own foundation and the Asisat Oshoala Academy to teach digital skills.

The evolution of connectivity: from 4G to 5.5G

Mobile technology has evolved rapidly in recent years to meet the growing need for connectivity in an increasingly connected world. While 4G was mainly aimed at connecting people and things, 5G has already expanded connectivity in the home. However, with the introduction of 5.5G, the boundaries are being pushed again to enable even broader connectivity, including the vehicles and the industry.

The benefits of 5.5G:

Connectivity for vehicles: 5.5G enables the seamless integration of vehicles into the Internet of Things, leading to greater safety, more efficient traffic management and new entertainment and communication options.

Connectivity for industry: The integration of 5.5G into industrial applications and production processes will enable seamless communication between machines, sensors and other devices.

Better performance and efficiency: 5.5G will increase bandwidth, reduce latency, and increase data volumes, resulting in faster and more efficient connectivity.

Further developments and innovations

In addition to advances in connectivity, other important topics and developments were also discussed at MWC24. The partnership between the European Space Agency (ESA) and the GSMA Foundry to drive innovation in terrestrial satellite communications was one of the most exciting pieces of news.

The dominance of 5G and the future of 5.5G

New figures from GSMA Intelligence showed that 5G is expected to account for more than half of all mobile connections by the end of the decade.

5G has proven to be the fastest-adopted mobile generation and is expected to reach 5.5 billion connections worldwide by 2030. This development will fundamentally change the way we communicate, work and live. 5.5G will enable even greater connectivity between people, things, homes, vehicles and industries. This will play a key role in shaping our connected and digitized future.

The role of open access [Open Gateway] at MWC24

While artificial intelligence (AI) was undoubtedly the focus of MWC24, the Open Gateway also played an important role. Major mobile operators such as Telefónica, Orange, Deutsche Telekom and Vodafone are showing increasing interest in using the Open Gateway to develop and share a growing number of APIs to monetize their 5G networks. These APIs provide developers with universal access to operator networks under the umbrella of the GSMA’s Open Gateway Initiative.

Demonstrations and use cases

Various demonstrations were shown at MWC24 to illustrate the versatility of Open Gateway. For example, Telefónica enabled visitors to immerse themselves in a multi-camera sporting event with the help of virtual reality headsets. The Open Gateway made it possible to experience the event with 180- and 360-degree views “in the best service quality” and without interruptions.

Increasing importance and support

The importance of the Open Gateway was also underlined by industry leaders, including Mats Granryd, Director General of the GSMA, and José María Álvarez-Pallete, Chairman and CEO of Telefónica. According to the GSMA, almost 50 mobile operator groups, representing around 65% of global connections, have now signed up to the Open Gateway initiative.

Opportunities and risks

Opening up networks to developers through Open Gateway offers mobile operators enormous opportunities to offer new and innovative services. A study by McKinsey & Company shows that the market for network APIs could generate between 100 and 300 billion dollars in revenue for operators over the next five to seven years. However, the company warns that operators will not be the only ones competing for this lucrative market.

MWC Barcelona 2024 in numbers

MWC Barcelona 2024 attracted more than 101,000 unique attendees from 205 countries and territories, with more than 59% of attendees representing industries outside the core mobile ecosystem. With more than 2,700 exhibitors, sponsors, and partners and over 1,100 speakers and opinion leaders, of which more than 40% were women, MWC24 was an impressive gathering of the industry’s leading minds and innovators.

Summary and outlook

Mobile World Congress 2024 was another milestone in the evolution of the technology industry. With groundbreaking innovations, important discussions and pioneering partnerships, MWC24 showed that the future of technology is bright and full of possibilities. As we prepare for the launch of 5.5G and beyond, we are on the brink of an exciting era of connectivity that has the potential to change the world as we know it.

Original article: www.moneycab.com

Der Beitrag MWC24: A Revolution In The World Of Technology erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

SwissCognitive Guest Blogger:  Utpal Chakraborty, Chief Technology Officer, IntellAI NeoTech – “Reflecting On 2023: A Year Of Technological Wonders And The Future That Awaits In 2024”

We can admit that 2023 was a year of technological revolution. We witnessed the explosive rise of Generative AI, the increasing interconnectedness of the digital world, and the gradual ascent of Quantum Computing. As we stand on the crossover of 2024, reflecting on the technological revolution of 2023 brings into focus a transformative year for Information Technology. Generative Artificial Intelligence (GenAI) has taken centre stage, with advancements and applications proliferating at an unprecedented pace. The past year witnessed a surge in the development and deployment of generative AI models, revolutionizing sectors from healthcare to finance, to entertainment and beyond.

Key Developments and Figures:

• Generative AI models became more sophisticated with some achieving near-human levels of creativity and understanding.
• Adoption across industries soared with a reported increase of over 60% in enterprises integrating generative AI into their operations as co-pilot and into different applications.
• Investment in AI research and development reached new heights with billions of dollars allocated globally.

Bright Prospects: The Expanding Horizons of Generative AI in 2024

2023 was the year when Generative AI became capable of creating novel content like text, code, and even images, broke free from the confines of research labs and into the mainstream. Generative AI models like of DALL-E 2 and Midjourney captivated the world with their ability to generate photorealistic images from mere text prompts while GPT-4 showcased its uncanny ability to craft human-quality prose. The impact was immediate, industries from advertising to design, media to medicine, saw the potential of AI-powered content creation. A study by PwC predicts that Generative AI will add $15.7 trillion to the global economy by 2030.

Insights for the Future:

• By the end of 2024, generative AI is projected to contribute upwards of $1 trillion to the global economy.
• Customization and personalization services powered by AI are anticipated to become the norm, enhancing user experience and efficiency.
• The integration of AI with other emerging technologies, like the Internet of Things (IoT) and blockchain, is set to unlock new potential.

Quantum Computing is the Next Frontier

While Generative AI steals the spotlight, Quantum Computing (QC) is making waves in its own way. Although still in its nascent stages, the field is advancing rapidly, promising to tackle problems beyond the reach of classical computers. In 2023, significant milestones in quantum research and infrastructure laid the groundwork for future breakthroughs.

Quantum Leap:

• Global investment in quantum technology saw a substantial increase, signaling strong confidence in its future.
• Partnerships between academia, industry and government intensified, driving forward the quantum agenda.
• Experts predict that within the next few years, quantum computing will begin solving complex problems in areas like drug discovery, logistics and cryptography.

The Imperative of Ethical and Responsible AI

As we embrace these technological advancements, the importance of ethical and responsible AI usage has become paramount. The call for transparent, fair & accountable AI systems is echoed worldwide, urging developers, enterprises, and governments to adhere to ethical standards.

Responsible Innovation:

• Policies and frameworks for responsible AI use have been implemented globally gradually, with an emphasis on privacy, security and fairness.
• Initiatives to educate and raise awareness about the ethical implications of AI have been rolled out across educational institutions and organizations.
• The establishment of ethics boards and review committees has become more common, ensuring oversight and accountability.

Investing in the Future

The technological revolution of 2023 is a proof to human ingenuity, but a strong call to action in the same time. Enterprises and governments are encouraged to invest in these burgeoning technologies, fostering innovation and securing a competitive edge.

Strategic Investments:

• Increased funding for AI and quantum computing research is imperative to maintain momentum and achieve breakthroughs.
• Collaboration between the public and private sectors can accelerate development and application.
• Education and workforce development in these fields are crucial to prepare for the demands of tomorrow.

A Call to Embrace the AI Future:

The mentioned advancements in AI necessitate a proactive approach from both enterprises and governments. Businesses must invest in building AI-powered solutions and upskilling their workforce to thrive in the new landscape. Governments, meanwhile, need to foster responsible AI development by establishing ethical guidelines and addressing potential bias issues. The World Economic Forum’s “Principles for Responsible AI”  offer a valuable framework for this endeavor.

While concerns about job displacement and ethical implications remain, the potential benefits of AI are vast. By embracing AI responsibly and proactively, we can step into a future where technology augments human capabilities, creating a world of unimaginable possibilities.

2024 has arrived, and we can expect Generative AI to create something spectacular.

Der Beitrag Reflecting On 2023: A Year Of Technological Wonders And The Future That Awaits In 2024 erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

Copyright: cxomagazine.com – Jacques Ludik – “Creating Transformative Solutions for A Better Future”

Dr. Ludik, please tell us about your background and areas of interest.

My journey began with a deep-rooted curiosity about the workings of intelligence, both human and artificial. With a Ph.D. in Artificial Intelligence from Stellenbosch University, I ventured into the realm of smart technology entrepreneurship, establishing several AI companies over the past two and a half decades. From founding Africa’s first AI company, CSense Systems, and selling it to General Electric, to my later endeavours at JUMO.WORLD and the companies I have subsequently founded such as Cortex Logic, Cortex AI Group, Vive Teen Wellness, Journey Wellness and the Machine Intelligence Institute of Africa, as well as my investment in educational platforms like The Student Hub, it’s evident that my journey is fuelled by a combination of intellectual curiosity, a business acumen, and a deep-seated desire to foster positive change through technology. Across the diverse roles I’ve held, from being an academic to leading AI-based companies and engaging in global AI initiatives, the common thread has been my passion for AI and its transformative potential, and building AI-based companies with data rich platforms that leverages AI technologies to unlock business, customer and societal value at scale.

My endeavours have always been driven by the desire to harness AI for the betterment of business, society, and individuals at scale, solving complex problems and making a positive impact in the world as also communicated in my latest book “Democratising Artificial Intelligence to Benefit Everyone: Shaping a better future in the Smart Technology Era (jacquesludik.com). I have also introduced an massive transformation purposes (MTP) for humanity and its associated goals (that complement the United Nations’ sustainable development goals) to help shape a beneficial human-centric future and founded Sapiens.Network as a decentralized, human-centric, user-controlled AI-driven super platform. I have recently co-founded Sustainable Technology Venture Capital (STVC) Fund of Funds with its own AI-driven investment automation platform and am also currently pushing for establishing a global AI Leader and pushing AI Innovation to amongst others develop state-of-the-art personalized AI and intelligent agents on trustworthy AI guardrails for a decentralized world.

Which disruptive technology are you fascinated by and why?

The boundless potential of Artificial Intelligence captivates me. Its ability to mimic human intelligence, learn from data, and automate complex tasks holds the promise of solving some of humanity’s most pressing challenges, from healthcare and education to climate change. Moreover, the convergence of AI with other technologies like blockchain and IoT is creating a foundation for an innovative, decentralized, and human-centric digital future. The realm of Generative AI, particularly its ability to create new content and solutions, truly fascinates me. It’s like opening up a universe of possibilities that were previously unimagined or unreachable. This technology has the potential to revolutionize numerous industries by fostering creativity, innovation, and efficiency, which is incredibly inspiring.

What was the inspiration behind establishing Cortex Logic? Tell us about its key offerings.

Although the original vision for Cortex Logic was a combination of building scalable AI-driven platforms (which was eventually built in, especially the wellness space with solutions such as Vive Teen Wellness (viveyou.com) and Journey Wellness (journeywellness.co.za)) and solving intelligence (similar to Deepmind), the focus initially shifted to providing an AI engine for business and delivering AI-driven enterprise solutions aligned with key business value drivers and assisting enterprises on their AI-driven digital transformation journey. Our key offerings revolve around providing AI-powered solutions that drive operational efficiencies, improve customer experiences, and create new revenue streams. Whether it’s healthcare, finance, or retail, our aim is to leverage AI to solve critical problems and deliver tangible value.

How do you envision the next phase of Cortex?

As we consolidate the current Cortex Logic business activities and transition to Cortex AI, we envision establishing a global AI leader in emerging markets to develop state-of-the-art personalized AI and intelligent agents on trustworthy AI guardrails for a decentralized world. Cortex AI’s focus is aligned with my own massive transformative purpose around pushing AI innovation, the creation of a personal AI that operates in a decentralized, human-centric, user-controlled, private, trustworthy and explainable fashion, and shaping a better future in the Smart Technology Era (see also my book on “Democratizing AI to Benefit Everyone: Shaping a Better Future in the Smart Technology Era (jacquesludik.com)).

We envision a future where everyone has access to Personalized AI that can help them to live better lives and operates in a decentralized, human-centric, user-controlled, private, trustworthy and explainable fashion. We believe that AI has the potential to revolutionize the way we interact with the world through Intelligent Agents that are operating on trustworthy AI guardrails in a decentralized world that empowers people and optimizes quality of life in accordance with a Massive Transformative Purpose for Humanity that complements the United Nations’ Sustainable Development Goals. We envision a decentralized human-centric user-controlled AI-driven Super Platform with personalized AI agents that not only empower individuals and monetizes their data and services, but can also be extended to families, virtual groups, companies, communities, cities, city-states, digital nations and beyond (sapiens.network). We envision an “ecosystems of intelligence” where collectives of intelligent agents, both human and synthetic, collaborate in harmony and work together to create a better and smarter world.

How do you intend to pushing AI innovation to build better personalized AI and intelligent agents on trustworthy AI guardrails?

Although we need to build on the current state-of-the-art Generative AI stack and address the current limitations of large language models (LLMs) and related deep learning models, I believe that there are also other complementary important building blocks that should be in the smart technology toolbox for the development of personalized AI and Intelligent Agents: (1) Active Inference AI based on the Free energy principle for distributed intelligence and development of autonomous intelligent agents; (2) Energy-based Self-supervised Learning AI for development of autonomous intelligent agents

We need to build trustworthy personalized AI and intelligent agents that learn reliable world models, learn and adapt to new situations, reason, predict, and plan complex action sequences at multiple time horizons. We need to address the lack of Sympathetic AI that can understand and respond to the emotions and needs of people and other AIs. There is also a lack of Shared AI that can work together with humans, other agents and physical systems to solve complex problems and achieve goals.

You are the Founder & President at Machine Intelligence Institute of Africa. Can you please tell us about this non-profit organization and its vision?

MIIA (miiafrica.org) is a testament to my belief in the transformative power of AI for Africa. This non-profit initiative aims at building a strong, innovative, and collaborative AI and Data Science community across the continent. Through MIIA, we envision fostering innovation and leveraging AI to address African challenges, thus playing a part in the continent’s transformation. MIIA has also assisted and collaborated with other AI and Data Science organization on the African continent such as Data Science Nigeria, Artificial Centre of Excellence in Kenya, and Zindi that connects organisations with a global community of data scientists.

Your latest book is titled “Democratizing Artificial Intelligence to Benefit Everyone”. Can you share the major takeaways from this book?

My latest book, Democratizing Artificial Intelligence to Benefit Everyone, takes us on a holistic sense-making journey and lays a foundation to synthesize a more balanced view and better understanding of AI, its applications, its benefits, its risks, its limitations, its progress, and its likely future paths. The book also synthesizes, assimilates, and acts as a filter on a wide spectrum of thought leadership, information, ideas, and research to enable as many people as possible to not only interpret and make sense of this, but also participate in helping shape a better future for ourselves, our children and humanity going forward. It helps us to more accurately understand where we are heading given the current dynamics on a global and national economic and political level as well as across ideologies and industries. Specific solutions are also shared to address AI’s potential negative impacts, designing AI for social good and beneficial outcomes, building human-compatible AI that is ethical and trustworthy, addressing bias and discrimination, and the skills and competencies needed for a human-centric AI-driven workplace.

I specifically argue for a more decentralized beneficial human-centric future where AI and its benefits can be democratized to as many people as possible. It further examines what it means to be human and living meaningful in the 21st century and share some ideas for reshaping our civilization for beneficial outcomes as well as various potential outcomes for the future of civilization. The book also proposes a Massive Transformative Purpose for Humanity and associated goals that complement the United Nations’ 2030 vision and sustainable development goals to help shape a beneficial human-centric future in a decentralized hyperconnected world. As a practical step towards a building block in support of this purpose and goals, this initiative has been introduced and an invitation extended to people around globe to participate in the development, deployment and use of a decentralized, human-centric, and user-controlled AI-driven super platform called Sapiens. To help shape this better future we need a collective, integrated, and comprehensive response that involves all stakeholders of the global system of governing, from the private and public sectors to civil society and academia.

Career-defining moment: What has been your most career-defining moment that you are proud of?

The establishment and subsequent acquisition of Africa’s first AI company, CSense Systems, by General Electric in 2011, was a pivotal moment in my career. It not only validated the potential of AI but also opened doors for me to drive significant AI initiatives on a global scale.

What’s the best advice you have received in your career?

The best advice I received was to continually learn and adapt as well as always remain curious and open to learning. The field of AI is ever-evolving, and staying abreast of new developments while being open to new perspectives has been instrumental in my journey. This advice has kept me on a path of continuous learning and exploration.

How do you motivate yourself and stay motivated?

The impact that AI can have on humanity and the exciting challenges that lie ahead keep me motivated. Every day is an opportunity to learn, innovate, and contribute towards a better future. My motivation stems from the potential of AI to significantly improve lives and create a more equitable world. The thought of contributing to a larger purpose keeps me motivated. Moreover, surrounding myself with a community of like-minded individuals who are equally passionate about making a positive impact through technology, fuels my enthusiasm and drive.

What mantra do you live by?

My mantra is “Innovation with Purpose, Collaborate, and Transform.” It reflects my belief in the power of innovation, the importance of collaborative efforts, and the ultimate goal of creating transformative solutions for a better future. I believe that technological advancements should always aim at creating positive societal impact. It’s not about what we can achieve with AI, but what we should achieve to build a better future.

What advice would you offer others looking to build their career in technology?

I would encourage individuals to remain curious, be willing to learn continuously, and be adaptable to new technologies and methodologies. Engaging with communities, collaborating on projects, and building a network within the tech ecosystem can significantly accelerate learning and open doors to exciting opportunities. The tech landscape is fast-evolving, and continuous learning is crucial. Secondly, find your niche – a domain that truly resonates with you, and strive to make a meaningful impact within that sphere. Lastly, build a strong network within the tech community. Collaboration and knowledge-sharing are the bedrocks of innovation in our field.

Original article.

Jacques will be speaking at the SwissCognitive World-Leading AI Network AI Conference focused on The AI Trajectory 2024 – Invest for Impact on 13th December.

Der Beitrag Creating Transformative Solutions for A Better Future erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

SwissCognitive Guest Blogger: Meike Krautscheid – “The Synergy of AI & Blockchain – What are the Use Cases?”

The world of technology has experienced a whirlwind in recent years, driven by two overwhelming forces: the hype surrounding artificial intelligence and the meteoric rise in the realm of cryptocurrencies and blockchain. While the AI hype has been accompanied by rapid technological advancements and mass adoption through platforms like ChatGPT, the blockchain world, particularly the realm of cryptocurrencies, has seen its share of ups and downs. However, crypto enthusiasts eagerly await the next upswing.

While the once-dominant cryptocurrency hype was initially overshadowed by the unstoppable wave of artificial intelligence, a question arises:

How can the worlds of AI and blockchain harmoniously converge and potentially unleash synergy?

Within the blockchain community, the belief is widespread that the true magic of the technology unfolds when combined with other groundbreaking technologies. Alongside the Internet of Things (IoT), sensors, Smart Contracts, and Ricardian Contracts, Artificial Intelligence is coming under the spotlight. But before we delve deeper into the potential synergy between AI and blockchain, it is crucial to establish a foundation by understanding what blockchain is and what makes it unique.

Blockchain technology has revolutionized the way we can store and manage data. As early as the late 1980s, scientists Scott Stornetta and Stuart Haber recognized that the increasing flood of data would pose a challenge: the need to determine the time of data creation, authenticate it, and verify it to prevent fraud, such as tampering with transactions by backdating and editing.

The scientists’ approach was to use a kind of mathematical “blender” (cryptographic hash function) to generate a unique serial number, known as a hash, which is as unique as a fingerprint, for each file. This makes even the slightest change in a file detectable. Documents previously encrypted in data blocks using hash values and timestamps and chained together are resistant to retroactive alterations; only new data can be easily added.

Stornetta and Haber have been offering this system through their central company since the 1990s, allowing users to timestamp their files with a digital timestamp that proves the authenticity and integrity of the file at a specific time. This is a crucial tool for securing the integrity of electronic documents and data.

The innovation of a central timestamp system developed by Stornetta and Haber served as the template for the decentralized system in the Bitcoin blockchain. In Bitcoin, timestamping occurs in a decentralized network without the need for a central authority. Each transaction is hashed and protected by cryptographic keys. A protocol and consensus mechanism ensure that coins cannot be double-spent, and data cannot be retroactively manipulated. The order of transactions and blocks in Bitcoin is secured through the Proof-of-Work mining process. Even if multiple actors in the Bitcoin network fail, falter, or attempt dishonest actions, the system remains robust and continues to be a trusted, decentralized, and secure method for transferring value and data.

A decentralized blockchain is crucial for data integrity because it ensures that no central authority has the ability to retroactively manipulate data. Similar to a global accounting system, the blockchain updates its records simultaneously and decentralizes the origin of data. Moreover, it enables transparent tracking of changes to the data, including the detection of manipulations.

How can these advantages of data security through blockchain now intersect with Artificial Intelligence?

High-quality datasets are essential for developing powerful AI models. AI entities require high-quality data to learn patterns and make accurate predictions or decisions. For example, when the Retrieval Augmented Generation (RAG) framework is employed to retrieve results from an internal source, a blockchain safeguard can be used to verify that the data assets returned are authentic and that the content extracted from these assets aligns with the original consensus against these assets. However, it’s important to note that this is not meant for everyday use, as it is highly costly and is suitable for specific critical cases, such as mortgage documents and financial statements. Think of it as two databases converging: the vectorized database from RAG and the blockchain decentralized database using a consensus mechanism that is widely accepted as the standard. Therefore, the synergy with blockchain could improve the reliability of training data for AI models and enable more effective use of AI in various applications.

With the rise of generative AI-generated digital content, the boundary between reality and fiction is growing increasingly ambiguous. It’s becoming difficult to determine which images and videos are genuine, technically manipulated, or entirely AI-generated. However, a potential solution arises: we can label media content, including Deep Fakes, with universal indicators and facilitate the verification of the authenticity of such content through a blockchain by storing a simple hash of the content. This technology can confirm that the content remains unaltered and genuine, whether it is stored or indexed in the blockchain, and it is verifiable by anyone.

The potential of the alliance between AI and blockchain can also be explored in areas such as the Internet of Things (IoT), financial markets, Smart Cities, supply chain management, personalized medicine, and more.

In the field of Supply Chain Management, the combination of Artificial Intelligence and Blockchain technology could enable the analysis of data while ensuring a seamless tracking of the origin and the entire product supply chain. Usually, such data is centrally stored in data lakes, and when it is, there is a risk of data manipulation or the possibility that information does not reach relevant stakeholders in the supply chain in real-time.

AI algorithms can validate data before it’s entered into the blockchain to ensure it meets predefined criteria and standards. Real-time fraud detection is also made possible as AI models continuously monitor transactions for anomalies, with the transparency of the blockchain ensuring secure recording. Furthermore, AI data analysis facilitates informed decision-making, providing valuable insights and predictive analytics. This benefits supply chain quality assurance and empowers consumers to verify the quality and authenticity of products – provided that producers grant access to this data.

In Smart Cities, AI agents (AIAs) or Convolutional Neural Networks (CNNs), in conjunction with data stored on the blockchain, could enable a more economical and resilient urban economy. This combination allows for real-time data processing, crucial for urban emergencies, traffic control, and improving citizens’ quality of life. Convolutional Neural Networks (CNNs) are relevant for analyzing visual data in Smart Cities, including traffic pattern recognition, environmental monitoring, and security applications, while AI agents can recognize patterns and make intelligent decisions, such as resource allocation.

Similarly, Blockchain and AI offer numerous advantages in the healthcare sector. Firstly, blockchain allows the decentralized storage and secure encryption of health data, protecting it from hackers and unauthorized access. Patients have control over who can access their data, and with the help of Zero-Knowledge Proofs (ZKPs), patients can share their data without revealing their identity and compromising their privacy. AI agents can then access this data, identify patterns, and make informed decisions. For example, if DNA data is available, it can be used to detect rare genetic diseases.

Furthermore, imagine an AI trading bot that operates on the blockchain without revealing its detailed workings but proves its effectiveness through Zero-Knowledge Proofs. The combination of machine learning (ML) and yield farming also takes place on-chain, with crucial parts of the process remaining confidential. Blockchain enables verification and transparency of information, with critical parameters protected by ZKPs.

It’s worth noting that all transactions occurring on the blockchain can be traced using analytics tools. For example, the blockchain intelligence company Gray Wolf Analytics provides a tool that uses artificial intelligence to understand on-chain and off-chain activities. If fraudulent transactions are detected, financial and cybercriminal activities can be prevented or traced by relevant authorities.

There will also be a revolution in the software sector, as modern NoCode super-app builder platforms will be used to create apps, APIs, and websites with the help of AI. While AI initiates software creation, the use of blockchain creates a secure and verifiable environment for bug-free versions that can be verified by any user.

In another scenario, AI could serve as a “sheriff” monitoring punctuality to meetings. If someone arrives late, the AI triggers a Smart Contract on the blockchain, resulting in a donation from the tardy person to charitable projects. However, there is a certain risk associated with the use of these technologies, especially in authoritarian states concerning the monitoring of legal violations, as individuals’ identities could potentially be listed on a social rating or blacklist on the blockchain, leading to significant restrictions.

Blockchain technology could potentially address issues that come with the use of AI. In the context of Generative Artificial Intelligence (GAI), a challenge is that it might use copyrighted content to generate new content, potentially leading to conflicts with copyright owners. By utilizing digital signatures and hash functions, data integrity is significantly improved, allowing for cryptographic verification that a data record existed at a specific point in time and remained unchanged.

In a later article, we will delve deeper into how blockchain ensures transparent tracking of the creation and modification of content, addressing the legal aspects related to GAI and potential copyright infringements.

We can expect that in the future, blockchain will help distinguish between good and bad data. While blockchains offer ideal attributes for storing critical data, which can be a valuable data source for AIs, it’s important to consider that models like the Generative pre-trained Transformer (GPT-3) were trained on approximately 45 terabytes of text files – a massive amount of data. Given that storing data on the blockchain incurs monetary costs, it’s likely that only indexes like pointers or the most essential data will be directly stored on the blockchain for use as data sources for AIs. Economic and other incentives will be crucial with blockchain usage. Beyond a minimum of revenues that must occur, there are additional challenges to overcome, including scalability, interoperability, and legal issues like GDPR.

It’s worth noting that both AI and blockchain technologies are still in their developmental stages, but we can anticipate exciting developments and innovations on the horizon, with numerous opportunities yet to be explored.

About the Author:

Meike Krautscheid is an entrepreneur and expert in blockchain-based applications. Her extensive knowledge of blockchain, NoCode, AI and related technologies has established her as a recognized thought leader. Meike is a sought-after keynote speaker at international conferences and events. Furthermore, she shares her expertise and vision through lectures and workshops at renowned universities worldwide. Through her dedication, she engages with a worldwide audience and plays an active role in spreading innovations.

Der Beitrag The Synergy of AI & Blockchain – What are the Use Cases? erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

SwissCognitive Guest Blogger: Nicolas Maréchal, AI Consultant – “Three AI Trends in the F&B Industry (2023)”

In recent years, we have observed several significant developments that demonstrate the increasing impact of AI in this industry. Artificial intelligence is transforming the food and beverage (F&B) industry. The sector is projected to reach a USD 35.42 billion valuation by 2028 (USD 7 billion in 2023), at a CAGR rate of 38.30% during the forecast period (2023-2028)¹. From that perspective, this article covers three AI trends that are disrupting the global F&B industry’s landscape in 2023.

1. AI-powered chatbots

Chatbots can simulate conversations with human users and are being used by restaurants and food retailers to provide quick and accurate responses to customers. Leveraging Natural Language Processing (NLP) technologies, chatbots can understand a customer’s inquiry in multiple languages and immediately reply with the relevant information, making communication more efficient and accurate.

Amongst others, chatbots can take and process orders, support the booking process, answer specific questions about menu items (such as allergens, sources, etc.) or provide information about special deals and promotions. They can also be combined with recommender systems (intelligent systems based on user preferences) to create personalized offers to retain clients and consolidate loyalty.

With the recent rise of LLMs (Large Language Models), we can expect many more breakthroughs in this field. For example, considering the topic of automatic recipe generation and menu creation, chatbots can suggest ingredient combinations and flavor profiles that are likely to be well-received by customers. This supports chefs to create new relevant and exciting dishes while meeting the dietary requirements of different customers and providing nutritional information.

In conclusion, chatbots save customers time and contribute to improving their overall experience with the brand, in addition to increasing efficiency.

More use cases related to LLMs and chatbots.

2. Cameras as sensors (Computer Vision)

One of the main sub-fields of Artificial Intelligence is known as Computer Vision. It basically refers to the processing, analysis, and understanding of digital images. Based on this technology, major use cases have emerged around the images and videos recorded by (surveillance) cameras.

For example, AI can detect visitors entering and leaving a restaurant to analyze occupancy over time (people counting applications), enabling managers to plan staff based on actual demand. It can also monitor important safety measures (such as hand washing, surface cleaning, gloves detection, mask detection, etc.), to avoid cross-contamination or improper food handling, and assist the workforce in improving overall food safety.

AI-powered cameras can also be used to identify any areas where staff need further training and even to detect and prevent theft. Trained to recognize specific products and packaging, AI models can for example send a real-time alert if any unauthorized items are removed from the kitchen.

However, one important consideration with this kind of model is the risk of privacy violations, depending on where the surveillance cameras are installed and located and what is recorded. These types of projects should be implemented in accordance with national policies and data privacy regulations such as the General Data Protection Regulation (GDPR), The EU Artificial Intelligence Act (EU AI Act), and more.

More use cases on how AI cameras can improve safety in restaurants.

3. AI-driven Robots, Automation, and Smart Kitchen

AI technologies also drive disruption in food production departments, enabling chefs to automatize non-critical and time-consuming tasks. AI Robots or “Robot chefs” (a mix of AI, Robotics, and Computer Vision) are already able to handle some entire cooking procedures end-to-end. This can include monitoring the cooking process or automatizing equipment such as ovens or cleaning vacuums, simply requiring a push of a button or voice activation.

The fundamental concept around Smart Kitchens concerns the transformation of select kitchen appliances into “sensors” and their integration with Internet of Things (IoT) technologies. This process facilitates the smooth interconnection of these devices, enabling the collection and analysis of real-time data. Smart Kitchen can ingest and process data from these interconnected appliances and subsequently provide prescriptive or predictive alerts and insights to users. This dynamic integration of technology empowers restaurants and individuals to optimize their cooking experiences, enhance efficiency, and make informed decisions. Tailored for individuals, we observe a rising demand for this type of device, such as Smart Fridge, making the cooking experience smarter and simpler.

More info on AI-driven robot chefs.

Conclusion

As Artificial Intelligence (AI) brings obvious benefits to the F&B sector, it is also important to underline the potential drawbacks that it can have on humans. In fact, AI could lead to reducing the demand for human labor, with a significant impact on the workforce needs in the industry. However, with the appropriate planning and management, restaurants and food retailers can adopt AI without necessarily negatively affecting jobs but rather helping to improve the industry overall.

The F&B industry is projected to skyrocket to a staggering USD 35.42 billion valuation by 2028, and embracing AI as well as aligning with expert partners becomes not just a choice but an imperative. By seizing this transformative technology, players can unlock unparalleled growth and secure their position in this increasingly fiercely competitive landscape.

If you are interested in AI trends and use cases applied to the Security sector, check out this article from SwissCognitive.

Sources

¹https://www.mordorintelligence.com/industry-reports/artificial-intelligence-in-food-and-beverages-market

https://www.mordorintelligence.com/industry-reports/artificial-intelligence-in-food-and-beverages-market

https://www.technavio.com/report/artificial-intelligence-market-in-food-and-beverage-industry-analysis

https://www.forbes.com/sites/jennysplitter/2020/04/23/this-ai-camera-can-help-restaurants-show-that-their-food-is-safe-from-covid-19/?sh=52973f0925b9

https://www.columbusglobal.com/en-us/blog/blog/6-ai-use-cases-in-the-food-and-beverage-manufacturing-industry

https://www.qsrmagazine.com/outside-insights/how-artificial-intelligence-reshaping-restaurant-world

https://timesofindia.indiatimes.com/blogs/voices/how-artificial-intelligence-is-revolutionizing-the-food-and-beverage-industry/

https://www.sourcesecurity.com/insights/staying-speed-utilising-ai-video-analytics-co-1538138049-ga.1629100806.html

https://goliathconsulting.blog/2020/12/12/five-ways-ai-cameras-will-help-your-restaurant-in-2021/

https://thespoon.tech/expect-more-restaurants-to-use-ai-cameras-like-dragontails-to-monitor-kitchen-cleanliness/

https://www.aiplusinfo.com/blog/ai-enabled-smart-kitchens/

https://aicontentfy.com/en/blog/chatgpt-in-food-industry-recipe-generation-and-personalization

https://fortune.com/2022/10/18/tech-forward-everyday-ai-robots-pizza/

About the Author:

Nicolas Maréchal is an AI Consultant at Artificialy SA, a Swiss company specializing in Artificial Intelligence. From consultancy, all the way to custom turn-key AI solutions, Artificialy SA delivers value to clients’ processes, products, data, and decisions. Nicolas is also Visiting Lecturer at EHL Hospitality Business School and teaches Python Programming.

Der Beitrag 3 AI Trends in the F&B Industry (2023) erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

SwissCognitive Guest Blogger: Dr. Sachin Kumar Agrawal, Director Innovation Artificial intelligence – “Revolutionizing Healthcare: The Power of Generative AI in Patient Care”

Innovation in healthcare has always been a driving force in improving patient care and outcomes. The emergence of generative artificial intelligence (AI) is set to revolutionize the way we approach healthcare, providing novel and inventive solutions to some of the most pressing challenges. This article explores the potential benefits of using generative AI in patient care and showcases a few exciting use cases that demonstrate its transformative power.

Enhancing Diagnostics: Generative AI algorithms have the ability to analyze vast amounts of patient data, including medical records, lab results, and imaging scans, to generate insights and aid in diagnostics. By training on a diverse dataset, generative AI models can identify patterns and subtle correlations that may elude human physicians. This technology holds great promise in improving the accuracy and speed of diagnosis, leading to early detection of diseases and more personalized treatment plans.

Personalized Treatment Plans: The advent of generative AI opens up new horizons for personalized medicine. These intelligent algorithms can process large-scale genomic data and combine it with an individual’s medical history, lifestyle factors, and environmental influences to create tailored treatment plans. By considering the unique genetic makeup of each patient, generative AI can predict drug responses and identify the most effective therapies, optimizing treatment outcomes and minimizing adverse reactions.

Virtual Assistants for Healthcare Providers: Generative AI-powered virtual assistants can support healthcare providers in their day-to-day activities. These assistants can analyze patient symptoms, medical records, and literature databases to generate evidence-based recommendations, ensuring that physicians have the most up-to-date and comprehensive information at their fingertips. By streamlining administrative tasks and providing real-time clinical decision support, generative AI virtual assistants can help alleviate the burden on healthcare professionals and enhance overall patient care.

Predictive Analytics and Preventive Care: Generative AI algorithms excel in analyzing large-scale data sets, enabling them to identify hidden patterns and predict future health outcomes. By analyzing patient data in real time, these algorithms can flag potential health risks and alert healthcare providers to intervene before a condition worsens. This proactive approach to healthcare can lead to early intervention, prevention of complications, and improved patient outcomes.

Patient Empowerment and Education: Generative AI can be harnessed to develop innovative patient education tools. By processing vast amounts of medical literature, clinical guidelines, and patient experiences, these algorithms can generate personalized educational materials and recommendations. Patients can gain a better understanding of their conditions, treatment options, and self-care strategies, empowering them to actively participate in their own healthcare journey.

Overall,  Generative AI represents a game-changing technology that holds immense potential to revolutionize patient care. By leveraging this technology, healthcare providers can enhance diagnostics, personalize treatment plans, improve efficiency, and empower patients to take control of their health. However, it is crucial to address ethical considerations, data privacy and ensure proper validation and regulation to fully harness the benefits of generative AI in healthcare. As we continue to push the boundaries of innovation, generative AI will undoubtedly play a significant role in shaping the future of patient care.

About the Author:

Dr. Sachin Kumar Agrawal is leading projects in emerging technologies like Generative AI, Metaverse, AR, VR, IOT, Artificial intelligence, ANN, machine learning, 5G, 6G, Wireless, and Cloud as Director of Innovation and Artificial intelligence. Dr. S Kumar has a Ph.D. in Artificial Intelligence and has been working with top Fortune 100 companies. Expertise: “Intelligent Innovation for Research and Monetization”

Der Beitrag Revolutionizing Healthcare: The Power of Generative AI in Patient Care erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

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.

Der Beitrag 10 AI Trends to Catapult the Global Agricultural Landscape in 2024 erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

SwissCognitive Guest Blogger: Agnieszka Maciąg – “Leveraging the Potential of AI in Manufacturing: How to Implement and Scale Up?”

Since quite a while, AI stopped being just a buzzword. Propelled by introduction of ChatGPT, more and more organizations are looking for opportunities how to leverage this promising technology in order to drive business value. In this case manufQacturing industry is also not an exception. According to Statista, the adoption rate of artificial intelligence is expected to grow in manufacturing and supply chain industries from 2022 to 2025. In 2022, only 11% of senior executives reported that AI is critical and 34% expected a widescale adoption of this technology, respectively in 2025 these numbers increased to 38% of respondents claiming AI criticality in successful manufacturing operations and lowered down to 30% on widescale adoption.

While these numbers are still relatively low, there is a hope for an increase in technology adoption in the upcoming years. However, there is a debate on how to achieve that. Below, there is a comprehensive guide on how to effectively integrate AI into manufacturing.

1. Understand AI Power

Among AI capabilities, in 2022, it was mostly leveraged in technologies such as Robotic Process Automation (39%) and computer vision (34%). Rethinking how these can be used in the manufacturing spectrum, one can point out automating manual repetitive processes within production planning – handling production orders, booking transportation, or extracting data from purchase orders and invoices with the use of OCR. While automating production processes is the baseline for eliminating human non-value-added work, AI can bring business to the forefront of innovation and allow for production risk elimination and building successful forecasts for demand to fully optimize manufacturing levels.

2. Build a strategy

With limitless growth opportunities, the second step after grasping AI capabilities should be to fully understand business needs and connect them. A good AI integration strategy should ensure improving employee satisfaction, in addition to, minimizing product waste, and optimizing overall production. It should also go in line with the main business strategy and serve as a support to achieve goals and initiatives.

The first step in devising an artificial intelligence strategy should be to set objectives and determine AI algorithms that are relevant to manufacturing needs. Whether it should be machine learning, computer vision, or natural language processing (NLP), each aspect should reflect factors such as data availability, computational resources, and know-how in the company in order to implement and provide maintenance of AI systems.

3. Investigate data sources and prepare

Effective use of AI starts with having profound sources of data which can be leveraged for algorithms’ training and decision-making. In the manufacturing reality, data collection can include technologies such as IoT devices and sensors within the production line or just historical records and manual inputs. The important step should be to clean and preprocess data to eliminate any outliers and inconsistencies which can disrupt the final result of AI models. Due to security issues, it is crucial also to implement safety measures to protect sensitive information and ensure data privacy.

4. Develop AI algorithms

After devising an AI strategy and selecting data sources, appropriate methodologies and algorithms should be selected to develop AI models tailored to the identified manufacturing needs. Some of the most commonly used algorithms in manufacturing include supervised learning (used for predictive tasks and classification), unsupervised learning (spotting patterns and data structures on unlabeled datasets), or reinforcement learning (usually used in optimization tasks or resource allocation). The selection of the algorithm should rely on the data structure available and set objectives and goals. To achieve the best accuracy, it is important to iterate and refine the parameters of the AI models using both historical and current data with the help of data scientists, AI experts, or external partners in case of a lack of AI expertise within the organization.

5. Integrate and monitor

Once AI models are selected, it is time to integrate them with the existing IT systems and processes in place. This step should be achieved by a close collaboration of IT business partners and operations to ensure streamlined data flow between the production environment and devised AI recommendations. Before any move to production, thorough testing and validation are required to sustain the reliability of the systems and don’t cause any disruptions in production. After passing User Acceptance Testing (UATs), the baseline is to introduce standard protocols, establish thorough documentation to facilitate transparent communication in the future, and allow implementation improvements. All this should be also supported by data analytics tools such as BI reporting to gain insights into system accuracy, and performance, and track any errors or anomalies.

6. Look out for scale-up opportunities

1. Continuous improvement

Ensuring successful implementation of AI in such a complex industry as manufacturing is relying on continuous improvement of AI models by updating and retraining them to improve their accuracy, in addition to, regular upskilling of the employees to promote digital skills and ensure trust in technology eliminating the fear factor of being replaced by “robots”.

2. Scale up and experiment

As with most business activities, organizations should investigate how they can scale up utilized algorithms across the company. This can include identifying similar processes or needs in other markets, departments, or business areas. However, there shouldn’t be fear of the adoption of AI – in some cases, it can be implemented as a small pilot project which will validate whether the use of such technology is profitable and brings value.

In conclusion, the manufacturing industry has great potential to leverage artificial intelligence capabilities to aid human workers in various manufacturing activities. However, the implementation of such technology also brings challenges concerning upskilling technical and nontechnical employees, in addition to, deriving the most effective results from the models. Nevertheless, above-described guide should point a direction on how to start off with integrating AI into daily manufacturing activities.

About the Author:

Agnieszka Maciąg is a professional specializing in artificial intelligence and automation in the realms of manufacturing and supply chain. With a strong foundation in consulting, where she gained perspective on business needs and optimization opportunities, she is right now a manager of Automation and Digitization in one of the leading FMCG companies.

Der Beitrag The Potential of AI in Manufacturing: How to Implement and Scale Up? erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.