Innovation and Technology
The Key
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Artificial Intelligence: Generative vs. Agentic
Generative AI: The Creative Powerhouse
Generative AI is all about creation. Think of it as the imaginative side of artificial intelligence. These systems are designed to produce content—text, images, music, code, and even video. At its core, generative AI learns from existing data and uses that knowledge to generate new, original outputs that mimic human creativity.
The rise of tools like ChatGPT, DALL•E, and MidJourney has catapulted generative AI into the mainstream. These systems rely on advanced machine learning models, particularly neural networks, to analyze and replicate patterns in the data they are trained on.
But generative AI isn’t perfect. Its outputs are only as good as the data it’s trained on. Feed it biased or incomplete data, and it will reflect those flaws. Moreover, it doesn’t truly “understand” the content it creates. It’s simply predicting what might come next based on patterns it has seen before. Despite this limitation, generative AI is already revolutionizing industries, from marketing to entertainment.
Agentic AI: The Autonomous Problem-Solver
While generative AI focuses on creating, agentic AI is all about doing. This type of AI is designed to act autonomously to achieve specific goals. Agentic AI systems don’t just generate outputs; they make decisions, take actions, and adapt to changing environments.
Think of agentic AI as the brains behind autonomous vehicles, robotic process automation, or smart assistants that can schedule your meetings and order your groceries. These systems are equipped with sensors, algorithms, and actuators that enable them to perceive their environment, process information, and execute actions.
What sets agentic AI apart is its ability to act with purpose. It’s not just reacting to input but considering objectives and making choices to achieve them. For instance, an autonomous drone delivering packages must navigate obstacles, optimize its route, and adapt to unforeseen circumstances—all without human intervention.
The Core Differences Between Generative And Agentic AI
The easiest way to differentiate generative AI from agentic AI is to think of their primary functions. Generative AI is about producing something new, while agentic AI is about achieving something specific. One creates, and the other acts.
Generative AI is largely static. It produces outputs based on the data it has learned but doesn’t adapt in real-time or interact dynamically with the world. It operates within predefined boundaries. In contrast, agentic AI is dynamic. It’s constantly processing new information, learning from its environment, and adjusting its actions accordingly.
Where They Intersect And Complement Each Other
Despite their differences, generative AI and agentic AI aren’t mutually exclusive. In fact, they often work together in powerful ways. For instance, an agentic AI system could use generative AI to help it communicate more effectively or create custom content on the fly.
Consider a virtual customer service agent. The agentic AI handles the real-time interaction, making decisions based on user input and guiding the conversation. Meanwhile, a generative AI component could craft nuanced and personalized responses to specific questions.
Why Understanding These Differences Matters
As AI becomes more integrated into our lives, understanding its various forms is crucial. Generative AI and agentic AI serve different purposes and come with distinct benefits and challenges. Recognizing these nuances can help businesses and individuals make informed decisions about how to leverage AI effectively.
For businesses, this knowledge is invaluable for strategic planning. Do you need AI to create compelling marketing content? Generative AI is your go-to. Do you need AI to automate complex processes or manage tasks? Agentic AI is the answer. Knowing which type of AI fits your needs can save time, money, and resources.
The Future Of Generative And Agentic AI
The lines between generative and agentic AI will blur further as these two types of AIs evolve and improve. Advances in technology could lead to systems that seamlessly integrate creation and action, combining the best of both worlds. Imagine an AI that not only generates innovative ideas but also implements them autonomously—a game-changer for industries ranging from healthcare to manufacturing.
Conclusion
The future of artificial intelligence depends on our ability to understand and leverage both generative and agentic AI effectively. By recognizing their unique strengths and limitations, we can unlock their full potential and create a world where AI serves humanity in meaningful and transformative ways.
FAQs
What is the primary function of generative AI?
Generative AI is designed to produce content—text, images, music, code, and even video.
What is the primary function of agentic AI?
Agentic AI is designed to act autonomously to achieve specific goals, making decisions, taking actions, and adapting to changing environments.
Can generative and agentic AI work together?
Yes, these two types of AI often work together in powerful ways, enabling them to leverage each other’s strengths and achieve more complex goals.
Innovation and Technology
Banks Will Extend Real-Time Payments To Send In 2025
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The Rise of Real-Time Payments in the US
Real-Time Payments to Increase in 2025
According to John Byl, SVP and product development manager at Mercantile Bank of Michigan, 2025 is expected to be a year where banks that have tried real-time payments in receive-only mode will take the next big step – sending payments.
Rise of Real-Time Payments Networks
The first real-time payments system was launched by The Clearing House (TCH) about seven years ago. It recently announced that it had processed a total of more than one billion payments by Jan 31, 2024. TCH covers more than 70% of the demand deposits in the US, and its network has been processing a significant number of transactions.
FedNow and RTP
The Federal Reserve launched its own real-time payments network, FedNow, a year ago and has signed up over 1,000 financial institutions and is adding new participants at a good clip. The two services have very different maximum transaction limits. RTP increased the limit to $10 million, while FedNow has a default credit transfer limit of $100,000 and a maximum of $500,000.
Increased Demand for Real-Time Payments
Erika Baumann, director of the commercial banking & payments practice at Datos Insights, a financial tech consultancy, expects payment software providers to offer solutions that work for both RTP and FedNow. She also predicts that the volume, both number of transactions and value, will be concentrated at the largest banks – the top five banks by number of accounts hold more than 246 million accounts, according to the Federal Reserve.
Banks Taking a Wait-and-See Approach
Many banks have approached real-time payments cautiously, starting with receiving payments, which is low risk. "Everybody’s chosen to receive and now they’re taking a wait and see approach to the origination side of things and are watching to see what others are doing," said John Byl.
Challenges and Risks
Sending payments runs the risk of getting the recipient or the amount wrong, and since the payment is real-time, it is difficult, or impossible, to recover misdirected funds. The biggest challenge in sending real-time payments is the risk of fraud, which can be prevented by having the appropriate systems in place.
Conclusion
As real-time payments become more widespread, it is expected to revolutionize the way payments are made. With the rise of real-time payments, customers will be able to send and receive money instantly, making transactions faster and more convenient. However, there are challenges and risks associated with real-time payments, such as fraud and misdirected payments, which must be addressed by financial institutions.
FAQs
Q: What is the current state of real-time payments in the US?
A: Real-time payments are becoming increasingly popular, with The Clearing House (TCH) processing over one billion payments by January 2024.
Q: What are the differences between RTP and FedNow?
A: RTP increased the limit to $10 million, while FedNow has a default credit transfer limit of $100,000 and a maximum of $500,000.
Q: What are the challenges of real-time payments?
A: The biggest challenge is the risk of fraud, which can be prevented by having the appropriate systems in place. There is also the risk of getting the recipient or the amount wrong, and since the payment is real-time, it is difficult, or impossible, to recover misdirected funds.
Innovation and Technology
Inclusive Education: Breaking Down Barriers with Digital Technologies
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Technology has the power to transform lives. It can bridge gaps, connect communities, and empower individuals. In the context of education, technology can be a game-changer, breaking down barriers and creating a more inclusive learning environment for all. In this article, we’ll explore the ways in which digital technologies are revolutionizing education, making it more accessible, engaging, and effective for students of all abilities, cultures, and backgrounds.
The Importance of Inclusive Education
Inclusive education is not just a moral imperative, but a necessary step towards creating a more just and equitable society. Every individual, regardless of their abilities, gender, race, or socioeconomic status, deserves access to quality education. Unfortunately, many students face significant barriers to learning, including physical and learning disabilities, language barriers, and socioeconomic disparities. These barriers can lead to a lack of confidence, low self-esteem, and a sense of isolation.
Breaking Down Barriers with Digital Technologies
Fortunately, digital technologies are helping to break down these barriers, creating a more inclusive and accessible education system. Here are some ways in which technology is making a positive impact:
Personalized Learning
Adaptive learning systems and AI-powered educational software can tailor learning experiences to individual students’ needs, abilities, and learning styles. This personalized approach can help students with disabilities, English language learners, and students from diverse cultural backgrounds to better engage with the material and achieve their full potential.
Accessible Content
Digital resources, such as e-books, online courses, and educational apps, are making it possible for students to access a wide range of educational content from anywhere, at any time. This is particularly important for students with disabilities, who may have difficulty accessing traditional physical classrooms or materials.
Virtual Learning Environments
Virtual learning environments, such as virtual reality (VR) and augmented reality (AR), are creating immersive and interactive learning experiences that can be particularly effective for students with learning disabilities, such as autism, ADHD, or dyslexia. These technologies can also help to reduce feelings of anxiety and social isolation in traditional classroom settings.
Communication and Collaboration
Digital tools, such as video conferencing software and online collaboration platforms, are enabling students to communicate and collaborate more effectively with peers and educators from around the world. This can be particularly beneficial for students who may face language barriers or have difficulty participating in traditional classroom discussions.
Challenges and Opportunities
While digital technologies are transforming education, there are still significant challenges to overcome. These include:
Equity and Access
Ensuring that all students have access to digital technologies, including devices, internet connectivity, and educational software, is a significant challenge. This is particularly true for students from low-income backgrounds, rural areas, or developing countries.
Teacher Training and Support
Teachers need training and support to effectively integrate digital technologies into their teaching practices, particularly in areas such as personalized learning, virtual learning environments, and online collaboration.
Data Protection and Security
Ensuring the security and protection of student data is critical, particularly in the context of online learning. This requires educators and policymakers to prioritize data protection and security measures.
Conclusion
Inclusive education is a fundamental human right, and digital technologies have the power to break down barriers and create a more just and equitable education system. By leveraging these technologies, we can create personalized learning experiences, provide accessible content, and foster communication and collaboration. While there are challenges to overcome, the benefits of inclusive education far outweigh the costs. It is time for policymakers, educators, and technologists to work together to create a more inclusive and effective education system for all.
FAQs
What are the benefits of inclusive education?
Inclusive education promotes social justice, equity, and diversity, and helps to break down barriers and create a more inclusive society.
What are some examples of digital technologies that can support inclusive education?
Examples include adaptive learning systems, AI-powered educational software, virtual reality (VR) and augmented reality (AR), video conferencing software, and online collaboration platforms.
How can educators integrate digital technologies into their teaching practices?
Educators can start by familiarizing themselves with digital tools and technologies, and seeking training and support to effectively integrate them into their teaching practices.
What are some of the challenges to overcome in implementing inclusive education?
Some of the challenges include ensuring equity and access to digital technologies, providing teacher training and support, and prioritizing data protection and security.
Innovation and Technology
Steve Mann, Father of Wearable Computing
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Steve Mann at the 2025 IEEE ICCE
Awards and Recognition
At the 2025 IEEE International Conference on Consumer Electronics, ICCE, as Past President of the IEEE, I presented Steve Mann with the IEEE Masaru Ibuka Consumer Electronics Award.
About Steve Mann
Steve is a Professor of Computer Engineering in the Department of Electrical and Computer Engineering at the University of Toronto in Ontario, Canada. He is widely regarded as "The father of wearable computing." Professor Mann founded the MIT Wearable Computing Project, which has had a major impact on the development of Virtual Reality, Augmented Reality, and eXtended Reality products and services.
Innovative Achievements
In 1998, he invented, designed, and built the world’s first smartwatch capable of downloading and running a wide variety of apps for health, well-being, and fitness tracking, ushering in a new era of personal health. More than 30 years ago, Mann also invented High Dynamic Range imaging, which is now used in nearly every commercially manufactured smartphone, as well as many other cameras and computer vision systems, including systems to help the visually impaired see. He invented HDR imaging in his childhood and brought this invention to MIT and further refined it there.
Personal Interests and Inventions
Steve lives in Toronto and is an avid swimmer, including ice swimming in the Winter. One of his inventions is a hydraulophone, a musical instrument that uses a pressurized hydraulic fluid, such as water, to make sound. He also developed wearable augmented reality goggles for swimming that allow a group of swimmers to monitor the state of fellow swimmers, especially for ice swimming. In the 1990’s Mann continuously transmitted his life’s experiences, in real-time, to his website for other people to view and respond to.
Extended Reality and Terminology
Steve has created his own terminology to describe interesting aspects of our experiences of reality. The figure below illustrates his view of the elements of our modern human experience, including the traditional physical world, composed of atoms, a modern social world of humans, which he characterizes as genes, and a virtual or cyber world of bits.
Chart to show relationship of extended reality to the world of genes, atoms and bits.
Combining the Cyber, Human, and Physical Worlds
Combining the cyber world with the physical world gives us the ability to compute and create models, such as digital twins. Combining the cyber world with the human world enables social media and the metaverse. Adding all three elements leads to various cyber/human/physical experiences that can be generally described as extended reality, XR.
Demonstrating the Interconnectedness of Reality
At the ICCE, Steve strove to give attendees experiences that illustrate his observations. For example, he held a lit light source in his hand to show that we are all made of meat and blood on the inside.
The IEEE Masaru Ibuka Consumer Electronics Award
The IEEE Masaru Ibuka Consumer Electronics Award was established in 1987 and recognizes outstanding contributions in the field of consumer electronics technology. The award is sponsored by the IEEE Ibuka Fund and is named in honor of Dr. Masaru Ibuka, who was the Honorary Chairman and co-founder of Sony Corporation. Ibuka’s innovative achievements and leadership have been an inspiration to several generations of electrical, electronics, and computer engineers.
Conclusion
Steve Mann’s contributions to the field of consumer electronics have been recognized with the IEEE Masaru Ibuka Consumer Electronics Award at the 2025 IEEE ICCE in Las Vegas.
Frequently Asked Questions
- Who is Steve Mann?
- Steve Mann is a Professor of Computer Engineering at the University of Toronto and is widely regarded as "The father of wearable computing."
- What is the IEEE Masaru Ibuka Consumer Electronics Award?
- The IEEE Masaru Ibuka Consumer Electronics Award recognizes outstanding contributions in the field of consumer electronics technology.
- What are Steve Mann’s notable inventions?
- Steve Mann has invented the world’s first smartwatch, High Dynamic Range imaging, and wearable augmented reality goggles for swimming, among other inventions.
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