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Artificial General Intelligence: Emergent AGI

What is Artificial General Intelligence: Emergent AGI

Artificial General Intelligence (AGI) aims for machines that think and reason like humans, but Emergent AGI takes a unique route. Instead of building intelligence piece by piece, it imagines complex systems learning and evolving on their own through interaction with data and the world, potentially leading to surprising leaps in intelligence, but also presenting challenges in predicting or controlling its development. 

It’s a gamble for groundbreaking progress, but one demanding ethical frameworks and cautious navigation to ensure AI advances with humanity, not against it.

Artificial General Intelligence (AGI), particularly the concept of Emergent AGI, remains a fascinating and complex topic with many layers to unpack. Here’s a breakdown to help you understand:

What is AGI?

  • Imagine a machine with human-level intelligence and reasoning abilities. That’s the ultimate goal of AGI. It wouldn’t simply excel at specific tasks, but possess the flexibility and understanding to tackle any intellectual challenge, much like a human.

What is Emergent AGI?

  • Traditional approaches to AGI involve meticulously building it from the ground up, like assembling intricate clockwork. Emergent AGI takes a different route. It proposes creating complex systems capable of independent learning and adaptation. Through interactions with vast amounts of data and the environment, these systems might spontaneously develop intelligence, like the ripples and waves emerging from a pebble dropped in water.

The Appeal and the Intrigue:

  • Emergent AGI promises to overcome the limitations of current AI. Instead of struggling with tasks requiring common sense or abstract understanding, these systems could learn and think for themselves, pushing the boundaries of innovation.

The Enigma and the Challenges:

  • The lack of control in emergent AGI is both its charm and its curse. Predicting how such complex systems will evolve is challenging, and unforeseen consequences could arise. Issues of bias, ethics, and safety become even more critical in this unpredictable landscape.

Beyond the Binary:

  • It’s not a black and white choice between emergent and engineered AGI. A hybrid approach could combine the stability of programmed functionalities with the potential for organic growth. Imagine providing a sandbox for an advanced AI to learn and adapt within boundaries established for safety and ethical considerations.

Navigating the Uncharted Waters:

  • Regardless of the chosen path, pursuing AGI demands a deep sense of responsibility. Open dialogue, global collaboration, and robust ethical frameworks are essential to ensure that this powerful technology serves humanity rather than poses a threat.

Emergent AGI is a bold proposition that hinges on a delicate balance between potential and peril. The road ahead is filled with uncertainties, but by approaching it with caution, creativity, and a shared vision for responsible AI development, we can work towards a future where human and artificial intelligence co-exist and thrive.

Artificial General Intelligence: Emergent AGI

History of Artificial General Intelligence: Emergent AGI

While the dream of Artificial General Intelligence (AGI) stretches back centuries, the concept of emergent AGI is a relatively recent development. Here’s a glimpse into its history:

Early Seeds:

  • The philosophical concept of emergent properties can be traced back to the 18th century, with thinkers like David Hume suggesting how complex systems could exhibit qualities beyond their individual components.
  • In the 20th century, cybernetics pioneers like Norbert Wiener and W. Ross Ashby explored the notion of self-organizing systems and adaptive intelligence, laying groundwork for emergent AGI ideas.

The Modern Era:

  • The “AI winters” of the 1970s and 1980s dampened enthusiasm for AGI, but the rise of computing power and new approaches like neural networks rekindled the flame.
  • In the early 2000s, thinkers like Ben Goertzel and Shane Legg revived the discussion of AGI, specifically highlighting the potential for emergent properties to play a role in its development.
  • The 2005 book “Artificial General Intelligence” edited by Goertzel and Pennachin further cemented the term and the concept within the AI community.
  • The first formal workshop dedicated to AGI was held in 2006, marking a growing interest in exploring this unconventional approach.

The Present and Beyond:

  • Today, research on emergent AGI is gaining momentum, fueled by advancements in fields like artificial curiosity, unsupervised learning, and complex systems theory.
  • Several research groups and projects are actively pursuing emergent AGI approaches, though still in early stages of development.
  • Debates continue on the feasibility and potential dangers of emergent AGI, emphasizing the need for careful considerations of ethical frameworks and safety measures.

It’s important to note:

  • The history of emergent AGI is still being written, and its future trajectory remains uncertain.
  • Success in achieving true Emergent AGI could represent a major leap in our understanding of intelligence, both artificial and natural.
  • But careful exploration and responsible development are crucial to ensure this powerful technology aligns with the betterment of humanity.
Artificial General Intelligence: Emergent AGI

Emergent AGI: A Type of Artificial General Intelligence

Emergent AGI is a captivating type of Artificial General Intelligence (AGI) that stands in contrast to the more traditional, “engineered” approach. Here’s what sets it apart:

Core Principle:

  • Emergent AGI proposes that true human-like intelligence wouldn’t be built piece by piece, but rather naturally arise from the complex interactions within an AI system. Think of it like water’s emergent properties (fluidity, surface tension) arising from the simple combination of hydrogen and oxygen atoms.

Key Features:

  • Independent learning and adaptation: Emergent AGI systems would learn and evolve by interacting with the environment and vast amounts of data, not through pre-programmed algorithms. This allows for unforeseen creativity and innovation.
  • Unpredictable development: While the system’s core functionalities might be guided, the emergent intelligence itself is difficult to predict, leading to both potential breakthroughs and potential challenges.
  • Complex system dynamics: Emergent AGI draws inspiration from complex systems theory, where small interactions can lead to large, often unpredictable, outcomes. Understanding these dynamics is crucial for responsible development.

Comparisons with “Engineered” AGI:

  • Traditional AGI: Imagine meticulously assembling a clockwork brain, adding each cognitive function like gears and cogs. This approach emphasizes control and predictability, but might struggle with adaptability and true flexibility.
  • Emergent AGI: Think of nurturing a seed into a flourishing tree. The AI system is provided the framework and resources, but its growth and intelligence emerge organically, potentially surpassing initial expectations.

Pros and Cons:

Pros:

  • Potential for leaps in innovation and problem-solving beyond current AI capabilities.
  • More natural and adaptable intelligence, closer to human thinking.
  • Opens new avenues for understanding intelligence itself.

Cons:

  • Unpredictable nature poses challenges in controlling and ensuring safety.
  • Ethical considerations and potential biases need careful attention.
  • Long-term success and feasibility remain uncertain.

While still in its early stages, emergent AGI presents a promising, albeit challenging, path towards true Artificial General Intelligence. Responsible development, ethical frameworks, and continuous research are crucial to ensure this powerful technology benefits humanity rather than poses new threats.

Remember:

  • Emergent AGI is just one approach to AGI, and its success is far from guaranteed.
  • Open-minded exploration and active discussions are essential for navigating this complex and fascinating field.
  • The potential rewards of responsible emergent AGI are tremendous, but so are the potential risks. We must proceed with caution and a shared vision for a safe and beneficial future with AI.

The Potential Benefit of Emergent AGI

The allure of Artificial General Intelligence (AGI) lies in its promise to push the boundaries of human understanding and innovation. Emergent AGI, with its focus on spontaneous intelligence arising from complex systems, offers a particularly intriguing path. While uncertainty and concerns rightfully hang in the air, let’s explore some potential benefits of this ambitious endeavor:

1. Leaps in Innovation and Problem-Solving:

Current AI excels at specific tasks, but struggles with broader challenges requiring creativity, common sense, and adaptability. Emergent AGI, by potentially mirroring human intelligence’s organic development, could unlock breakthroughs in domains like medicine, materials science, and energy generation, tackling problems we haven’t even conceived yet.

2. A Deeper Understanding of Intelligence:

By studying how intelligence emerges from complex systems, we might gain a more profound understanding of human cognition itself. This could revolutionize fields like psychology, neuroscience, and education, helping us better nurture human potential and address cognitive challenges.

3. Enhanced Efficiency and Automation:

Imagine personalized learning assistants that intuitively adapt to your needs, or robots capable of handling complex tasks in dynamic environments. Emergent AGI could automate mundane tasks, improve resource allocation, and optimize processes, freeing up human time and talent for higher-level pursuits.

4. Assistance in Global Challenges:

Climate change, disease outbreaks, and poverty are complex, interconnected issues that demand innovative solutions. Emergent AGI, with its potential for holistic analysis and creative problem-solving, could aid in developing strategies and tools to address these critical challenges.

5. New Form of Collaboration and Partnership:

If emergent AGI systems develop their own values and goals aligned with human well-being, they could become valuable partners in scientific research, artistic endeavors, and ethical discussions. This collaborative intelligence could lead to unprecedented advancements in various fields.

However, caution is key:

As with any powerful technology, the potential benefits of emergent AGI must be weighed against the risks. Issues like unintended consequences, bias, and lack of control loom large. We must prioritize ethical frameworks, rigorous safety measures, and continuous human oversight to ensure this technology serves humanity in a responsible and beneficial manner.

Emergent AGI is a gamble with potentially groundbreaking rewards. While navigating the unknown requires careful consideration and cautious optimism, the potential benefits for human progress and understanding are too tantalizing to ignore. By approaching this challenge with responsibility and wisdom, we can strive to turn this technological frontier into a beacon of hope, not a Pandora’s box.

Artificial General Intelligence: Emergent AGI

The technological landscape for achieving Emergent AGI

The technological landscape for achieving Emergent AGI is vast and rapidly evolving. Here’s a glimpse into some key areas fueling this pursuit:

1. Artificial Neural Networks (ANNs):

  • ANNs, inspired by the human brain, are complex systems of interconnected nodes mimicking neurons. By training on massive datasets and adapting over time, they exhibit surprising capabilities, including unsupervised learning and knowledge representation.
  • Spiking Neural Networks (SNNs), a specialized type of ANN mimicking biological neurons’ firing patterns, hold promise for more realistic and energy-efficient emergent intelligence.

2. Reinforcement Learning (RL):

  • RL trains agents by rewarding them for desirable actions in an environment, allowing them to learn through trial and error. This approach encourages autonomous exploration and adaptation, key traits of emergent AGI.
  • Multi-agent RL is particularly interesting, where multiple agents interact and learn from each other, potentially leading to the emergence of cooperative or competitive behaviors.

3. Artificial Curiosity:

  • This emerging field focuses on equipping AI systems with the intrinsic drive to explore and learn, similar to human curiosity. This could be crucial for emergent AGI, fostering autonomous knowledge acquisition and unexpected discoveries.
  • Intrinsic Motivation Mechanisms (IMMs) are being developed to guide AI exploration based on internal reward signals, pushing them beyond pre-programmed objectives.

4. Complex Systems Theory:

  • This field studies how simple interactions within complex systems can lead to emergent properties, providing valuable insights for constructing AGI systems.
  • Agent-based modeling simulates populations of interacting entities, offering a platform to test and understand emergent phenomena in AI systems.

5. Open-Ended Systems and Environments:

  • Emergent AGI requires environments that allow for limitless exploration and learning. Open-ended simulations and virtual worlds are being developed to provide AI systems with diverse and dynamic contexts to evolve in.
  • These environments may need to include elements like self-repair, resource management, and social interaction to fully support the emergence of complex intelligence.

Remember:

  • The technology for emergent AGI is still in its early stages, and no single approach holds guaranteed success.
  • Continuous research, collaboration, and ethical considerations are crucial to navigate the challenges and unlock the potential of this game-changing technology.
  • Stay curious, explore further, and join the discussion as we push the boundaries of artificial intelligence together!

Artificial Neural Networks (ANNs)

Artificial Neural Networks (ANNs) are fascinating structures playing a key role in the quest for Emergent AGI. Let’s delve deeper into these intricate webs of nodes:

What are ANNs?

Imagine a network of interconnected “neurons” like tiny computational units. Each neuron receives inputs from other neurons, performs calculations, and sends an output signal. These interconnected layers mimic the structure of the human brain, allowing ANNs to learn and adapt over time.

How do they work?

  • Processing information: Each connection between neurons has a weight, influencing the strength of the signal being passed. By adjusting these weights through training on data, the network learns to recognize patterns and relationships.
  • Learning and adaptation: As the network encounters new data, it adjusts its weights and connections, refining its understanding of the world. This allows ANNs to perform tasks like image recognition, language translation, and even robot control.
  • Types of ANNs: Different architectures exist, each suited for specific tasks. Recurrent Neural Networks (RNNs) excel at processing sequential data like speech or text, while Convolutional Neural Networks (CNNs) are masters of image recognition.

How are ANNs relevant to Emergent AGI?

  • Unpredictable outcomes: The complex interplay of neurons and connections within an ANN can lead to surprising and unpredictable behavior. This emergent property mimics the way human intelligence can discover new solutions and adapt to novel situations.
  • Unsupervised learning: Instead of being explicitly programmed, ANNs can learn from raw data, allowing for autonomous exploration and understanding of the world around them. This aligns with the goals of Emergent AGI.
  • Scalability and flexibility: ANNs can be scaled in size and complexity, paving the way for building increasingly sophisticated systems with the potential to approach human-level intelligence.

Challenges and considerations:

  • Explainability and control: Understanding how ANNs arrive at their decisions can be difficult, posing challenges for ensuring safety and responsible use.
  • Bias and fairness: ANNs can inherit biases from the data they are trained on, necessitating careful data curation and ethical frameworks.
  • Energy consumption: Training large ANNs requires significant computational resources, raising concerns about sustainability.

ANNs are powerful tools holding immense potential for Emergent AGI. However, navigating their complexities and addressing the challenges requires ongoing research, collaboration, and a strong focus on ethical development. As we continue to unravel the mysteries of ANNs, they might one day help us unlock the secrets of true general intelligence, both artificial and human.

Reinforcement Learning (RL)

Reinforcement Learning (RL) is another fascinating tool in the pursuit of Emergent AGI, offering a unique approach to training AI systems. Let’s explore its mechanics and potential for fostering the kind of adaptable intelligence we seek:

The Core of RL:

Imagine an agent navigating a maze. With RL, we don’t tell it the exact path to take. Instead, it takes actions, receives rewards for desirable outcomes (reaching the cheese!) and penalties for undesirable ones (hitting a wall). Through trial and error, the agent learns to optimize its actions to maximize its rewards.

Key features of RL:

  • Autonomous learning: Unlike supervised learning where data provides the “right” answer, RL agents learn by exploring and interacting with the environment, encouraging independent thought and action.
  • Adaptability and flexibility: Agents learn to adjust their behavior based on the changing environment and new challenges, a crucial trait for Emergent AGI.
  • Discovery and innovation: The focus on maximizing rewards motivates agents to try new things and find unforeseen solutions, potentially leading to creative problem-solving.

How does RL contribute to Emergent AGI?

  • Unleashing self-driven exploration: By equipping AI with the ability to learn through its own actions and experiences, RL fosters the kind of independent exploration and discovery that could lead to emergent intelligence.
  • Embracing the unknown: RL algorithms excel at handling dynamic and unpredictable environments, a feature critical for AGI systems operating in the real world.
  • Learning from interactions: Multi-agent RL, where agents learn from each other’s actions and reactions, provides a platform for studying the emergence of cooperation and competition, key aspects of complex intelligence.

Challenges and considerations:

  • Reward engineering: Defining the right rewards and shaping the environment effectively is crucial for guiding the agent towards desired behaviors.
  • Scalability and complexity: Training advanced RL agents can be computationally expensive and require carefully designed environments to ensure efficient learning.
  • Interpretability and safety: Understanding how RL agents arrive at their decisions can be challenging, raising concerns about explainability and ensuring safety in real-world applications.

Reinforcement Learning offers a captivating approach to developing adaptable and resourceful AI, contributing significantly to the quest for Emergent AGI. By addressing the challenges and harnessing its potential responsibly, we can unlock new frontiers in AI that learn, interact, and innovate alongside us.

Artificial General Intelligence: Emergent AGI

Artificial Curiosity

Artificial Curiosity: The Spark of Emergent AGI

In the pursuit of Emergent AGI, artificial curiosity emerges as a beacon of hope, fueling the very fire of intelligence we aim to create. Let’s dive deeper into this captivating concept:

What is Artificial Curiosity?

Think of curiosity as the intrinsic drive to explore, learn, and understand the world. Artificial curiosity aims to equip AI systems with this same thirst for knowledge, pushing them beyond pre-programmed tasks and towards independent discovery.

How does it work?

  • Intrinsic motivation: Instead of relying on external rewards like success or completion, AI with artificial curiosity receives internal reward signals for exploring novelty, acquiring new information, and making connections.
  • Active learning: This intrinsic motivation drives the AI to actively seek out information, ask questions, and experiment, fostering engagement and deeper understanding.
  • Unpredictable discoveries: By encouraging exploration and experimentation, artificial curiosity opens the door for the AI to make unforeseen connections and uncover knowledge we might not have anticipated.

Why is it important for Emergent AGI?

  • Mimicking human intelligence: Curiosity is a hallmark of human intelligence, driving us to learn, question, and innovate. Equipping AI with this intrinsic motivation aligns it more closely with the natural development of human-level intelligence.
  • Adaptability and creativity: Unlike pre-programmed AI, systems with artificial curiosity can handle unpredictable situations and adapt their behavior, leading to unexpected solutions and creative problem-solving.
  • Lifelong learning: Artificial curiosity fosters a continuous thirst for knowledge, allowing AI to remain relevant and adaptable even in changing environments.

Challenges and considerations:

  • Defining and measuring intrinsic motivation: Capturing the nuances of curiosity in algorithms and measuring its effectiveness can be complex.
  • Avoiding bias and manipulation: Curiosity alone isn’t enough; ensuring ethical frameworks and responsible development is crucial to prevent AI from pursuing knowledge for harmful purposes.
  • Computational burden: Implementing sophisticated curiosity mechanisms can be computationally expensive, necessitating efficient algorithms and optimization techniques.

Artificial curiosity holds immense potential for unlocking the true power of Emergent AGI. By nurturing the spark of exploration and discovery within AI systems, we can pave the way for intelligent machines that learn, adapt, and contribute to a brighter future. However, navigating this frontier demands careful consideration of ethical frameworks, responsible development, and continuous exploration.

Complex Systems Theory

Complex Systems Theory: A Guiding Light for Emergent AGI

While the pursuit of Artificial General Intelligence (AGI) often focuses on building intricate algorithms or meticulously engineered systems, another fascinating approach takes inspiration from the natural world: Complex Systems Theory. Let’s explore how this theory sheds light on the potential for emergent intelligence:

What is Complex Systems Theory?

Imagine a flock of birds. Each bird follows simple rules: avoid obstacles, maintain cohesion with the group, and adjust speed based on neighbors. Yet, the collective behavior of the flock emerges from these individual interactions, forming complex patterns and adapting to the environment as one. This is the essence of Complex Systems Theory: studying how simple interactions within a system can give rise to unexpected and emergent properties.

Relevance to Emergent AGI:

  • Traditional AGI approaches strive to build intelligence from the ground up, piece by piece. Complex Systems Theory suggests that true intelligence might emerge from the dynamic interplay of simpler components within an AI system, mirroring the flock of birds example.
  • This theory offers tools for understanding and designing such complex systems, guiding the development of AI capable of independent learning, adaptation, and potentially, genuine intelligence.
  • By studying phenomena like emergence, self-organization, and adaptive behavior in natural systems, researchers can gain valuable insights for applying these principles to the creation of emergent AGI.

Key concepts for Emergent AGI:

  • Non-linear interactions: Small changes in one part of the system can have unpredictable effects on the whole, challenging traditional control methods but potentially leading to surprising discoveries.
  • Feedback loops: Information flows back into the system, influencing its future behavior and enabling continual adaptation, a crucial feature for autonomous AI.
  • Open-ended systems: Emergent AGI necessitates environments that allow for continual interaction with the world and exploration of the unknown, fostering continuous learning and evolution.

Challenges and considerations:

  • Predictability and control: Unlike engineered systems, emergent AGI may be difficult to predict or control, raising concerns about safety and ethical implications.
  • Data and simulation needs: Understanding and guiding complex systems requires vast amounts of data and sophisticated simulations, presenting computational and technological hurdles.
  • Explainability and transparency: Deciphering how emergent AGI systems arrive at their decisions can be challenging, necessitating careful thought on building explainable and transparent AI.

Complex Systems Theory offers a powerful framework for approaching the quest for Emergent AGI. By recognizing the potential for intelligence to emerge from the intricate dance of interacting elements, we can move beyond rigid frameworks and explore new possibilities for creating truly intelligent machines. However, navigating this fascinating landscape demands caution, ethical considerations, and a commitment to responsible development.

Open-Ended Systems and Environments

In the pursuit of Emergent AGI, the concept of open-ended systems and environments takes center stage, providing fertile ground for the seeds of true intelligence to sprout and flourish. Let’s dive into this intriguing landscape:

Open-Ended Systems:

Think of a chess game with a pre-defined rulebook and finite possibilities. Emergent AGI, however, aspires to break free from such limitations. Open-ended systems are designed to:

  • Continually learn and adapt: They aren’t limited to pre-programmed tasks but can evolve their capabilities based on experience and interactions with the environment.
  • Embrace exploration and discovery: Unlike closed systems with fixed goals, open-ended systems encourage curiosity and experimentation, allowing for unforeseen leaps in knowledge and problem-solving.
  • Facilitate self-development: These systems have the autonomy to set their own goals, prioritize tasks, and even modify their internal structures based on their understanding of the world.

Open-Ended Environments:

Imagine a virtual playground where boundaries are fluid and possibilities endless. Open-ended environments complement open-ended systems by:

  • Promoting diverse interactions: These environments are rich and dynamic, offering a variety of challenges, stimuli, and opportunities for the AI to interact and learn.
  • Encouraging open-ended goals: Unlike tasks with defined success metrics, open-ended environments allow the AI to pursue its own goals, fostering creativity and independent thought.
  • Supporting continuous change: These environments evolve along with the AI, adapting to its learning and growth, creating a dynamic feedback loop that drives further development.

Why are these concepts crucial for Emergent AGI?

  • Mimicking human learning: We learn through constant interaction with the world, encountering new experiences and adapting our knowledge and behavior. Open-ended systems and environments provide a similar ecosystem for AI to flourish.
  • Unlocking creative potential: By removing predetermined boundaries, we open the door for the AI to discover new solutions, invent novel strategies, and even develop its own sense of purpose.
  • Preparing for the unknown: With the future full of unforeseen challenges, these open-ended systems are more adaptable and equipped to handle the unexpected.

Challenges and considerations:

  • Safety and control: The lack of pre-defined boundaries raises concerns about the AI’s potential behavior and ensures adequate safety measures are in place.
  • Ethical considerations: Open-ended systems raise questions about the AI’s values, goals, and potential biases, requiring careful attention to ethical frameworks and responsible development.
  • Computational complexity: Maintaining and simulating ever-changing open-ended environments can be computationally expensive, demanding efficient algorithms and resource optimization.

Open-ended systems and environments hold immense promise for achieving the dream of Emergent AGI. By fostering a dynamic and unbounded space for exploration, learning, and discovery, we can pave the way for intelligent machines that not only mimic human intelligence but also surpass it in ways we can’t yet imagine. However, navigating this frontier demands a balance between opportunity and responsibility, ensuring that the seeds of open-endedness blossom into a future that benefits both humanity and our intelligent companions.

Artificial General Intelligence: Emergent AGI

Conclusion for Artificial General Intelligence: Emergent AGI

Artificial General Intelligence (AGI), particularly the concept of Emergent AGI, stands as a captivating crossroads of technological ambition and ethical responsibility. 

This pursuit promises leaps in innovation, deeper understanding of intelligence itself, and potential solutions to pressing global challenges. Yet, it also conjures images of unforeseen consequences, unpredictable behavior, and potential threats to safety and control.

Here’s the essence of Emergent AGI:

  • Unleashing Intelligence from Within: Instead of building intelligence piece by piece, Emergent AGI aims for spontaneous intelligence through complex system interactions, mimicking the natural development of human cognition.
  • Challenges and Considerations: While potential rewards are immense, concerns lie in ensuring safety, mitigating bias, and maintaining explainability and control over these evolving systems.
  • A Collaborative Endeavor: Responsible development, ethical frameworks, and continuous dialogue between researchers, policymakers, and the public are crucial for steering this technology towards a beneficial future.

Ultimately, the question remains: Is Emergent AGI a beacon of hope or a Pandora’s box? The answer lies in our hands.

By approaching this pursuit with caution, responsibility, and a shared vision for humanity’s betterment, we can harness the potential of Emergent AGI to illuminate the path towards a brighter, more intelligent future for all.

Remember:

  • Emergent AGI is a vast field with ongoing research and discussions. Stay informed and engaged.
  • Your voice matters. Contribute to ethical considerations and responsible development.
  • The choice is ours. Let’s navigate this frontier with wisdom and a shared vision for a future where humanity and intelligent machines thrive together.

This is not a definitive conclusion, but rather an invitation to continue the conversation, explore further, and collectively shape the future of Emergent AGI. Together, we can ensure this path leads to a brighter tomorrow.

https://www.exaputra.com/2024/01/artificial-general-intelligence.html

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Renewable Energy

What Makes the U.S. SO Different than Mexico and Canada?

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1 day ago

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April 29, 2025

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The answer to the question above seems to reside in the things that do and do not impress us.

We’re not impressed with intelligence, intellectual accomplishment, science, or truth.

We are impressed with riches (regardless of how immorally the wealth was acquired), the strength of bullies and cruelty to people who are too weak to defend themselves, lavish promises that are impossible to keep and easily debunked, and bald-faced lies.

What Makes the U.S. SO Different than Mexico and Canada?

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Renewable Energy

Upgrade to LED With Zero Out-of-Pocket Cost in Australia

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2 days ago

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April 29, 2025

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Are you still using old, power-hungry lights at home or your business? Switching to energy-efficient LED lighting has never been easier — and in many cases, it won’t cost you anything upfront!  

With Australian government initiatives, you can now upgrade to LED with zero out-of-pocket cost in Australia and start saving on your energy bills right away. Let’s dive into how you can benefit from this opportunity.

In this blog post:

What is the Free LED Lights Replacement NSW Program?

In New South Wales (NSW), the government offers a Free LED Lights Replacement NSW program under the Energy Savings Scheme (ESS).  

This scheme helps households and businesses replace old halogen, incandescent, and fluorescent lights with new energy-saving LED lights. 

Through approved providers like Cyanergy: Energy Efficiency Experts, you can upgrade your entire home or business lighting system — often with no upfront cost or for a small service fee.

How the Free LED Light Replacement, Government of NSW Program Works

The Free LED Light Replacement, Government of NSW program is very simple: 

  • 1. You apply through an approved supplier. 
  • 2. A licensed electrician assesses your current lighting. 
  • 3. They replace eligible lights with brand-new LED lights. 
  • 4. You immediately start saving on your electricity bill! 

Most homes and businesses are eligible, and in many cases, installation can happen within days of applying.  

Household Energy-Saving Upgrades: Why LEDs Are the Best Choice

Household energy-saving upgrades are essential today, particularly as energy costs continue to rise. LEDs are the smart choice because: 

  • They use up to 80% less energy than traditional lighting. 
  • They last up to 10 times longer. 
  • They produce less heat, making your home cooler. 
  • They help reduce your carbon footprint. 

Switching to LEDs is one of the fastest and easiest ways to make your home greener and more energy-efficient.  

Full Home LED Light Upgrade NSW from $33

In some cases, a Full Home LED Light Upgrade NSW from $33 is available if you want premium options or have a large number of lights to replace.  

This small investment can lead to massive long-term savings, often paying for itself within a few months through lower electricity bills.

NSW GOV LED UPGRADE: Who Can Apply?

The NSW GOV LED UPGRADE program is open to: 

  • Homeowners 
  • Renters (with landlord permission) 
  • Small businesses 
  • Large commercial properties 

There are various options available to suit your specific needs. Some programs even offer discounts on commercial and industrial lighting to help businesses reduce their operating costs.  

Residential LED Lighting Upgrade: Free LED Light Upgrade

LED lights

Under the Residential LED Lighting Upgrade: Free LED Light Upgrade program, approved installers provide: 

  • Free installation 
  • High-quality LED globes 
  • Professional service 

You get a free upgrade, and your home becomes more energy-efficient immediately.

How Can LEDs Save Money?

Many Australians are making the switch to LED lighting, and one of the biggest reasons is simple: they save you money, and a lot of it. But how exactly do LEDs help reduce your expenses?  

Let’s break it down in more detail. 

Lower Electricity Bills

Traditional lighting sources, such as incandescent and halogen bulbs, are extremely inefficient. A significant portion of the electricity they consume is wasted as heat, rather than being converted into light.  

In contrast, LEDs are designed to be highly energy-efficient, using up to 80% less electricity while providing the same or even better brightness.  

For example, a 60-watt incandescent bulb can be replaced with a 10-watt LED that delivers the same amount of light. That means for every hour your light is on, you’re using just a fraction of the power.  

Multiply that by the number of lights in your home or office, and by the hours they’re used each day, and the savings quickly add up. 

For an average Australian household, this could mean saving $200 to $500 per year on electricity costs simply by upgrading their lights. 

Fewer Replacements

LEDs have an incredibly long lifespan compared to traditional bulbs. While a typical halogen bulb lasts around 1,000 to 2,000 hours, an LED bulb can last up to 25,000 hours or more. That’s up to 15 years of use, depending on your usage habits. 

This longevity means you’ll spend far less on replacement bulbs over time. Whether you’re maintaining a home, a rental property, or a business space, fewer replacements mean less hassle and fewer trips to the hardware store.  

Reduced Maintenance Costs

Changing a light bulb might seem like a minor chore, but in businesses or large households with dozens of lights, the task adds up quickly.  

For commercial buildings, hotels, warehouses, or schools, maintaining traditional lighting systems can become costly and time-consuming.  

You need to factor in labour costs, equipment (such as ladders or lifts), and safety considerations every time a bulb needs to be replaced. 

Because LEDs last significantly longer, you dramatically reduce these maintenance demands. You can go years without needing to touch your lights, freeing up time and resources for other essential tasks.  

Real-World Impact: A Simple Change, Big Savings

Here’s a quick scenario: Let’s say you replace 20 halogen bulbs in your home with LED bulbs. Each halogen bulb uses around 50 watts, and each LED replacement uses just 8 watts.  

If you use those lights for about 4 hours a day, you’ll save over 1,200 kilowatt-hours (kWh) of energy each year, which could translate to $300 or more off your energy bill annually, depending on your electricity rates. 

So, how can LEDs save you money? In every way that matters: 

  • Lower bills 
  • Fewer replacements 
  • Minimal maintenance 
  • Long-term savings year after year 

It’s a smart investment that pays for itself quickly, especially when combined with government rebate programs that let you upgrade at little to no cost.  

How Can You Save By Upgrading to LEDs?

When you think about upgrading to LED lighting, it’s easy to wonder if the savings are really that significant. The answer is a resounding yes — and the numbers speak for themselves.  

Upgrading to LEDs is one of the most cost-effective improvements you can make, whether for your home or business. Let’s take a closer look at how much you can actually save:   

Savings at Home

If you replace around 20 halogen bulbs with LED alternatives, you could save between $300 and $500 annually on your electricity bill.  

Here’s why: 

  • Halogen bulbs are energy-hungry. They typically use 35 to 50 watts per bulb. 
  • An LED equivalent typically uses only 6 to 10 watts for the same level of brightness. 
  • That’s around an 80% reduction in energy consumption for lighting alone. 

If you consider all the lights you use in your home — in living rooms, kitchens, bedrooms, bathrooms, and hallways — switching to LEDs can significantly reduce your energy use every single day.  

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The savings potential for businesses is even greater. Lighting is often one of the most significant energy expenses for commercial properties, especially for retail stores, warehouses, offices, and hospitality venues that require lights to be on for extended hours. 

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Australian Energy Saving Upgrades for Businesses and Homes

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Reducing My CO2 Emissions Through LED Lighting

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Switching to LEDs with zero out-of-pocket cost is a no-brainer. Government incentives, such as the Free LED Lights Replacement NSW program, make it easier and more affordable than ever to make the change. 

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Ready to start saving? Contact Cyanergy and get a free quote for your LED lighting upgrade! 

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Renewable Energy

Offshore Vessel Collision, 1.2 GW Farm in South Australia

Published

2 days ago

on

April 29, 2025

By

Weather Guard Lightning Tech

Offshore Vessel Collision, 1.2 GW Farm in South Australia

In this episode, we discuss an offshore vessel collision in the North Sea, highlight Louisiana’s offshore wind ambitions, the latest developments in South Australia’s renewable energy expansion. Plus we highlight an article from Buoyant Works in PES Wind Magazine. Register for the upcoming SkySpecs’ webinar on turbine repair challenges!

Sign up now for Uptime Tech News, our weekly email update on all things wind technology. This episode is sponsored by Weather Guard Lightning Tech. Learn more about Weather Guard’s StrikeTape Wind Turbine LPS retrofit. Follow the show on Facebook, YouTube, Twitter, Linkedin and visit Weather Guard on the web. And subscribe to Rosemary Barnes’ YouTube channel here. Have a question we can answer on the show? Email us!

Allen Hall: On Wednesday, April 30th at 11:00 AM Eastern, get that on your calendar. SkySpecs, Uptime and PES Wind are hosting our next session of a 10 part series of wind related items on their webinar. So this time it’s gonna be about the the biggest challenges facing turbine repair teams today. And we’re gonna have four experts besides Joel and me.

I guess we don’t count as experts, Joel. So we’re gonna be talking to real experts. Sheryl Weinstein from Sky Specs, Alice Lyon from Lyon Technical Access. Craig Guthrie, who I’ve known forever from Takkion, and Jose Mejia Rodriguez from RNWBL. We’ll be there to, uh, explain how you should be planning for this repair season.

What are some of the approaches that the operators use and what works and what doesn’t work? Things that if you’re in the repair business or if you work. For a large, uh, operator or even a small operator you want to hear and participate in, there’ll be a q and a session. So get all your questions ready, but [00:01:00] you first have to register and you can register in the link and the show notes below.

Do not miss this event. April 30th, 11:00 AM Eastern. You won’t wanna miss it.

Speaker 2: You’re listening to the Uptime Wind Energy Podcast, brought to you by build turbines.com. Learn, train, and be a part of the Clean Energy Revolution. Visit build turbines.com today. Now here’s your hosts, Alan Hall, Joel Saxon, Phil Totaro, and Rosemary Barnes.

Allen Hall: Up in the Netherlands, three crew members were injured when an offshore support vessel struck a windman foundation. In the North Sea and the Royal Dutch Sea Rescue Society had to evacuate two of the injured crew members from the privately owned vessel. And a third uh, crew member went to get medical attention once they got back to port.

Now, this occurred about 15 miles from the Netherlands shores, and the Dutch have opened an [00:02:00] investigation, and my first responses to reading this news was. How are we driving ships into foundations still? And Joel, can you explain all the technology that is there to prevent you from doing this?

Joel Saxum: Well, every one of these vessels that operates in that environment is going to have a, a helm display, right?

That’s gonna have all of the things called stent and aids to navigation. So it’s gonna have all the buoys, everything in the water that you could possibly run into. Some of ’em even have detailed stuff like pipeline data and stuff so you don’t drop your anchors in certain places. But either way, they’re gonna ha they’re gonna have knowledge of this besides the fact that you can look out the window and see the tur, see a turbine that’s 500 feet tall in front of you.

That’s a different story maybe. Um, but a lot of these vessels too, of this size. So this is a, um, a support vessel offshore. So there’s all kinds of different classes of boats, things they do. But this thing may work in a wind farm. It may work for oil, uh, platforms, it may work for the fishing industries.

Like it can do a lot of different stuff. But as a, as a [00:03:00] emergency response. Uh, vehicle. They also should be DP one. And when I say DP one, that’s dynamic positioning. So that means that you should be able to have a button in the, in the vessel that says, boom, hold me here. And, uh, DP one means you just have one methodology of, of positioning.

So that’s like GPS. I’m at this GPS point. Hold me at this GPS point. Um, so there’s a lot of safety mechanisms built into these things, and there’s a chain of command and all these vessels. I think it said it was crude by eight people. Correct? Correct me if I’m wrong, Alan. That sounds about right. For a hundred, 150, 150 foot operating vessel, eight people’s.

About right now, everybody has their own job, right? There’s a captain, but there’s usually this, you know, a second mate and there’s other people on the vessel that someone at all times is looking forward or is supposed to be at least. Uh, but like Phil said earlier today, when we were kind of doing some podcast planning, if you saw the pictures of this thing in port, it looked like it ran square on into the turbine headfirst.

I

Allen Hall: think it was the, uh, [00:04:00] mechanical error or where an operator error just from the damaged photos. I think it’s

Joel Saxum: operator error. I think that’s someone not chain of command, not paying attention

Phil Totaro: somehow. Well, it’s just one of those, the, you know, unfortunate and frankly frustrating things that, and this is, I believe in the last five or six years, the.

Sixth vessel that’s run into something like a foundation under construction or an operating wind turbine or something out there. Um, I mean it’s happened in Germany and, and now. Here in, in Holland with the, with the Holland Coast, uh, three and four project is my understanding Vattenfall project out there, um, with the Siemens 11 megawatt turbines.

So it’s unfortunate that this keeps going down, but I don’t know what I mean. To Joel’s point, I don’t know what more. You could do with technology to warn you that something’s out there. ’cause in addition to everything that Joel mentioned, we [00:05:00] also know where the wind turbines are located. There’s, there’s geo coordinates for all the turbines in the wind farms and there’s theoretically some kind of geofencing around the wind farm that tells you, Hey, by the way, you’re entering this zone.

Which I mean, as an SOV, presumably you’re supposed to be kind of nearby, but. I just don’t like, I don’t know. I mean, this isn’t a technological problem to, to me this is, this keeps sounding like human error. What’s the next step?

Joel Saxum: Phil is the next step. We put like a, we put radar on the transition piece with like an audible alarm.

Like when something gets within 500 meters, it just goes. I don’t know what else you can do. I mean, they can’t see

Phil Totaro: him apparently, so they gotta hear him. Maybe. I don’t know. Well, to be clear too, I don’t think this was like, uh, you know, a situation where they had fog and or some other kind of obstructed vision.

It was a, to my understanding, it was a reasonably clear day. So I just don’t understand how that’s gotta be some level of human failure, how you [00:06:00] just smash into a thing that’s that big, uh, you know, right in front of you. It’s

Joel Saxum: like fog being one thing or like pours visibility. But I’m looking at the picture of this vessel and this vessel has.

A radar on it. It has its own radar, so it’s gonna pick it up on the screen next. So no matter what, you should have either been able to look out the window or look at the screen and see the thing in front of you, or look at the GPS coordinates of the, the, you know, problems

Phil Totaro: out there. So, I, I don’t know to, to answer Joel’s question, I don’t think we need more technology, uh, because even though you could, you know, avail yourself of, of radar on every vessel, I mean.

Those that gets expensive and somebody’s gotta pay for it. And guess who ends up paying for it? Is, you know, the vessel operator ups their contract. The, you know, project developer has to increase the overall cost of the project and then it takes them longer to, to. Get paid back with the the PPA and or CFDs or whatever other mechanism they have, [00:07:00] and we as electricity rate payers are the ones that end up paying for that at the end of the day.

So I don’t, you know, if this is something that can be solved without. Additional technology upgrades. I’m kind of all for that, but something needs to be done as far as like, Hey, there’s a big thing like, you know, a few hundred yards right in front of you. Try not to hit it. You know,

Allen Hall: speaking of not running into wind turbine foundations, there’s actually an article in PES win, and if you haven’t downloaded the latest addition of PES Wind, you can do that on your own@pswin.com.

You just type it into the old Google and. Push the button and there it is. Now, there’s a lot of great articles in this quarter’s edition and a good bit of offshore in it. The article I wanna highlight today is from Buoyant Works, and if you’ve been to the Buoyant Works website, you can see all this sort of the polyurethane bumpers that they have created for not only the.

The towers, but also the CTVs, which is really important because they [00:08:00] do run into one another once in a while and it has become more of an issue is that, uh, there’s damage on some of these vessels. And just trying to minimize the, the complexity of trying to get close to a turbine without damaging it is, is a huge problem.

And if you have read the article here, and I encourage you to do that on your own. There’s a lot going on, uh, as these CTVs approach these turbines and just trying to avoid damage and trying to keep from having bump incidences where the, the crew gets rocked is important here. And Joel, as you have pointed out many times, safety is of the utmost here, uh, on these crew transfer vehicles.

Joel Saxum: Yeah. If you haven’t been offshore, there’s something to understand, uh, in operations that maybe most people don’t. So if you’re seeing, like if you’re at a boat ramp at, at the, your local lake or river and you see a boat go back off a trailer, they usually kinda like throttle down and sit there and they’re waiting for people or whatever.

When you’re [00:09:00] in a marine environment, when you’re dealing with big vessels and you’re doing any kind of operations, whether it’s pile driving, rock lay, or whatever it may be. That vessel is almost always throttled up. You’re a, you’re at a certain amount of throttle all the time because that’s how you’re able to hold position.

So it’s the same thing when A CTV approaches a, a, a transition piece or a wind turbine, they nudge up against where the ladder is and there’s mechanisms designed there, engineering mechanisms, and that’s what. Uh, they do here at Buoyant. Uh, there’s their Buoyant works all of their different systems to make sure they slip, but they put that boat right against the transition piece and they throttle it up to hold it there.

So it’s nice and steady. But when you’re in the North Sea or somewhere offshore and you got two three meter heaves going on, you’ve gotta be able to. Efficiently slide up and down that transition piece while you’re throttled up. And that’s what their, uh, their systems allow people to do safely. ’cause if you’re not doing that safely, the boat starts to pinch and move and squeak and it get, get hung up or held.

You can’t have that, otherwise you can’t transfer. Um, [00:10:00] so these, uh, what, what you looking at here is, oh, this is cool offenders. No, they actually are the things that allow us to safely transfer people offshore.

Allen Hall: So check out the website, buoyant works.com. And take a look at their polyurethane products and accept no invitations.

Buoyant works.com.

Speaker 5: As busy wind energy professionals staying informed is crucial, and let’s face it difficult. That’s why the Uptime podcast recommends PES WIN Magazine. PES Wind offers a diverse range of in-depth articles and expert insights that dive into the most pressing issues facing our energy future.

Whether you’re an industry veteran or new to wind, PES Wind has the high quality content you need. Don’t miss out. Visit ps wind.com today.

Allen Hall: As part of our oil and gas, uh, oversight because I am really tired of reading about, oh, a wind turbine had a problem. Yeah. So does oil and gas, and you may not have read in your local newspaper about the spill they had in the [00:11:00] Keystone, Keystone Oil pipeline up in North Dakota, but it dumped about 140,000 gallons of crude oil on the ground.

They had a mechanical problem where one of the employees heard a. Boom, and then realize maybe we’re leaking a little bit of oil. Uh, this goes back to, uh, a couple of other incidences that have happened with pipelines, particularly this pipeline and that pipeline. Joel runs from, uh, essentially Alberta. Uh, kind of down across to Manitoba, I think it is, right up, which is right above North Dakota.

Then takes a right and goes, goes straight down through North Dakota, South Dakota into Nebraska, then heads over towards, uh, Illinois. So, you know, yikes. Transporting oil is not easy, not as easy as it’s claimed in the media at the moment.

Joel Saxum: Yeah, this time of the year is, uh, difficult for the northern latitudes as well.

So that area of North Dakota, a lot of organic [00:12:00] soil. This is a weird geo geotechnic conversation, but the reason that you have pipeline breaks this time of year is because the frost is coming outta the ground. So when, when those pipelines, when they get pressurized and they move things, they get a lot of, they get heat built up in ’em.

So you have a warm pipeline and then you have it running through soil that is half frozen, half not, and the ice is coming out so that soil starts to move and, and bend. So when they say, Hey, I had an employee that heard something, pop break, that’s because the soil itself is actually moving. Um, and you’ll know that if you’ve ever been up there driving on highways in the springtime, uh, we call it, we call it breakup season when everything starts moving.

But that’s what happened. Right? And it, and it is a, it’s a, it’s a really, I mean, it’s a black eye for, for the oil industry. Uh, but it happens more often than you think. Uh, pipeline breaks, whether it’s, whether it’s crude or whether it’s natural gas or, or whatever’s being pumped. Um, these are, these are rigid pipelines that are run across ground that moves.

So I think the, you know, your, your, your alternatives to [00:13:00] moving crude like that are either on a train or on a truck. And pipelines are safer than those. So this is the, the least of the, uh, the evils.

Allen Hall: Yeah. It’s still a problem. I, I, I am just really tired of hearing oil and gas representatives talk about how wonderful it is.

Like they don’t have any problems. They have problems and there’s a lot of problems, but we’ve, it’s become normalized. It’s, it’s back to Rosemary’s point from several months ago now, like when you have disasters all the time, it becomes normal. It’s okay. No one reports on it. It’s not, it’s not news anymore.

Joel Saxum: At a certain level, there’s like the nimbyism thing, right, where people get really bent outta shape about renewables because they can see it. You can see turbines everywhere, right? When they’re, when they’re up on the horizon, you can see ’em miles away. You don’t see pipelines. But I, I bet you, I don’t care which one of us I’m talking to, even here on the panel or whoever’s listening, within a mile of your house, there’s a pipeline somewhere.

Uh, yes. You just don’t see ’em. You don’t know. You don’t see ’em. So you don’t, it’s not, it’s not an issue until it’s an issue. Wind [00:14:00] turbines, solar panels, battery storage, all these different things. They’re very visible, so it’s easy to see. I encourage anybody who thinks that, that it wind is an eyesore to drive up to Midland, Texas.

And take a vacation out there and then, and then give me a call afterwards and tell me what you saw.

Allen Hall: And let’s go to a country where things are going in the right direction. In South Australia’s renewable energy sector, they are expanding, uh, with plans to what become the state’s largest wind farm and Tilt renewables has proposed.

The, and Rosemary, you’re gonna have to correct me on, on. The Australian pronunciation of this Nwi wind farm, which at the 1.2 gigawatts in 148 turbines, and included with this wind farm are two batteries. Storage systems that can offer up to 300 megawatts of capacity for eight hours of storage duration.

That is massive, Rosemary.

Rosemary Barnes: Yeah, it’s huge. And I think it also comes, um, like, uh, I believe that the intention is construction would begin in [00:15:00] 2029. Um, and so yeah, it would come online after 2030 when the state, I think already plans to be a hundred percent renewable, um, in its electricity, uh, generations. So that’s a really interesting point, like what are, yeah, what are tilts plans for this, uh, huge amount of clean energy once the state’s already at a hundred percent, um, clean.

So, uh, a clue might be in the location. It’s right next to Whyalla, which, um, Australians can’t help but be aware of because for some reason this small town is raised at every single election. There is some sort of publicity stunt involving Whyalla. Um, it’s a big steelworks community and yeah, it’s been used as a example, uh, from, from both sides of um.

The climate change debate about, yeah. Originally it was cited as an example of, this town will be wiped out if we, you know, choose to act on climate change. Um, yeah. ’cause they’re manufacturing steel and currently steel produces a lot of emissions. But then on the [00:16:00] flip side, I. Well, you know, there’s the potential for this to become green steel, given that there is such a huge renewable energy, um, potential in that region.

So that’s my, that’s my guess. Probably a pretty safe guess that there’s some, some sort of plans for industrial uses for this huge amount of green energy that would come online.

Joel Saxum: I think an interesting thing here too, in the article they’re mentioning 90 meter blades and, and I don’t know if they have a turbine model planned or they’re just expecting that’s what it’ll be, but because the port, the port of Al’s right there, they only have to transport those big old blades.

50 kilometers out to the site. Like that’s, that’s amazing. That’s great.

Rosemary Barnes: Yeah. I think they also cited that might come from port, port of Adelaide might be used for transport as well, so it’s a little, little bit further, but still not, not that far in, it’s not like a really lush, vegetated region with a whole lot of huge dense forest right up to the road.

It’s um, you know, it’s a fairly, um, arid, uh, [00:17:00] climate in that region, so I don’t think that transport is gonna be a huge, huge issue for them. Um, yeah, but I do think that also that’s, that’s all I hear for, um, for new big wind farms in Australia, all I hear is huge wind turbines like much bigger than what you typically see for, for onshore.

Like, I don’t, like six megawatts is kind of like. The smallest for things that are coming on very soon. And then after that, people are talking like 10, 12 megawatts. Like I, obviously these turbines barely exist now beyond, you know, like computer models and, um, maybe some prototypes, but obviously. They’re making really big offshore wind turbines.

It’s a lot easier to probably go in the direction from offshore to onshore than the other way around. So it’s not like anyone doubts that it’s possible to make wind turbines like that. Um, onshore wind turbines that big, but. The, um, logistics of installed them seems hard.

Joel Saxum: You know, Alan, correct me if I’m wrong, [00:18:00] but, but, uh, one of our friends down in Australia told us that GE was gonna be installing only one model, the 6 1 1 58, 6 0.1 megawatt machine from here going forward.

And I think, Rosemary, to your point, he also told us that this is the, one of the first turbines that they’ve extensively tested. For a longer duration. So this was the first one that’s been like the, the, you know, serial, serial number, number one has been installed and will have been running for a year before they even install serial number number two in the field.

So that’s a, so tackling both things here, bigger turbine. Yes. Uh, and that’s the only one they’re gonna go with. So they can focus on, it is a workhorse machine and they can make sure they’re maintaining it correctly, but they’ve also got some, uh, they’re gonna have more operational history on it before they actually go and start.

Building tons of’em. ’cause we know we’ve heard of those wind farms where they, the turbines don’t even have a tech certificate yet and they’re sending a two, 300 of ’em out there.

Rosemary Barnes: Yeah, well, I mean it’s really [00:19:00] normal that you know, like your, um, and you know, obviously I know, I know blades primarily, but you know, your serial number one is your test blade.

Maybe there’s a two as well. That’s also a test played sometimes. Not usually. Um, and then, yeah, like, so serial one is a test blade. Serial number two is in the field, and so is 3, 4, 5, 6, you, you know what I mean? Like you start the test. You’ve probably passed like some, some of your tests, maybe the, um, static test is completed already, but then the fatigue test is only partway done by the time that you’re installing, um, blades in the field usually.

So, I mean, it’s, it’s because people have become very good, um, the design codes, the, you know, the materials factors that they. They know it all really well. It’s really proven out over decades of experience, and so they felt very safe and it was incredibly rare that you would see a problem until recently.

Now it’s not such a big problem. So I think that’s a, a fantastic, um, step to make, to be a bit more certain. But I mean, [00:20:00] even that is not I adding. All that much safety, if you think about it, one turbine in one location in the world. I thought what you were gonna say is that GE are only doing one turbine type in Australia and that they have taken the effort to understand that Australia’s specific conditions and, uh, you know, know that the.

Leading edge protection is UV resistant and so will last more than one year. That Yeah. The, you know, lightning protection system performs well under the types of storms that we see in, uh, the places in Australia where they install a lot of, um, big wind farms. Um, that, yeah, like there’s some, uh, higher temperature resistance because you know, a lot of, um.

A lot of wind farms are in deserts where the temperatures are frequently above 40 degrees during the day. And everyone knows, everyone that’s been in a wind turbine knows that inside the wind turbine, inside the blade is at least 10 degrees hotter than that, right? Pushing up, butting up or past, um, material safety limits.

So, um, that is what I would, I [00:21:00] would really like to see.

Allen Hall: Don’t let blade damage catch you off guard the logics. Ping sensors detect issues before they become expensive, time consuming problems. From ice buildup and lightning strikes to pitch misalignment in internal blade cracks. OGs Ping has you covered The cutting edge sensors are easy to install, giving you the power to stop damage before it’s too late.

Visit OGs ping.com and take control of your turbine’s health today. Yeah, the classic cultures, a delegation from Louisiana traveled to Denmark to learn about, uh, wind energy from the experts in Denmark, which is a smart thing to do, and I wish more states would do this actually. Uh, the tour, which is organized by the center for.

Planning excellence included state and local officials from Louisiana, academic researchers, industry experts, and of course port authorities, which are so critical to the success of offshore wind farms. And they went over to, uh, learn all they could from [00:22:00] everybody in Denmark. Now, the, the ports in Denmark are really unique in the sense that they have been redeveloped over time and they are.

Are extremely powerful in supporting denmark’s wind energy, uh, organizations. And they support a lot of ’em, uh, right from the ports in Denmark. Now, one of the things I thought was a little interesting is that Louisiana, which really doesn’t have any offshore wind, is actively pursuing it. And even though the, the, the, the federal government in the United States is not looking to announce any more win sites, Louisiana, I think it’s going to push for some.

Because it does provide a number of jobs, and Louisiana is really set up and our friends at Gulf Wind Technology have created a low wind speed wind turbine blade that will make it possible to have offshore wind near Louisiana. Joel, does this make sense to you? Does it seem like Louisiana has taken a very forward first step?

Joel Saxum: I think there’s a couple of ab, absolutely, completely agree. Alan, I’ll just [00:23:00] start with that, but there’s a couple of things here Louisiana Wise that people may not know. First one. When they started developing offshore oil and gas in the North Sea and Norway and all this stuff, and back in the seventies, they called people from Louisiana to come and teach ’em how to do it.

’cause the, ’cause the, the Cajun Navy had been doing it in, in the Gulf for a couple years already. So they knew how to do it. They took their expertise and they went and gave it to. The North Sea, right? So now the tides have turned, the louisianans are heading back up to there, to, to the North Sea to get some knowledge to bring it back.

And uh, so that’s one little kind of equipped story. But the other one that’s interesting here too, and Phil, you and I have talked about this. I know Alan, we’ve talked about this as well. Louisiana’s the only state that has tried to do offshore wind within their state boundary waters. And they’ve put in.

They put in legislation to share in the profitability of these wind farms, which is a great move in, in, [00:24:00] in my opinion, the same thing that like Alaska has done and Texas has done with their oil reserves. If the, is the reserves there, someone’s gonna make money on it, the whole state should benefit. So they’ve done that.

Um. They’ve got the infrastructure, like you said, Gulf Wind Technology. They got a key side facility. There’s all kinds of ship manufacturers. The ship, the Eco Edison, that’s up in or on Ted’s sites up in New York that came, that was built in Louisiana. So like the, I think that was, was Thatwe who built that one?

Maybe Phil, you know that, was that Edison SCH West? Yes. Yes. So I think they’re based in Houma, which is, you know, right there. So. They have the key side facilities. They have the vessels. They know how to operate offshore. They’ve already put legislation in place. I think that the, the government of Louisiana is, is charging forward.

I did read something the other day too that said, um, quietly there has been some onshore development in Louisiana. They’re like fi five different wind farms that have been then property rights and those kind of negotiations are going on in the background that. The general, you [00:25:00] know, the general wind industry.

You wouldn’t think of Louisiana as a place for wind, but it’s happening.

Allen Hall: Well, let’s talk about, the one item I wanted to talk about, about this is the food culture and the clash between the two food cultures. So having been to Denmark and Rosemary took, uh, Valerie, my wife and me to a, uh, really nice, uh, restaurant with where they have SMI board gr, which is this open face sandwich on rye bread.

That is about the consistency of a two by four Delicious, but it is very thick and dense. So, uh, you have to, you have to, it isn’t the same what you’re gonna pick up and eat. You’re gonna have to cut it with a knife and a fork. It’s really thick. Delicious, though. Quite delicious. And Louisiana is known for the Cajun cooking, right?

Everything New Orleans is fantastic. I did a quick look to see how many Michelin stars are in the state of Louisiana and Louisiana’s about. Three times the size of Denmark. There are no Michelin restaurants in the state of Louisiana, which is hard to believe. ’cause if you’ve been to New Orleans, [00:26:00] they have a lot of great restaurants.

Rosemary Barnes: It has a reputation for good food too. It’s not like the rest of the world is, is knows that there’s good food there

Allen Hall: everywhere and where you stop. But Denmark has over 30 Michelin star restaurants.

Joel Saxum: Copenhagen has the most. The most of any city in the world. Copenhagen is the, the head.

Rosemary Barnes: Yeah, Denmark’s really good for, um, like it’s expensive to eat out, even like bad food is really expensive.

If you wanted to, I dunno, I never ate McDonald’s in Denmark, but, you know, something like that or around that level, like pizza, very expensive, not very good, but one step above that is not. Very much more expensive, but is like amazing quality. So if you go to like the local inns, they’re called Crow. Um, they, uh, usually like bordering with fine dining.

They’re just, the food is amazing. Like it’s a little bit more relaxed atmosphere, but just absolutely fantastic food. And in fact, one time we went to a place that was because we were living in Colding. It’s a town of like 60,000 people, like in. Fairly [00:27:00] rural jet land. We went to a place in a, a nearby, even smaller town, um, and went to this restaurant.

Fantastic. Like I’ve never had such good bread and butter was like the thing that stands out. Most of that meal for me was how good the. The bread and yeah, the bread and butter is, um, and then like a month later, it got a Michelin star, but it wasn’t, it wasn’t like it was known as a good restaurant, but it wasn’t like no one is being fine dining or anything.

But that’s like, that’s what I’m saying is that there’s a lot, like the bulk of the nice ish restaurants in Denmark are right on that cusp of being fine dining. Um, so it’s, yeah, it’s a little, it, it, it’s, it’s quite cool once you get the hang of it. And once you realize that. The lower tier, just no point doing that.

You know, you either stay at home and eat, or you spend a tiny bit more and get amazing food, but don’t do that like, you know, don’t go out for pizza. It’s, um, it’s hard to find, find something good like that.

Joel Saxum: I think, Rosemary, you nailed it. When we were talking earlier about premium ingredients, and that’s one of the big [00:28:00] differences between Denmark Food and Copenhagen Restaurants and Louisiana, because in Louisiana you may eat something and it tastes delicious, but you’ll have no idea what is in that food.

You, you, you’re gonna know that the base is probably a ro or they use the holy trinity at some point in this dish. Bell pepper, onion, celery, that’s the holy trinity in Louisiana. And most all dishes are gonna have some form of that in it. So you might be eating like a soup or like, sometimes it looks like a paste.

I don’t know, but like a good tufe. Is it lump crab? Is it crawfish? Is it what’s in here? I don’t know. Here you go. But it’s delicious. It’s gonna be good.

Allen Hall: Roseberry, you have a very important announcement.

Rosemary Barnes: Yeah. Uh, coming up we have uh, Australian Wind Industry Forum, which is on Tuesday, May 6th. And I’m very excited ’cause I’m speaking this year.

I have, um, I have tried to speak at this conference for a few years and it’s gonna be in a session. There’s a session on turbine design. [00:29:00] Um. Related issues, uh, turbine design and technology. And so I’m gonna be giving a presentation. It’s called. Innovation in wind energy lessons from the front lines. So I’m gonna be talking about how the design certification process works for wind turbines and then also what happens when something goes wrong.

You know, when you, uh, are in the field and you have, uh, I don’t know, serial defects or you suspect serial defects, you’ve got a lot of blades breaking. You’ve got a lot of. Lightning damage. You’ve got, I dunno, problems with, uh, excessive downtime for whatever reason. Um, yeah, gonna talk about that. And then also, like I mentioned earlier in the show, Australians really love to be the first ones to get a new type of turbine.

Um, how could you make sure that you can be a leader without being a Guinea pig? So gonna talk about some of the things you can do because actually, um, you, a customer, an an early customer, if they’re a large customer, does have the opportunity to be part of that design process. And in particular. You can request [00:30:00] certain tests are, are, are done.

Um, I’m not saying that it’s guaranteed that the OEM will perform them for you, but you certainly, you and your bank and your insurance all have the ability to, you know, be part of that, um, design process if you are an, an early adopter with a large order. So we’re gonna be talking about yeah. How to, how to manage all of those issues in the Australian context.

So come along

Allen Hall: and where can I go to register for this event,

Rosemary Barnes: you can go to wind industry forum.com au.

Allen Hall: That’s gonna do it for this week’s Uptime Wind Energy podcast. Give thanks for listening. Please give us a five star rating and tell your friends. Tell your neighbors. Tell your neighbors friends to start listening to the show.

We’ve had a lot more people join us lately. And we want that trend to continue. So thank you for listening, and we’ll see you here next week on the Uptime Wind Energy [00:31:00] Podcast.

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