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AI to control solar panels, and enable power sharing? How US Energy Sector startups are leading the AI race

As the global energy landscape evolves to meet the necessities of climate change and burgeoning demand, Artificial Intelligence (AI) and Machine Learning (ML) are rapidly emerging as linchpins for sustainable energy solutions. The nexus between these advanced technologies and energy sustainability is not merely theoretical but manifests in real-world applications, driving tangible benefits. The global AI market in the energy sector is predicted to reach a staggering $19.2 billion by 2028, and the potential of AI to unlock $1.6 trillion in savings by 2030, underpins the seismic shift underway. This transition is not just an indicator of optimized energy management and reduced greenhouse gas emissions but also a fertile ground for startups to innovate and contribute to a more sustainable, efficient, and resilient energy ecosystem.

The Energy Sector in the USA is Booming At a Rapid Pace

The energy sector stands at the cusp of a transformative phase, with AI and ML being the vanguards of this transformation. 

The global AI market in the energy sector is set to ascend at a CAGR of 25.1%, reaching a valuation of $19.2 billion by 2028, a testament to the growing affinity towards AI-driven solutions. The prowess of AI extends to a potential saving of $1.6 trillion for the global energy sector by 2030, embodying the financial prudence of embracing AI.

In terms of efficiency and sustainability:

What AI Can Do for the Energy Sector in the USA?

A few years back, no one knew how AI could be used in the US energy sector. Now, however, we have pretty splendid examples of companies using AI to enhance the customer experience and sustainability further. Let’s go through a few examples.

Customer Experience

AI is still in its infancy and there’s a lot to come. However, thanks to tech partners like Mantra Labs, energy companies in the US are able to leverage modern technology to enhance their customer experience exponentially. GreenBrilliance (a leading solar panel installer in the US) is one such example. The solution developed by GreenBrilliance helps customers know how many solar panels will be required to power a house, how much power does a solar panel produce, and more. Further, it would help them monitor, control, and troubleshoot their solar panels on their smartphones.

Customer experience is one such thing that has started getting attention in the last few years. B2C companies, irrespective of their industry, not only build products or render services but try to provide the best customer experience possible. Reports predict that Solar could fulfill 40-50% of U.S. electricity demand by 2050. Also, the cost of installing and servicing solar panels has also been reduced by 60% over the last decade. This has been possible only through implementing automation, simplifying operations, and bringing transparency to the customer, along with many other things. 

Efficiency and Sustainability

Efficiency and sustainability are the USPs of solar power and AI is helping to boost that further. 

For example, accurate demand forecasting is pivotal for energy efficiency and cost-effectiveness. Startups like GridX are leveraging AI to predict energy demand and optimize power flows, thereby reducing energy costs and enhancing system efficiency.

Companies like Power Ledger are using AI systems to modernize and decentralize grid systems, enabling efficient trade of solar power among neighbors. This fosters a balanced supply and demand, optimized power flows, and improved grid reliability. Moreover, AI-driven innovative energy storage solutions are instrumental in integrating renewable energy into the grid and enhancing energy security.

These diverse applications underscore the boundless potential of AI and ML to revolutionize the energy sector, making it more sustainable, efficient, and resilient.

What Future AI Promises to the US’s Energy Sector?

As AI technology continues to evolve, the horizon of possibilities in the energy sector broadens. Large corporations like Google, Amazon, and Microsoft, alongside agile startups, are exploring the AI energy landscape continuously, indicating a robust and growing ecosystem.

And it’s not only the private sector that is putting effort into harnessing the power of AI. The US Department of Energy (DOE), the National Renewable Energy Laboratory (NREL), and other governmental bodies are also leveraging AI to pioneer new generations of nuclear reactors, develop new solar and wind technologies, and create smart grid systems.

Integration of AI and ML with the energy sector is a narrative of innovation, sustainability, and vast potential. The journey of companies like Green Brilliance Predictum, Heliogen, GridX, Amperio, and Power Ledger illustrates the transformative power of AI and ML in forging a sustainable energy future. As the global AI market in the energy sector burges, the call for startups to innovate and contribute to this burgeoning ecosystem is loud and clear. The narrative of AI and ML in the energy sector is still being written, and startups have a golden opportunity to be the authors of many success stories in this narrative.

Further Readings: Bringing Solar Renewable Energy Closer to Consumers in the USA

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Platform Engineering: Accelerating Development and Deployment

The software development landscape is evolving rapidly, demanding unprecedented levels of speed, quality, and efficiency. To keep pace, organizations are turning to platform engineering. This innovative approach empowers development teams by providing a self-service platform that automates and streamlines infrastructure provisioning, deployment pipelines, and security. By bridging the gap between development and operations, platform engineering fosters standardization, and collaboration, accelerates time-to-market, and ensures the delivery of secure and high-quality software products. Let’s dive into how platform engineering can revolutionize your software delivery lifecycle.

The Rise of Platform Engineering

The rise of DevOps marked a significant shift in software development, bringing together development and operations teams for faster and more reliable deployments. As the complexity of applications and infrastructure grew, DevOps teams often found themselves overwhelmed with managing both code and infrastructure.

Platform engineering offers a solution by creating a dedicated team focused on building and maintaining a self-service platform for application development. By standardizing tools and processes, it reduces cognitive overload, improves efficiency, and accelerates time-to-market.  

Platform engineers are the architects of the developer experience. They curate a set of tools and best practices, such as Kubernetes, Jenkins, Terraform, and cloud platforms, to create a self-service environment. This empowers developers to innovate while ensuring adherence to security and compliance standards.

Role of DevOps and Cloud Engineers

Platform engineering reshapes the traditional development landscape. While platform teams focus on building and managing self-service infrastructure, application teams handle the development of software. To bridge this gap and optimize workflows, DevOps engineers become essential on both sides.

Platform and cloud engineering are distinct but complementary disciplines. Cloud engineers are the architects of cloud infrastructure, managing services, migrations, and cost optimization. On the other hand, platform engineers build upon this foundation, crafting internal developer platforms that abstract away cloud complexity.

Key Features of Platform Engineering:

Let’s dissect the core features that make platform engineering a game-changer for software development:

Abstraction and User-Friendly Platforms: 

An internal developer platform (IDP) is a one-stop shop for developers. This platform provides a user-friendly interface that abstracts away the complexities of the underlying infrastructure. Developers can focus on their core strength – building great applications – instead of wrestling with arcane tools. 

But it gets better. Platform engineering empowers teams through self-service capabilities.This not only reduces dependency on other teams but also accelerates workflows and boosts overall developer productivity.

Collaboration and Standardization

Close collaboration with application teams helps identify bottlenecks and smooth integration and fosters a trust-based environment where communication flows freely.

Standardization takes center stage here. Equipping teams with a consistent set of tools for automation, deployment, and secret management ensures consistency and security. 

Identifying the Current State

Before building a platform, it’s crucial to understand the existing technology landscape used by product teams. This involves performing a thorough audit of the tools currently in use, analyzing how teams leverage them, and identifying gaps where new solutions are needed. This ensures the platform we build addresses real-world needs effectively.

Security

Platform engineering prioritizes security by implementing mechanisms for managing secrets such as encrypted storage solutions. The platform adheres to industry best practices, including regular security audits, continuous vulnerability monitoring, and enforcing strict access controls. This relentless vigilance ensures all tools and processes are secure and compliant.

The Platform Engineer’s Toolkit For Building Better Software Delivery Pipelines

Platform engineering is all about streamlining and automating critical processes to empower your development teams. But how exactly does it achieve this? Let’s explore the essential tools that platform engineers rely on:

Building Automation Powerhouses:

Infrastructure as Code (IaC):

CI/CD Pipelines:

Tools like Jenkins and GitLab CI/CD are essential for automating testing and deployment processes, ensuring applications are built, tested, and delivered with speed and reliability.

Maintaining Observability:

Monitoring and Alerting:

Prometheus and Grafana is a powerful duo that provides comprehensive monitoring capabilities. Prometheus scrapes applications for valuable metrics, while Grafana transforms this data into easy-to-understand visualizations for troubleshooting and performance analysis.

All-in-one Monitoring Solutions:

Tools like New Relic and Datadog offer a broader feature set, including application performance monitoring (APM), log management, and real-time analytics. These platforms help teams to identify and resolve issues before they impact users proactively.

Site Reliability Tools To Ensure High Availability and Scalability:

Container Orchestration:

Kubernetes orchestrates and manages container deployments, guaranteeing high availability and seamless scaling for your applications.

Log Management and Analysis:

The ELK Stack (Elasticsearch, Logstash, Kibana) is the go-to tool for log aggregation and analysis. It provides valuable insights into system behavior and performance, allowing teams to maintain consistent and reliable operations.

Managing Infrastructure

Secret Management:

HashiCorp Vault protects secretes, centralizes, and manages sensitive data like passwords and API keys, ensuring security and compliance within your infrastructure.

Cloud Resource Management:

Tools like AWS CloudFormation and Azure Resource Manager streamline cloud deployments. They automate the creation and management of cloud resources, keeping your infrastructure scalable, secure, and easy to manage. These tools collectively ensure that platform engineering can handle automation scripts, monitor applications, maintain site reliability, and manage infrastructure smoothly.

The Future is AI-Powered:

The platform engineering landscape is constantly evolving, and AI is rapidly transforming how we build and manage software delivery pipelines. The tools like Terraform, Kubecost, Jenkins X, and New Relic AI facilitate AI capabilities like:

  • Enhance security
  • Predict infrastructure requirements
  • Optimize resource security 
  • Predictive maintenance
  • Optimize monitoring process and cost

Conclusion

Platform engineering is becoming the cornerstone of modern software development. Gartner estimates that by 2026, 80% of development companies will have internal platform services and teams to improve development efficiency. This surge underscores the critical role platform engineering plays in accelerating software delivery and gaining a competitive edge.

With a strong foundation in platform engineering, organizations can achieve greater agility, scalability, and efficiency in the ever-changing software landscape. Are you ready to embark on your platform engineering journey?

Building a robust platform requires careful planning, collaboration, and a deep understanding of your team’s needs. At Mantra Labs, we can help you accelerate your software delivery. Connect with us to know more. 

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