Codedevza AI Blogs

  The Greenhouse Gas Protocol has released a draft revision of its Scope 2 Guidance, opening a consultation period through December 19, 2025. This update recognises that nearly 40 per cent of global greenhouse gas emissions originate from energy generation, with roughly half of that consumed by industrial and commercial organisations. The proposed changes include the introduction of Scope 2 Quality Criteria for market based methods, a requirement for hourly matching and deliverability of electricity purchases, and an expanded use of consequential accounting to capture system wide impacts of energy choices. This post unpacks what the draft means for businesses, how it changes data strategy and procurement, and what leaders should start doing now to stay compliant and credible. The primary keyword for this discussion is Scope 2 emissions reporting. For a broader perspective on AI and data governance, see Codedevza AI infrastructure insights. The Challenge: The Problem with Scope 2 R...

  In an era where climate accountability shapes corporate strategy, the latest draft revision to the GHG Protocol’s Scope 2 Guidance arrives at a pivotal moment. Organisations worldwide grapple with reporting emissions from purchased energy sources like electricity, steam, heat, and cooling. This update, released on 27 October 2025 with consultations open until 19 December 2025, introduces stricter standards to match the rapid evolution of energy markets. For AI engineers, CTOs, and sustainability leads in tech firms, understanding these changes is crucial. This blog explores the core revisions, their implications for accurate ESG disclosures, and how innovative AI tools can streamline compliance. By the end, you will grasp how to turn these requirements into opportunities for credible, data-driven sustainability. The Challenges in Traditional Scope 2 Reporting Reporting Scope 2 emissions has long been a cornerstone of corporate sustainability efforts, yet it remains fraught with c...

The Greenhouse Gas Protocol (GHG Protocol) has unveiled a draft revision of its Scope 2 Guidance, marking a significant shift in how businesses report emissions from purchased energy. With nearly 40% of global greenhouse gas (GHG) emissions linked to energy generation, this update is poised to reshape corporate sustainability reporting. The proposed changes, including hourly matching and stricter deliverability criteria , aim to enhance transparency and accuracy in emissions disclosures. For businesses navigating the evolving landscape of sustainability compliance , understanding these updates is no longer optional, it’s a strategic imperative. The Problem: Outdated Scope 2 Reporting Standards Currently, many companies rely on annualised data and renewable energy certificates (RECs) to report their Scope 2 emissions. While these methods provide a high-level overview, they often lack the granularity needed to reflect actual energy consumption patterns. Key challenges with existing stan...

The landscape of artificial intelligence is changing at an unprecedented pace, with new models and capabilities emerging that redefine what’s possible. For developers, engineers, and product leaders, keeping abreast of these advancements isn’t just about curiosity; it is about strategic advantage. Google’s announcement of Gemini 3, their latest flagship family of large multimodal models, marks a significant moment. Positioned as Google’s most capable system to date, Gemini 3 is not merely an incremental update; it represents a unified, pervasive AI platform set to reshape both consumer and enterprise applications from day one. This deep dive explores the technical prowess, strategic implications, and transformative potential of Gemini 3 for the AI-driven world. The Unifying Challenge of Artificial Intelligence Scalability Historically, developing sophisticated AI applications often involved a fragmented approach. Different models were required for distinct modalities, a vision model fo...

Google’s Gemini 3 marks a significant shift in how organisations will build and run AI at scale. This flagship family of large multimodal models is positioned as Google’s most capable system to date, deployed from day one across Search, the Gemini app, AI Studio, Vertex AI, the Gemini CLI, and the Antigravity IDE. Unlike earlier releases that appeared in a subset of products, Gemini 3 arrives as a unified platform designed to underpin both consumer and enterprise experiences. The core focus at launch is Gemini 3 Pro, with Deep Think positioned as a higher-intensity reasoning mode that will roll out to premium and Ultra tiers. In practical terms, Gemini 3 Pro aims to excel at multimodal understanding and agentic coding, blending text, code and rich media into cohesive workflows. Deep Think is pitched as an offline-style engine for the hardest reasoning tasks, including long-horizon planning. Gemini 3 Deep Think is a stride beyond previous capabilities, a claim backed by the notoriety of...

In the fast-paced world of artificial intelligence, staying ahead means constantly pushing the boundaries of what models can achieve. Google has just announced Gemini 3, its most advanced family of large multimodal models to date. This launch marks a significant shift, positioning Google to reclaim its throne in the AI landscape after some early stumbles with previous iterations. For AI engineers, CTOs, and product managers, Gemini 3 promises to transform how we handle complex, real-world tasks that blend text, code, images, and more. This blog post dives into the core challenges of current AI systems, explores the broader implications for enterprise adoption, and unpacks how Gemini 3 delivers innovative solutions. By the end, you will understand why this unified platform could redefine your development workflows and business strategies. Whether you are building scalable AI infrastructure or seeking ethical, efficient tools, Gemini 3’s capabilities offer fresh insights into multimodal ...

In the ever-evolving landscape of artificial intelligence, Google has once again raised the bar with the launch of Gemini 3. Announced on 18 November 2025, this flagship family of  large multimodal models  represents Google’s most capable AI system to date, seamlessly integrated across consumer and enterprise applications from day one. But what sets Gemini 3 apart? Beyond its technical prowess, it’s the platform’s unified approach to  multimodal understanding ,  agentic coding , and  long-horizon reasoning  that signals a transformative shift in AI development. For tech leaders and engineers, this isn’t just an upgrade it’s a paradigm shift in how AI can be deployed at scale. Curious how this impacts your AI strategy? Let’s dive in. The Challenge: Fragmented AI Systems and Limited Reasoning Capabilities Historically, AI systems have struggled with two critical limitations: 1.  Modality Silos : Most models excel at processing text, images, or code in is...