Azumo

The latest edition of the AI Intelligence Briefing is now available, summarizing recent developments in model performance, new development tools, and major infrastructure investments across the AI industry. Google released Gemini 3 with updated benchmark results—95–100% on advanced mathematics, 91.9% on graduate-level science, and improvements in multimodal reasoning. The company also introduced Antigravity, an agent-first development environment designed to support more autonomous coding workflows. Anthropic announced a $50 billion investment in U.S. data center capacity, outlining a path toward profitability by 2028 in contrast with OpenAI’s projected losses for the same period. In this edition, you’ll find analysis on: The implications of Gemini 3’s reasoning performance for enterprise use How agent-first development tools may reshape engineering work Differences in business models across major AI vendors Considerations for organizations adapting to rapid capability shifts Read the full publication below.

The LLM world in 2025 looks nothing like it did a year ago. Bigger models no longer mean better results and parameter count is no longer the headline. We just published a new deep-dive on the 10 Best LLMs of November 2025, focused on real performance, enterprise readiness, and cost - not hype: 🔹 Which LLMs actually shine for coding and agentic workflows 🔹 The best options for long-context RAG and massive document analysis 🔹 How smaller models like Phi-4 and Llama 3.3 70B compete with 400B+ parameter giants 🔹 When to choose open-source vs proprietary for your AI roadmap 🔹 How multimodal models (text, image, audio, video) are changing enterprise AI If you’re a CTO, product leader, or engineering manager trying to choose between Qwen, Claude, Gemini, Nova, Llama, Phi, and more - this guide breaks down features, use cases, pricing, and trade-offs in one place. Read the full article here: https://hubs.la/Q03V8rs90

This week marks a defining moment in the evolution of AI. In my latest newsletter edition, I break down why the second week of November 2025 may be remembered as the point where AI officially shifted from assistive tools to autonomous agents - and what that means for enterprises preparing for the next wave of transformation. Here’s what’s inside: - Simultaneous flagship model releases from OpenAI (GPT-5.1) and Anthropic (Claude 4), with major advances in adaptive reasoning and agentic workflows. - Europe’s first sovereign Industrial AI Cloud, launched by Deutsche Telekom and NVIDIA, signaling a new era of national AI infrastructure. - One of the largest AI deployments ever - Cognizant rolling out Claude to 350,000+ employees globally. - Microsoft forms its own Superintelligence team, marking a strategic shift toward independent frontier AI R&D. - SAP’s Physical AI breakthroughs, delivering up to 50% downtime reduction and 25% productivity gains in real industrial environments. Across all these stories, one theme is clear: AI is taking action! This week’s edition dives deep into the strategic implications for enterprise architecture, workforce transformation, and competitive advantage. Read the full analysis below. (insert link to your newsletter)

Software development is entering a new era, one where AI doesn’t just assist, it orchestrates. In our latest article, “The AI-Orchestrated Development System: Reimagining Software Project Execution,” @Matias Margossian, key player at Azumo, explores how a two-phase AI architecture is transforming the way teams bridge the gap between planning and implementation. What’s inside: • How AI-driven orchestration compresses planning cycles by 85% • A workflow intelligence layer that reduces bug resolution time by 75% • Real-world outcomes from complex fintech deployments • Why orchestration - not just automation - defines the next generation of software delivery The result: faster, smarter, and more consistent development that preserves institutional knowledge and eliminates coordination debt. Find the link in the first comment below 👇

This week marks a defining moment in the global AI landscape. From record-breaking valuations to infrastructure commitments and public literacy initiatives. Key developments shaping the future of AI: - Google explores a $350B investment in Anthropic, setting new benchmarks for AI valuation. - NVIDIA, Oracle, and the U.S. Department of Energy unveil plans for a 100,000-GPU supercomputer — the largest government AI deployment to date. - Microsoft and major media publishers pioneer new AI content licensing models as search traffic declines. - San Jose launches AI for All, the nation’s first citywide AI literacy program. South Korea secures 260,000 NVIDIA GPUs, strengthening its national AI strategy. These stories reveal a powerful convergence: AI infrastructure as a national priority, valuation as a strategic signal, and literacy as the foundation of enterprise readiness. Read the full edition for insights on how these trends will shape enterprise AI strategy and investment priorities:

The Week AI Became Big Business! This week, the AI industry crossed a threshold - from innovation to industrialization. - OpenAI is preparing for a $1 trillion IPO while reshaping its partnership with Microsoft, signaling a new phase of strategic independence. - Sora 2 delivers 60-second, hyperrealistic videos with synchronized sound, transforming AI video from novelty to production tool. - Anthropic expands to Seoul as Claude usage surges 6× in Korea — highlighting the rapid global adoption of AI. - Google’s CodeMender autonomously patches vulnerabilities in open-source code, advancing AI’s role in cybersecurity. - Google × Anthropic’s multi-billion-dollar TPU partnership marks the rise of multi-cloud, gigawatt-scale AI infrastructure. AI platforms are now entering a new phase defined by global expansion, infrastructure investment, and enterprise deployment. At Azumo, we help organizations navigate this transformation - selecting the right AI platforms, integrating them securely, and achieving measurable ROI. Read this week’s AI Intelligence Briefing below.

Inside Azumo’s AI Toolkit: Building Better Projects with Smarter Tools When enterprise clients ask what gives Azumo the edge in delivering AI-powered projects, the answer isn’t just our talent or methods - it’s the AI tools we use every day. From Valkyrie, our scalable compute platform, to the AI Schema Generator and Charlibot, these internal innovations help our teams prototype faster, enforce governance, and deliver consistently high-quality outcomes across every stage of the project lifecycle. In this new article, @Camila Volante takes you behind the scenes to show how these tools drive speed, reliability, and trust — setting a new standard for enterprise AI excellence. Find the link to the full article in the first comment below.

Edition 3 just dropped! Late October brings a decisive shake-up across browsers, infrastructure, and enterprise rollouts. Inside this edition: - OpenAI launches ChatGPT Atlas: an AI-powered browser with conversational search, a built-in ChatGPT sidebar, and paid Agent Mode for autonomous web workflows. - Anthropic × Deloitte: Claude rolls out to 470,000 employees across 150 countries, paired with certifications and a Center of Excellence. - AMD + Oracle momentum: 50,000 Instinct GPUs on OCI and broader AMD commitments offer credible alternatives to NVIDIA-only strategies. - Regulatory heat: White House advisors push a federal pause on state AI rules while states advance their own measures. - Adoption vs. ROI: enterprise usage keeps rising, yet 80% still report no tangible EBIT impact. Why it matters: Competition now plays out in the browser, the data center, and the boardroom - while governance and ROI define the next phase. Read the full briefing in the link below.

Ever wondered how Match-3 games like Candy Crush actually work? They’ve been keeping us entertained for over 20 years - but behind all those colorful tiles and satisfying combos lies some surprisingly elegant logic. In our latest article, we break down the technical magic behind Match-3 games, exploring how Unity and C# power their: ✅ Grid-based logic systems ✅ Match detection and cascading combos ✅ Special tiles and power-ups ✅ Controlled randomness (so the board never breaks!) ✅ And the clever Model-View structure that keeps everything smooth Whether you’re a game developer, designer, or just curious about how your favorite games come to life, this deep dive shows how much brilliance hides behind the simplicity of swapping gems. Read the full article: https://hubs.la/Q03PpYzv0 #GameDevelopment #Unity3D #CSharp #GameDesign #MobileGames #Match3 #IndieDev #TechInsights

How do you keep your ML experiments organized when you’re tuning hundreds of models? We’ve just launched a new video series on Experiment Tracking with MLflow, led by Franco Matzkin, Machine Learning Engineer at Azumo, as part of our Level Up with AI initiative. In this hands-on series, Victor breaks down: • What makes experiment tracking essential in every ML workflow • How to manage hyperparameters, version models, and avoid “parameter chaos” • How MLOps connects everything — from training to production — using MLflow If you’re an ML engineer, data scientist, or just getting started with MLOps, this is a must-watch. 🎥 Watch the full series here: https://hubs.la/Q03NGRXM0 #MachineLearning #MLOps #MLflow #DataScience #AI #Azumo