Top AI & Tech News (Through April 13th)

Hello AI Citizens 🤖,

This week, we dive into a major leap in AI infrastructure. At the heart of many AI breakthroughs are specialized chips called Tensor Processing Units (TPUs) — hardware built specifically to accelerate the heavy computations behind machine learning models. TPUs are optimized for handling vast amounts of data in parallel, enabling enterprises to train and run powerful AI systems faster and more efficiently. With Google’s Ironwood, we’re entering the "age of inference," where AI doesn’t just respond — it proactively thinks, analyzes, and delivers insights at unprecedented scale and speed. For businesses, this means smarter applications, faster insights, and the ability to harness AI’s full potential with greater energy efficiency and lower costs.

Here are the key headlines shaping the AI & tech landscape:

• Mira Murati’s Thinking Machines Targets $2B Seed Round

• Google Unveils Ironwood: Powering the AI Age of Inference

• Google Agentspace Gets No-Code Boost & Enterprise Agents

• China Makes AI Education Mandatory for All Students from 2025

• Microsoft Eyes Managerial Cuts in Major Restructuring Push

• Canva Enters AI Coding

• AI Index 2025: AI Surges Into Daily Life, Business, and Policy

Ready to unpack these stories? Let’s dive into the details 🚀

💰 Mira Murati’s Thinking Machines Targets $2B Seed Round

Ex-OpenAI CTO Mira Murati’s stealth AI startup, Thinking Machines Lab, is reportedly aiming to raise a staggering $2 billion in its seed round — potentially valuing the company at over $10 billion. Despite having no product or revenue yet, the startup is attracting major investor interest thanks to its high-profile team, including ex-OpenAI heavyweights like Bob McGrew and Alec Radford. The company promises to build AI systems that are more customizable, transparent, and broadly capable than today’s leading models. Source: Tech Crunch

💡Thinking Machines is positioning itself as a serious contender in the AI race by leveraging top-tier talent and ambitious goals to capture early capital. If successful, this seed round would be one of the largest in history, reflecting growing investor appetite for next-generation AI models that prioritize user control and generality. For businesses, this signals an accelerating trend toward more versatile and enterprise-friendly AI ecosystems.

⚙️ Google Unveils Ironwood: Powering the AI Age of Inference

At Google Cloud Next 2025, Google unveiled Ironwood, its most powerful and energy-efficient Tensor Processing Unit yet, purpose-built for inference at massive scale. Designed to meet the demands of advanced AI models like LLMs and Mixture of Experts (MoEs), Ironwood features up to 9,216 liquid-cooled chips, delivering over 42.5 exaflops — 24x more than the world’s largest supercomputer. With enhanced memory, bandwidth, and the Pathways runtime, Ironwood can seamlessly train and serve the next generation of thinking models across industries. Source: Google Blog

💡Ironwood represents a strategic leap toward AI systems that proactively generate insights rather than just respond to queries, a game-changer for enterprises leveraging generative AI. Its massive scalability, energy efficiency, and infrastructure-first design give businesses the horsepower needed to run the most demanding AI applications while controlling costs. For leaders, this signals an era where AI workloads shift from experimental to essential — with infrastructure built to scale alongside ambition.

🧩 Google Agentspace Gets No-Code Boost & Enterprise Agents

At Google Cloud Next, Google unveiled major upgrades to Agentspace, its enterprise AI workspace. Now integrated directly into Chrome’s search box, Agentspace offers powerful unified search, analysis, and synthesis features for employees. New additions include a no-code Agent Designer to let anyone build custom AI agents, plus two new expert Google-built agents: Deep Research and Idea Generation. These tools join existing offerings like NotebookLM for Enterprise, giving organizations an expanded suite to create and deploy AI agents at scale. Source: Google Blog

💡Google’s Agentspace evolution signals a major push to democratize AI agent development within the enterprise, empowering employees at all technical levels to create tailored tools for their workflows. By embedding agent capabilities directly into everyday tools like Chrome, Google is lowering adoption barriers and accelerating operational efficiency. For businesses, this offers a fast track to scaling AI-driven insights and automation, boosting productivity without heavy IT dependencies.

📚 China Makes AI Education Mandatory for All Students from 2025

China will require AI education in all primary and secondary schools starting September 2025, making it the first country to fully integrate AI literacy into its national curriculum. Students as young as six will receive at least eight hours of AI instruction annually, covering everything from foundational concepts to advanced topics like machine learning and robotics. The program aims to nurture early interest in STEM, fast-track AI competency, and build a future workforce of AI experts and innovators. Source: Asia Education Review

💡This move positions China as a global front-runner in embedding AI into societal foundations, signaling long-term ambitions to dominate future technology leadership. By equipping an entire generation with AI fluency, China is not just creating users but future architects of the AI economy. For global businesses and policymakers, this raises the stakes: AI education is shifting from a competitive advantage to a national priority.

🔍 Microsoft Eyes Managerial Cuts in Major Restructuring Push

Microsoft is reportedly planning another round of job cuts as early as May, focusing on trimming middle management and non-coding roles. Leaders are aiming to increase the ratio of coders to managers, with some divisions targeting a 10-to-1 engineer-to-manager ratio. This follows earlier cuts of 2,000 employees deemed low performers, as Microsoft seeks to streamline teams and boost productivity across its security and cloud operations. The move mirrors broader industry trends, with tech giants like Amazon and Google also downsizing management layers to improve efficiency. Source: Business Insider

💡Microsoft’s move underscores a critical shift: managers who want to stay relevant must embrace AI to manage and optimize teams more effectively. As companies streamline and prioritize technical output, the role of managers evolves from traditional oversight to leveraging AI-driven insights for productivity, team performance, and resource allocation. Leaders who harness AI tools to enhance decision-making and reduce operational drag will be better equipped to thrive in this new efficiency-driven landscape.

🖌️ Canva Enters AI Coding & Spreadsheet Arena

Canva is going all-in on generative AI with its latest Visual Suite 2.0 update, merging design, productivity, and AI tools into one seamless platform. The suite introduces Canva Code, an AI assistant that empowers users to generate apps, widgets, and interactive content without any coding skills, alongside Canva Sheets, a creative spreadsheet tool that uses AI to analyze data and build striking visualizations. With its new conversational AI partner and upgraded photo editor rivaling pro tools like Photoshop, Canva is positioning itself as the ultimate no-code creative workspace — targeting designers, marketers, and office teams alike. Source: The Verge

💡 Canva's move reflects a broader trend: the fusion of design, data, and AI-powered automation into accessible, no-code tools. As businesses prioritize speed and collaboration, platforms that let non-technical users build sophisticated assets and insights will command serious attention. Canva’s strategy aims to democratize creative and technical tasks, opening new productivity frontiers for teams of all sizes. 

📊 AI Index 2025: AI Surges Into Daily Life, Business, and Policy

The Stanford AI Index 2025 reveals AI’s unstoppable march across industries, daily life, and global policy. AI models now outperform humans in select programming tasks, while generative AI investment soared to $33.9B globally. U.S. leadership continues, producing the most top models, but China is closing fast on performance benchmarks. The tech is rapidly becoming more affordable, with the cost of GPT-3.5 level inference dropping over 280-fold in two years, and governments worldwide racing to regulate and invest, from the U.S.'s 59 new regulations to Saudi Arabia’s $100 billion AI initiative. Source: Stanford HAI

💡 AI is evolving from experimentation to infrastructure, becoming embedded across healthcare, transport, enterprise tools, and government policy. The global AI race is intensifying, but so is accessibility: lower costs and open models are democratizing advanced AI capabilities. However, challenges persist — from gaps in responsible AI practices to the ongoing complexity of multi-step reasoning tasks. For leaders, the message is clear: success now depends on mastering AI adoption, policy alignment, and talent development at speed and scale.

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