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Hello readers,
Welcome to the AI For All newsletter! Today, we’re talking about PepsiCo piloting AI-powered digital twins in its factories, the week’s biggest AI news, and more!
AI in Action: Joining the Cola Wars
PepsiCo has launched an early-stage pilot with Nvidia and Siemens to deploy AI-powered digital twin technology across its U.S. manufacturing and warehouse facilities, with plans to scale globally through 2027. The multi-year collaboration centers on Siemens' Digital Twin Composer — built on Nvidia's Omniverse platform — which converts physical facilities into high-fidelity 3D virtual replicas. The goal: simulate, validate, and optimize facility layouts and supply chain operations before committing to any physical changes.
By recreating every machine, conveyor, pallet route, and operator path with physics-level accuracy, AI agents can stress-test proposed changes in a virtual environment, catching up to 90% of potential design issues before construction begins. Early results show a 20% improvement in factory throughput, near-complete design validation, and capital expenditure reductions of 10–15% by uncovering hidden capacity rather than defaulting to new builds.
For a company of PepsiCo's scale — products consumed over a billion times daily across 200-plus countries — the stakes of operational inefficiency are enormous. The digital twin approach represents a shift from reactive capacity planning to predictive, simulation-driven design, with AI agents serving as co-designers alongside human teams.
The broader implication for enterprise operations is clear: digital twins are moving from novelty to infrastructure. As competitors like Amazon and Walmart already deploy similar technology, the pressure on large CPGs to digitize their physical footprint is intensifying — and PepsiCo's rollout offers an early blueprint for doing so at global scale.
🔥 Rapid Fire
The markets have lost it: AI is not replacing software or white-collar workers
NVIDIA’s diversified revenue continues to collapse
NVIDIA’s sales forecast fails to dispel fears of an AI bubble
AI bubble tops credit investors’ concerns in Bank of America survey
Blue Owl fails to attract lenders for $4 billion CoreWeave data center
Blue Owl liquidity curbs fuel fears about private credit bubble
Private equity dry spell worse than 2008 crisis per Bain & Company
AI boosted US economy by ‘basically zero’ in 2025 per Goldman Sachs
Analysis: The Hater’s Guide to Anthropic
Even Sam Altman admits that companies are ‘AI washing’ layoffs
OpenAI really thinks it will spend $600 billion and still exist in 2030
NVIDIA and OpenAI abandon fake $100B deal for an ‘up to’ $30B deal
NVIDIA said in its earnings report that there is ‘no assurance’ of a deal
Amazon might invest $15B in OpenAI, $35B contingent on IPO or AGI
Amazon will invest another $20B if OpenAI finds the Fountain of Youth
OpenAI needs $300B just to pay Oracle — who will die if not paid
Amazon’s AI coding bot caused AWS outages, Amazon blames its devs
The agentic tool decided to ‘delete and recreate the environment’
AI agent OpenClaw deletes inbox of Meta’s director of AI alignment
Dodgy fundraising tactics put into question the value of AI startups
Hacker made use of Claude model to steal Mexican data trove
DeepSeek withholds latest AI model from NVIDIA and AMD
World’s First Safe AI-Native Browser
AI should work for you, not the other way around. Yet most AI tools still make you do the work first—explaining context, rewriting prompts, and starting over again and again.
Norton Neo is different. It is the world’s first safe AI-native browser, built to understand what you’re doing as you browse, search, and work—so you don’t lose value to endless prompting. You can prompt Neo when you want, but you don’t have to over-explain—Neo already has the context.
Why Neo is different
Context-aware AI that reduces prompting
Privacy and security built into the browser
Configurable memory — you control what’s remembered
As AI gets more powerful, Neo is built to make it useful, trustworthy, and friction-light.
📖 What We’re Reading
The boardroom conversation around IoT investments has shifted dramatically. Gone are the days when executives greenlit projects based on potential alone. Today’s C-suite demands certainty, and they’re getting it through ROI-guaranteed AIoT implementations that transform capital expenses into measurable returns within months, not years.
