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Hi {{first_name|everyone}},
In this issue:
🤝 In Partnership: Turn AI usage into something you understand
🤿Deep Dive: Eight tech giants now power the US Military's AI push
🎁Referral Rewards: Earn perks by inviting friends
🤝Supported by: Five companies tied to defense tech
🤿Deep Dive: Penn's new AI method uses decades old mathematics to crack a problem
⚒Tool Snapshots: Tools for AI, no-code, and productivity
🖼AI Art: Examples of great and trending AI art
🤝IN PARTNERSHIP WITH HARMONIC
Stop making AI decisions in the dark. Understand AI usage.
Leadership is asking: are we getting value from AI? Which tools are worth the spend? Where are we exposed? Right now, most teams have no idea.
Harmonic Security Usage Explorer changes that. It automatically classifies every AI interaction across your organization into the use cases driving real work, specific to your business. Not generic categories. Not raw prompts. Actual patterns to understand: how your teams are using AI, how much time they spend in AI, the cost, and where risk lives.
CIOs get the data to rationalize spend and cut wasted licenses. CISOs get risk in context. AI committees get proof of impact.
Early access is now open to a limited number of organizations. Request your spot.
🤿 DEEP DIVE
US Military Locks In Google OpenAI Amazon and More for Any Lawful Operational AI Use
Intelligence: The Pentagon just formalized AI contracts with 8 major tech companies including Google, OpenAI, Amazon, Microsoft, SpaceX, Oracle, Nvidia, and startup Reflection, opening the door for AI use across any lawful military operation. The one notable absence is Anthropic, which refused to accept that language and is now suing the government over what it calls retaliation.
The Pentagon said the agreements help it avoid vendor lock by spreading AI capabilities across multiple companies rather than depending on one.
More than one million people across the Defense Department have used the military's AI platform since it launched last year, cutting some tasks from months to days.
Anthropic was actually the first AI company deployed for classified government work but the relationship broke down when CEO Dario Amodei publicly raised concerns about mass domestic surveillance and autonomous weapons.
Defense Secretary Pete Hegseth labeled Anthropic a supply chain risk shortly after, effectively banning its use in government settings, and a legal challenge is expected in court in September.
Google's Gemini will for the first time handle classified government work under this agreement, despite hundreds of Google and DeepMind employees sending a letter to Sundar Pichai urging the company not to deepen military ties.
SpaceX is included as the parent company of xAI and Grok, while Nvidia is contributing its open source Nemotron models but no hardware as part of the deal.
🎁REFERRAL REWARDS
If TIW has been useful, invite one friend or coworker who’d actually use AI/automation at work.
1 referral → get the TIW No-Code Workflows PDF (25 plug-and-play workflows)
10 referrals → get a full course free (your choice)
Your referral link: {{rp_refer_url}}
Tip: send it to a friend who’s AI-curious, a coworker who wants to move faster, or anyone trying to automate repetitive tasks.
🤝 SUPPORTED BY THE CHEAP INVESTOR
5 Stocks Powering the Next Era of Defense
The defense sector's biggest reallocation in decades is underway. AI, space infrastructure, and advanced aerospace are capturing a growing share of procurement budgets. Our free report profiles the five companies investors should know now.
🤿 DEEP DIVE
University of Pennsylvania Team Cuts AI Training Time by 10x Using a 1940s Mathematical Concept
Intelligence: Researchers at the University of Pennsylvania built a new AI method called Mollifier Layers that makes it significantly easier for AI to solve one of science's trickiest problems, figuring out the hidden rules behind something you can already observe. Think of it as teaching AI to look at ripples in a pond and reliably work out where the pebble fell, even when the water is choppy.
Image credit: Transactions on Machine Learning Research
The method draws on a mathematical concept called mollifiers developed in the 1940s, inserting a smoothing step before derivatives are calculated rather than letting the AI grind through unstable recursive calculations.
In benchmark tests the mollified approach reduced peak memory use from 2.75 gigabytes to 0.23 gigabytes and cut training time from 3,386 seconds to 335 seconds on the hardest problem tested.
Accuracy jumped dramatically too with one correlation score rising from 0.44 to 0.99 on a fourth order reaction diffusion problem where standard methods often fall apart.
The layer is lightweight and can be added to multiple types of existing physics informed AI models without redesigning them from scratch.
For the Penn team the immediate application is chromatin, the DNA packaging inside cell nuclei that controls gene expression, aging, and disease, where the method finally lets them infer the hidden reaction rates driving structural changes.
The approach could travel well to weather modeling, materials science, fluid mechanics, and genetics anywhere scientists need to estimate hidden quantities from sparse or noisy measurements.
The paper is published in Transactions on Machine Learning Research and will be presented at NeurIPS 2026.
⚒ TOOL SNAPSHOTS
Futuristic tools within AI, no-code, and productivity
🌐 Radar - Streamline Kubernetes workflows with single, open-source UI.
🔍 PandaProbe - Trace, monitor and debug AI agents effortlessly.
☁️ Huddle01 VMs - Control your infrastructure setup with AI chat.
📝 Mockin 2.0 - Your complete toolkit for landing UX/UI jobs.
📉 Rosentic - Effortless PR analysis ensuring efficient, clean merges.
🖼 AI ART
Examples of great and trending AI art
Images by m0shing_smurf
ℹ️ ABOUT US
The Intelligent Worker helps you to be more productive at work with AI, automation, no-code, and other technologies.
We like real, practical, and tangible use-cases and hate hand-wavy, theoretical, and abstract concepts that don’t drive real-world outcomes.
Our mission is to empower individuals, boost their productivity, and future-proof their careers.
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