Taco Monday.. If you know what I mean. We did not even make it to Taco Tuesday, and he has chicken out again. At least the markets are back, but surveillance technology never left and never will, as the world becomes an algorithm and tech companies are out to predict your next move. Also, we dive into the state of AI and show you an amazing Cartography of GenAI that explains how the tech has permeated everything in our universe.
Let’s dive in and stay curious.
The World Has Become an Algorithm
AI Tools
The 2025 State of AI Report
The Cartography of Generative AI 2025
AI Guides
📰 AI News and Trends
Campus, a college startup backed by Sam Altman, has hired Meta’s former AI Vice President Jerome Pesenti as its technology head
Google today officially announced Nano Banana in Lens and AI Mode. It’s rolling out now in English to the US and India, with “more countries and languages coming soon,” on Android and iOS.
Apple nears deal to acquire talent and technology from computer vision startup Prompt AI
Berlin-based n8n has raised $180 million, pushing its valuation to $2.5 billion. The no-code AI automation orchestration platform's advantage over OpenAI’s AgentKit is its developer path. Its JSON-based flow engine lets engineers build agentic automations
The other AI tech stock rally is in China
Other Tech News
Google says Australian law on teens having to be older than 16 to use social media is ‘extremely difficult’ to enforce
Google Chrome silences pesky notifications from sites you have never used
Major banks explore issuing stablecoin pegged to G7 currencies
Initial Jobless claims increase to 235k
The World Has Become an Algorithm
What is Behavioral prediction?
Behavioral prediction models collect and correlate data from many sources, like location pings, transactions, social media, security cameras, supply chains, and even health records, creating a digital behavioral fingerprint.
Palantir is one of the most advanced and controversial players in this space, but not he only one. Its platforms like Gotham, Foundry, and AIP (Artificial Intelligence Platform) are built to fuse siloed datasets into unified, analyzable networks. Using Temporal modeling (how behavior evolves), Network analysis (who interacts with whom), Anomaly detection (spotting deviations from routine), and Machine learning (training models to forecast “next likely actions”)
The goal is to anticipate what individuals or groups will do before they act, whether that means predicting purchases, detecting fraud, preventing crime, or forecasting military logistics. Now, how is the above being applied everywhere? well…
How is the World an Algorithm?
Walk through a store, scroll your feed, or speak near a microphone, use any AI model, and you’re already training an algorithm. Cameras, sensors, and transaction logs have quietly turned the physical world into a living data stream. Every gesture, glance, and purchase becomes a behavioral input, fuel for predictive systems learning what we’ll want, wear, or say next. Retail is simply the clearest mirror of this transformation.
From Gap’s full-stack partnership with Google Cloud to Revolve’s AI stylist and The Body Shop’s predictive supply chain, retail is no longer transforming but being rewritten. In the past week alone, more than a dozen global retailers unveiled AI integrations, digital closets, AR try-ons, dynamic shelf pricing, and retail media networks. The message is clear: personalization is now the baseline, and data liquidity is the new logistics edge.
But now we have this on a world scale. Every corner has sensors and cameras; we are being monitored at all times, and we are monitoring ourselves with the use of our mobiles, homes, and smart devices. We are leaving a trail with every step we take. With companies like Palantir grabbing, structuring, and analyzing all this data (captured from satellites to your IG likes), it is possible to create a blueprint of who you are and what exactly you are most likely to do the very next minute. Perhaps there will not be a need for brain implants (BCIs) to police citizens; this is already providing brain access to corporations and governments.
What we are reading:
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The 2025 State of AI Report
The 2025 State of AI Report shows that artificial intelligence has shifted from an experimental tool to a core global industry. OpenAI continues to lead, but Chinese models like DeepSeek, Qwen, and Kimi are quickly closing the performance gap, especially in reasoning and coding.
The new frontier focuses on multi-step reasoning, planning, and scientific collaboration, with AI systems now capable of generating and testing hypotheses autonomously. Commercial adoption is booming, 44% of U.S. companies now pay for AI tools, up from 5% in 2023, with average enterprise contracts around $530,000 and AI-first startups growing 1.5× faster than competitors.
Nearly all professionals (95%) use AI at work or personally, and most pay for tools out of pocket. The report highlights that compute and energy capacity, not just model innovation, have become the new bottlenecks; megawatt-scale data centers are now strategic assets. Regulation is tightening globally, with the U.S. pushing “America-first AI,” Europe debating its AI Act, and China investing heavily in domestic silicon and open-source models. The narrative around AI safety has matured from existential risk toward robustness, reliability, and transparency. Overall, 2025 marks a turning point where AI fully permeates the economy, policy, and infrastructure—redefining how companies, nations, and individuals operate in a computational world.
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The Cartography of Generative AI 2025
AI does not run on code alone; it learns from examples. Generative AI models are processing billions (if not trillions) of words, images, and sounds to find patterns and reassemble them into new text, visuals, and music for output purposes. This isn’t intelligence, but rather statistical mimicry powered by vast datasets, expensive chips (mostly from Nvidia/TSMC), and global labor networks.
Behind every chatbot or image generator lies a chain of extraction: internet data scraped without consent, underpaid human labelers in the Global South, and energy-hungry data centers that consume water and power equal to tens of thousands of homes. Each model update generates more servers, increased energy use, and additional waste, making AI’s footprint larger than that of aviation.
Culturally, AI shifts from prediction to creation, automating aesthetics, storytelling, and human expression. Economically, it’s dominated by a few U.S. firms and venture-backed startups driving both hype and infrastructure growth. Politically, it shapes discourse, regulation, and misinformation.
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AI will continue to come close to replicating human thought and behaviour but will never succeed, as clothes out of the dryer will never smell like clothes off the line.