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Will thinking bodies be a hot market this year? Maybe we share why. Google’s Auto Browser will change the game by actually doing the work for you, no clicks, just instructions. At the same time, DeepSeek is proving that efficiency, not brute force, is what truly scales. Let’s dive in. Stay curious.

• Google’s Gemini Auto Browser will change the Game

• 🧰 AI Tools - AI Browsers

• 🛠️ AI Jobs Corner

• From Frankenstein to AI Companions: The Rise of Thinking Bodies

• Are DeepSeek’s LLMs More Efficient Than Bigger Models?

• 📘Learning Corner -

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📰 AI News and Trends

• TSMC Can’t Make AI Chips Fast Enough

• Beijing Restricts Nvidia’s H200 Purchase, Banning the Chips From Entering China

• Apple to fine-tune Gemini independently, no Google branding on Siri, more

• Chinese AI developer Zhipu on Wednesday released a new open-source AI image model trained entirely with chips from Huawei Technologies

• Google’s Veo now turns portrait images into vertical AI videos and upgrades Veo 3.1 with Ingredients and 4K upscaling

Other Tech News

• Meta Considers Doubling Ray-Ban Glasses Production

• As SpaceX Works Toward 50K Starlink Satellites, China Eyes Deploying 200K

• Iran crippled Starlink, the service that became synonymous with censorship-proof connectivity. Iran has just proved that assumption wrong.

• Meta is slashing hundreds of workers from Reality Labs VR division. The job cuts come as the social media giant doubles down on AI and grapples with a big bet on the metaverse that didn’t pan out

• Apple To Offer “Creator Studio” Subscription Bundle With Tools For Making Films, Music & More

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From Frankenstein to AI Companions The Rise of Thinking Bodies

One of the best movies of 2025 for me was Frankenstein. Guillermo del Toro took Mary Shelley’s masterpiece and gave it new life, literally. Watching it, I couldn’t help but see parallels with where AI is today and where we’re clearly heading.

In the film, Frankenstein is a fully functional being assembled from different parts, powered by a brain that learns, reasons, and improves with time and experience. The creator has his story, but Frankenstein has his own version of it, too. That part feels especially familiar.

In today’s tech landscape, LLMs are the brain. They’re evolving fast, and inference is pushing them toward reasoning capabilities that won’t mirror humans, but also won’t need to. They’re built differently. They absorb knowledge differently. And now, we’re watching robotics, the global race to attach those brains to bodies.

This isn’t a secret anymore. Soon, most human interaction with AI will be through voice, not keyboards. And when those voices live inside robots, humanoids, and digital companions with human-like forms, talking to AI will feel less like “using software” and more like, well… having a human conversation. Possibly one that never interrupts you. Or forgets what you said five minutes ago.

I recently read about how advanced the sex doll industry has become, and when you combine that with the fact that 10 million+ people use Replika daily (2023 numbers), plus millions more creatively jailbraking LLMs for companionship and sexual conversations, the direction is obvious. Human-like humanoids we can talk to, work with, rely on, and yes, have sex and form bonds with, will be a massive industry.

Frankenstein wasn’t really about monsters.
It was about creation catching up to the creator.

And this time, the monster ships with software updates.

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Are DeepSeek’s LLMs More Efficient Than Bigger Models?

DeepSeek’s Engram shows how Chinese AI labs are advancing faster by focusing on efficiency, not just scale.

Instead of forcing large language models to repeatedly recompute common phrases and facts, Engram adds a conditional memory layer that lets models look up frequent language patterns in O(1) time, like giving the model a second brain. This delivers strong gains across knowledge, reasoning, code, and long-context tasks (including a +12.8 jump in long-context retrieval) at the same parameter count and FLOPs as traditional MoE models.

More importantly, it cuts wasted computation, shifts work from power-hungry GPUs to cheap memory, and enables massive memory tables to be offloaded to the CPU with <3% overhead. The result is higher performance with lower data-center and electricity demand, highlighting a key advantage of Chinese AI teams: architectural innovation that treats compute, power, and infrastructure as scarce resources, not unlimited ones.

Google’s Gemini Auto Browser will change the Game

Google is testing Auto Browse for Gemini, giving the AI direct control over Google Chrome.
The feature lets Gemini autonomously open tabs, navigate pages, manage sessions, and complete multi-step browsing tasks. Early code hints suggest it may launch as a Gemini Ultra (premium) feature, likely via a Chrome sidebar or extension.

This follows agentic browsing moves from Perplexity and OpenAI, where AI agents already perform delegated web research and actions.

Will AI Browsers change the game?

1. Browsers become execution layers, not just viewers
Auto Browse turns the browser into an AI-controlled workspace, where humans describe goals and agents execute clicks, searches, and workflows. This is a fundamental shift from “search and read” to “delegate and verify.”

2. Agentic browsing becomes mainstream
Until now, autonomous browsing has been experimental or niche. Google embedding it directly into Chrome pushes agent-based web navigation to billions of users. This accelerates adoption by years, not months.

3. Search → Action → Outcome
Traditional search ends with links. Auto Browse ends with completed tasks.

• Research + summarization

• Comparing products

• Filling forms

• Managing multi-tab workflows
  This threatens classic SEO-only models and favors AI-readable, structured, task-completable websites.

4. Premium AI = productivity leverage
Positioning Auto Browse under Gemini Ultra signals a new pricing logic:

• Free AI = answers

• Paid AI = work done
  This mirrors what happened with cloud and dev tools: power users pay for automation, not information.

5. The web becomes “AI-first” with agent navigation, tool calling, structured extraction, and Deterministic actions. Human UX still matters, but machine UX becomes equally critical.

🧰 AI Tools of The Day

AI Browsers

• Perplexity Comet - Navigates the web, automates research, and can manage tasks like email or organization.

• ChatGPT Atlas - Helps you search, summarize, automate multi-step tasks, and act on websites.

• Dia Browser - Let’s you chat with your open tabs, interpret content, and handle browsing tasks using AI.

• Opera Neon - AI “Tasks” that analyze, compare, and act across multiple sources with minimal input.

• Browserbase - Enables AI agents to read, write, and perform tasks on the web autonomously (good for automation services or demos).