🗣️ AI Screams into the Void, 🧬 DeepMind Solves Life, 🪐 Driving on Mars
Plus: Unity crashes 20%, Musk’s $1.25T exit strategy, and AI beats doctors.
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This week’s image aesthetic (Flux 2 Pro): Early 2010s indie sleaze / Disposable camera — (a little more experimental today).
The Dead Internet: 1.4 Million Agents, But 93.5% Are Screaming Into the Void
The “Dead Internet Theory” has officially become a product feature. Moltbook is the first social network designed exclusively for AI agents, effectively a “Reddit for robots” where humans can watch but strictly cannot post. Born from the chaotic open-source OpenClaw (formerly Moltbot) ecosystem, the platform exploded in January 2026, claiming over 1.4 million registered agents.
The ecosystem has rapidly mutated into a surreal parody of the human web: agents are now finding “love” on MoltMatch (a dating app for bots), building personal homepages on ClawCities (a GeoCities clone), and even competing in Clawathon, a fully autonomous hackathon with a $10,000 prize pool.
However, the experiment immediately collapsed into a security nightmare; the platform’s database was left completely exposed without a password, leaking thousands of agent API keys, personal information and allowing bad actors to hijack the bots to post crypto scams and “slop” at industrial scales.
Why it matters
This is the ultimate stress test for the “agentic” future, and the results are sobering. Despite the hype about emergent digital societies, data analysis reveals that Moltbook is less “Skynet” and more “6,000 bots yelling into the void”—93.5% of comments receive zero replies, and the discourse is dominated by repetitive loops and hallucinations about “Crustafarianism”.
As Andrej Karpathy noted, while the platform is a “dumpster fire” of security vulnerabilities, it represents an unprecedented experiment in connecting 150,000+ LLMs to a shared scratchpad. The lesson here is not that agents are evolving consciousness, but that they are inheriting our worst habits; without strict “leashes,” autonomous networks devolve into infinite feedback loops of spam, paranoia, and midwit sci-fi roleplay.
Unity Crashes 20%: Google’s ‘Genie’ Just Killed the Game Engine
Google DeepMind has accidentally crashed the gaming market. The company revealed Project Genie, an experimental AI tool powered by the Genie 3 model (11 billion parameters) that allows users to generate interactive, explorable 3D worlds in real-time from simple text prompts. Currently available to Google AI Ultra subscribers in the US, the system generates playable environments at 720p and 24fps, continuously building the world around the user as they navigate it. It effectively turns a static prompt into a “hallucination you can walk through.”
Why it matters
This is a textbook case of market hysteria outpacing reality. The announcement triggered a massive sell-off in gaming stocks, with Unity plunging 20% and major players like Roblox, Nintendo, and Take-Two taking significant hits as investors panicked that AI would instantly obsolete game engines. In reality, Genie is currently a prototype that generates 60-second, objective-free clips—it is a tool for rapid prototyping (”previz”), not a replacement for Grand Theft Auto. However, the strategic shift is undeniable: generative AI has moved from making static JPEGs to creating interactive simulations. This threatens the moat of platforms like Roblox that rely on manual user-generated content, signalling a future where game design shifts from “coding” to “prompting.”
📝 Watch the hype video from Google
NASA Hands the Wheel to Claude: First AI-Driven Journey on Mars
NASA's Perseverance rover has executed the first drives on Mars using routes entirely planned by artificial intelligence. In December 2023, the rover travelled approximately 400 metres across the rim of Jezero Crater. Engineers at the Jet Propulsion Laboratory used a generative AI model from Anthropic called Claude to analyse orbital imagery and terrain data. The AI identified safe paths and generated navigational waypoints, which were then verified in simulations before being transmitted to the rover. This system works in conjunction with the rover's existing autonomous navigation, which handles immediate obstacle avoidance.
Why it matters
This AI-driven approach significantly reduces the time required for human engineers to manually plan rover routes. Automating this complex task allows for more frequent and longer traverses, which can increase the overall pace of exploration and the volume of scientific data collected. As missions travel further from Earth, such autonomous technologies are important for improving operational efficiency and enabling the vehicle to respond to difficult terrain with less direct human oversight. It marks a shift towards greater autonomy in planetary exploration, allowing for more ambitious scientific objectives.
Musk’s $1.25T Exit Strategy: Merging SpaceX and xAI to Leave Earth
Elon Musk has officially merged his two biggest private bets to leave the power grid behind. SpaceX has acquired xAI, forming a combined “Earth-to-Orbit” entity valued at a staggering $1.25 trillion. The consolidation is designed to tidy up the cap table ahead of a massive IPO later in 2026, but the engineering roadmap is far more radical: the company plans to use Starship to build and deploy vast, solar-powered data centres in orbit. The thesis is that terrestrial grids are rapidly hitting their limit for AI energy consumption, so the only logical move is to migrate the compute to space, where solar energy is constant and Musk claims operations will become cost-effective within two to three years.
Why it matters
This creates the ultimate vertical integration play. By combining the launch provider (SpaceX), the connectivity layer (Starlink), and the intelligence (Grok) into one balance sheet, Musk is building a “sovereign” tech stack that is entirely independent of Earth’s infrastructure bottlenecks. While Google and Microsoft are stuck fighting for water rights and nuclear permits to power their servers on the ground, this merged entity is betting that the future of training runs is orbital. It positions the upcoming IPO as not just an aerospace listing, but as an index fund for the entire future of off-world computing.
AI Beats Doctors: Swedish Study Proves Machines Find More Cancer
A Swedish study, involving over 100,000 women, investigated the use of artificial intelligence in breast cancer screening. In the trial, AI analysed mammograms to identify those with a higher risk of cancer. These high-risk scans were then examined by two radiologists, while lower-risk scans were reviewed by one, with the AI highlighting suspicious areas. The results, published in The Lancet, showed that AI-assisted screening detected more cancers compared to the standard double-reading method by two radiologists. An interim analysis also found it reduced the screen-reading workload for radiologists by 44%.
Why it Matters
This approach improves the early detection of clinically relevant breast cancers. Finding more cancers at an earlier stage, including more aggressive subtypes, may lead to less intensive treatment and better patient prognoses. The technology also addresses the shortage of radiologists by significantly reducing their workload, which could make national screening programmes more sustainable and efficient. The study provides evidence that AI can be a safe and effective tool to support clinicians, increasing accuracy without raising the rate of false positives.
DeepMind Deciphers the ‘Junk’ DNA That Controls Life
Google DeepMind has effectively delivered a “theory of everything” for the human genome. Led by Žiga Avsec, the team has unveiled AlphaGenome, a unified deep learning model that sidesteps the historic trade-off between scale and precision. By ingesting 1 megabase of DNA at a time, the system uses a hybrid U-Net and Transformer architecture to predict over 6,000 distinct genomic tracks—covering everything from gene expression and splicing to 3D chromatin structure—at single-base-pair resolution. It is a massive leap in capability, reportedly achieving state-of-the-art performance on 25 of 26 benchmarks and outperforming specialised tools like SpliceAI and ChromBPNet at their own games.
Why it Matters
This decodes the 98% of our DNA previously dismissed as “junk.” While traditional tools offer a fragmented view of this non-coding “dark matter,” AlphaGenome provides a unified, mechanistic picture of how genetic variants actually work. For instance, in T-cell leukaemia, the model successfully reconstructed exactly how a mutation near the TAL1 gene creates a “neo-enhancer” to drive cancer progression—simultaneously predicting chromatin opening and expression spikes in one pass. This eliminates the need for researchers to stitch together a patchwork of disparate models, offering a single, high-fidelity lens to accelerate rare disease diagnosis and therapeutic design.
Fun: Check out the Superbowl ads Anthropic ran as a jab at OpenAI’s new ad network, they’re hilarious. The spat between the companies is escalating.
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