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🌍The Race to Build “World Models” Is Splitting Into Five Approaches

Plus: Warren Questions Pentagon Deal With xAI

Yaro Celis

Mar 16

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Prediction markets are taking over our lives, as anyone can basically bet even as little as a $1 on any future event. As these platforms generate billions in trading volume, Wall Street is beginning to pay attention and explore similar financial products. At the same time, “world models” are becoming one of the hottest areas in AI, with startups raising over $2B in recent weeks to build systems that help machines understand and simulate the physical world. We break down five major approaches shaping this emerging field.

Meanwhile in Washington, Sen. Elizabeth Warren is questioning how safe classified government data is when shared with AI companies, raising concerns about security risks as the Pentagon deepens partnerships with frontier AI developers.

Let’s get into it. Stay curious.

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The Race to Build “World Models” Is Splitting Into Five Approaches
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Wall Street Moves Into Prediction Markets
Warren Questions Pentagon Deal With xAI

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📰 AI News and Trends

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Anduril wins up to $20B, 10-year US Army contract.
Facebook makes it easier for creators to report impersonators.

AI startups are pouring huge capital into “world models” systems that help AI understand and simulate reality. In the past few weeks alone, AMI Labs raised $1.03B, and World Labs raised $1B, but the term “world model” now covers several very different technical strategies. Zhuokai Zhao shared on X

1. JEPA latent prediction
Led by Yann LeCun and AMI Labs. Instead of predicting pixels, JEPA models predict abstract representations of the world, making them far more efficient. One model trained on 1M+ hours of video and needed just 62 hours of robot data to perform zero-shot planning.

2. Spatial intelligence (3D worlds)
Fei-Fei Li is betting that AI needs explicit 3D understanding of environments. World Labs’ system generates persistent 3D scenes that can be explored and edited like real environments.

3. Learned simulation
Companies like Google DeepMind are building models that simulate worlds directly. Systems such as Genie and Dreamer allow AI agents to learn by interacting with simulated environments, even achieving complex goals like finding diamonds in Minecraft without human data.

4. Physical AI infrastructure
NVIDIA is building the platform layer. Its Cosmos stack trains world models on 20M hours of video (9,000T tokens) and provides tools for robotics, autonomous systems, and physical AI.

5. Active inference
VERSES AI uses a neuroscience-inspired approach where agents minimize “surprise” in the world using probabilistic reasoning instead of deep learning.
World models may become the next major AI architecture after large language models, powering robotics, simulation, and autonomous systems, but the industry is still experimenting with multiple competing approaches.

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Wall Street Moves Into Prediction Markets

Prediction markets, platforms where traders bet on future events, are gaining traction in traditional finance.

Trading platform Tradeweb recently partnered with Kalshi and saw overwhelming interest from institutional clients. Kalshi says billions in trading volume already come from investors trading contracts tied to climate, tech, and macro events.

Major finance players are entering the space:

Intercontinental Exchange invested $2B in Polymarket
Jump Trading and Susquehanna International Group are providing liquidity
Nasdaq is exploring event-based trading contracts

Prediction markets are being used to forecast elections, interest rates, wars, and economic indicators, turning collective market bets into real-time forecasting tools.

Investor takeaway: If regulators approve new products like prediction-market ETFs, the sector could evolve into a new derivatives asset class on Wall Street.

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Warren Questions Pentagon Deal With xAI

Sen. Elizabeth Warren is demanding answers from Defense Secretary Pete Hegseth about reports that the Pentagon may allow xAI to operate on classified military networks.

Warren warned that xAI’s chatbot Grok could pose cybersecurity and safety risks, including leaking classified information, producing inaccurate responses, or lacking proper safeguards for military use. She requested documentation showing how the Defense Department evaluated Grok’s security and data-handling practices.

The concern comes after the Pentagon awarded xAI a contract worth up to $200 million to develop AI systems and reportedly reached a deal in February to expand its use on secure networks. Grok has faced scrutiny from regulators and governments worldwide over weak guardrails and controversial outputs, including manipulated images and antisemitic responses.
Doge may have already given xAI and all its vertical companies unprecedented access to sensitive government and citizen data. And now that Anthropic shows us that AI companies can be ethical, the governments are rushing to find less ethical companies to replace Claude AI to adopt frontier AI. Policymakers are increasingly questioning whether emerging models are secure and reliable enough for national security systems.

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