Meta has made one of the largest AI acquisitions of 2025, acquiring Singapore-based AI agent startup Manus for over $2 billion. The company developed a general-purpose AI agent capable of market research, coding, data analysis, and more—processing 147 trillion tokens and creating over 80 million virtual computers.

Why it matters: This acquisition signals Meta's aggressive push into autonomous AI agents across Facebook, Instagram, and WhatsApp—positioning them at the forefront of the agentic AI revolution.

💰 Valuation: $500M → $2-3B  |  🤝 Operating independently  |  📊 ByteDance retains 19.9%

NVIDIA negotiating to acquire Israeli AI startup AI21 Labs, bringing ~200 AI experts along with Jamba LLMs and Maestro agent platform.
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Microsoft & NVIDIA invested $15B in Anthropic; $40B acquisition of Aligned Data Centers; Google committed $40B to Texas data centers; OpenAI-NVIDIA targets $100B.
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New joint venture: 50% owned by Oracle, Silver Lake, MGX; ByteDance retains 19.9%. Oracle manages data security. U.S. operations valued at ~$14B.
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Record funding: OpenAI ($40B), Anthropic ($16.5B), xAI ($10B). But sentiment shifted toward bubble concerns. DeepSeek's models ($6M, 2 months) challenged U.S. dominance.
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NVIDIA's largest deal ever—a $20B licensing agreement for Groq's AI inference technology. Groq founder Jonathan Ross joins NVIDIA while Groq continues independently.
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A groundbreaking approach to training LLMs for real-world forecasting. The OpenForecaster 8B model matches larger proprietary models in accuracy using synthesized forecasting questions from daily news.

Impact: Advances AI's ability to make reliable predictions for high-stakes decision-making in finance, policy, and strategic planning.

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Uses code-generating LLMs to synthesize optimal heuristics for OS/distributed systems. Outperforms human-designed algorithms by up to 69% for cache eviction.

Impact: Could transform systems engineering by automating heuristic optimization and enabling self-tuning infrastructure.

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Introduces "Choice Policy" for humanoid robots—generating multiple candidate actions and learning to score them. Significantly outperforms diffusion policies.

Impact: Provides a practical path toward scalable humanoid manipulation in manufacturing, logistics, and domestic settings.

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