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THE DAILY INDEX

Technology, AI, software, security, crypto and business

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SYSTEM INSTRUCTIONS FOR GEMINI 3 PRO

This post provides system instructions for Gemini 3 Pro that improved performance on various agentic benchmarks by up to around 5%. Specific instructions are often required to control how the model reasons, plans, and executes tasks for deep agentic workflows. Complex agents often require a trade-off between computational cost (latency and tokens) and task accuracy. A guide on how to build better agentic workflows is linked in the thread.

FROM CODE FOUNDATION MODELS TO AGENTS AND APPLICATIONS: A COMPREHENSIVE SURVEY AND PRACTICAL GUIDE TO CODE INTELLIGENCE (16 HOUR READ)

This study presents a comprehensive analysis of code-generating large language models across their entire life cycle. It examines both general-purpose models and code-specialized models. The researchers bridged the gap between academic benchmarks and real-world software development challenges through systematic experiments on scaling laws, architectures, and training methodologies. They also conducted a series of experiments that analyzed code pre-training, supervised fine-tuning, and reinforcement learning across multiple dimensions.

ANTHROPIC CEO SAYS SOME TECH FIRMS TOO RISKY WITH AI SPENDING

Anthropic's CEO, Dario Amodei, says that some artificial intelligence companies are taking on too much risk by committing to spending hundreds of billions of dollars to develop and support AI systems. The industry is facing a real dilemma due to the need to balance costly investments in data centers with uncertainty in how quickly the economic value is going to grow. Anthropic is trying to manage risk responsibly. While it has increased its spending, it has largely concentrated on growing its enterprise business rather than focus on customers.

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