This paper explores the role of computational neuroscience in bridging the gap between linguistic theoretical frameworks and empirical neuroscience data. Computational neuroscience formalizes the hierarchical and dynamic structures of language into testable neural models through modeling, simulation, and data analysis.

Recent advances in Large Language Models (LLMs) have significantly advanced this pursuit, offering a new scale for exploring the neural basis of linguistic processing. The "model-brain alignment" framework provides a methodology to evaluate the biological plausibility of language-related theories.

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Databricks CEO Ali Ghodsi suggests that while AI may not directly threaten SaaS, it will significantly alter how SaaS products are used as natural language becomes the predominant interface. The company reported a 65% year-on-year revenue growth, with $1.4 billion coming from AI products.

Ghodsi warns that the specialized user interface expertise, once a key differentiator for SaaS companies, may become irrelevant due to AI. To address this, Databricks is developing Lakebase, a database designed for AI agents, which has already generated double the revenue of its data warehouse product.

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InfiniMind, a startup founded by former executives from Google Japan, Aza Kai and Hiraku Yanagita, has raised $5.8 million in seed funding to build AI infrastructure that transforms corporate video archives into searchable and analyzable business intelligence. Their DeepFrame platform can process over 200 hours of footage to answer complex queries.

This infrastructure combines computer vision, natural language processing, and audio analysis to identify scenes, speakers, and events within video content. This enables rapid and efficient analysis that previously required weeks of manual effort, with applications expected in media, retail, and security sectors.

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