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DeepSeek and the Seven Dwarf Problems for LegalTech (ft Joe Rayment)
Feb 3, 2025
Join Joe Rayment, CEO of Automatise, an Australian legal tech expert, as he dives into the buzz around DeepSeek, a revolutionary AI language model. He tackles the dynamic between open-source and proprietary tech, emphasizing the impact on the legal landscape. Rayment discusses the financial and ethical implications of DeepSeek, exploring data ownership and vendor lock-in challenges. He also highlights the geopolitical narratives behind AI advancements and raises awareness of the nuanced risks in machine learning and cybersecurity for legal firms.
42:00
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Quick takeaways
- DeepSeek's emergence as an open-source alternative to proprietary models highlights a potential shift towards cost-effective and competitive AI solutions for legal tech firms.
- The complexities surrounding data privacy and licensing issues with DeepSeek raise significant concerns for law firms about maintaining client confidentiality and navigating intellectual property rights.
Deep dives
Rise of DeepSeek and Open Source Implications
DeepSeek is a new large language model launched as an open-source alternative to proprietary AI systems like OpenAI's models. Created by a Hong Kong hedge fund, it reportedly cost $5.6 million to train and has demonstrated competitive performance while being significantly cheaper to operate. This transition to open-source models raises crucial discussions about the economic viability of proprietary systems, as open-source technology tends to attract developers and businesses. The broader implications for legal tech suggest that firms may benefit from more affordable AI solutions, as competition could drive down costs across the board.
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