TechCheck Takes: How DeepSeek supercharged AI’s distillation problem 2/25/25
Feb 25, 2025
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Arvind Jain, the CEO of Glean and a former Google veteran, discusses the transformative power of AI distillation techniques like DeepSeek’s. He highlights how these methods empower smaller teams to build competitive AI models, challenging larger players. Jain delves into the ethical dynamics of AI, touching on allegations against rivals for misusing resources. The conversation also emphasizes the impact of open-source AI on innovation, cost-effectiveness, and the burgeoning potential in the evolving tech landscape.
The distillation technique enables smaller teams to leverage advanced AI capabilities from larger models, fostering competition against major industry players.
The shift towards open-source AI models is democratizing access and pushing established companies to innovate or risk becoming obsolete.
Deep dives
The Impact of Distillation on AI Development
The distillation technique in AI has revolutionized how models are built by allowing smaller teams to access advanced capabilities without extensive resources. This method involves training a smaller model by leveraging the knowledge of a larger, more complex model, enabling startups to compete effectively against industry leaders. For example, a new reasoning model was created for only $450, demonstrating how distillation can significantly reduce costs and increase efficiency in developing AI applications. This shift opens the door for innovation, as more players can now enter the AI space with less capital investment, challenging established companies.
Open Source vs. Closed Source Paradigm
The podcast highlights a fundamental shift towards open-source AI models, suggesting that transparency and accessibility foster faster innovation compared to traditional closed-source strategies. Companies like DeepSeek have made their models available for anyone to download and customize, which raises questions about the sustainability of closed-source approaches used by major players like OpenAI. As the advantage of open-source systems becomes evident, even leaders in the field are rethinking their strategies, with OpenAI's CEO acknowledging past missteps regarding openness. This shift not only democratizes AI access but also pressures proprietary models to improve their offerings or risk obsolescence.
Cost Efficiency and Competitive Dynamics
The entry of new players utilizing distillation has led to significant price reductions for AI services, changing the competitive landscape for companies like OpenAI and Microsoft. Distilled models offer comparable performance at a fraction of the cost, compelling enterprises to reassess their usage of established models. For instance, DeepSeek's R1 model costs only $2.19 per million tokens, while similar services from OpenAI reach $60. This cost efficiency empowers developers and business leaders to create more applications, ultimately driving broader AI adoption and fostering a more competitive market environment.
The Race Towards Artificial General Intelligence
Despite the promising developments in model distillation and cost efficiency, the pursuit of Artificial General Intelligence (AGI) by major tech companies remains a critical focus. Leaders like Sam Altman advocate for aggressive investment strategies aimed at achieving breakthrough innovations in AI, suggesting that foundational advancements cannot be replicated through distillation alone. The podcast indicates that while smaller, efficient models are beneficial, they may not lead to the revolutionary advancements required to reach AGI. As competition escalates and industry dynamics shift, the pressure is on for established players to innovate continuously while navigating the evolving landscape shaped by newcomers.
Silicon Valley is reckoning with an AI development technique that could upend the leaderboard. Distillation is the idea that a small team can make an advanced AI model by extracting knowledge from a larger one. DeepSeek didn’t invent the method, but its use roiled the markets and woke the AI world up to its potential. It’s now enabling startups to compete at the cutting edge, and is deadly for the biggest AI players’ competitive edges. This video includes an interview with Glean CEO Arvind Jain.
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