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Building AI That Actually Works
Listen to this episode from AI-podden on Spotify. In this week's episode, Ather chats with Magnus Hambleton, investor at byFounders and former data lead at Natural Cycles. Magnus has successfully applied transformers to improve fertility predictions in a medical setting. As an investor, he focuses on agentic AI and backs startups slightly ahead of what’s currently possible, betting on near-future model capabilities. He remains cautious about LLMs’ reliability and generalization, believing new architectures may be needed for AGI. While big tech is dominant, he sees room for startups in complex, workflow-driven applications.
Bing
Building AI That Actually Works
Listen to this episode from AI-podden on Spotify. In this week's episode, Ather chats with Magnus Hambleton, investor at byFounders and former data lead at Natural Cycles. Magnus has successfully applied transformers to improve fertility predictions in a medical setting. As an investor, he focuses on agentic AI and backs startups slightly ahead of what’s currently possible, betting on near-future model capabilities. He remains cautious about LLMs’ reliability and generalization, believing new architectures may be needed for AGI. While big tech is dominant, he sees room for startups in complex, workflow-driven applications.
DuckDuckGo
Building AI That Actually Works
Listen to this episode from AI-podden on Spotify. In this week's episode, Ather chats with Magnus Hambleton, investor at byFounders and former data lead at Natural Cycles. Magnus has successfully applied transformers to improve fertility predictions in a medical setting. As an investor, he focuses on agentic AI and backs startups slightly ahead of what’s currently possible, betting on near-future model capabilities. He remains cautious about LLMs’ reliability and generalization, believing new architectures may be needed for AGI. While big tech is dominant, he sees room for startups in complex, workflow-driven applications.
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