Rafid Mahmood
@rafidrm.bsky.social
Assistant Prof @ Telfer School of Management + Sr. Research Scientist @ NVIDIA working on data-centric ML & operations of AI systems
https://rafidrm.github.io
https://rafidrm.github.io
Due to competition, Gen AI models must continue to improve or face being underpriced.
Given 2 tasks, we show pricing reduces to 3 regimes based on the ratio of competitive ratios versus the ratio of user demands:
1) high prices,
2) low prices,
3) 0 revenue!
8/n
Given 2 tasks, we show pricing reduces to 3 regimes based on the ratio of competitive ratios versus the ratio of user demands:
1) high prices,
2) low prices,
3) 0 revenue!
8/n
November 25, 2024 at 5:55 PM
Due to competition, Gen AI models must continue to improve or face being underpriced.
Given 2 tasks, we show pricing reduces to 3 regimes based on the ratio of competitive ratios versus the ratio of user demands:
1) high prices,
2) low prices,
3) 0 revenue!
8/n
Given 2 tasks, we show pricing reduces to 3 regimes based on the ratio of competitive ratios versus the ratio of user demands:
1) high prices,
2) low prices,
3) 0 revenue!
8/n
2️⃣ Models are best evaluated by user satisfaction to responses (e.g., Chatbot Arena).
For instance on Github Copilot, the ‘acceptance rate’ of AI suggestions is the largest predictor of user productivity.
dl.acm.org/doi/pdf/10.1...
3/n
For instance on Github Copilot, the ‘acceptance rate’ of AI suggestions is the largest predictor of user productivity.
dl.acm.org/doi/pdf/10.1...
3/n
November 25, 2024 at 5:55 PM
2️⃣ Models are best evaluated by user satisfaction to responses (e.g., Chatbot Arena).
For instance on Github Copilot, the ‘acceptance rate’ of AI suggestions is the largest predictor of user productivity.
dl.acm.org/doi/pdf/10.1...
3/n
For instance on Github Copilot, the ‘acceptance rate’ of AI suggestions is the largest predictor of user productivity.
dl.acm.org/doi/pdf/10.1...
3/n