Yes, to reduce pricing power you need to reduce network effects and lock-in
BUSINESS
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Software Pricing Power: Network Effects and Lock-in Dynamics
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Software’s pricing power doesn’t derive from its development costs. Instead, generally, it derives from either – network effects (consumer) or – lock-in/reference selling (prosumer and enterprise).
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LLMs in Finance: S&OP and Integrated Business Planning Applications
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Hints of things to come via this research paper of
#LargeLanguageModel’s #LLM’s in Finance Will S&OP & Integrated Business Planning be next?
MT @KirkDBorne cc @PawlowskiMario @Nicochan33 @pascal_bornet @mvollmer1 @BlueYonder @alvinfoo @EvanKirstel https://
ar5iv.labs.arxiv.org/html/2310.17784 -
Strategic focus on AI tooling vs. model development
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Yep, + they won't have their model to care about (yet iirc) so they can focus on tooling. And they are burning huge money into it already
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Generative AI Revolutionizing Design Materials Discovery Business
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Explore how generative AI is revolutionizing industries from building design to materials discovery! Follow @ingliguori for more insights and discover how to leverage AI in your business with 'The Digital Edge' : https://
bit.ly/3u4pILl #AI #Innovation #TechTrends -
App adoption challenges at consumer events
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Tried to use it at my birthday party and it‘s just *really* hard to get non tech people excited about registering for yet another app.
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NVIDIA CEO Staff Structure Reveals Seven Layers Organizational Flattening
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“…if the CEO’s direct staff is 60 people, the number of layers you’ve removed in a company is probably something like seven.”
— 🖤 Christine (@christinelu) 2 juin 2024
Interesting approach. #nvidia https://t.co/56Sf4c1y8o“…if the CEO’s direct staff is 60 people, the number of layers you’ve removed in a company is probably something like seven.” Interesting approach. #nvidia
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LLMs for Financial Analysis and Profitable Trading Strategies
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9/ Financial Statement Analysis with LLMs – claims that LLMs can generate useful insights from its analysis of trends and financial ratios; shows that GPT-4 performs on par with narrowly specialized models; and achieves a profitable trading strategy based on GPT’s predictions.
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LLM Fine-tuning and Model Merging for Cost-Effective Adaptation
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“Training LLMs from scratch costs $ millions in compute. But LLMs can cheaply be adapted to new tasks via fine-tuning, leading to a proliferation of models that suit specific use cases. Fine-tuned models can be rapidly merged to combine capabilities and generalize to new skills.”