Now we'll have to see if any of those API providers make a move to drop their product into something that works in a VPC. Until then, it looks like we're starting to see how the "business" of the current iteration of generative AI will play out.
@mattlynley
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API Providers Business Models and Enterprise Data Security Concerns
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And as OpenAI puts together its business model, so too with other API providers likely follow. The challenge, though, is that companies that are skittish about using APIs don't want additional controls and a promise that their companies won't use their data—they want it in a VPC.
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OpenAI GPT-4 API Rate Limiting Issues Impact Enterprise Performance
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OpenAI is trying to pitch some controls and privacy additions for enterprise companies, but from companies I talk to, this is about performance and reliability. he GPT-4 API is really powerful, but users also end up running into issues with rate limiting and have to drop to 3.5T.
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ChatGPT Pricing Tiers: Free to Enterprise Strategy
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A "free" version that employees can use internally (w/ IT's blessing or not) by copy/pasting into the interface. A "base" version with the 3.5-Turbo API. A "plus" version with the fine-tuned 3.5-Turbo API. A "premium" version of the base GPT-4 API. And finally an enterprise tier.
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OpenAI’s Tiered Pricing Strategy Mirrors Web 2 Model
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OpenAI's launch of a fine-tuned GPT 3.5-Turbo version and an enterprise tier essentially creates a track of increasing performance for its APIs with an up-to-the-right pricing model. If it looks familiar, it should: it's pretty much the route that companies took in the Web 2 era.
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API Provider Business Models Emerge One Year Post-ChatGPT
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As we head into the one-year mark after the launch of ChatGPT, we're finally starting to see the business models for API providers come into focus. And it turns out everything old is new again.
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RAG Technology: A Major Development in AI Systems
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RAG’s a big deal! Everyone is talking about it. https://
supervised.news/p/a-clever-way
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Google Unifies Vertex AI Suite to Compete with Bedrock Azure
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Google's push to unify Vertex AI into a suite to compete with Bedrock and Azure AI is coming into focus as it looks to avoid letting its competitors run off with its ground-breaking technology for a third time
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Google’s Hardware-Software Stack Strategy for AI Dominance
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We don't really have a lot of details on the latter, but it represents a tantalizing opportunity to offer a very Google-only stack—hardware optimized for its software—to recapture its dominance in AI. And, in this case, avoid repeating history for the third time.
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Google Nvidia Launch PaxML Language Model Framework
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Second, and much more subtly, came in the form of the announcement of a language model development framework co-built with Nvidia called PaxML. More importantly, PaxML is built on top of Google's cutting-edge AI framework, JAX, and XLA.