We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
️ AI Assistants & ️ Data Ops: PyData Heilbronn #1 @ IPAI
Discover the pros and cons of building a private AI assistant in-house, including data privacy concerns and customization options, with expert insights on open-source and proprietary models, TCO, and more.
- The speaker suggests that building a private AI assistant in-house can be a good option for companies, especially those with complex use cases.
- The main concern is data privacy, as companies may not want to send their data to the cloud for processing.
- OpenAI’s GPT-3 model is a popular option, but it’s not suitable for all use cases, especially those that require customizations or control over the data.
- Building a private AI assistant in-house requires a significant investment in hardware and software, but it provides complete control over the data and customization options.
- The speaker suggests using a combination of open-source models and proprietary models to achieve the desired level of customization and control.
- The trade-off between exploration and waiting or taking risks is crucial when deciding whether to build a private AI assistant in-house or use a cloud-based service.
- The speaker highlights the importance of considering the total cost of ownership (TCO) when deciding which option to choose.
- The speaker mentions that some companies, such as Bosch and PM, have built their own AI assistants in-house.
- The speaker also mentions that there are open-source alternatives available, such as Langdag, which offers a private AI assistant solution.
- The speaker suggests that companies should consider the capabilities, price, and privacy when deciding which option to choose.
- The speaker mentions that some companies may prefer to use consumer-grade hardware, such as NVIDIA’s A6000, instead of professional-grade hardware.
- The speaker concludes that building a private AI assistant in-house can be a good option for companies that require customization and control over their data.