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GPT4All: ChatGPT on your computer, free, open-source, and privacy-aware
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ChatGPT has some major problems... here is the solution.
00:00 - The Problems with ChatGPT
00:40 - The Solution: GPT4All
01:07 - Demo
03:25 - Integrating GPT4All with Python
EQUIPMENT I USE
BOOKS I RECOMMEND:
DISCLAIMER: Links might be affiliate links. As an Amazon Associate I earn from qualifying purchases. There is no additional charge to you, so thank you for supporting my channel!
A local, offline version of ChatGPT could have profound implications for data privacy. Since all data would be processed within your own machine, there would be no risk of third-party access, ensuring that sensitive information remains protected. This feature could be particularly appealing to users dealing with confidential data, as they would not need to worry about potentially exposing this data over the internet.
Beyond just privacy, this arrangement also offers increased data security. Since the data never has to travel across the internet, it eliminates the risk of data interception or breaches, further fortifying the information against potential cyber threats.
One of the most substantial benefits of an offline version of ChatGPT would be its availability. Even in our connected world, internet access is neither universal nor consistently reliable. With a version of ChatGPT that can function on a local machine, users could have access to the AI anytime and anywhere, so long as their machine has power. This would be particularly useful in remote areas or places with poor internet connectivity.
Another potential advantage is the reduction in latency. An AI model running locally on your machine does not have to deal with the delay of sending a request to a server and waiting for the response to return. This can make the system more responsive, providing users with a smoother and more efficient experience.
Lastly, costs could be mitigated with a local version of ChatGPT. Using AI models in the cloud often involves a cost per query or computation time. Conversely, once a locally-run AI model has been purchased or freely distributed, these per-use costs would no longer apply, which could lead to substantial savings over time.
#ai #programming #chatgpt
00:00 - The Problems with ChatGPT
00:40 - The Solution: GPT4All
01:07 - Demo
03:25 - Integrating GPT4All with Python
EQUIPMENT I USE
BOOKS I RECOMMEND:
DISCLAIMER: Links might be affiliate links. As an Amazon Associate I earn from qualifying purchases. There is no additional charge to you, so thank you for supporting my channel!
A local, offline version of ChatGPT could have profound implications for data privacy. Since all data would be processed within your own machine, there would be no risk of third-party access, ensuring that sensitive information remains protected. This feature could be particularly appealing to users dealing with confidential data, as they would not need to worry about potentially exposing this data over the internet.
Beyond just privacy, this arrangement also offers increased data security. Since the data never has to travel across the internet, it eliminates the risk of data interception or breaches, further fortifying the information against potential cyber threats.
One of the most substantial benefits of an offline version of ChatGPT would be its availability. Even in our connected world, internet access is neither universal nor consistently reliable. With a version of ChatGPT that can function on a local machine, users could have access to the AI anytime and anywhere, so long as their machine has power. This would be particularly useful in remote areas or places with poor internet connectivity.
Another potential advantage is the reduction in latency. An AI model running locally on your machine does not have to deal with the delay of sending a request to a server and waiting for the response to return. This can make the system more responsive, providing users with a smoother and more efficient experience.
Lastly, costs could be mitigated with a local version of ChatGPT. Using AI models in the cloud often involves a cost per query or computation time. Conversely, once a locally-run AI model has been purchased or freely distributed, these per-use costs would no longer apply, which could lead to substantial savings over time.
#ai #programming #chatgpt
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