In addition to Copilot and ChatGPT,there are many other applications available. Here are the most prospective ones to investigate, with an emphasis on those that offer self-hosting. Launch date appears between brackets:

Tabnine (2019)
GitHub Copilot (2021)
Replit Ghostwriter (2022)
Amazon CodeWhisperer (2022)
Codeium (2022)
Cody SourceGraph (2023)
CodeComplete (2023)
FauxPilot (2023)
Tabby (2023)

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ChatGPT substitutes

Important to note about ChatGPTis that it trains its model using your input via the web interface by default. Employees of Samsung disclosed confidential information by requesting ChatGPT to generate meeting notes. ChatGPT stores user information, including that of paying users. If you do not agree with this, you must opt out.

The following alternatives to ChatGPT do not "leak" data, in the sense that user-entered data does not become part of a training set that can be accessed by all customers:

• OpenAIAPIs. ChatGPT uses data inputted through its web interface for training, but not via its APIs. Consequently, using the APIs with a wrapper, such as the open-source Chatbot UI, is an apparent workaround.
• AzureOpenAIService. Employ company-specific data and hyperparameters to fine-tune custom AImodels.
• MosaicML. In a secure environment, train large AImodels on your business's data. Simply point to an AWS S3 bucket, and you're done!
• Glean. Large language models (LLM) based on deep learning provide AI-powered workplace search across the company's applications.
• Aleph Alpha. A company emphasizing that it is a European AI technology company that has open-sourced its codebase and does not use consumer data to train its models.
• Cohere. A collection of LLMs for text generation, summarization, classification, and retrieval.
• Writer. A platform for generative AI that is trained on the company's data.

Building your own company model as opposed to utilizing a centralized LLM provider is another option, and this strategy may be judicious for businesses wary of sharing sensitive and proprietary information with vendors. Dolly, which was developed by Databricks, is a low-cost LLM that performs fairly well in comparison to ChatGPT, despite the fact that its model is obsolete. They also open-sourced 15,000 training data records. Do more research on Dolly.

In the impending era of LLMs, "buy, build, or self-host" will be a very pertinent question. This is due to the fact that the utility of LLMs depends on both the model and supplementary training data. Companies will want to train LLMs using internal data to maximize their utility for employees. However, trusting a vendor with internal data is riskier than constructing and operating an LLM internally or self-hosting one. Self-hosting and specifically the construction of a server incur considerable expenses. Nevertheless, it's still early, so perhaps such experimentation makes sense?

It seems to me that ChatGPT alternatives are a very popular topic, and that we have likely only scratched the surface of companies working in this area. There are over 50 LLMs with 1 billion or more parameters that can be accessed through open-source checkpoints or proprietary APIs.

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This article is an excerpt from The impact of AI coding tools on productivity. The complete article also addresses:

1.The study. A summary of the queries and respondent profiles.
2.Comparable advances in productivity. The benefits provided by GitHub Copilot and ChatGPT are enticing, but not entirely unprecedented in technology. Engineers with decades of experience provide examples of previous comparable productivity enhancements.
3.GitHub Copilot. Its most common use cases, where the greatest gains can be realized, and when this tool is not particularly beneficial.
4.ChatGPT. Typical usage scenarios and when to proceed with caution.
5.ChatGPT versus Copilot. How the instruments stack up. When is one superior to another?
6.The present and future of AI programming languages. Respondents to a survey made common observations and intriguing predictions.
7."Will AI coding tools eliminate my position?" A very prevalent question that causes some engineers concern.

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