Slack has introduced Slack AI, a suite of AI-powered features aimed at solving the constant problem of “chat overload” faced by office workers. These features utilize the power of the LLM language model to assist in tackling the overwhelming amount of chat messages encountered on a daily basis.
Slack AI is divided into two main groups: summarize/recap and search. The summarize/recap feature helps users by reading through various chat rooms and providing concise summaries of the main points (in the future, there will even be a channel recap feature that summarizes chat conversations in rooms that users may not have had a chance to read). Meanwhile, the search feature allows users to easily search and extract specific information and answers from chat history, using human-like language (for example, new employees can simply ask AI questions like “what is Project Gizmo” and receive a summary without having to manually read through the entire chat conversation).
According to Slack’s own figures, users who have access to Slack AI can save up to 97 minutes per week in reading and responding to messages.
Slack has confirmed that the chat data is not used to train the LLM model, although they have not disclosed the specific model they are using. It is important to note that these features currently only support the English language.
TLDR: Slack has launched Slack AI, an AI-powered feature set that helps employees deal with excessive chat messages. It includes summarize/recap to provide short summaries of chat conversations and search to extract detailed information from chat history. Users with Slack AI can save 97 minutes per week. The chat data is not used to train the model, and the features only support English language.
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