A team of researchers from MIT and other institutions have found a way to prevent chatbots driven by large language machine-learning models from collapsing during lengthy conversations. The failure typically occurs when the key-value cache, or "conversation memory", in some methods cannot contain more information than its capacity, resulting in the first data points being…
Research from MIT and other institutions has developed a method, called StreamingLLM, that enables AI chatbots to maintain continuous dialogue without crashing or slowing down. The technique tweaks the key-value cache or conversation memory at the core of large language models. Failure often occurs when this cache needs to store more information than it can…
A team of researchers from MIT and other institutions has discovered a key issue with large-scale machine learning models causing chatbot performance to degrade. When engaged in extensive dialogues, the huge language models behind bots like ChatGPT sometimes begin to fail. However, the team devised a solution enabling nonstop conversation without deterioration or lag. The…
When engaging in lengthy dialogues, advanced AI-powered chatbots often become inept, resulting in a significant performance downturn. A team of researchers from MIT alongside others have deduced a reason for this issue and devised a straightforward solution to prevent the bot from crashing or slowing down. The method, StreamingLLM, effectively ensures a continuous discussion irrespective…
A team of researchers from MIT and other institutions has discovered a remarkable cause of performance deterioration in chatbots and found a simple solution that allows persistent, uninterrupted dialogue. This problem occurs when human-AI interaction involves continuous rounds of conversation, which can overburden the large language machine-learning models that power chatbots like ChatGPT.
The researchers have…
Researchers from MIT and other institutions have developed a method that prevents large AI language machines from crashing during lengthy dialogues. The solution, known as StreamingLLM, tweaks the key-value cache (a sort of conversation memory) of large language models to ensure the first few data pieces remain in memory. Typically, once the cache's capacity is…
Researchers from MIT and other institutions have found a solution to an issue that causes machine-learning model-run chatbots to malfunction during long, continuous dialogues. They found that significant delays or crashes happen when the key-value cache, essentially the conversation memory, becomes overloaded leading to early data being ejected and the model to fail. The researchers…