Human-computer interaction

Large language AI models are notorious for crashing or slowing down during lengthy human-AI dialogues, posing a major barrier to the effective use of chatbots in many applications. Now, a team of researchers from MIT and other institutions propose a novel solution - by modifying the key-value cache, or the 'conversation memory', they improved the…

MIT researchers have discovered a fault in the design of language machine-learning models that can cause AI chatbots' performance to drastically deteriorate during lengthy conversations. Essentially, when data stored in a chatbot's "memory" (known as the key-value cache) exceeds its capacity, the earliest data is removed, sometimes causing the chatbot to malfunction or slow down.…

Researchers from MIT and other institutions have developed a method that enables a chatbot to carry on unbroken conversation without crashing or losing performance. This method, named StreamingLLM, involves a tweak to the key-value cache, a form of "conversation memory", that helps AI operate. The team found when the cache became too full, the first…

Researchers from MIT and other institutions have discovered the key to why AI chatbot conversations can break down and developed a solution that enables continuous dialogue. The issue lies in the chatbot's key-value cache (akin to a conversational memory). In some models, earlier data points are discarded when the cache reaches its limit, causing the…

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…