Algorithms, Artificial Intelligence, Computer science and technology, Electrical Engineering & Computer Science (eecs), Human-computer interaction, Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, National Science Foundation (NSF), Research, School of Engineering, UncategorizedMay 25, 202434Views0Likes0Comments
Researchers from MIT and other institutions have developed a method to prevent chatbot performance from deteriorating during prolonged human-AI interactions. The method, called StreamingLLM, is based on a slight modification to the crucial key-value cache (KV Cache) that is central to large language models employed by many AI-driven platforms. The KV Cache, similar to a…
Researchers from the Massachusetts Institute of Technology (MIT) and partner organizations have developed a solution to address a key issue limiting the effectiveness of AI chatbots. Large language machine-learning models, such as ChatGPT, often crash or slow down during extended rounds of dialogue with humans. The study identified the cause of this problem as the…
A group of researchers from the Massachusetts Institute of Technology (MIT) have developed a revolutionary anti-tampering ID tag. Notably smaller and significantly less expensive than traditional radio frequency identification (RFID) tags, this evolution could revolutionize the way technology authenticates the legitimacy of a product. But how does it secure itself from the common issue of…
A team of MIT researchers has created a cryptographic ID tag that boasts several advantages over existing technologies - spurring hope it will revolutionize supply chain verification. The tag is several times smaller, much cheaper, and offers better security than the radio frequency identification (RFID) tags currently used for product verification. The new tag uses…
Researchers from MIT and other institutions have developed a solution to maintain continuous human-AI interactions without the chatbot crashing or slowing down. The solution, known as StreamingLLM, involves tweaking the key-value cache (like a conversation memory) that forms the heart of many large language models. Under the conventional setup, the cache, when filled beyond its…
A team of researchers from MIT has developed an innovative antitampering cryptographic ID tag, which is smaller, cheaper, and more secure than traditional radio frequency identification (RFID) tags. Traditional RFIDs can be detached from a genuine item and reattached on counterfeit products, compromising the authenticity of the item. As a solution, the MIT team creates…
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 developed a new tiny cryptographic ID tag with revolutionary terahertz technology, making it smaller, cheaper, and more secure than traditional radio frequency tags (RFIDs). The latter are often attached to products to verify authenticity but can easily be compromised by counterfeiters who remove and reattach them to fake products. To combat this,…
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.…