The ability for AI systems to understand what you say and respond has advanced, but you still have to speak literally and clearly to prevent them from being confused. LaMDA is a new language model that Google has been developing that’s better suited to following natural conversations instead of searching through bad queries.
LaMDA stands for “Language Model for Dialogue Applications”. Built on the transformer architecture, Google released it as open-source in 2017 alongside BERT and GPT-3. This architecture allows the model to predict text focusing only on how previous words relate to each other (attention mechanism).
LaMDA is similar to other existing models in that sense. However, this system crucially differs from other chatbots. LaMDA can handle conversations with an “open-ended nature”. Human conversations have this characteristic chaotic quality, explain Eli Collins and Zoubin Ghahramani in their blog article.
Within a few minutes, we can move from one topic to a very different one. Conversations are often sparked by unexpected connections among issues.
Transformer, a Google project for open source artificial neural networks, is the foundation of LaMDA. Models trained on this platform are capable of finding patterns in sentences, predicting what word will come next, and creating correlations between words.
The transformer was used to enhance machine translation capabilities.
We can see from the information provided that Lambda exhibits qualities listed above: context-sensibility, specificity, and interest.
Uses of LaMDA?
In its current form, LaMDA is a work-in-progress undertaking and does not have any use cases yet. LaMDA, being a Google product, has the potential to work as an assistant or search engine with virtually any other product on the web.
The LaMDA project is best suited to chatbots.
To ensure better customer satisfaction, LaMDA can help enterprises build chatbots that can engage in human-like conversations with customers. This type of chatbot can enhance the customer shopping experience in an e-commerce application or website.
Furthermore, the developers of the project mentioned that LaMDA could is trained on different types of data, including images, audio, and videos. Integrating LaMDA with YouTube, for example, will enable users to navigate videos and find specific moments or clips within the video.
The uniqueness of human communication:
Observing a conversation in retrospect can be challenging because it is so unpredictable. If you can, recall a great conversation you had with a friend or your parent in the past. Your most memorable moments, what led to them? Is it possible for you to repeat it? Did it end the same way it began? That’s what makes human language and conversation unique. There are a thousand unique paths that can be created from each sentence. You need to make just one choice, then a whole new world can appear. The same can be done with Lambda.
While LaMDA still has a long way to go. This intelligent conversational model will eventually be integrated with Google Workspace, Google Assistant, as well as other third-party apps to ensure seamless conversations between humans. This may lead to a change in search behavior and change how we interact with customer support, shop online, query search engines, and many other applications.