Basic Introduction of Google’s LaMDA AI
- Google is committed to making conversations with chatbots smooth and easy and in this regard, Google has come up with an AI language model by the name of “LaMDA” or “Language Model for Dialogue Applications.” Google came up with the announcement at Google I/O 2021. Google’s new model has been developed with the aim of making conversations more meaningful and lively.
- If you are a technology enthusiast, you will like this blog post for sure.
- In this post, we will be covering all about Google LaMDA AI – What LaMDA is all about, how it works, its difference from a typical chatbot, the application of LaMDA, and what the future looks like for LaMDA.
What is Google’s LaMDA? | All about Google’s LaMDA AI
- Google aims at facilitating open-ended yet meaningful dialogues with the help of LaMDA AI. CEO Sundar Pichai gave a peek into his life when he talked about how his son conversed with Pluto, the planet (LaMDA). The model is said to have thrown light on the New Horizons Spacecraft and the coldness that is there in space. What has surprised everyone is the fact that has been disclosed by Pichai and that is, the responses given by LaMDA were not pre-programmed. The responses rather were sensible focusing on an open-ended dialogue. He further added that LaMDA is capable of continuing a conversation without any retraining.
Watch Google’s AI LaMDA program talk to itself at length With Sunder Pichai
How does LaMDA AI work?
- Google has said in its blog post that LaMDA’s conversational skills are a result of years of development. It is developed on a neural network architecture named, Transformer. The neural network architecture, Transformer has been open-sourced by Google research in 2017 just like other language models like BERT and GPT-3.
- Google first came up with a research paper about LaMDA AI in January 2020, throwing light on the fact that the model could learn to converse on any topic under the sun. Since its research paper came out, Google has been looking for ways to make the model more sensible and its responses more specific.
- At Google I/O, CEO, Sundar Pichai, said that LaMDA sometimes gives illogical responses. For example, it imagined Pluto doing flips and talked about playing with a “favorite ball”, the moon! However, Google is committed to making LaMDA a fair and accurate AI language model while keeping privacy in mind.
- As per Pichai, the language model, LaMDA, is developed keeping in mind Google’s AI principles and is made in such a way that it is capable of making information and computing easier to make use of.
Differences between LaMDA AI and a typical chatbot Here are the differences:
1) Basis of Training –
- While a typical chatbot is trained on datasets that are topic-specific, LaMDA has received training on multi-content internet resources.
2) Source of Answers –
- A typical chatbot is capable of providing answers only from training data. On the other hand, LaMDA picks up answers and topics based on the conversation flow.
3) Conversation Flow –
- A typical chatbot has a limited conversation flow. On the other hand, LaMDA enables open-ended dialogues/conversations.
Application of LaMDA AI | How To Use Google Lamda:
- Building a Virtual Assistant suitable for Google Workspace.
- Enabling Search navigation on Google’s Search Engine.
- Improving dialogues and tasks of Google Assistant and Google Home.
- Translating on a real-time basis.
- Enhancing commercial chatbots.
- The developers have also said that LaMDA can be trained on various types of data like images, audios, or videos so that the responses and conversations are more flexible.
What does the future look like for LaMDA AI?
- Google’s LaMDA AI aims at naturalizing conversations but it is trained only on text as of now. Google’s move/strategy to integrate audio, videos, and photos with LaMDA is where all eyes are fixed as that is going to determine the fate of this language model. If Google is successful in the integration, it can be capable of providing one source of conversational AI across various applications including Google Maps and YouTube, among others. Also, the computational infrastructure that Google uses for LaMDA will determine its success. Although developers are leaving no stone unturned to eliminate biases that may emerge as LaMDA is trained on different datasets, Google has to keep looking for newer and more innovative ways to make LaMDA more ethical.