Bard

From
Revision as of 07:50, 31 March 2023 by BPeat (talk | contribs)
Jump to: navigation, search

YouTube ... Quora ...Google search ...Google News ...Bing News



Bard is a large language model (LLM) that is trained on a massive dataset of text and code. This dataset includes everything from books and articles to code and code comments. Bard is able to learn from this data and generate text that is similar to the text that it has been trained on.

The data that Bard is trained on is processed using a technique called tokenization. Tokenization is the process of breaking down text into smaller units, called tokens. In the case of Bard, tokens are typically words or phrases. The model learns to associate these tokens with the meaning of the text that they are found in. The tokens that Bard is trained on are typically words or phrases. These tokens are learned from the massive dataset of text and code that Bard is trained on. The model learns to associate these tokens with the meaning of the text that they are found in.

For example, the token "the" is typically associated with the beginning of a sentence, while the token "a" is typically associated with the beginning of an indefinite noun phrase. The model learns to associate these tokens with their meaning in the context of the text that they are found in.

This allows Bard to generate text that is grammatically correct and that makes sense in the context of the user's query. The specific tokens that Bard is trained on are a trade secret. However, it is likely that the tokens include common words and phrases, as well as more specialized tokens that are related to specific domains of knowledge.

When a user prompts Bard with a question or request, the model uses the tokens that it has learned to generate text that is relevant to the user's query. The model also uses the tokens to generate text that is grammatically correct and that makes sense in the context of the user's query.

The user interface for Bard is simple and easy to use. The user can type in a question or request, and the model will generate text that is relevant to the user's query. The model will generate text that is relevant to the user's query by using the tokens that it has learned to associate with the meaning of the user's query. The user can also ask the model to generate text in a specific style, such as a poem or a code snippet.


LaMDA

LaMDA is “the language model” that people are afraid of. After a Google employee believed LaMDA was conscious, the AI became a topic of discussion due to the impression it gave off in its answers. In addition, the engineer hypothesized that LaMDA, like humans, expresses its anxieties through communication. First and foremost, it is a statistical method for predicting the following words in a series based on the previous ones. LaMDA’s innovativeness lies in the fact that it may stimulate dialogue in a looser fashion than is allowed by task-based responses. So that the conversation can flow freely from one topic to another, a conversational language model needs to be familiar with concepts such as Multimodal user intent, reinforcement learning, and suggestions. | Sundar Pichal - Dataconomy

Retrieved from "https://primo.ai/index.php?title=Bard&oldid=24875"