In Google I/O 2023 which happened in May 10th 2023, Google unveiled its successor for its previous AI based model PaLM which was released in 2022. It’s Google’s next generation large language model that was build on Google’s legacy breakthrough research in machine learning and AI.
What is PaLM 2?
We know – everyone is talking about PaLM 2 is a Pathways Language Model (Full form for PaLM) and it can do certain things which a normal program or app can not achieve. So lets learn what actually is a language model and how it works.
A language model is a statistical method that predicts the next word in a sequence. It is trained on a large corpus of text, and it learns the probability of each word appearing after a given sequence of words. This information can be used to generate text, translate languages, and answer questions.
There are two main types of language models: statistical and neural. Statistical language models use a variety of techniques to calculate the probability of each word appearing after a given sequence of words. Neural language models use artificial neural networks to learn the probability of each word appearing after a given sequence of words.
Statistical language models are typically faster and easier to train than neural language models. However, neural language models are more accurate and can be used for more complex tasks, such as machine translation and question answering.
Language models are a powerful tool for natural language processing. They can be used to generate text, translate languages, and answer questions. As language models continue to improve, they will become even more powerful and versatile tools.
What are the use cases of PaLM 2?
Since release from 2022, there are a lot of hype about Google’s PaLM model. So lets see what are the practical use uses for the PaLM 2. Since it is a massive language model with 1.56 trillion parameters, trained on a massive dataset of text and code. PaLM 2 is capable of a wide range of tasks, including:
Natural language understanding: PaLM 2 can understand natural language, including text, code, and other forms of human communication. It can understand the meaning of words, phrases, and sentences, and it can use this information to answer questions, generate text, and translate languages.
Code generation: PaLM 2 can generate code in a variety of programming languages, including Python, Java, and C++. It can generate code that is correct, efficient, and idiomatic. Question answering: PaLM 2 can answer questions in a comprehensive and informative way, even if they are open-ended, challenging, or strange. It can use its knowledge of the world to answer questions about a wide range of topics.
Translation: PaLM 2 can translate text from one language to another. It can translate text accurately and fluently, even if it is complex or technical.
Other tasks: PaLM 2 can also perform other tasks, such as writing different kinds of creative content, summarizing text, and generating different creative text formats.
Summary
To summarise the above, the Google’s PaLM 2 is really an impressive step to the AI. We have already seen AI tools like ChatGPT, Google’s BARD which uses language models to provide the response to user queries. In short in near future we are going to see a huge number of apps also adapting to AI and machine learning to achieve greater things.