During the opening keynote of Google I/O, Google unveiled a new version of its language model, PaLM2 (Pathways Language Model). Developed as an alternative to GPT-4, the latest iteration behind ChatGPT, PaLM2 distinguishes itself first by its support for 100 different languages. By training the model on content written in a wide variety of languages, Google claims to have “improved its ability to understand, generate, and translate nuanced texts.” The model benefits from a fine understanding of language, including expressions, riddles, and poems, whose metaphors can complicate the task of generative AI.

PaLM 2 benefits

In addition, PaLM 2 benefits from better logic, improved common sense, and enhanced math skills. To achieve these significant optimizations, Google explains that it trained the model with “scientific articles and web pages that contain mathematical expressions.” In theory, PaLM 2 will be able to rival GPT-4, whose reasoning ability had impressed us.

PaLM2 model is designed to be better at programming

Moreover, the model is designed to be better at programming thanks to training based on “a large number of publicly accessible source code datasets.” According to Google, PaLM 2 excels at generating code in Python and JavaScript. It can also produce code in less common programming languages such as Prolog, Fortran, and Verilog. The company does not hesitate to highlight AI as a coding assistant.

This new language model enables the search giant to bring serious improvements to Bard, its intelligent chatbot. Powered by PaLM 2, the conversational robot benefits from better reasoning, calculation, and coding skills. In the near future, the model will enable Bard to understand and write in over 40 different languages.

Several PaLM2 versions available

In parallel with its competitors such as Meta or OpenAI, Google has developed several versions of PaLM 2: Gecko, Otter, Bison, and Unicorn. If Unicorn represents the most powerful and heavy version of the model, Gecko is presented as a lighter version that is compatible with less powerful devices than a computer:

“It can run on mobile devices and is fast enough for excellent interactive applications on the device, even offline.”

This variety of sizes aims to facilitate the deployment of the model for “a wide range of use cases.” With less resource-intensive iterations, Google also seems to be responding to the boom in open-source artificial intelligence. By relying on the leak of LLaMA, for Large Language Model Meta AI, Meta’s language model, the open-source community quickly developed AI solutions that run smoothly on low-speed devices such as a mobile phone. A Google engineer has expressed concern about the innovations born of open-source, estimating that they represent a threat to the search giant, much more than OpenAI or Microsoft. It is therefore not surprising that Google has developed a version of PaLM 2 that can run on a smartphone.

With this quartet of models, Google aims to add generative AI to its product ecosystem. In addition to Bard, PaLM 2 will enhance tools such as Gmail, Google Docs, or Google Sheets. Google boasts that over 25 new products and features already rely on the language model. It is notably behind Med-PaLM 2, a model dedicated to the medical field. Trained on medical data using machine learning, this iteration…

ChatGPT4 vs PaLM2

ChatGPT-4 is a large language model developed by OpenAI, based on the GPT-3.5 architecture. It has 13.5 billion parameters, making it one of the largest language models ever created. This model is designed to perform a wide range of natural language tasks, including language generation, translation, and question answering.

When comparing these two models, we need to consider their performance on different tasks. For example, in terms of language modeling, both ChatGPT-4 and PalM-2 have achieved impressive results. However, ChatGPT-4 has been shown to outperform PalM-2 on a range of other tasks. Such as question answering and text classification.

Overall, ChatGPT-4 is a highly impressive language model that has the potential to advance natural language processing in a range of different fields. Its massive size and impressive performance on a range of tasks make it one of the most powerful language models ever created.

PROs and CONs

ChatGPT4– ChatGPT-4 is based on the GPT-3 architecture, which has already shown impressive performance in natural language processing tasks.
– ChatGPT-4 has been trained on a large corpus of data and can generate coherent and relevant responses in a variety of conversational contexts.
– ChatGPT-4 has been trained to understand context and can generate responses that are sensitive to the conversation history.
– ChatGPT-4 is a proprietary model, which means that it is not openly available for use by researchers or developers.
– ChatGPT-4 may suffer from some of the same limitations as GPT-3, such as being prone to generating biased or inappropriate responses in certain contexts.

PaLM2– PALM-2 is an open-source language model, which means that it is freely available for use by researchers and developers.
– PALM-2 has been designed specifically for use in conversational AI applications and has been trained on a diverse corpus of conversational data.
– PALM-2 has been designed to prioritize coherence and relevance in its responses, which can be beneficial in conversational contexts.
– PALM-2 has not been extensively benchmarked against other language models in the field of conversational AI.
– PALM-2 may not perform as well as other language models in tasks that require a deep understanding of context or that involve generating long and complex responses.

Ultimately, the choice between ChatGPT-4 and PALM-2 will depend on the specific needs of the project or application. Developers and researchers should consider factors such as performance, accessibility. And the ability to customize the model for their specific use case when making a decision.

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