Google has officially launched PaLM 2, its latest large language model (LLM) that will empower an updated version of Google’s AI-driven chatbot Bard. During the I/O developer conference, Google made the announcement, highlighting the model’s improved common-sense reasoning and expanded capabilities in mathematics and logic.
This release holds significance for Google as its generative AI product, Bard, has faced tough competition from major rivals such as OpenAI’s ChatGPT and Microsoft’s Bing in recent months.
PaLM 2 not only represents a significantly more robust language model but also includes specialized iterations tailored to specific domains like cybersecurity (Sec-PaLM 2) and the medical industry (Med-PaLM 2).
ChatGPT, developed by OpenAI and introduced to the public in November 2022, quickly gained popularity and became the fastest platform to reach 100 million users. Users were amazed by its ability to process information, solve problems, and generate high-quality, human-like responses to queries.
ChatGPT was hailed as a groundbreaking technology with the potential to revolutionize information work and business operations. Its release triggered a race among major tech companies to develop similar generative AI tools and integrate them into their existing products. Microsoft invested a substantial $10 billion in OpenAI, while Google, Tencent, and Amazon raced to develop their own generative AI tools.
Is PaLM 2 superior to ChatGPT?
Google argues that PaLM 2, having been trained extensively on mathematical and scientific texts, can handle complex mathematical puzzles more efficiently and reason through intricate problems. It is also claimed to excel in writing and debugging code, as it has been trained in 20 coding languages. Furthermore, PaLM 2 is designed to function in over 100 human languages.
When asked if PaLM 2 can compete with GPT4 by analysts at Dataconomy.com, Google Bard responded affirmatively, stating that PaLM 2 has the potential to rival GPT4.
The chatbot emphasized that PaLM 2 is a newer model trained on a larger dataset of text and code, implying that it possesses greater power and versatility compared to GPT4.
PaLM2
PaLM 2 demonstrates superior performance in advanced reasoning areas, encompassing code and mathematical tasks, classification, question answering, translation, multilingual proficiency, and natural language generation. Its success can be attributed to a combination of compute-optimal scaling, an enhanced dataset mixture, and improvements in model architecture.
Google has developed PaLM 2 with a responsible approach to AI development and deployment. The model underwent rigorous evaluation to address potential harms, biases, capabilities, and downstream applications in both research and product settings. PaLM 2 serves as the foundation for other cutting-edge models such as Med-PaLM 2 and Sec-PaLM, while also driving generative AI features and tools like Bard and the PaLM API at Google.
Logic
PaLM 2 surpasses previous LLMs, including PaLM, in its ability to break down intricate tasks into more manageable subtasks. It also demonstrates superior comprehension of the intricacies of human language. An illustrative example of PaLM 2’s prowess lies in its aptitude for deciphering riddles and idioms, which necessitates grasping the ambiguous and figurative connotations of words beyond their literal interpretations.
More than 100 Language Translations
PaLM 2 underwent pre-training using parallel multilingual text and a significantly larger corpus of diverse languages compared to its predecessor, PaLM. As a result, PaLM 2 demonstrates exceptional performance in multilingual tasks.
Coding Capability
PaLM 2’s pre-training involved a substantial amount of web page, source code, and other datasets. As a result, it outperforms in popular programming languages like Python and JavaScript, and also possesses the ability to generate customized code in languages like Prolog, Fortran, and Verilog. This feature, along with its language proficiency, can facilitate cross-language collaboration among teams.
