PaLM2
Tech major Google has unveiled its large language model (LLM) PaLM 2, a move seen to compete against ChatGPT.
"Building on this work, today we’re introducing PaLM 2, our next generation language model. PaLM 2 is a state-of-the-art language model with improved multilingual, reasoning and coding capabilities," read the Google website.
The new model is expected to power Google’s updated Bard chat tool.
It is the company's competitor to OpenAI’s ChatGPT.
Features:
Multilinguality: PaLM 2 is more heavily trained on multilingual text, spanning more than 100 languages.
This has significantly improved its ability to understand, generate and translate nuanced text — including idioms, poems and riddles — across a wide variety of languages, a hard problem to solve. PaLM 2 also passes advanced language proficiency exams at the “mastery” level.
Reasoning: PaLM 2’s wide-ranging dataset includes scientific papers and web pages that contain mathematical expressions. As a result, it demonstrates improved capabilities in logic, common sense reasoning, and mathematics.
Coding: PaLM 2 was pre-trained on a large quantity of publicly available source code datasets. This means that it excels at popular programming languages like Python and JavaScript, but can also generate specialized code in languages like Prolog, Fortran and Verilog.
"Even as PaLM 2 is more capable, it’s also faster and more efficient than previous models — and it comes in a variety of sizes, which makes it easy to deploy for a wide range of use cases. We’ll be making PaLM 2 available in four sizes from smallest to largest: Gecko, Otter, Bison and Unicorn. Gecko is so lightweight that it can work on mobile devices and is fast enough for great interactive applications on-device, even when offline. This versatility means PaLM 2 can be fine-tuned to support entire classes of products in more ways, to help more people," read the statement.
Powering over 25 Google products and features
At I/O today, we announced over 25 new products and features powered by PaLM 2.
That means that PaLM 2 is bringing the latest in advanced AI capabilities directly into our products and to people — including consumers, developers, and enterprises of all sizes around the world. Here are some examples:
PaLM 2’s improved multilingual capabilities are allowing us to expand Bard to new languages, starting today. Plus, it’s powering our recently announced coding update.
Workspace features to help you write in Gmail and Google Docs, and help you organize in Google Sheets are all tapping into the capabilities of PaLM 2 at a speed that helps people get work done better, and faster.
Med-PaLM 2, trained by our health research teams with medical knowledge, can answer questions and summarize insights from a variety of dense medical texts. It achieves state-of-the-art results in medical competency, and was the first large language model to perform at “expert” level on U.S.
Medical Licensing Exam-style questions. We're now adding multimodal capabilities to synthesize information like x-rays and mammograms to one day improve patient outcomes. Med-PaLM 2 will open up to a small group of Cloud customers for feedback later this summer to identify safe, helpful use cases.
Advancing the future of AI
PaLM 2 shows us the impact of highly capable models of various sizes and speeds — and that versatile AI models reap real benefits for everyone. Yet just as we’re committed to releasing the most helpful and responsible AI tools today, we’re also working to create the best foundation models yet for Google.
Our Brain and DeepMind research teams have achieved many defining moments in AI over the last decade, and we’re bringing together these two world-class teams into a single unit, to continue to accelerate our progress.
Google DeepMind, backed by the computational resources of Google, will not only bring incredible new capabilities to the products you use every day, but responsibly pave the way for the next generation of AI models.
"We’re already at work on Gemini — Our next model created from the ground up to be multimodal, highly efficient at tool and API integrations, and built to enable future innovations, like memory and planning," read the Google website.
Gemini is still in training, but it’s already exhibiting multimodal capabilities never before seen in prior models.
Once fine-tuned and rigorously tested for safety, Gemini will be available at various sizes and capabilities, just like PaLM 2, to ensure it can be deployed across different products, applications, and devices for everyone’s benefit.
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