Remove briefing translational-research
article thumbnail

PaLM 2 vs. Llama 2: The next evolution of language models

Data Science Dojo

From virtual assistants like Siri and Alexa to personalized recommendations on streaming platforms, chatbots, and language translation services, language models surely are the engines that power it all. This feature greatly enables fostering global communication and collaboration.

article thumbnail

LLM Use-Cases: Top 10 industries that can benefit from using large language models

Data Science Dojo

A large language model, abbreviated as LLM, represents a deep learning algorithm with the capability to identify, condense, translate, forecast, and generate text as well as various other types of content. Legal research: LLMs can be used to search and analyze legal documents, such as case law, statutes, and regulations.

professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

How to streamline and enhance critical F&A functions with generative AI

IBM Journey to AI blog

” Moreover, some Large Language Models (LLMs) can already research and summarize, translate and interpret, generate and create, comprehend and report, converse and engage based on the knowledge gained from massive datasets used by F&A.

AI 55
article thumbnail

Conker AI creates quizzes for your selected topic

Dataconomy

This user-friendliness translates to valuable time-saving for teachers, allowing them to divert their focus more towards teaching and less on cumbersome quiz preparation. While there’s a brief waiting period as the AI crafts your quiz, the time saved in research and quiz assembly is significant. What is Conker AI?

AI 188
article thumbnail

Addressing the Challenges in Multilingual Prompt Engineering

Heartbeat

Effective multilingual prompt engineering not only improves the accessibility of AI technologies but also offers a wide range of applications, ranging from automated translation and cross-cultural dialogue to global information retrieval and language-specific content development. This can be useful for languages with limited data.

article thumbnail

Working of Encoder-Decoder model

Mlearning.ai

Sequence models have gained traction in the past 5 years and it’s been very active research of study, even the GPT models — on which ChatGPT was implemented using the concept of Transformers and BERT , which is based on Self-Attention model — it is based on Attention models — which uses the base of Encoder-Decoder sequence models.

article thumbnail

Getting Started with AI

Towards AI

Classify, predict, detect, translate, etc. Hosni, “ Brief Guide for Machine Learning Model Selection,” MLearning.ai, Dec. From research to projects and ideas. MIT Overview of AI and ML Source: Toward Data Science Project Definition The first step in AI projects is to define the problem. 12, 2014. [3] 16, 2020. [4] 12, 2021. [6]