Remove Auto-complete Remove BERT Remove Large Language Models
article thumbnail

Evaluate large language models for your machine translation tasks on AWS

AWS Machine Learning Blog

Large language models (LLMs) have demonstrated promising capabilities in machine translation (MT) tasks. Depending on the use case, they are able to compete with neural translation models such as Amazon Translate. When the indexing is complete, select the created index from the index dropdown.

article thumbnail

Best Large Language Models & Frameworks of 2023

AssemblyAI

However, among all the modern-day AI innovations, one breakthrough has the potential to make the most impact: large language models (LLMs). Large language models can be an intimidating topic to explore, especially if you don't have the right foundational understanding. What Is a Large Language Model?

professionals

Sign Up for our Newsletter

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

article thumbnail

Researchers from Fudan University and Shanghai AI Lab Introduces DOLPHIN: A Closed-Loop Framework for Automating Scientific Research with Iterative Feedback

Marktechpost

Researchers want to create a system that eventually learns to bypass humans completely by completing the research cycle without human involvement. Fudan University and the Shanghai Artificial Intelligence Laboratory have developed DOLPHIN, a closed-loop auto-research framework covering the entire scientific research process.

article thumbnail

Beyond ChatGPT; AI Agent: A New World of Workers

Unite.AI

Transformers and Advanced NLP Models : The introduction of transformer architectures revolutionized the NLP landscape. Systems like ChatGPT by OpenAI, BERT, and T5 have enabled breakthroughs in human-AI communication. AI Agents vs. ChatGPT Many advanced AI agents, such as Auto-GPT and BabyAGI, utilize the GPT architecture.

article thumbnail

TensorRT-LLM: A Comprehensive Guide to Optimizing Large Language Model Inference for Maximum Performance

Unite.AI

As the demand for large language models (LLMs) continues to rise, ensuring fast, efficient, and scalable inference has become more crucial than ever. Kernel Auto-tuning : TensorRT automatically selects the best kernel for each operation, optimizing inference for a given GPU. build/tensorrt_llm*.whl

article thumbnail

Making Sense of the Mess: LLMs Role in Unstructured Data Extraction

Unite.AI

Unlocking Unstructured Data with LLMs Leveraging large language models (LLMs) for unstructured data extraction is a compelling solution with distinct advantages that address critical challenges. Context-Aware Data Extraction LLMs possess strong contextual understanding, honed through extensive training on large datasets.

article thumbnail

This AI Paper by Microsoft and Tsinghua University Introduces YOCO: A Decoder-Decoder Architectures for Language Models

Marktechpost

This field primarily enhances machine understanding and generation of human language, serving as a backbone for various applications such as text summarization, translation, and auto-completion systems. Efficient language modeling faces significant hurdles, particularly with large models.