NAVER Cloud Researchers Introduce HyperCLOVA X: A Multilingual Language Model Tailored to Korean Language and Culture

LexC-Gen, a method proposed by researchers at Brown University, addresses data scarcity in low-resource languages using bilingual lexicons and large language models (LLMs). It generates labeled task data for low-resource languages by leveraging LLMs and bilingual…

Advancements in large language models (LLMs) have made interactive conversational AI in healthcare possible. Google DeepMind developed AMIE, an AI system designed to take medical histories and engage in diagnostic discussions, which outperformed primary care physicians…

Practical Solutions for Language Model Outputs Challenges in Language Model Outputs Language models often produce unstructured and inconsistent outputs, posing challenges in real-world applications. Extracting specific information, integrating with systems, and presenting data in preferred formats…

The Anticipatory Music Transformer, developed by Stanford scholars, empowers composers with unique control over generative AI music composition. Differentiating itself from other tools, it focuses on symbolic music and incorporates users’ preferences. Integrated with the GPT…

The YAYI2-30B model is a pioneering solution tailored for Chinese applications, aiming to overcome limitations in existing large language models like MPT-30B, Falcon-40B, and LLaMA 2-34B. It adopts a unique decoder-only design with FlashAttention 2 and…

Nvidia and Foxconn are joining forces to build “AI factories” that will accelerate the production of autonomous electric vehicles (EVs). Foxconn, known for manufacturing Apple’s iPhone, aims to capture 5% of the EV manufacturing market by…

Accelerating Generative AI Inference Speed with NVIDIA TensorRT Model Optimizer Generative AI, while powerful, faces challenges with slow inference speed in real-world applications. This impacts user experiences, turnaround times, and scalability. NVIDIA addresses these challenges with…

Practical Solutions and Value of HELP (Hierarchical Embeddings-based Log Parser) Challenges in Log Parsing Technology Logs are crucial for system maintenance and failure diagnostics, but traditional log parsing techniques face obstacles, leading to performance issues. Practical…

A team of researchers is developing an electronic tongue that mimics how taste affects our food choices, potentially offering a blueprint for AI that processes information like humans. However, AI is not yet capable of getting…

AltUp is a novel method that addresses the challenge of scaling up token representation in Transformer neural networks without increasing computational complexity. It partitions the representation vector into blocks and processes one block at each layer,…

Maximize Web Data Extraction with Reworkd AI Collecting, monitoring, and maintaining web data can be challenging, especially with large amounts of data. Traditional approaches struggle with pagination, dynamic content, bot detection, and site modifications, compromising data…

deepsense.ai has partnered with LangChain, a framework that simplifies the development of Large Language Models (LLMs) applications. The partnership allows deepsense.ai to provide support and contribute to the LangChain community. Additionally, deepsense.ai gains exclusive access to…

Understanding Tensor Product Attention (TPA) Large language models (LLMs) are essential in natural language processing (NLP), excelling in generating and understanding text. However, they struggle with long input sequences due to memory challenges, especially during inference.…

Google has introduced a new grammar correction feature in its search engine called EdiT5. This feature addresses the challenges of complex grammatical error correction by using a text editing approach. It reduces latency by minimizing decoding…

NVIDIA has introduced the HELPSTEER dataset, a collection of annotated responses that influence helpfulness in language models. The dataset covers qualities such as accuracy, coherence, complexity, verbosity, and overall helpfulness. Researchers used the dataset to train…

Understanding the Importance of AI Safety The field of Artificial Intelligence (AI) is progressing quickly, especially with Large Language Models (LLMs) becoming essential in AI applications. These models come with built-in safety features to prevent unethical…