marktechpost3d
KAIST and DeepAuto AI Researchers Propose InfiniteHiP: A Game-Changing Long-Context LLM Framework for 3M-Token Inference on a Single GPU
In large language models (LLMs), processing extended input sequences demands significant computational and memory resources, leading to slower inference and higher hardware costs. The attention ...
marktechpost3d
This AI Paper from IBM and MIT Introduces SOLOMON: A Neuro-Inspired Reasoning Network for Enhancing LLM Adaptability in Semiconductor Layout Design
Adapting large language models for specialized domains remains challenging, especially in fields requiring spatial reasoning and structured problem-solving, even though they specialize in complex ...
marktechpost4d
How AI Chatbots Mimic Human Behavior: Insights from Multi-Turn Evaluations of LLMs
AI chatbots create the illusion of having emotions, morals, or consciousness by generating natural conversations that seem human-like. Many users engage with AI for chat and companionship, reinforcing ...
marktechpost4d
This AI Paper from Apple Introduces a Distillation Scaling Law: A Compute-Optimal Approach for Training Efficient Language Models
Language models have become increasingly expensive to train and deploy. This has led researchers to explore techniques such as model distillation, where a smaller student model is trained to replicate ...
marktechpost4d
TransMLA: Transforming GQA-based Models Into MLA-based Models
Large Language Models (LLMs) have gained significant importance as productivity tools, with open-source models increasingly matching the performance of their closed-source counterparts. These models ...
marktechpost4d
ReasonFlux: Elevating LLM Reasoning with Hierarchical Template Scaling
Large language models (LLMs) have demonstrated exceptional problem-solving abilities, yet complex reasoning tasks—such as competition-level mathematics or intricate code generation—remain challenging.
marktechpost5d
Microsoft Research Introduces Data Formulator: An AI Application that Leverages LLMs to Transform Data and Create Rich Visualizations
Most modern visualization authoring tools like Charticulator, Data Illustrator, and Lyra, and libraries like ggplot2, and VegaLite expect tidy data, where every variable to be visualized is a column ...
marktechpost5d
ByteDance Introduces UltraMem: A Novel AI Architecture for High-Performance, Resource-Efficient Language Models
Large Language Models (LLMs) have revolutionized natural language processing (NLP) but face significant challenges in practical applications due to their large computational demands. While scaling ...
marktechpost5d
Layer Parallelism: Enhancing LLM Inference Efficiency Through Parallel Execution of Transformer Layers
LLMs have demonstrated exceptional capabilities, but their substantial computational demands pose significant challenges for large-scale deployment. While previous studies indicate that intermediate ...
marktechpost5d
This AI Paper from UC Berkeley Introduces a Data-Efficient Approach to Long Chain-of-Thought Reasoning for Large Language Models
Large language models (LLMs) process extensive datasets to generate coherent outputs, focusing on refining chain-of-thought (CoT) reasoning. This methodology enables models to break down intricate ...
marktechpost6d
Step by Step Guide on How to Build an AI News Summarizer Using Streamlit, Groq and Tavily
In this tutorial, we will build an advanced AI-powered news agent that can search the web for the latest news on a given topic and summarize the results. This agent follows a structured workflow: To ...
marktechpost6d
Can Users Fix AI Bias? Exploring User-Driven Value Alignment in AI Companions
Large language model (LLM)–based AI companions have evolved from simple chatbots into entities that users perceive as friends, partners, or even family members. Yet, despite their human-like ...