Remove Computer Vision Remove Data Scarcity Remove NLP
article thumbnail

Computer Vision in Robotics – An Autonomous Revolution

Viso.ai

One of the computer vision applications we are most excited about is the field of robotics. By marrying the disciplines of computer vision, natural language processing, mechanics, and physics, we are bound to see a frameshift change in the way we interact with, and are assisted by robot technology.

article thumbnail

Computer Vision in Robotics – An Autonomous Revolution

Viso.ai

One of the computer vision applications we are most excited about is the field of robotics. By marrying the disciplines of computer vision, natural language processing, mechanics, and physics, we are bound to see a frameshift change in the way we interact with, and are assisted by robot technology.

professionals

Sign Up for our Newsletter

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

article thumbnail

Meet AnomalyGPT: A Novel IAD Approach Based on Large Vision-Language Models (LVLM) to Detect Industrial Anomalies

Marktechpost

On various Natural Language Processing (NLP) tasks, Large Language Models (LLMs) such as GPT-3.5 They optimize the LVLM using synthesized anomalous visual-textual data and incorporating IAD expertise. Direct training using IAD data, however, needs to be improved. Data scarcity is the first.

article thumbnail

Achieving accurate image segmentation with limited data: strategies and techniques

deepsense.ai

SegGPT Many successful approaches from NLP are now being translated into computer vision. For instance, the analogy of the masked token prediction task used to train BERT is known as masked image modeling in computer vision. Comparison of few-shot inference between NLP and CV. Source: own study.

article thumbnail

Award-Winning Breakthroughs at NeurIPS 2023: A Focus on Language Model Innovations

Topbots

A key finding is that for a fixed compute budget, training with up to four epochs of repeated data shows negligible differences in loss compared to training with unique data. However, beyond four epochs, the additional computational investment yields diminishing returns.

article thumbnail

Zero-Shot Learning: Unlocking the Power of AI Without Training Data

Pickl AI

By leveraging auxiliary information such as semantic attributes, ZSL enhances scalability, reduces data dependency, and improves generalisation. This innovative approach is transforming applications in computer vision, Natural Language Processing, healthcare, and more.

article thumbnail

How Fastweb fine-tuned the Mistral model using Amazon SageMaker HyperPod as a first step to build an Italian large language model

AWS Machine Learning Blog

Overcoming data scarcity with translation and synthetic data generation When fine-tuning a custom version of the Mistral 7B LLM for the Italian language, Fastweb faced a major obstacle: high-quality Italian datasets were extremely limited or unavailable. In his free time, Giuseppe enjoys playing football.