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How to Implement ChatGPT with OpenAI API in Python Synchronously and Asynchronously | by Lynn G. Kwong | Mar, 2024

Learn to use AI to boost the efficiency of your business Image by geralt on PixabaySince the advent of ChatGPT, it has brought tremendous shock to human society. Especially for us developers, our lives have been reshaped dramatically because of it. ChatGPT can answer all kinds of technical and non-technical questions correctly, accurately, and efficiently.…

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Meet CoLLaVO: KAIST’s AI Breakthrough in Vision Language Models Enhancing Object-Level Image Understanding

The evolution of Vision Language Models (VLMs) towards general-purpose models relies on their ability to understand images and perform tasks via natural language instructions. However, it must be clarified if current VLMs truly grasp detailed object information in images. The analysis shows that their image understanding correlates strongly with zero-shot performance on vision language tasks.…

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This AI Research from Google DeepMind Unlocks New Potentials in Robotics: Enhancing Human-Robot Collaboration through Fine-Tuned Language Models with Language Model Predictive Control

In robotics, natural language is an accessible interface for guiding robots, potentially empowering individuals with limited training to direct behaviors, express preferences, and offer feedback. Recent studies have underscored the inherent capabilities of large language models (LLMs), pre-trained on extensive internet data, in addressing various robotics tasks. These tasks range from devising action sequences based…

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Leveraging Large Language Models for Business Efficiency | by Benoît Courty | Mar, 2024

In the rapidly evolving landscape of technology, Artificial Intelligence (AI) and Machine Learning (ML) have emerged as pivotal forces driving innovation, efficiency, and competitive advantage across industries. For Chief Technology Officers, IT Directors, Tech Project Managers, and Tech Product Managers, understanding and integrating these technologies into business strategies is no longer optional; it’s imperative. It’s…

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Apple Researchers Propose MAD-Bench Benchmark to Overcome Hallucinations and Deceptive Prompts in Multimodal Large Language Models

Multimodal Large Language Models (MLLMs), having contributed to remarkable progress in AI, face challenges in accurately processing and responding to misleading information, leading to incorrect or hallucinated responses. This vulnerability raises concerns about the reliability of MLLMs in applications where accurate interpretation of text and visual data is crucial. Recent research has explored visual instruction…

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