Revolutionary Applications of Google’s Gemini in Medical AI

Revolutionary Applications of Google's Gemini in Medical AI

Paper Title: Capabilities of Gemini Models in Medicine Compiled by: Sienna Reviewed by: Los Healthcare is undoubtedly one of the fields that urgently needs disruption and innovation today. It accounts for nearly 10% of the Gross Domestic Product (GDP) on average, and in some specific contexts, such as the United States, this proportion even rises … Read more

Why Gemini Is Considered Stronger Than ChatGPT?

Why Gemini Is Considered Stronger Than ChatGPT?

Years ago, Google created a wave of artificial intelligence (AI) with the stunning performance of AlphaGo. However, in the past year, Google has been under pressure due to the AI wave triggered by OpenAI’s ChatGPT, and they urgently need a phenomenal AI product to prove their strength. Since the release of ChatGPT, people have been … Read more

Generating Impressive Videos from Text Instructions: Overview of Sora, Stable Diffusion, Lumiere, and Similar Models

Generating Impressive Videos from Text Instructions: Overview of Sora, Stable Diffusion, Lumiere, and Similar Models

By: This article is translated from the English paper “Generate Impressive Videos with Text Instructions: A Review of OpenAI Sora, Stable Diffusion, Lumiere and Comparable Models” (KARAARSLAN, Enis; AYDIN, Ömer, 2024) using software, and has not been polished. Errors and omissions are inevitable. For interested readers, it is recommended to read the original paper. In … Read more

Detecting Adversarial Samples Using Influence Functions and Nearest Neighbors

Detecting Adversarial Samples Using Influence Functions and Nearest Neighbors

Reference Cohen G, Sapiro G, Giryes R. Detecting adversarial samples using influence functions and nearest neighbors[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2020: 14453-14462. Abstract Deep neural networks are notorious for being vulnerable to adversarial attacks, which involve adding small perturbations to input images to mislead their predictions. Therefore, detecting adversarial … Read more

Novel Graph Neural Network Framework for Single-Cell RNA-Seq

Novel Graph Neural Network Framework for Single-Cell RNA-Seq

Single-cell RNA sequencing (scRNA-seq) technology enables gene expression detection across the transcriptome within individual cells, which can be used to study somatic clonal structures and characterize cellular heterogeneity in complex diseases. However, the data from scRNA-seq analysis are characterized by complexity, uncertain distributions, large data volumes, and high missing rates, making scRNA-seq analysis for biological … Read more

Improving Chinese Text Classification Algorithm Using Word Vectors and kNN

Improving Chinese Text Classification Algorithm Using Word Vectors and kNN

Ding Zhengsheng, Ma Chunjie (Xi’an University of Science and Technology, Shanxi Xi’an 710600) Abstract: In order to improve the efficiency and accuracy of Chinese text classification, a Chinese text classification algorithm based on deep learning is established in response to the characteristics of Chinese characters and the dramatic increase in data volume in the big … Read more

Machine Learning: From Priors to Automation

Machine Learning: From Priors to Automation

This article discusses five major prior assumptions and how to overcome these limitations to further enhance the effectiveness of machine learning. Based on this, we propose the concept of machine learning automation and the SLeM framework. SLeM provides a formalized, modeled, and scientific research framework and approach for machine learning automation. Existing applications indicate that … Read more

Understanding AI, Machine Learning, and Deep Learning Concepts

Understanding AI, Machine Learning, and Deep Learning Concepts

Introduction:In today’s information age, the concepts of artificial intelligence, machine learning, and deep learning are no longer as lofty as they were over a decade ago. They have gradually permeated various aspects of our lives, and we understand and use them. For example, the “Siri” voice assistant on iOS devices is a typical representation of … Read more

What Are the Differences Between Machine Learning and Deep Learning?

What Are the Differences Between Machine Learning and Deep Learning?

Deep learning has become particularly popular in recent years, much like big data did five years ago. However, deep learning primarily falls within the field of machine learning. In this article, we will discuss the differences in algorithm processes between machine learning and deep learning. The Algorithm Processes of Machine Learning and Deep Learning I … Read more

Introduction to Artificial Intelligence, Machine Learning, and Deep Learning

Introduction to Artificial Intelligence, Machine Learning, and Deep Learning

Artificial Intelligence Machine Learning Deep Learning Introduction For beginners, it can be difficult to distinguish between artificial intelligence (AI), machine learning (ML), and deep learning (DL) when first encountering them, as well as to understand their connections, concepts, and what they can do. 1 Concepts and Definitions In simple terms, artificial intelligence is about making … Read more