Table of Contents
Machine Learning and Artificial Intelligence
Artificial Intelligence in B2B Retail: Benefits and Risks
Home Technology peripherals AI The advantages of artificial intelligence in B2B retail

The advantages of artificial intelligence in B2B retail

Aug 20, 2023 pm 06:53 PM
AI

The advantages of artificial intelligence in B2B retail

Machine Learning and Artificial Intelligence

(AI) vs. Customer Centricity The integration of big data has revolutionized various industries, including retail. The COVID-19 pandemic has accelerated the adoption of digitalization and AI, forcing policymakers to seriously consider responsible AI use while protecting consumers and ensuring fair markets. Data-centric AI is a revolutionary shift from model- and code-centric approaches, with a greater focus on leveraging data to enhance AI systems. It involves leveraging solutions such as AI-specific data management, synthetic data and data labeling technologies to address various data challenges, including accessibility, capacity, privacy, security, complexity and scope. There is a growing trend to use generative AI to create synthetic data, reducing the need for real-world data to effectively train machine learning models. According to Gartner forecasts, by 2024, 60% of data used for artificial intelligence will be synthetic, enabling simulations of real-world and future scenarios while significantly reducing the risks of artificial intelligence, a significant increase from 1% in 2021 Growth

Artificial Intelligence in B2B Retail: Benefits and Risks

The retail industry is undergoing a profound transformation caused by the convergence of artificial intelligence

With the help of abundant big data and affordable computing power, artificial intelligence and machine learning models can identify complex patterns and relationships that exceed human capabilities. In the B2B retail industry, the application of artificial intelligence streamlines operational workflows, enhances risk management, and improves the overall customer experience. Through natural language generation (NLG), data analysis becomes simpler for retailers, enabling smarter decisions. However, deploying artificial intelligence in retail also brings some challenges. This can lead to biased decision-making and data quality issues, resulting in potentially discriminatory results and inaccurate predictions. Policymakers are therefore actively engaged in discussions to ensure the responsible use of AI to promote transparency, fairness and consumer protection

AI Research and Startup Investment

The retail industry is increasingly recognizing the potential of AI, which is reflected in interest in AI research and investment in startups. Startups are developing advanced AI solutions that disrupt traditional retail practices, and their success relies primarily on integrating customer-centric big data and developing powerful and accurate AI algorithms

Regulatory Technology Artificial Intelligence in

Through the use of artificial intelligence technology, regulatory and supervisory technology (RegTech and SupTech) can improve efficiency and gain a more comprehensive understanding of risk and compliance developments, by analyzing large amounts of regulatory data and quickly identifying Potential risks and ensuring compliance with regulatory standards, enabling retailers to effectively navigate the complex regulatory environment

The power of customer-centric big data in B2B retail returns automation

Leveraging customer-centric big data and artificial intelligence, the B2B retail returns automation platform is able to analyze transaction details, customer behavior, feedback and preferences, and achieve this by optimizing operational efficiency and improving customer satisfaction. These platforms integrate AI systems with varying degrees of autonomy and are able to create personalized returns policies to increase customer loyalty and prevent returns fraud

Potential benefits of adopting AI in B2B retail and Risk

By applying artificial intelligence technology in the B2B retail field, many potential benefits can be realized, including improved operational efficiency, enhanced customer experience, and more accurate decision-making. However, to ensure that all players in the retail industry operate on a level playing field, concerns arising from potential concentration of power and data quality issues among large companies must be addressed

Based on Artificial Intelligence And blockchain-based retail products

The integration of artificial intelligence and blockchain-based retail products brings new possibilities for improving efficiency and transparency. In blockchain systems, the use of artificial intelligence applications enhances the automation of risk management, governance, and smart contracts. However, concerns have been expressed about the autonomy, governance and ethical issues raised by the application of artificial intelligence in self-regulating smart contracts and decentralized retail

Conclusion

In various industries, the integration of customer-first big data and artificial intelligence has brought about huge changes

In the B2B retail field, the use of returns automation platforms can achieve personalized solutions through artificial intelligence, improve efficiency and increase customer satisfaction. While the application of artificial intelligence presents exciting opportunities, policymakers and industry stakeholders need to work together to address potential risks and challenges. The key is to leverage customer-centric big data, artificial intelligence and machine learning to optimize operational efficiency and customer satisfaction while ensuring responsible and ethical AI deployment in the B2B retail space

The above is the detailed content of The advantages of artificial intelligence in B2B retail. For more information, please follow other related articles on the PHP Chinese website!

Statement of this Website
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

AI Hentai Generator

AI Hentai Generator

Generate AI Hentai for free.

Hot Article

R.E.P.O. Energy Crystals Explained and What They Do (Yellow Crystal)
4 weeks ago By 尊渡假赌尊渡假赌尊渡假赌
R.E.P.O. Best Graphic Settings
4 weeks ago By 尊渡假赌尊渡假赌尊渡假赌
R.E.P.O. How to Fix Audio if You Can't Hear Anyone
4 weeks ago By 尊渡假赌尊渡假赌尊渡假赌
WWE 2K25: How To Unlock Everything In MyRise
1 months ago By 尊渡假赌尊渡假赌尊渡假赌

Hot Tools

Notepad++7.3.1

Notepad++7.3.1

Easy-to-use and free code editor

SublimeText3 Chinese version

SublimeText3 Chinese version

Chinese version, very easy to use

Zend Studio 13.0.1

Zend Studio 13.0.1

Powerful PHP integrated development environment

Dreamweaver CS6

Dreamweaver CS6

Visual web development tools

SublimeText3 Mac version

SublimeText3 Mac version

God-level code editing software (SublimeText3)

Bytedance Cutting launches SVIP super membership: 499 yuan for continuous annual subscription, providing a variety of AI functions Bytedance Cutting launches SVIP super membership: 499 yuan for continuous annual subscription, providing a variety of AI functions Jun 28, 2024 am 03:51 AM

This site reported on June 27 that Jianying is a video editing software developed by FaceMeng Technology, a subsidiary of ByteDance. It relies on the Douyin platform and basically produces short video content for users of the platform. It is compatible with iOS, Android, and Windows. , MacOS and other operating systems. Jianying officially announced the upgrade of its membership system and launched a new SVIP, which includes a variety of AI black technologies, such as intelligent translation, intelligent highlighting, intelligent packaging, digital human synthesis, etc. In terms of price, the monthly fee for clipping SVIP is 79 yuan, the annual fee is 599 yuan (note on this site: equivalent to 49.9 yuan per month), the continuous monthly subscription is 59 yuan per month, and the continuous annual subscription is 499 yuan per year (equivalent to 41.6 yuan per month) . In addition, the cut official also stated that in order to improve the user experience, those who have subscribed to the original VIP

Context-augmented AI coding assistant using Rag and Sem-Rag Context-augmented AI coding assistant using Rag and Sem-Rag Jun 10, 2024 am 11:08 AM

Improve developer productivity, efficiency, and accuracy by incorporating retrieval-enhanced generation and semantic memory into AI coding assistants. Translated from EnhancingAICodingAssistantswithContextUsingRAGandSEM-RAG, author JanakiramMSV. While basic AI programming assistants are naturally helpful, they often fail to provide the most relevant and correct code suggestions because they rely on a general understanding of the software language and the most common patterns of writing software. The code generated by these coding assistants is suitable for solving the problems they are responsible for solving, but often does not conform to the coding standards, conventions and styles of the individual teams. This often results in suggestions that need to be modified or refined in order for the code to be accepted into the application

Can fine-tuning really allow LLM to learn new things: introducing new knowledge may make the model produce more hallucinations Can fine-tuning really allow LLM to learn new things: introducing new knowledge may make the model produce more hallucinations Jun 11, 2024 pm 03:57 PM

Large Language Models (LLMs) are trained on huge text databases, where they acquire large amounts of real-world knowledge. This knowledge is embedded into their parameters and can then be used when needed. The knowledge of these models is "reified" at the end of training. At the end of pre-training, the model actually stops learning. Align or fine-tune the model to learn how to leverage this knowledge and respond more naturally to user questions. But sometimes model knowledge is not enough, and although the model can access external content through RAG, it is considered beneficial to adapt the model to new domains through fine-tuning. This fine-tuning is performed using input from human annotators or other LLM creations, where the model encounters additional real-world knowledge and integrates it

Seven Cool GenAI & LLM Technical Interview Questions Seven Cool GenAI & LLM Technical Interview Questions Jun 07, 2024 am 10:06 AM

To learn more about AIGC, please visit: 51CTOAI.x Community https://www.51cto.com/aigc/Translator|Jingyan Reviewer|Chonglou is different from the traditional question bank that can be seen everywhere on the Internet. These questions It requires thinking outside the box. Large Language Models (LLMs) are increasingly important in the fields of data science, generative artificial intelligence (GenAI), and artificial intelligence. These complex algorithms enhance human skills and drive efficiency and innovation in many industries, becoming the key for companies to remain competitive. LLM has a wide range of applications. It can be used in fields such as natural language processing, text generation, speech recognition and recommendation systems. By learning from large amounts of data, LLM is able to generate text

To provide a new scientific and complex question answering benchmark and evaluation system for large models, UNSW, Argonne, University of Chicago and other institutions jointly launched the SciQAG framework To provide a new scientific and complex question answering benchmark and evaluation system for large models, UNSW, Argonne, University of Chicago and other institutions jointly launched the SciQAG framework Jul 25, 2024 am 06:42 AM

Editor |ScienceAI Question Answering (QA) data set plays a vital role in promoting natural language processing (NLP) research. High-quality QA data sets can not only be used to fine-tune models, but also effectively evaluate the capabilities of large language models (LLM), especially the ability to understand and reason about scientific knowledge. Although there are currently many scientific QA data sets covering medicine, chemistry, biology and other fields, these data sets still have some shortcomings. First, the data form is relatively simple, most of which are multiple-choice questions. They are easy to evaluate, but limit the model's answer selection range and cannot fully test the model's ability to answer scientific questions. In contrast, open-ended Q&A

Five schools of machine learning you don't know about Five schools of machine learning you don't know about Jun 05, 2024 pm 08:51 PM

Machine learning is an important branch of artificial intelligence that gives computers the ability to learn from data and improve their capabilities without being explicitly programmed. Machine learning has a wide range of applications in various fields, from image recognition and natural language processing to recommendation systems and fraud detection, and it is changing the way we live. There are many different methods and theories in the field of machine learning, among which the five most influential methods are called the "Five Schools of Machine Learning". The five major schools are the symbolic school, the connectionist school, the evolutionary school, the Bayesian school and the analogy school. 1. Symbolism, also known as symbolism, emphasizes the use of symbols for logical reasoning and expression of knowledge. This school of thought believes that learning is a process of reverse deduction, through existing

SOTA performance, Xiamen multi-modal protein-ligand affinity prediction AI method, combines molecular surface information for the first time SOTA performance, Xiamen multi-modal protein-ligand affinity prediction AI method, combines molecular surface information for the first time Jul 17, 2024 pm 06:37 PM

Editor | KX In the field of drug research and development, accurately and effectively predicting the binding affinity of proteins and ligands is crucial for drug screening and optimization. However, current studies do not take into account the important role of molecular surface information in protein-ligand interactions. Based on this, researchers from Xiamen University proposed a novel multi-modal feature extraction (MFE) framework, which for the first time combines information on protein surface, 3D structure and sequence, and uses a cross-attention mechanism to compare different modalities. feature alignment. Experimental results demonstrate that this method achieves state-of-the-art performance in predicting protein-ligand binding affinities. Furthermore, ablation studies demonstrate the effectiveness and necessity of protein surface information and multimodal feature alignment within this framework. Related research begins with "S

Laying out markets such as AI, GlobalFoundries acquires Tagore Technology's gallium nitride technology and related teams Laying out markets such as AI, GlobalFoundries acquires Tagore Technology's gallium nitride technology and related teams Jul 15, 2024 pm 12:21 PM

According to news from this website on July 5, GlobalFoundries issued a press release on July 1 this year, announcing the acquisition of Tagore Technology’s power gallium nitride (GaN) technology and intellectual property portfolio, hoping to expand its market share in automobiles and the Internet of Things. and artificial intelligence data center application areas to explore higher efficiency and better performance. As technologies such as generative AI continue to develop in the digital world, gallium nitride (GaN) has become a key solution for sustainable and efficient power management, especially in data centers. This website quoted the official announcement that during this acquisition, Tagore Technology’s engineering team will join GLOBALFOUNDRIES to further develop gallium nitride technology. G

See all articles