Table of Contents
IoT and 5G will change visibility
Artificial Intelligence and Machine Learning Will Optimize Performance
Next-generation technologies will future-proof the industry
Home Technology peripherals AI How artificial intelligence technology will change the future of supply chains

How artificial intelligence technology will change the future of supply chains

Apr 07, 2023 pm 05:01 PM
AI supply chain

How artificial intelligence technology will change the future of supply chains

Technology is always disrupting and improving the way we manage supply chains—from new wheeled carts strapped to camels on the ancient Silk Road, to today’s ultra-accurate retail replenishment demand forecasting powered by artificial intelligence.

But while these developments continue to push society forward, they are not always welcomed initially. Take barcodes for example.

When bar codes first came into commercial use, skeptical manufacturers had to be convinced to print them on products and hesitant supermarkets to buy scanners. But within a few years, barcoding was widely recognized as transforming the efficiency and accuracy of the entire retail lifecycle.

As business leaders, we must always overcome initial reluctance and take advantage of transformative new technologies. Supply chains that can adapt to external changes, from geopolitics to the environment, are a major competitive advantage in today's volatile economic environment. So, which new technologies can increase speed, support reliability, and increase the resiliency of businesses like yours? Let’s take a look.

IoT and 5G will change visibility

The COVID-19 pandemic has caused an economic slowdown, but now that the worst may be behind us, IoT and 5G can advance if not prioritized Consider the level they would have been at given the pandemic.

The benefits of 5G technology are obvious. It’s 1,000 times faster than 4G and can handle 10,000 times more traffic. It also reduces latency from 10 milliseconds to less than 1 millisecond and increases device connectivity from 100,000 to 1 million devices per square kilometer. Simply put, it facilitates an explosion in the number of devices and applications that can be interconnected simultaneously.

For supply chains, this enables unprecedented levels of speed and responsiveness when tracking the movement of goods around the world. Low-cost 5G chips can collect and analyze supply chain data in real time. 5G-enabled IoT sensors can then be placed at different points along the supply chain, allowing managers to remotely monitor product location, labeling and status and immediately begin planning workarounds if delays or disruptions occur.

5G will also help organizations optimize their operations and minimize inefficiencies, such as using geolocation technology to avoid traffic congestion. By combining 5G with IoT, organizations can ensure that products reach warehouses and shelves at the right time and in the perfect quantity.

Artificial Intelligence and Machine Learning Will Optimize Performance

Another area of ​​technology that promises to revolutionize supply chain management is artificial intelligence (AI) and its subset of machine learning (ML). Remember, it’s important to note the subtle difference between AI and ML: AI enables computer systems to “think” for themselves using mathematics and logic and perform tasks autonomously. At the same time, ML allows the system to “learn” and improve its output based on its experience.

Machine learning-driven supply chains allow organizations to automatically improve their forecasts of product demand over time. This not only improves the accuracy of inventory and inventory forecasts to prevent the “bullwhip effect,” but also opens up new retail opportunities, such as dynamic pricing. Additionally, data models can highlight anomalies in product demand and automatically set up control mechanisms, such as customer purchase limits and additional inventory ordering.

At the same time, with the help of artificial intelligence, menial back-end tasks such as document processing and order picking can be automated, allowing employees to take on more impactful and fulfilling work. AI can also help managers evaluate supplier performance, from pricing to reliability, to further reduce disruptions and strengthen supply chains.

These are not just speculative breakthroughs, either. Research from McKinsey shows that early adopters of AI and machine learning have seen huge success, with “an average improvement in logistics costs of 15%, inventory levels by 35%, and service levels by 65%.”

As costs rise and disruptions escalate, business leaders should strive to leverage the benefits of AI-driven supply chains to prevent faster-moving competitors from getting too far ahead.

Next-generation technologies will future-proof the industry

While supply chains need to become faster, safer, and more resilient, supply chains that are truly future-proof must also be sustainable. As we move towards a net-zero society, greener supply chains will be highly sought after – not least because they can avoid fluctuations in fossil fuel prices and availability, and attract eco-conscious customers, investors and employees.

Luckily, governments are starting to take notice and provide substantial incentives for environmentally friendly purchasing and distribution. The United States recently passed a sweeping energy bill that will invest approximately $370 billion over the next decade in a variety of low-carbon energy technologies. Research already shows the legislation could help significantly reduce U.S. emissions and achieve net-zero goals.

At the same time, the Russo-Ukrainian war and its impact on the flow of oil and gas to Europe may lead countries on the continent to follow the United States and invest heavily in sustainable energy.

Quadrupling renewable energy generation and building electricity infrastructure could save the EU more than $1 trillion by 2035, with additional benefits for climate, health and energy security, research shows. Similarly, the UK’s energy security strategy sets out how the country will use renewable energy to ensure that up to 95% of electricity is low carbon by 2030.

Currently, the cost per watt of electricity obtained from solar and wind energy is comparable to that of fossil fuels. But if green energy investments succeed, we could see independence from fossil fuels, revolutionizing sourcing, operations and excessive waste in supply chains.

Meanwhile, other emerging technologies are giving us glimpses of incredible futures. Ten years from now, will AI even be able to engineer living organisms? A research team of roboticists and scientists has shown that it's certainly possible. Innovation is always just around the corner, and it’s our responsibility to be ready for whatever technology may come next to our supply chains, businesses, and lives.

The above is the detailed content of How artificial intelligence technology will change the future of supply chains. 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

Video Face Swap

Video Face Swap

Swap faces in any video effortlessly with our completely free AI face swap tool!

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

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

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

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

SK Hynix will display new AI-related products on August 6: 12-layer HBM3E, 321-high NAND, etc. SK Hynix will display new AI-related products on August 6: 12-layer HBM3E, 321-high NAND, etc. Aug 01, 2024 pm 09:40 PM

According to news from this site on August 1, SK Hynix released a blog post today (August 1), announcing that it will attend the Global Semiconductor Memory Summit FMS2024 to be held in Santa Clara, California, USA from August 6 to 8, showcasing many new technologies. generation product. Introduction to the Future Memory and Storage Summit (FutureMemoryandStorage), formerly the Flash Memory Summit (FlashMemorySummit) mainly for NAND suppliers, in the context of increasing attention to artificial intelligence technology, this year was renamed the Future Memory and Storage Summit (FutureMemoryandStorage) to invite DRAM and storage vendors and many more players. New product SK hynix launched last year

See all articles