#Artificial Intelligence In Logistics

[medicaldevicesindustrynews]

Germany was the Leader of Smart Shipping Container Market

The smart shipping container market will grow at a compound annual growth rate of 18.4% in the years to come, to touch a value of USD 15,341.5 million by 2030. The development of the industry can be chiefly credited to the guideline of temperature, recover security, and instantaneous GPS tracking, which these containers allow. The sensors combined into gathering and tracking data on the…

[arvistchicago]

AI and Analytics: Optimizing the Supply Chain

AI and Analytics: Optimizing the Supply Chain

Artificial intelligence and data analysis are already taking off. While many industries still struggle to recover from the effects of the pandemic, there are some industries who have embraced these technologies on a large-scale. Know more about supply chain ai software at arvist

The supply chain industry is one of them. Statista data shows that AI solutions have improved inventory management, smart manufacturing and dynamic logistic systems.

AI is primarily used to improve efficiency and productivity in the supply chain. The introduction of AI to supply chain management has resulted in more sustainability. This makes every company wonder if digitalization at this scale will benefit their supply chain business.

McKinsey conducted a recent study that determined the implementation of AI enabled supply-chain management led to significant improvements. Adopters of this technology saw a 15% decrease in logistics costs, 35% in inventory, and a 65% increase in service. This shows the power of AI-enabled Supply-Chain Management to revolutionize an industry and its importance for the modern business landscape.

Let's look at the impact of AI on the supply chain. We will also look at the impact of integrating AI services into your enterprise on your workforce, machines and software.

Artificial Intelligence in supply chain management: Data analytics and modern supply chains

AI and/or Analytics in Supply Chain refers to a process whereby smart machines can solve problems. The IIoT (Industrial Internet of Things) can automate the smart manufacturing process, which will drive the supply chain. AI-driven supply chain operations are aimed at making the supply chain more efficient.

Instrumented

Machine-generated data streaming out of IoT devices

Intelligent -

Data analytics and modeling can help you make more accurate and reliable assumptions

The Interconnected System -

Connectivity for better decisions

Supply chain data analysis can optimize workflows where large data sets are used to identify inefficiencies, forecast and drive innovation. You can use four types of supply chain analysis to make data-driven business decisions.

Here are a few examples of supply chain analytics:

1. Predictive Analytics

Predictive Analytics is a technique which uses statistical modeling and regression to understand and identify trends in historical data to make predictions for future trends.

It helps companies in the supply chain predict future outcomes and their business implications. Predictive analytics can be used to reduce risks and disruptions.

2. Descriptive Analysis

Data mining is a type of descriptive analytics that uses large datasets for the purpose of identifying patterns and generating summaries to help users gain an understanding of a situation. This type of analysis uses historical data to identify trends and make conclusions that can help inform decision making.

You can also use descriptive analysis to help you better understand analytics in the supply chain. This provides visibility and certainty for all types of internal and external information across the supply management.

3. Prescriptive Analysis

Prescriptive analysis is a powerful tool that can be used to explore how changes in the supply chain will impact outcomes. This allows for the identification of potential improvements and recommendations, which is a great resource to optimize supply chain operations.

It is important to work with logistics partners in order to maximize business value. SRM (Supplier Relationship Management) is a popular analytic method that uses a prescriptive approach.

4. Cognitive analytics is the best way to learn advanced analytics for supply chain management. It is most effective in improving customer relationships and experience. The data collected by AI-driven systems are analyzed, and then used to create dashboards and reports that answer complex questions.

Supply chain analytics is a powerful tool that can help your business pursue new ideas and meet customer needs.

[probablyasocialecologist]

The supply chain capitalism of AI. This image partially captures the supply chain of AI as a global and complex phenomenon. Natural resources, components and materials to build AI infrastructure are extracted, shipped, manufactured and produced across the globe. For instance, NVIDIA obtains tungsten from Brazil; gold from Colombia and tantalum from Kazakhstan. Minerals are assembled to manufacture GPUs by TSMC. NVIDIA sells GPUs across data centres in the world. Given the refresh rates of these materials, data centres sent their components to recycle plants or dumps. The human labour wrapped-up in this chain includes, data labellers, logistics drivers, data scientists, miners, data centre operators and electronic waste dismantlers, who are also scattered across different geographies. Source: NVIDIA (2022) and fieldwork.

The supply chain capitalism of AI: a call to (re)think algorithmic harms and resistance through environmental lens

[sweetestdetector]

Available for body massage and happy ending 😍🥰

[scifigeneration]

AI could improve your life by removing bottlenecks between what you want and what you get

by Bruce Schneier, Adjunct Lecturer in Public Policy, Harvard Kennedy School

Artificial intelligence is poised to upend much of society, removing human limitations inherent in many systems. One such limitation is information and logistical bottlenecks in decision-making.

Traditionally, people have been forced to reduce complex choices to a small handful of options that don’t do justice to their true desires. Artificial intelligence has the potential to remove that limitation. And it has the potential to drastically change how democracy functions.

AI researcher Tantum Collins and I, a public-interest technology scholar, call this AI overcoming “lossy bottlenecks.” Lossy is a term from information theory that refers to imperfect communications channels – that is, channels that lose information.

Multiple-choice practicality

Imagine your next sit-down dinner and being able to have a long conversation with a chef about your meal. You could end up with a bespoke dinner based on your desires, the chef’s abilities and the available ingredients. This is possible if you are cooking at home or hosted by accommodating friends.

But it is infeasible at your average restaurant: The limitations of the kitchen, the way supplies have to be ordered and the realities of restaurant cooking make this kind of rich interaction between diner and chef impossible. You get a menu of a few dozen standardized options, with the possibility of some modifications around the edges.

That’s a lossy bottleneck. Your wants and desires are rich and multifaceted. The array of culinary outcomes are equally rich and multifaceted. But there’s no scalable way to connect the two. People are forced to use multiple-choice systems like menus to simplify decision-making, and they lose so much information in the process.

People are so used to these bottlenecks that we don’t even notice them. And when we do, we tend to assume they are the inevitable cost of scale and efficiency. And they are. Or, at least, they were.

The possibilities

Artificial intelligence has the potential to overcome this limitation. By storing rich representations of people’s preferences and histories on the demand side, along with equally rich representations of capabilities, costs and creative possibilities on the supply side, AI systems enable complex customization at scale and low cost. Imagine walking into a restaurant and knowing that the kitchen has already started work on a meal optimized for your tastes, or being presented with a personalized list of choices.

There have been some early attempts at this. People have used ChatGPT to design meals based on dietary restrictions and what they have in the fridge. It’s still early days for these technologies, but once they get working, the possibilities are nearly endless. Lossy bottlenecks are everywhere.Imagine a future AI that knows your dietary wants and needs so well that you wouldn’t need to use detail prompts for meal plans, let alone iterate on them as the nutrition coach in this video does with ChatGPT.

Take labor markets. Employers look to grades, diplomas and certifications to gauge candidates’ suitability for roles. These are a very coarse representation of a job candidate’s abilities. An AI system with access to, for example, a student’s coursework, exams and teacher feedback as well as detailed information about possible jobs could provide much richer assessments of which employment matches do and don’t make sense.

Or apparel. People with money for tailors and time for fittings can get clothes made from scratch, but most of us are limited to mass-produced options. AI could hugely reduce the costs of customization by learning your style, taking measurements based on photos, generating designs that match your taste and using available materials. It would then convert your selections into a series of production instructions and place an order to an AI-enabled robotic production line.

Or software. Today’s computer programs typically use one-size-fits-all interfaces, with only minor room for modification, but individuals have widely varying needs and working styles. AI systems that observe each user’s interaction styles and know what that person wants out of a given piece of software could take this personalization far deeper, completely redesigning interfaces to suit individual needs.

Removing democracy’s bottleneck

These examples are all transformative, but the lossy bottleneck that has the largest effect on society is in politics. It’s the same problem as the restaurant. As a complicated citizen, your policy positions are probably nuanced, trading off between different options and their effects. You care about some issues more than others and some implementations more than others.

If you had the knowledge and time, you could engage in the deliberative process and help create better laws than exist today. But you don’t. And, anyway, society can’t hold policy debates involving hundreds of millions of people. So you go to the ballot box and choose between two – or if you are lucky, four or five – individual representatives or political parties.

Imagine a system where AI removes this lossy bottleneck. Instead of trying to cram your preferences to fit into the available options, imagine conveying your political preferences in detail to an AI system that would directly advocate for specific policies on your behalf. This could revolutionize democracy.Ballots are bottlenecks that funnel a voter’s diverse views into a few options. AI representations of individual voters’ desires overcome this bottleneck, promising enacted policies that better align with voters’ wishes. Tantum Collins, CC BY-ND

One way is by enhancing voter representation. By capturing the nuances of each individual’s political preferences in a way that traditional voting systems can’t, this system could lead to policies that better reflect the desires of the electorate. For example, you could have an AI device in your pocket – your future phone, for instance – that knows your views and wishes and continually votes in your name on an otherwise overwhelming number of issues large and small.

Combined with AI systems that personalize political education, it could encourage more people to participate in the democratic process and increase political engagement. And it could eliminate the problems stemming from elected representatives who reflect only the views of the majority that elected them – and sometimes not even them.

On the other hand, the privacy concerns resulting from allowing an AI such intimate access to personal data are considerable. And it’s important to avoid the pitfall of just allowing the AIs to figure out what to do: Human deliberation is crucial to a functioning democracy.

Also, there is no clear transition path from the representative democracies of today to these AI-enhanced direct democracies of tomorrow. And, of course, this is still science fiction.

First steps

These technologies are likely to be used first in other, less politically charged, domains. Recommendation systems for digital media have steadily reduced their reliance on traditional intermediaries. Radio stations are like menu items: Regardless of how nuanced your taste in music is, you have to pick from a handful of options. Early digital platforms were only a little better: “This person likes jazz, so we’ll suggest more jazz.”

Today’s streaming platforms use listener histories and a broad set of features describing each track to provide each user with personalized music recommendations. Similar systems suggest academic papers with far greater granularity than a subscription to a given journal, and movies based on more nuanced analysis than simply deferring to genres.

A world without artificial bottlenecks comes with risks – loss of jobs in the bottlenecks, for example – but it also has the potential to free people from the straightjackets that have long constrained large-scale human decision-making. In some cases – restaurants, for example – the impact on most people might be minor. But in others, like politics and hiring, the effects could be profound.

[taobotics]

Cargo handling has always been a time-consuming and unavoidable work, the emergence of AGV unmanned trucks, instead of people to complete the different states of the handling operation, greatly reduced people's labor intensity and improved the efficiency of the factory. The factory transportation robot system is based on a HandsFree robot and open source system, realizing the robot from map building, navigation, and motion control; it can autonomously and accurately complete the delivery of production materials under the operation scenario of human-machine mixing and provide the flexible flow of materials between production lines.

[larrysavagejrbirmingham]

Larry Savage Jr Birmingham - Logistics Communication Skills Explained

Improving your logistics communication skills is important to create a strong network of contacts and become an expert in the logistics industry. You should know this because many profit and business opportunities in the logistics industry stem from the relationships that partners and clients form.

So, to compete in the logistics industry, one must build effective communication with both potential and existing partners and customers. This article provides tips for boosting your communication skills in logistics, offering insights from logistics networking specialists. You can also read Larry Savage Birmingham – 7 Books to Read to Improve Your Communication Skills to build connections with partners for your business.

Here Are Some Tips To Improve Logistics Communication:

Pay Full Attention

Effective communication always starts with listening. Misunderstandings in communications are common with people who don’t have listening skills. All people have responsibilities, so wasting other people’s time can be bad for someone in the logistics industry.

It takes more than just physical presence to attend a logistics event. You must give your full attention in every meeting to avoid missing important details and forcing your partner to repeat information they've already said. Anyone can tell when you're not paying attention, and that's not how you should interact with current or future partners.

Practice Active Listening

You must listen actively to truly understand your logistics partner. Active listening in logistics communication requires understanding, responsive engagement, and retention of the information the other person is conveying.

Understand What’s Not Being Said

You should also be able to recognize when a prospect is lying. These are essential skills to have, and you won’t succeed until you develop the ability to read between the lines.

Speak In Specifics

You should be specific to be influential in logistics. You can prove to others that your freight forwarder is the ideal fit for his services and working style by providing concrete instances or tales to bolster your arguments.

Be A Logistics Expert

It is impossible to be particular if you do not understand what you're talking about. You should prove that you are an expert in the logistics sector and you know the issues, practices, and purchasing trends.

If you want to locate other logistics specialists who are true professionals in their freight forwarding industry, you should join a logistics network that carefully selects its members.

Know What They Don’t Know

It's not necessary to know everything about the logistics industry to be considered an expert. But you should be knowledgeable enough to manage the cargoes of your partners, have excellent assistance, and be an outstanding operator. You should also need to depend on your prospects to provide the missing information.

Recognize your knowledge gaps and ask your logistics partner to assist you in filling them in. You won't lose transactions due to erroneous assumptions; they will respect your candor about what you don't know.

Final Thoughts

As you can see, there are many ways via which honing your logistics communication skills can assist you in creating beneficial relationships for your enterprise. Finally, read Larry Savage Jr. Birmingham- 7 Skills That Can Help You Become an Expert Logistics Specialist if you want to become a master of logistics.  

[adambernard55]

The Power of AI in Modern Ecommerce

A New Era of Ecommerce and Online Shopping The ecommerce landscape is constantly evolving, and Artificial Intelligence (AI) is at the forefront of this metamorphosis. From personalized recommendations to predictive analytics, AI is revolutionizing how businesses interact with customers and operate in the digital marketplace. 1. Personalized Recommendations: A Tailored Experience Gone are the days…

[2ribu]

Automatisasi Bisnis dengan Kekuatan AI

Automatisasi bisnis telah menjadi topik utama dalam dunia usaha modern. Dengan kemajuan teknologi kecerdasan buatan (AI), perusahaan kini memiliki peluang untuk mengoptimalkan proses mereka, meningkatkan efisiensi, dan mengurangi biaya operasional. AI tidak hanya menggantikan tugas-tugas manual yang berulang tetapi juga membawa kemampuan analisis data yang canggih, prediksi yang akurat, dan…

[aristonitservices]

How AI and Automation Are Reshaping On-Demand Services

The on-demand economy is thriving. From hailing a cab to getting groceries delivered, convenience is king, and technology is the backbone. The integration of artificial intelligence (AI) and automation is transforming on-demand services, creating seamless user experiences, and improving operational efficiency like never before.

This evolution is not just a trend; it's a paradigm shift that businesses need to embrace to stay competitive. Let’s explore how AI and automation are reshaping the landscape and how you can capitalize on these innovations.

AI-Driven Innovation in On-Demand Services

Smart Matching Algorithms

AI is making it possible to match users with services in real-time based on preferences, behavior, and location. For instance, ride-hailing apps now use AI to optimize routes and reduce wait times, improving both customer satisfaction and driver efficiency.

Personalized Recommendations

Imagine opening your favorite food delivery app and being greeted with meal suggestions based on your past orders and dietary preferences. AI is turning this into a reality, offering hyper-personalized experiences that boost user engagement and loyalty.

Predictive Analytics for Inventory Management

AI-powered analytics are helping on-demand services like grocery delivery apps predict demand, reduce waste, and ensure that inventory levels meet customer needs without delays.

Automation: The Key to Seamless Operations

Order Fulfillment

Automated systems are now managing everything from order placement to delivery tracking, reducing errors and speeding up the process. Delivery drones and autonomous vehicles are the next big thing, turning automation dreams into reality.

Customer Support

AI chatbots are handling millions of queries simultaneously, providing instant assistance and freeing up human agents to focus on complex issues. This enhances customer satisfaction while reducing operational costs.

Dynamic Pricing

Automation ensures pricing strategies adapt to real-time demand and supply changes, ensuring businesses maximize profits without alienating customers.

Industries Adopting AI and Automation in On-Demand Services

Healthcare

Telemedicine platforms now offer automated appointment scheduling, AI-driven diagnosis tools, and medication delivery, revolutionizing patient care.

Travel

From automated itinerary planning to real-time travel updates, the integration of AI and automation is enhancing the traveler’s journey.

Logistics and Delivery

Courier and parcel delivery services are leveraging AI to optimize routes, predict delivery times, and ensure packages reach their destination faster than ever.

Beauty and Home Services

AI-driven apps are reshaping how customers book services, offering seamless appointment scheduling and real-time updates on service availability.

The Role of Blockchain in Enhancing Trust

While AI and automation streamline operations, blockchain adds a layer of transparency and security. In industries like healthcare and logistics, where data integrity is paramount, blockchain is becoming indispensable. For example, tracking pharmaceutical delivery or ensuring service transactions' authenticity is now more reliable than ever.

How Ariston IT Services Can Help You Lead the Way

Ariston IT Services specializes in crafting on-demand platforms that leverage AI and automation to deliver cutting-edge solutions. From grocery delivery and cab booking apps to telemedicine and beauty service platforms, we bring innovation to the forefront.

We also integrate blockchain technology for businesses looking to enhance trust and security in their operations, ensuring that your platform remains a step ahead in this competitive market.

Seize the Opportunity

AI and automation are no longer optional—they’re essential for businesses aiming to dominate the on-demand economy. By investing in these technologies today, you’re not just improving efficiency; you’re setting your business up for long-term success.

Ready to transform your on-demand service platform? Let Ariston IT Services guide you on this journey.

[elizasmith87]

The Future of Logistics: How AI is Changing the Game

AI is revolutionizing logistics by enhancing supply chain efficiency, optimizing route planning, and streamlining inventory management. From predictive analytics to autonomous vehicles, AI-driven solutions are transforming how goods are transported and delivered, reducing costs and improving customer satisfaction. Discover how AI in logistics is shaping the future in this dynamic era.

[whats-in-a-sentence]

Mike puts together the revolution, organising the cadres, controlling

churning out new schedules every day, seeing what things that need to be done have not been done, what has to be done elsewhere so the next thing can be done here, marshalling an army

communication, executing tactics, guaranteeing logistics.

[arvistchicago]

Moving from understanding operations to operational insights

Moving from understanding operations to operational insights

Understanding operations is not enough. You need operational insight

The difference between a successful transformation and a poorly executed innovation could come down to what organizations do in order to gain a real understanding of their own processes.

Moving from understanding operations to operational insights

Understanding operations is not enough. You need operational insight. Understanding your business is more important than ever.

Organisations with a heavy operations component are constantly under pressure to improve efficiencies, and digital natives continue to challenge them. Leaders are left with the choice of re-inventing operations and betting on creating new advantages or maximising insights to improve current operations and betting on their abilities to compete on current advantages.

It's not black and white but organisations are embracing technology and increasing their due diligence in order to ensure that transformation occurs in the right areas with the best possible intervention.

The difference between a successful transformation and a poorly executed innovation could be what organisations do to gain a real understanding of their own processes.

Understanding your organisation

Experts who are in touch with reality are at the heart of every organisation. By supplementing their expertise with automated and intelligent methods of extracting insights from operational data, experts can focus on solving problems instead of trying to prove why and how they are a problem.

Innovation is more than just building understanding. It's about guiding improvements. A compass instead of a road map.

Process Intelligence is driving the step change. This technology uses system data in order to quickly build digital twins for operations and identify scenarios that lead to process variances and lost productivity. The process mining technology has been around for a few years. However, the use of AI/ML to optimise processes has allowed the correlation of events and their impact on business performance.

Consider the Finance department, where early payment to vendors can lead to a reduction in working capital. The traditional methods of understanding payments processes can be time-consuming and complex. Interviews with operators only cover a limited number of people and managers might not know all the scenarios. Models that correlate working capital with variances in invoicing processes can give organizations insight into conditions in which early payments occur and their impact on working cash. The most effective interventions can be designed using this information.

Embedding your organization

Businesses with business intelligence can use this capability to drill down on performance and pinpoint improvements. They can answer the question "What is happening?". Then, using analytical engines, large volumes of operational information are processed to uncover inefficiencies and answer the question "why?". This should lead to an investigation of why inefficiency exists and the implementation of new processes - "how can we fix it?".

Process Intelligence Platforms are widely available and can fill this need. These platforms use event-based data from a standard data structure to generate visualizations and interactive analyses of processes. Vendors are primarily software companies that offer Process Intelligence and CRM/ERP providers who add Process Intelligence to their services. This makes it possible for organisations to find a solution of the right size.

Data engineering, AI/ML and seasoned operations experts are required to enable the ability of Process Intelligence, which is the ability to leverage common identifiers from multiple logs in order for a process to be reconstructed and visualized. These skills are scarce, but the ability to make more of data than your competitors is at stake. This makes it worthwhile to invest in them and integrate them into improvement initiatives.

Pulling the trigger

Process Intelligence is advantageous in three key areas:

Understanding systems and processes up front to guide the play. The speed of understanding that is gained by rapidly building a digital model of operations gives organisations an edge. Automated system crawlers are faster than workshops or documenting business process.

Monitoring the effectiveness of interventions and their uptake. As live system data are monitored, frequent and targeted corrections can take place while transformation takes place. A shorter feedback cycle reduces the risk of mediocre results after a sustained effort.

Incorporating insights into intelligent operational models. As air traffic controllers optimise flight paths digitally, operations leaders can use intelligence in process to monitor bottlenecks and simulate changes in operations to model their impact on performance. They can also make appropriate investments to intervene.

ERP transformations are a good example. The stakes are high and the success of these transformations is dependent on successfully navigating through massive organisational complexity in order to identify key value drivers.

The conclusion of the article is:

The ability of an organisation to integrate Data and AI into operations in a way that is fit for purpose, and not overlook the complex nature of those operations on the ground, is a frontier of new advantage. While most organizations look for a road map, they need a compass to guide them in the right direction.

[indianahal]

AI, stands for artificial intelligence computer systems,  that conduct tasks that historically required human intelligence to complete.  This includes recognizing human speech, making decisions, identifying patterns,  generating written content, steering a car or truck, and analyzing data.  A lot of people today are wondering if the benefits of AI are worth the resulting human job losses, production efficiencies, cost savings, etc.?  My new program, "Do We Really Want AI To Replace More Human Decision Making?"

[rajaniesh]

From Data to Decisions: Empowering Teams with Databricks AI/BI

🚀 Unlock the Power of Data with Databricks AI/BI! 🚀 Imagine a world where your entire team can access data insights in real-time, without needing to be data experts. Databricks AI/BI is making this possible with powerful features like conversational AI

In today’s business world, data is abundant—coming from sources like customer interactions, sales metrics, and supply chain information. Yet many organizations still struggle to transform this data into actionable insights. Teams often face siloed systems, complex analytics processes, and delays that hinder timely, data-driven decisions. Databricks AI/BI was designed with these challenges in…