This is a list of the 30 largest container shipping companies as of February 2024, according to Alphaliner, ranked in order of the twenty-foot equivalent unit (TEU) capacity of their fleet. In January 2022, MSC overtook Maersk for the container line with the largest shipping capacity for the ...

List of largest container shipping companies - Wikipedia

Learn the most important information about the top container shipping companies from all over the world.

Top 10 International Container Shipping Companies In 2024

Container shipping is the most widely used form of transport in the maritime world. A few container shipping giants have been ruling the sea for several years. We bring to you 20 largest container shipping companies.

20 Largest Container Shipping Companies in the World

Here’s a scenario for you to understand better: You run a small business that specializes in importing and exporting goods. Your company has just received a large shipment order, but you don’t have enough containers to fulfill it. You could spend hours, even days, contacting different container ...

Top 10 shipping container companies [+ market trends 2023]

DHL is the global leader in the logistics industry. Specializing in international shipping, courier services and transportation.

DHL Home - Global Logistics and International Shipping ...

The freight shipping companies we partner with have low damage claim rates and excel at providing transportation throughout the United States, Canada, Mexico, and beyond. This allows them or move your load in the most cost-effective way. Depending on your freight class and how your item is prepared for transport, we can help you find the best freight shipping service to execute the pickup and delivery of your shipment ...

Shipping Companies

Discover fast, reliable global shipping and logistics solutions with UPS. Explore our services and streamline your supply chain today.

UPS Global Shipping & Logistics Solutions | Worldwide ...

Create your listing, detailing the needs of your shipment. Then, freight shipping companies will provide you with rates as they compete for your business. You can talk to the shipping companies and review their carrier profiles so you know you’re working with the best freight transport company.

Freight Shipping and Delivery: Find the Best Rates | uShip Freight ...

Time Shipping is an international freight forwarding and shipment company. Sea freight, air freight, and vehicle transport and project cargo.

Time Shipping - Freight Forwarding and Shipment - About

Matson is a transportation and logistics company serving the North American market. Matson focuses on domestic and international rail intermodal service and highway brokerage. It also offers less-than-load shipping, supply chain services, and third-party logistics. Yes, shipping can be high risk. Demand can be volatile and having to send large freight ships without a full load can masssively reduce profits. Natural disasters and weather can also delay shipments...

10 Biggest Shipping Companies

Shipmnts

shipmnts

Active Inference AI: Here's Why It's The Future of Enterprise Operations and Industry Innovation

It’s November, which means the holiday season has started — and with it, an influx of online orders. Most consumers who have ordered something online have experienced delays, failed delivery attempts or worse — lost packages. Frankly, tracking numbers and text message updates aren’t cutting it. Could artificial intelligence finally provide a solution to this problem? Packages Are Going Missing and It’s a Problem A package is supposed to arrive today. The person who placed the order watches their front door like a hawk after their app’s tracker changes from “shipping” to “out for delivery.” The estimated delivery time comes and goes — and nothing gets dropped off. Their phone pings with a “Sorry we missed you” message. What happened? Situations like these are common. Whether the seller reschedules, a delivery driver skips part of their route to save time or a porch pirate swoops in at the last second, parcels go missing all the time. In 2023, almost 40% of people in the United States had at least one package stolen. This problem is challenging to remedy simply because the delivery network is massive. Accurately tracking missing orders is possible, but it is a tall order with today’s technical limitations. Companies must monitor warehouse workers, drivers and vehicles. Not to mention, they must handle fraud cases where customers claim to have received nothing when, in reality, they did. Even in ideal circumstances, accidents happen — a small envelope could fall behind the sorting machine or get stuck under a larger box. Even when shipments eventually reach the right address, they stay in the delivery network too long. According to the United States Postal Service (USPS), 17.3% of first-class mail was not delivered on time in the second quarter of the fiscal year 2024, up 3.2 percentage points from the previous quarter. Rates for marketing mail and periodicals also worsened. The number of parcels going missing in the reverse logistics process is often overlooked. Around 30% of all online orders are sent back, compared to just 9% in brick-and-mortar stores. A disappearing parcel is particularly frustrating here, as the person attempting the return may be denied a refund or end up on the hook for the full price of the item. Why Use AI to Track People’s Missing Packages? AI is a powerful technology. A single advanced algorithm can process massive datasets, make data-driven decisions and understand language, regardless of whether it is a chatbot, generative algorithm or deep learning model. Training determines its purpose and behavior, so it can be utilized in virtually any use case. Versatility is useful when analyzing data since processing centers can produce billions of drop-off images or location data points in short periods. There is even more to go through if they use Internet of Things (IoT) tools or telematics systems in their fleets. AI can respond to prompts with voice, image, text or audio output, streamlining information retrieval and summary. Only a technology like AI can handle all the data created by the delivery network’s massive, interconnected system of sellers, fleets, customers and warehouses. Its rapid analysis isn’t its only boon — it also has automation capabilities. An advanced model can operate around the clock without stopping for breaks, food or sleep. Is AI Already Being Used to Track Packages? Several delivery companies are already using AI to track shipments in transit. For instance, the United Parcel Service uses an AI-enabled supply chain. It uses historical and real-time data to calculate the fastest, safest way to boost the on-time delivery rate. Its algorithm can also anticipate disruptions and provide a comprehensive view of the fleet’s network. If other firms deploy AI at the edge — at the network’s boundary where data is created — they wouldn’t have to build data centers to process or analyze the massive amount of logistics information they receive. On top of using fewer computing resources, they’d enable real-time results with little to no delay, improving output accuracy. In a different approach, USPS uses an AI-enabled edge computing program powered by NVIDIA technology. Its model analyzes billions of images that the processing center generates. Before, finding a missing order took a team of up to 10 people multiple days. With this platform, a single individual can track one down in around two hours. 4 Ways AI Can Track Stolen and Lost Packages There are several ways AI can help people track their missing parcels. 1. Provide Real-Time Updates Even with a tracking number, updates are often too vague, inaccurate or outdated to be helpful. According to one survey, nine in 10 people want to be able to track their order, with 47% wanting to know exactly where their item is at all times. AI can fulfill this desire, providing real-time updates as shipments travel. 2. Calculate Delivery Estimate Since as many as 20% of deliveries fail on the first attempt, reschedules are common. While most people wait a few extra days, some don’t receive their items for weeks or months. With AI, they can see how long it will take for a driver to reattempt delivery. The algorithm can factor in variables like weather, consumer demand, route closures and delays. 3. Analyze the Drop-Off Photos An AI could leverage image recognition technology to analyze millions of drop-off photos. It can flag the delivery as incorrect or suspicious if it notices any discrepancies. If there are enough clues in the photo’s visual details or metadata, the model could help workers track down the missing parcel. 4. Answer Peoples’ Questions Globally, 46% of online shoppers expect to receive their orders within two to three days. However, delays, reschedules and cancellations are common. When these situations arise, an AI-powered chatbot can answer consumers’ questions to help them understand what happened. Depending on its design, it could discuss the item’s location or estimate delivery dates. How Integration Could Enhance AI’s Capabilities While AI is powerful on its own, companies could see significant improvements after integration. For example, embedding a machine learning model into a surveillance system or camera doorbell could help recipients identify porch pirates or misbehaving delivery drivers. This way, they could potentially narrow down the location of their missing item. An AI-powered computer vision system — an AI-powered device that can interpret visual information — could do something similar, monitoring production lines and automatic sorting machines for misplaced parcels. If something falls off of a belt, gets stuck under another container or slips between a crack in the machine, it could alert a human worker. Integrations can even help in transit. Combining AI and IoT sensors enables real-time updates on a product’s condition and location. Recipients could receive alerts if their item is tampered with, dropped off at the wrong location or stolen. The algorithm would filter out false positives and concisely explain what happened. Could AI Prevent Packages From Getting Lost? While finding missing parcels is an excellent use of a machine learning model, stopping this problem at the source is a more effective solution. Companies could prevent products from getting lost in the first place by leveraging chatbots for communication. The higher the success rate for the first delivery attempt, the less likely the item will disappear from the system. Decision-makers could also optimize routes to reduce workers’ stress. Demand has far outpaced the workforce’s capabilities — experts predict e-commerce sales will reach over $8 trillion in sales by 2027, a 237% increase in one decade — which puts pressure on drivers to haul more boxes and complete routes faster. Companies increasingly hire freelance and gig workers to compensate for their labor shortage. These workers are often paid by the number of packages they deliver, incentivizing them to race through their routes. Using AI to optimize their trip saves them time, lowering the chance they will make mistakes in transit. The Bottom Line of Using AI to Track Orders Although AI is not a miracle technology, it is one of the best solutions on the market for this problem. Processing centers and delivery drivers need something that can process information rapidly, output responses in natural language and interact with multiple people simultaneously. It’s November, which means the holiday season has started — and with it, an influx of online orders. It’s November, which means the holiday season has started — and with it, an influx of online orders. Most consumers who have ordered something online have experienced delays, failed delivery attempts or worse — lost packages. Frankly, tracking numbers and text message updates aren’t cutting it. Could artificial intelligence finally provide a solution to this problem? Most consumers who have ordered something online have experienced delays, failed delivery attempts or worse — lost packages. Frankly, tracking numbers and text message updates aren’t cutting it. Could artificial intelligence finally provide a solution to this problem? Packages Are Going Missing and It’s a Problem Packages Are Going Missing and It’s a Problem A package is supposed to arrive today. The person who placed the order watches their front door like a hawk after their app’s tracker changes from “shipping” to “out for delivery.” The estimated delivery time comes and goes — and nothing gets dropped off. Their phone pings with a “Sorry we missed you” message. What happened? Situations like these are common. Whether the seller reschedules, a delivery driver skips part of their route to save time or a porch pirate swoops in at the last second, parcels go missing all the time. In 2023, almost 40% of people in the United States had at least one package stolen. This problem is challenging to remedy simply because the delivery network is massive. almost 40% of people almost 40% of people Accurately tracking missing orders is possible, but it is a tall order with today’s technical limitations. Companies must monitor warehouse workers, drivers and vehicles. Not to mention, they must handle fraud cases where customers claim to have received nothing when, in reality, they did. Even in ideal circumstances, accidents happen — a small envelope could fall behind the sorting machine or get stuck under a larger box. Even when shipments eventually reach the right address, they stay in the delivery network too long. According to the United States Postal Service (USPS), 17.3% of first-class mail was not delivered on time in the second quarter of the fiscal year 2024, up 3.2 percentage points from the previous quarter. Rates for marketing mail and periodicals also worsened. 17.3% of first-class mail 17.3% of first-class mail The number of parcels going missing in the reverse logistics process is often overlooked. Around 30% of all online orders are sent back, compared to just 9% in brick-and-mortar stores. A disappearing parcel is particularly frustrating here, as the person attempting the return may be denied a refund or end up on the hook for the full price of the item. 30% of all online orders 30% of all online orders Why Use AI to Track People’s Missing Packages? AI is a powerful technology. A single advanced algorithm can process massive datasets, make data-driven decisions and understand language, regardless of whether it is a chatbot, generative algorithm or deep learning model. Training determines its purpose and behavior, so it can be utilized in virtually any use case. Versatility is useful when analyzing data since processing centers can produce billions of drop-off images or location data points in short periods. There is even more to go through if they use Internet of Things (IoT) tools or telematics systems in their fleets. AI can respond to prompts with voice, image, text or audio output, streamlining information retrieval and summary. Only a technology like AI can handle all the data created by the delivery network’s massive, interconnected system of sellers, fleets, customers and warehouses. Its rapid analysis isn’t its only boon — it also has automation capabilities. An advanced model can operate around the clock without stopping for breaks, food or sleep. Is AI Already Being Used to Track Packages? Several delivery companies are already using AI to track shipments in transit. For instance, the United Parcel Service uses an AI-enabled supply chain. It uses historical and real-time data to calculate the fastest, safest way to boost the on-time delivery rate. Its algorithm can also anticipate disruptions and provide a comprehensive view of the fleet’s network. uses historical and real-time data uses historical and real-time data If other firms deploy AI at the edge — at the network’s boundary where data is created — they wouldn’t have to build data centers to process or analyze the massive amount of logistics information they receive. On top of using fewer computing resources, they’d enable real-time results with little to no delay, improving output accuracy. In a different approach, USPS uses an AI-enabled edge computing program powered by NVIDIA technology. Its model analyzes billions of images that the processing center generates. Before, finding a missing order took a team of up to 10 people multiple days. With this platform, a single individual can track one down in around two hours. team of up to 10 people team of up to 10 people 4 Ways AI Can Track Stolen and Lost Packages There are several ways AI can help people track their missing parcels. 1. Provide Real-Time Updates Even with a tracking number, updates are often too vague, inaccurate or outdated to be helpful. According to one survey, nine in 10 people want to be able to track their order, with 47% wanting to know exactly where their item is at all times. AI can fulfill this desire, providing real-time updates as shipments travel. nine in 10 people nine in 10 people 2. Calculate Delivery Estimate Since as many as 20% of deliveries fail on the first attempt, reschedules are common. While most people wait a few extra days, some don’t receive their items for weeks or months. With AI, they can see how long it will take for a driver to reattempt delivery. The algorithm can factor in variables like weather, consumer demand, route closures and delays. as many as 20% of deliveries as many as 20% of deliveries 3. Analyze the Drop-Off Photos An AI could leverage image recognition technology to analyze millions of drop-off photos. It can flag the delivery as incorrect or suspicious if it notices any discrepancies. If there are enough clues in the photo’s visual details or metadata, the model could help workers track down the missing parcel. 4. Answer Peoples’ Questions Globally, 46% of online shoppers expect to receive their orders within two to three days. However, delays, reschedules and cancellations are common. When these situations arise, an AI-powered chatbot can answer consumers’ questions to help them understand what happened. Depending on its design, it could discuss the item’s location or estimate delivery dates. 46% of online shoppers 46% of online shoppers How Integration Could Enhance AI’s Capabilities While AI is powerful on its own, companies could see significant improvements after integration. For example, embedding a machine learning model into a surveillance system or camera doorbell could help recipients identify porch pirates or misbehaving delivery drivers. This way, they could potentially narrow down the location of their missing item. An AI-powered computer vision system — an AI-powered device that can interpret visual information — could do something similar, monitoring production lines and automatic sorting machines for misplaced parcels. If something falls off of a belt, gets stuck under another container or slips between a crack in the machine, it could alert a human worker. Integrations can even help in transit. Combining AI and IoT sensors enables real-time updates on a product’s condition and location. Recipients could receive alerts if their item is tampered with, dropped off at the wrong location or stolen. The algorithm would filter out false positives and concisely explain what happened. Could AI Prevent Packages From Getting Lost? While finding missing parcels is an excellent use of a machine learning model, stopping this problem at the source is a more effective solution. Companies could prevent products from getting lost in the first place by leveraging chatbots for communication. The higher the success rate for the first delivery attempt, the less likely the item will disappear from the system. Decision-makers could also optimize routes to reduce workers’ stress. Demand has far outpaced the workforce’s capabilities — experts predict e-commerce sales will reach over $8 trillion in sales by 2027, a 237% increase in one decade — which puts pressure on drivers to haul more boxes and complete routes faster. reach over $8 trillion in sales reach over $8 trillion in sales Companies increasingly hire freelance and gig workers to compensate for their labor shortage. These workers are often paid by the number of packages they deliver, incentivizing them to race through their routes. Using AI to optimize their trip saves them time, lowering the chance they will make mistakes in transit. The Bottom Line of Using AI to Track Orders Although AI is not a miracle technology, it is one of the best solutions on the market for this problem. Processing centers and delivery drivers need something that can process information rapidly, output responses in natural language and interact with multiple people simultaneously.

AI Can Help Track Your Missing Packages

The tech industry is no stranger to supply chain disruptions, but the recent U.S. port strike is creating new challenges that could have lasting effects. On the first day of October, thousands of dockworkers left key ports at a standstill along the East and Gulf Coasts. As a result, the flow of critical tech components and finished goods has slowed dramatically. This disruption comes at a critical time, especially when the tech industry is still recovering from supply chain issues caused by the COVID-19 pandemic. The Tech Industry’s Supply Chain Dependence on Ports The tech industry greatly relies on ports, especially those along the East and Gulf Coasts of the U.S. Ports serve as entry points for many components and raw materials needed to manufacture and assemble electronic devices. These parts often involve semiconductors, screens, batteries, and more. A single delayed shipment of any of these components can ripple through the supply chain, affecting production timelines, product availability, and pricing across the market. To put it into perspective, U.S. ports handle the majority of global trade. According to the National Association of Manufacturers, the affected ports manage 51% of the nation’s containerized imports. These containers often carry crucial tech parts from places like Asia and Europe, which then become distributed to manufacturing hubs within the U.S. As such, any disruption in the flow of these goods results in delayed product releases. The tech industry has long depended on a finely-tuned global supply chain that operates on just-in-time principles. This method is where components are precisely delivered when needed to minimize warehousing costs and maximize efficiency. However, this approach leaves little room for error. When a disruption like the U.S. port strike occurs, there isn’t a buffer to absorb the delay. As a result, you get stalled production lines, which delay product releases and cause a shortage of tech products. How Tech Companies Are Adapting Their Logistics Strategies The U.S. port strike has far-reaching consequences on the economy. As cargo remains stuck at the ports, companies face increasing shipping costs, production slowdowns, and an inability to meet consumer demand. To mitigate these economic effects, businesses are swiftly adapting their logistics strategies. Enhanced Visibility and Use of Technology in Logistics A lack of supply chain visibility is one major challenge within the U.S. port strike. According to recent findings, around 45% of stakeholders report having limited visibility beyond their first-tier suppliers. Unfortunately, this makes responding quickly to disruptions or anticipating potential issues difficult. To combat this, companies are adopting tech-driven logistics solutions that provide greater transparency in the supply chain. For instance, digital platforms now offer real-time tracking of every part of the supply chain process, providing stakeholders with better visibility of where goods are in transit. With machine learning improving route optimization, these technologies allow more efficient delivery routes and rapid responses to unforeseen events. Rerouting Shipments and Shifting Transportation Methods Many companies have resorted to rerouting cargo to ports on the West Coast or Canada to bypass the backlogs on the East and Gulf Coasts. However, these options come with unique challenges. West Coast ports are already operating at high capacity — with some facilities reaching 71% — leaving little room to accommodate the redirected shipments. Additionally, rerouting involves longer travel times and higher costs due to the need to manage new logistics routes. Air freight is becoming an increasingly attractive option for transporting time-sensitive tech products. However, these expensive methods often lead to higher costs for end products. Despite the increased expenses, air transport offers faster shipping times. Manufacturing facilities can ensure they receive their goods on time, but this method only works for smaller, high-value items that can absorb additional shipping costs. Shifting Toward Localization and Supply Chain Diversification Companies are also shifting toward localization as a strategic response to the strike. By sourcing materials closer to their consumer markets, they reduce the dependency on overseas shipments and minimize the risk associated with port congestion. The strategy of nearshoring — moving supply chains closer to home — offers faster transportation times and more stable supply chain operations. This method also makes it easier to respond to disruptions without heavily relying on international ports or long-haul transportation. Navigating the Shifts in the Supply Chain The U.S. port strike is a reminder of how quickly global supply chains can go into disarray and create lasting effects on the tech industry. Therefore, it is more important than ever for organizations to adapt their logistics. The strike presents immediate challenges, so companies must prepare for events like these and devise long-term strategies that help them increase their resiliency. The tech industry is no stranger to supply chain disruptions, but the recent U.S. port strike is creating new challenges that could have lasting effects. On the first day of October, thousands of dockworkers left key ports at a standstill along the East and Gulf Coasts. As a result, the flow of critical tech components and finished goods has slowed dramatically. This disruption comes at a critical time, especially when the tech industry is still recovering from supply chain issues caused by the COVID-19 pandemic. The Tech Industry’s Supply Chain Dependence on Ports The tech industry greatly relies on ports, especially those along the East and Gulf Coasts of the U.S. Ports serve as entry points for many components and raw materials needed to manufacture and assemble electronic devices. These parts often involve semiconductors, screens, batteries, and more. A single delayed shipment of any of these components can ripple through the supply chain, affecting production timelines, product availability, and pricing across the market. To put it into perspective, U.S. ports handle the majority of global trade. According to the National Association of Manufacturers, the affected ports manage 51% of the nation’s containerized imports. These containers often carry crucial tech parts from places like Asia and Europe, which then become distributed to manufacturing hubs within the U.S. As such, any disruption in the flow of these goods results in delayed product releases. the affected ports manage 51% the affected ports manage 51% The tech industry has long depended on a finely-tuned global supply chain that operates on just-in-time principles. This method is where components are precisely delivered when needed to minimize warehousing costs and maximize efficiency. However, this approach leaves little room for error. When a disruption like the U.S. port strike occurs, there isn’t a buffer to absorb the delay. As a result, you get stalled production lines, which delay product releases and cause a shortage of tech products. How Tech Companies Are Adapting Their Logistics Strategies The U.S. port strike has far-reaching consequences on the economy. As cargo remains stuck at the ports, companies face increasing shipping costs, production slowdowns, and an inability to meet consumer demand. To mitigate these economic effects, businesses are swiftly adapting their logistics strategies. Enhanced Visibility and Use of Technology in Logistics A lack of supply chain visibility is one major challenge within the U.S. port strike. According to recent findings, around 45% of stakeholders report having limited visibility beyond their first-tier suppliers. Unfortunately, this makes responding quickly to disruptions or anticipating potential issues difficult. To combat this, companies are adopting tech-driven logistics solutions that provide greater transparency in the supply chain. around 45% of stakeholders around 45% of stakeholders For instance, digital platforms now offer real-time tracking of every part of the supply chain process, providing stakeholders with better visibility of where goods are in transit. With machine learning improving route optimization, these technologies allow more efficient delivery routes and rapid responses to unforeseen events. now offer real-time tracking now offer real-time tracking Rerouting Shipments and Shifting Transportation Methods Many companies have resorted to rerouting cargo to ports on the West Coast or Canada to bypass the backlogs on the East and Gulf Coasts. However, these options come with unique challenges. West Coast ports are already operating at high capacity — with some facilities reaching 71% — leaving little room to accommodate the redirected shipments. Additionally, rerouting involves longer travel times and higher costs due to the need to manage new logistics routes. with some facilities reaching 71% with some facilities reaching 71% Air freight is becoming an increasingly attractive option for transporting time-sensitive tech products. However, these expensive methods often lead to higher costs for end products. Despite the increased expenses, air transport offers faster shipping times. Manufacturing facilities can ensure they receive their goods on time, but this method only works for smaller, high-value items that can absorb additional shipping costs. Shifting Toward Localization and Supply Chain Diversification Companies are also shifting toward localization as a strategic response to the strike. By sourcing materials closer to their consumer markets, they reduce the dependency on overseas shipments and minimize the risk associated with port congestion. The strategy of nearshoring — moving supply chains closer to home — offers faster transportation times and more stable supply chain operations. This method also makes it easier to respond to disruptions without heavily relying on international ports or long-haul transportation. Navigating the Shifts in the Supply Chain The U.S. port strike is a reminder of how quickly global supply chains can go into disarray and create lasting effects on the tech industry. Therefore, it is more important than ever for organizations to adapt their logistics. The strike presents immediate challenges, so companies must prepare for events like these and devise long-term strategies that help them increase their resiliency.

How Will the US Port Strike Affect the Global Tech Industry?

With AI being the flavor of the times, one hears of the technology being deployed for everything except for basic human functions. So, it is no surprise that one recently came across the term AI PC. Now what is that beast, I wondered? Obviously, it means a personal computer that uses artificial intelligence technology, but how exactly is it different from a regular computer, and does it radically alter or promise to alter everything to do with personal computing? As with most things AI hype precedes sober reality, so I decided to find out for myself. According to the chip-making behemoth Intel, AI PCs possess the capability to enhance everything ranging from productivity, entertainment, and security to creativity and security. It comprises a CPU apparently to handle smaller workloads requiring low potency, a GPU or Graphics Processing Unit for large workloads requiring parallel throughput, and an NPU Neural Processing Unit that is ideal for what Intel calls sustained heavily used AI workloads even as it consumes low power and provides greater efficiency.[1] This is all very well and well appreciated, but how is an AI PC different from a regular PC? Apparently, what these supercharged PCs do is enable the speedy execution of AI tasks, even while consuming less energy. What's more, you no longer need to send sensitive data to cloud-based AI servers in order to get them processed. With their ability to operate sans an internet connection, these PCs provide enhanced security because they store the data locally.[2] All the major PC manufacturers like DEL, HP, and Lenovo are betting big on AI PC systems incorporating NPUs. Apple, of course, has already cornered 60% of the AI PC market, with its products powered by its M series chip with a neural engine. As a matter of fact, AI PCs made up as much as 14% of PC sales in the second quarter, pointing to their growing popularity.[3] Should You Buy an AI PC? Going by all the marketing hype that one hears about how AI PCs are helping usher in a new dawn in personal computing what with the technology giants like Microsoft extolling its virtues, one might think that you would lose out if you didn't buy one pronto. While an AI PC might actually possess the mind-boggling potential to do wonderful things that we can't even begin to imagine at present, the question to ask yourself is should you buy yourself one now? The NPU, which lies at the heart of an AI PC sure has great untapped potential, but since Microsoft isn't yet up to speed with it and can't leverage it much in any really impactful manner and with third-party application developers lagging behind as well, this may not be the best time to plonk your hard earned money on the purchase of an AI PC. An AI PC can at best get you access to Windows Studio Effect which uses a PC’s NPU to enhance video and audio in video calls. If that is something that you simply can't do without, by all means, go and buy yourself one of these new toys.[4] Like with most new path-breaking (hopefully) technologies, one does not know how successful AI PCs eventually turn out to be, given that one really has no clear idea about what these wondrous machines can really achieve (remember the Metaverse, anyone?). One might want to wait for Windows 12 to be launched so that developers can sink their teeth into the new-fangled AI chips and figure out how these can be best leveraged.[5] If you are one of those who imagine that staying ahead of the curve will help you deal with future shock in a comprehensive manner, go right ahead and buy an AI PC at this very moment. The rest of us can bide our time for now. [1] https://www.intel.com/content/www/us/en/products/docs/processors/core-ultra/ai-pc.html#:~:text=the%20close%20button.-,What%20is%20an%20AI%20PC%3F,tasks%20locally%20and%20more%20efficiently. [2] https://www.zdnet.com/article/what-is-an-ai-pc-and-should-you-buy-one/ [3] https://www.reuters.com/technology/artificial-intelligence/ai-pcs-made-up-14-quarterly-personal-computer-shipments-canalys-says-2024-08-13/ [4] https://www.pcworld.com/article/2236372/does-your-next-laptop-really-need-to-be-an-ai-pc.html [5] https://www.forbes.com/sites/barrycollins/2024/01/10/what-is-an-ai-pc-should-you-buy-one-in-2024-heres-the-ces-verdict/ With AI being the flavor of the times, one hears of the technology being deployed for everything except for basic human functions. So, it is no surprise that one recently came across the term AI PC. Now what is that beast, I wondered? Obviously, it means a personal computer that uses artificial intelligence technology, but how exactly is it different from a regular computer, and does it radically alter or promise to alter everything to do with personal computing? As with most things AI hype precedes sober reality, so I decided to find out for myself. According to the chip-making behemoth Intel, AI PCs possess the capability to enhance everything ranging from productivity, entertainment, and security to creativity and security. It comprises a CPU apparently to handle smaller workloads requiring low potency, a GPU or Graphics Processing Unit for large workloads requiring parallel throughput, and an NPU Neural Processing Unit that is ideal for what Intel calls sustained heavily used AI workloads even as it consumes low power and provides greater efficiency. [1] [1] This is all very well and well appreciated, but how is an AI PC different from a regular PC ? but how is an AI PC different from a regular PC Apparently, what these supercharged PCs do is enable the speedy execution of AI tasks, even while consuming less energy. What's more, you no longer need to send sensitive data to cloud-based AI servers in order to get them processed. With their ability to operate sans an internet connection, these PCs provide enhanced security because they store the data locally. [2] [2] All the major PC manufacturers like DEL, HP, and Lenovo are betting big on AI PC systems incorporating NPUs. Apple, of course, has already cornered 60% of the AI PC market, with its products powered by its M series chip with a neural engine. As a matter of fact, AI PCs made up as much as 14% of PC sales in the second quarter, pointing to their growing popularity. [3] [3] Should You Buy an AI PC? Should You Buy an AI PC? Going by all the marketing hype that one hears about how AI PCs are helping usher in a new dawn in personal computing what with the technology giants like Microsoft extolling its virtues, one might think that you would lose out if you didn't buy one pronto. While an AI PC might actually possess the mind-boggling potential to do wonderful things that we can't even begin to imagine at present, the question to ask yourself is should you buy yourself one now? should you buy yourself one now? The NPU, which lies at the heart of an AI PC sure has great untapped potential, but since Microsoft isn't yet up to speed with it and can't leverage it much in any really impactful manner and with third-party application developers lagging behind as well, this may not be the best time to plonk your hard earned money on the purchase of an AI PC. An AI PC can at best get you access to Windows Studio Effect which uses a PC’s NPU to enhance video and audio in video calls. If that is something that you simply can't do without, by all means, go and buy yourself one of these new toys. [4] [4] Like with most new path-breaking (hopefully) technologies, one does not know how successful AI PCs eventually turn out to be, given that one really has no clear idea about what these wondrous machines can really achieve (remember the Metaverse, anyone?). One might want to wait for Windows 12 to be launched so that developers can sink their teeth into the new-fangled AI chips and figure out how these can be best leveraged. [5] [5] If you are one of those who imagine that staying ahead of the curve will help you deal with future shock in a comprehensive manner, go right ahead and buy an AI PC at this very moment. The rest of us can bide our time for now. [1] https://www.intel.com/content/www/us/en/products/docs/processors/core-ultra/ai-pc.html#:~:text=the%20close%20button.-,What%20is%20an%20AI%20PC%3F,tasks%20locally%20and%20more%20efficiently. [1] [2] https://www.zdnet.com/article/what-is-an-ai-pc-and-should-you-buy-one/ [2] [3] https://www.reuters.com/technology/artificial-intelligence/ai-pcs-made-up-14-quarterly-personal-computer-shipments-canalys-says-2024-08-13/ [3] [4] https://www.pcworld.com/article/2236372/does-your-next-laptop-really-need-to-be-an-ai-pc.html [4] [5] https://www.forbes.com/sites/barrycollins/2024/01/10/what-is-an-ai-pc-should-you-buy-one-in-2024-heres-the-ces-verdict/ [5]

Is There Something Called an AI PC?

The U.S. Government: Google Has Monopoly Power In The U.S. General Search Services Market

Counterfeiting is a massive problem that damages economies, companies, and customers. Unfortunately, conventional anti-counterfeit measures like labels, hidden patterns, and tracking tags are easy to copy, rendering them useless. What does artificial intelligence do differently that makes it an effective tool? How Big of a Problem Is Counterfeiting? Counterfeiting is a global problem that affects every major industry. It happens everywhere, from the smallest flea market to the largest e-commerce platform. With the emergence of online shopping and international shipping, even small-business owners have criminals infringing on their intellectual property. Counterfeits have multiple points of entry, which makes tracking them down challenging: Suppliers hire subcontractors who create copies and supply chain professionals take cash to look the other way.
Sellers accept returns, not realizing the buyer kept the original and sent back a fake.
Wholesale distributors unwittingly take in forgeries and resell them en masse.
Scammers set up stands on the street, promising passersby high-end products for impossibly cheap prices. Sometimes, marketplaces are aware of counterfeiting but don’t do anything about it. Many want to preserve their identity as the neutral intermediary. They’re worried they’ll lose profits if they do anything to upset their tentative role in the buyer-and-seller balance, so they sit by to keep customers returning to their storefront — even if it means those people end up with fakes. Does Counterfeiting Hurt Anyone? Counterfeiting harms economies, companies, and individuals. Governments miss out on taxes, businesses lose revenue from potential sales, and customers end up with forged items. It’s not just handbags and brand-name shirts that get copied — pharmaceutical products, electronics, children’s toys, car parts, and kitchen equipment get faked, too. Since counterfeiters aren’t held to the same standard as companies, they often make their copies in unhygienic conditions or use hazardous banned materials. These differences could have a severe, lasting impact when using fake items like baby carriers, vitamins, airbags, lithium-ion batteries, or bike helmets. Unfortunately, such situations aren’t hypothetical. Federal investigators say there was recently a $230 million scheme to counterfeit lifesaving medication. The fraudsters swapped the real pills for an antipsychotic. One person temporarily lost the ability to walk and talk after unknowingly taking it instead of his regular prescription. Each fake product that enters the supply chain results in a drop in revenue, domestic job losses, and misplaced customer anger. Seized counterfeit products had a total manufacturer’s suggested retail price of over $2.7 billion in 2023, highlighting how much companies stand to lose from each fraudulent sale. AI’s Role in Anti-Counterfeiting Efforts Algorithm-driven anti-counterfeit technology is necessary because detecting and preventing fake goods from entering the supply chain is too big for people to manage manually. Even an entire team of professionals can’t trace every shipment in real time as it moves across countries and changes hands — only AI can handle such a massive dataset. Another reason to use this technology to detect and prevent counterfeits is because the counterfeiters already use it themselves. For instance, on Amazon, some listings have deceptive titles like, “I’m sorry, but I cannot fulfill this request. It goes against OpenAI use policy.” Businesses that want to eliminate fakes from the supply chain must fight fire with fire. Committing to supply chain transparency is often one of the most effective ways to implement the processes needed for mapping and traceability. Companies would benefit from using chatbots to disclose their suppliers and logistics vendors to curious customers. Besides, AI is a powerful tool capable of automating tasks and carrying out orders with little to no human intervention. While it is already incredibly popular, indicators suggest it will only continue gaining traction. According to one estimate, it’s expected to add $15.7 trillion to the global economy by 2030. How AI Can Detect Counterfeit Products AI can detect potential counterfeits in marketplaces by monitoring geolocation, product images, and sales figures. Advanced machine learning subsets like deep learning models can cover hundreds of listings in a second, picking up on anomalies like abnormally long shipping times or a high number of returns. Natural language processing algorithms can analyze reviews or listing information and report potential counterfeiters. They can monitor online marketplaces for words or phrases that indicate someone is attempting to infringe upon another person’s intellectual property, meaning fake listings get identified and taken down much faster. AI can provide real-time updates as shipments move through the supply chain when paired with Internet of Things sensors or tracking tools. This way, business leaders can receive notifications as soon as unusual activity occurs, enabling them to detect when forgeries enter the supply chain. How AI Can Prevent Counterfeit Products AI can prevent fake goods from entering the supply chain by flagging suspicious activity or triggering a predefined incident response like banning an anomalous listing or auditing logs. This technology can even identify repeat offenders, helping companies eliminate persistent counterfeiters for good. It can also stop people who knowingly buy forgeries. About 52% of consumers intentionally purchase counterfeit items — and 21% of them do so frequently. Fortunately, AI can add value to products to make counterfeits less desirable. For example, chatbots can offer valuable insights, product details, or information on the dangers of fake goods to help people understand the importance of purchasing genuine goods. Businesses can also embed this technology into their systems, vehicles, or packaging. A research group has already developed an AI-generated cryptographic code that can be embedded into containers of any size. It essentially makes counterfeiting impossible because it generates a hidden authentication code that is only detectable by the product’s manufacturers. The Future of Using AI to Prevent Fakes As more companies become used to using AI to detect and prevent counterfeit products in the supply chain, the number of applications will likely grow. Supply chain professionals should expect to see their role expand. It may one day become the standard technology for shipment traceability. Counterfeiting is a massive problem that damages economies, companies, and customers. Unfortunately, conventional anti-counterfeit measures like labels, hidden patterns, and tracking tags are easy to copy, rendering them useless. What does artificial intelligence do differently that makes it an effective tool? Counterfeiting is a massive problem that damages economies, companies, and customers. Unfortunately, conventional anti-counterfeit measures like labels, hidden patterns, and tracking tags are easy to copy, rendering them useless. What does artificial intelligence do differently that makes it an effective tool? How Big of a Problem Is Counterfeiting? How Big of a Problem Is Counterfeiting? Counterfeiting is a global problem that affects every major industry. It happens everywhere, from the smallest flea market to the largest e-commerce platform. With the emergence of online shopping and international shipping, even small-business owners have criminals infringing on their intellectual property. Counterfeits have multiple points of entry, which makes tracking them down challenging: Suppliers hire subcontractors who create copies and supply chain professionals take cash to look the other way. Sellers accept returns, not realizing the buyer kept the original and sent back a fake. Wholesale distributors unwittingly take in forgeries and resell them en masse. Scammers set up stands on the street, promising passersby high-end products for impossibly cheap prices. Suppliers hire subcontractors who create copies and supply chain professionals take cash to look the other way. Sellers accept returns, not realizing the buyer kept the original and sent back a fake. Wholesale distributors unwittingly take in forgeries and resell them en masse. Scammers set up stands on the street, promising passersby high-end products for impossibly cheap prices. Sometimes, marketplaces are aware of counterfeiting but don’t do anything about it. Many want to preserve their identity as the neutral intermediary. They’re worried they’ll lose profits if they do anything to upset their tentative role in the buyer-and-seller balance, so they sit by to keep customers returning to their storefront — even if it means those people end up with fakes. Does Counterfeiting Hurt Anyone? Counterfeiting harms economies, companies, and individuals. Governments miss out on taxes, businesses lose revenue from potential sales, and customers end up with forged items. It’s not just handbags and brand-name shirts that get copied — pharmaceutical products, electronics, children’s toys, car parts, and kitchen equipment get faked, too. Since counterfeiters aren’t held to the same standard as companies, they often make their copies in unhygienic conditions or use hazardous banned materials. These differences could have a severe, lasting impact when using fake items like baby carriers, vitamins, airbags, lithium-ion batteries, or bike helmets. Unfortunately, such situations aren’t hypothetical. Federal investigators say there was recently a $230 million scheme to counterfeit lifesaving medication. The fraudsters swapped the real pills for an antipsychotic. One person temporarily lost the ability to walk and talk after unknowingly taking it instead of his regular prescription. a $230 million scheme to counterfeit a $230 million scheme to counterfeit Each fake product that enters the supply chain results in a drop in revenue, domestic job losses, and misplaced customer anger. Seized counterfeit products had a total manufacturer’s suggested retail price of over $2.7 billion in 2023, highlighting how much companies stand to lose from each fraudulent sale. price of over $2.7 billion price of over $2.7 billion AI’s Role in Anti-Counterfeiting Efforts Algorithm-driven anti-counterfeit technology is necessary because detecting and preventing fake goods from entering the supply chain is too big for people to manage manually. Even an entire team of professionals can’t trace every shipment in real time as it moves across countries and changes hands — only AI can handle such a massive dataset. Another reason to use this technology to detect and prevent counterfeits is because the counterfeiters already use it themselves. For instance, on Amazon, some listings have deceptive titles like, “I’m sorry, but I cannot fulfill this request. It goes against OpenAI use policy.” Businesses that want to eliminate fakes from the supply chain must fight fire with fire. some listings have deceptive titles some listings have deceptive titles Committing to supply chain transparency is often one of the most effective ways to implement the processes needed for mapping and traceability. Companies would benefit from using chatbots to disclose their suppliers and logistics vendors to curious customers. one of the most effective ways one of the most effective ways Besides, AI is a powerful tool capable of automating tasks and carrying out orders with little to no human intervention. While it is already incredibly popular, indicators suggest it will only continue gaining traction. According to one estimate, it’s expected to add $15.7 trillion to the global economy by 2030. expected to add $15.7 trillion expected to add $15.7 trillion How AI Can Detect Counterfeit Products AI can detect potential counterfeits in marketplaces by monitoring geolocation, product images, and sales figures. Advanced machine learning subsets like deep learning models can cover hundreds of listings in a second, picking up on anomalies like abnormally long shipping times or a high number of returns. Natural language processing algorithms can analyze reviews or listing information and report potential counterfeiters. They can monitor online marketplaces for words or phrases that indicate someone is attempting to infringe upon another person’s intellectual property, meaning fake listings get identified and taken down much faster. AI can provide real-time updates as shipments move through the supply chain when paired with Internet of Things sensors or tracking tools. This way, business leaders can receive notifications as soon as unusual activity occurs, enabling them to detect when forgeries enter the supply chain. How AI Can Prevent Counterfeit Products AI can prevent fake goods from entering the supply chain by flagging suspicious activity or triggering a predefined incident response like banning an anomalous listing or auditing logs. This technology can even identify repeat offenders, helping companies eliminate persistent counterfeiters for good. It can also stop people who knowingly buy forgeries. About 52% of consumers intentionally purchase counterfeit items — and 21% of them do so frequently. Fortunately, AI can add value to products to make counterfeits less desirable. For example, chatbots can offer valuable insights, product details, or information on the dangers of fake goods to help people understand the importance of purchasing genuine goods. 52% of consumers intentionally purchase 52% of consumers intentionally purchase Businesses can also embed this technology into their systems, vehicles, or packaging. A research group has already developed an AI-generated cryptographic code that can be embedded into containers of any size. It essentially makes counterfeiting impossible because it generates a hidden authentication code that is only detectable by the product’s manufacturers. essentially makes counterfeiting impossible essentially makes counterfeiting impossible The Future of Using AI to Prevent Fakes As more companies become used to using AI to detect and prevent counterfeit products in the supply chain, the number of applications will likely grow. Supply chain professionals should expect to see their role expand. It may one day become the standard technology for shipment traceability.

Using AI to Combat Counterfeit Goods in the Supply Chain

Founded in 2017, Morpheus.Network, a Toronto-based company, has harnessed blockchain technology to address the complex challenges that plague global logistics and supply chain. Dan Weinberger, co-founder and CEO of Morpheus.Network, brings over 25 years of supply chain expertise to the table. His deep understanding of the industry's pain points drove the creation of Morpheus.Network. "The inspiration was a bit selfish," Weinberger admits. "I knew the headaches I was experiencing first-hand—compliance, documentation, and filing. We envisioned a solution that could alleviate these burdens." Weinberger and his long-time friend and co-founder, Noam Eppel, conceptualized Morpheus.Network during a conversation about the inefficiencies they faced. A simple sketch on a napkin laid the foundation for a comprehensive blockchain-based solution that integrates seamlessly with existing systems. The napkin still exists and is framed in Weinberger’s office for posterity. Morpheus.Network employs blockchain technology to ensure all stakeholders in the supply chain have access to the same immutable data. "Blockchain's inherent advantage is that you can trust the data," Weinberger explains. "Everyone views the same document at the same time, regardless of location. “It’s an amazing use of blockchain where everyone's viewing the same document at the same time, in a digital form, from around the world, doesn't matter. It doesn't matter if you are in China, United States or down South America, you're viewing that exact same document on chain,” he says. This transparency eliminates errors and inefficiencies, paving the way for smoother operations. Smart contracts further enhance the system by automating workflows. From IoT devices setting up geofences to customs documentation and delivery notifications, Morpheus.Network's automated processes ensure compliance and accuracy, preventing costly delays and fines. “To give you an example, if you're importing a product into the United States, you need to file a ISF (Import Security Filing) beforehand. If you don’t, there may be delays, expensive fees or possibly your goods will be sent back to the country of origin. “So, we avoid all that by making sure we have these automated workflows. Finally, we make sure the documentation is available in time, as well as making sure that all the documents are accurate, without any human error often associated with copy and paste exercises.” This ensures trusted, accurate and transparent data. “Everyone is viewing live, immutable data is immutable. The inherent advantage of blockchain is that you can trust the data on chain. And when there are different stakeholders from different places around the world, everyone can trust the data and know that original data has never been manipulated.” Addressing Global Supply Chain Challenges Supply chains are notoriously complex, involving numerous moving parts, compliance requirements, and geopolitical considerations. Morpheus.Network tackles these challenges head-on, with solutions tailored to specific industry needs, including food certification and cross-border trade. A notable example is their recent project with the Government of Mongolia. Morpheus.Network digitized the country's certificate of origin process, transforming a manual, paper-based system into a streamlined, blockchain-enabled digital process. "It's about making things run smoother and faster," says Weinberger. "We've shown Mongolia can have one of the most advanced certificate of origin solutions in the world." "This is the fourth government project we've undertaken," remarked Dan Weinberger. "I have also collaborated extensively with the United Nations, where I teach a masterclass on paperless trade. Many of the accolades we receive for our work with governments, such as in Argentina and Uganda, stem from the credibility we've built through our projects with other governments and the UN." Weinberger elaborated on the scope of their work, again referencing the example of the Certificate of Origin solution implemented for Mongolia. "Currently, we're participating in a European sandbox initiative focused on digitalizing documentation to streamline shipping across the EU." These efforts exemplify the company's strategy of expanding projects with partners and clients, proving their effectiveness, and then replicating these successes with new partners. "It's about growing projects, proving our capabilities, and then scaling up by working with the next partner or client," Weinberger explained. Adopting advanced supply chain techniques is no longer optional—it's essential for staying competitive. Companies that have already integrated these innovative methods are reaping significant benefits, while those that lag behind risk falling by the wayside, unable to compete with more technologically advanced peers. In the realm of supply chains, efficiency isn't just about speeding up shipping processes. It's about ensuring accuracy and compliance at every step. “Take the food and beverage industry, for example. Proper food certification is a critical part of the supply chain. Companies can't simply decide to ship products without the necessary food certificates. At Morpheus.Network, we incorporate food certification into supply chain documentation, ensuring that everything is handled correctly, especially when dealing with cross-border shipments. “Our approach integrates various elements—food certification, customs documentation, and more—into an automated system. This automation tackles existing inefficiencies, making processes smoother and more reliable,” he says. “It's exciting to engage with companies about their current practices and introduce them to more efficient methods. The biggest challenge, however, is education. Many businesses are not aware that there are better ways to manage their supply chains. Our goal is to show them how these advanced techniques can transform their operations, leading to greater efficiency and competitiveness.” Morpheus.Network's agnostic middleware approach sets it apart from competitors. Instead of replacing existing IT systems, it integrates seamlessly with them, supporting various ERP and TMS systems. This flexibility makes it easier for companies to adopt Morpheus.Network's solutions without overhauling their entire infrastructure. “We enable companies to continue using their existing IT stacks, whether they're utilizing SAP ERP, Oracle ERP, JD Edwards, Sage, Microsoft Dynamics, or other systems. Our middleware seamlessly integrates with various Transportation Management Systems (TMS), such as Magaya and other Cloud-based solutions, without the need to replace any of these systems. “Our middleware sits between these IT systems, embracing the specific technologies companies already use. This approach simplifies the integration of our solutions into their current processes. By being an agnostic middleware, we differentiate ourselves from others who insist on replacing existing systems with their own. Instead, we enhance backend automation based on the current systems companies have in place. “This strategy has proven advantageous. For example, we have successfully integrated our solutions with over 30 different ERPs into a single system. If we had required companies to switch to a single ERP like SAP, it would have involved a multimillion-dollar implementation. Instead, we incorporated the data from their existing systems into their supply chain at a much lower cost.” This approach not only preserves companies' existing investments but also enhances efficiency and integration, making Morpheus.Network a valuable partner in optimizing supply chain management. Currently, the company is expanding its reach to small and medium enterprises (SMEs) with a new product called Speed.supply. This self-managed platform allows SMEs to automate documentation, insurance, and IoT integration, with blockchain ensuring data integrity. Looking ahead, Weinberger sees blockchain as the backbone of data integrity, with AI and machine learning revolutionizing demand forecasting, maintenance, and congestion avoidance. "Making supply chains more efficient is a $2 trillion opportunity," Weinberger notes, emphasizing the importance of technology in driving these efficiencies. “Right now, we're thinking about our kids and their future. When it comes to carbon emissions, there's nothing in this world that emits carbon not even close, as much as the supply chains of businesses. 90% of all carbon emissions are the supply chains of businesses” (a statistic from the EPA (Environmental Protection Agency) Morpheus.Network's success is underpinned by a collaborative and innovative company culture. "We operate with a flat hierarchy," says Weinberger. "Everyone feels ownership of their projects and understands the bigger picture—making supply chains more efficient for the environment and the economy." As Morpheus.Network continues to grow, it remains dedicated to transforming the supply chain industry, proving that technological innovation and sustainability can go hand in hand. Founded in 2017, Morpheus.Network, a Toronto-based company, has harnessed blockchain technology to address the complex challenges that plague global logistics and supply chain. Dan Weinberger, co-founder and CEO of Morpheus.Network, brings over 25 years of supply chain expertise to the table. His deep understanding of the industry's pain points drove the creation of Morpheus.Network. "The inspiration was a bit selfish," Weinberger admits. "I knew the headaches I was experiencing first-hand—compliance, documentation, and filing. We envisioned a solution that could alleviate these burdens." Weinberger and his long-time friend and co-founder, Noam Eppel, conceptualized Morpheus.Network during a conversation about the inefficiencies they faced. A simple sketch on a napkin laid the foundation for a comprehensive blockchain-based solution that integrates seamlessly with existing systems. The napkin still exists and is frame d in Weinberger’s office for posterity. d Morpheus.Network employs blockchain technology to ensure all stakeholders in the supply chain have access to the same immutable data. "Blockchain's inherent advantage is that you can trust the data," Weinberger explains. "Everyone views the same document at the same time, regardless of location. “It’s an amazing use of blockchain where everyone's viewing the same document at the same time, in a digital form, from around the world, doesn't matter. It doesn't matter if you are in China, United States or down South America, you're viewing that exact same document on chain,” he say s. s. This transparency eliminates errors and inefficiencies, paving the way for smoother operations. Smart contracts further enhance the system by automating workflows. From IoT devices setting up geofences to customs documentation and delivery notifications, Morpheus.Network's automated processes ensure compliance and accuracy, preventing costly delays and fines. “To give you an example, if you're importing a product into the United States, you need to file a ISF (Import Security Filing) beforehand. If you don’t, there may be delays, expensive fees or possibly your goods will be sent back to the country of origin. “So, we avoid all that by making sure we have these automated workflows. Finally, we make sure the documentation is available in time, as well as making sure that all the documents are accurate, without any human error often associated with copy and paste exercises.” This ensures trusted, accurate and transparent data. “Everyone is viewing live, immutable data is immutable. The inherent advantage of blockchain is that you can trust the data on chain. And when there are different stakeholders from different places around the world, everyone can trust the data and know that original data has never been manipulated.” Addressing Global Supply Chain Challenges Addressing Global Supply Chain Challenges Supply chains are notoriously complex, involving numerous moving parts, compliance requirements, and geopolitical considerations. Morpheus.Network tackles these challenges head-on, with solutions tailored to specific industry needs, including food certification and cross-border trade. A notable example is their recent project with the Government of Mongolia. Morpheus.Network digitized the country's certificate of origin process, transforming a manual, paper-based system into a streamlined, blockchain-enabled digital process. "It's about making things run smoother and faster," says Weinberger. "We've shown Mongolia can have one of the most advanced certificate of origin solutions in the world." "This is the fourth government project we've undertaken," remarked Dan Weinberger. "I have also collaborated extensively with the United Nations, where I teach a masterclass on paperless trade. Many of the accolades we receive for our work with governments, such as in Argentina and Uganda, stem from the credibility we've built through our projects with other governments and the UN." Weinberger elaborated on the scope of their work, again referencing the example of the Certificate of Origin solution implemented for Mongolia. "Currently, we're participating in a European sandbox initiative focused on digitalizing documentation to streamline shipping across the EU." These efforts exemplify the company's strategy of expanding projects with partners and clients, proving their effectiveness, and then replicating these successes with new partners. "It's about growing projects, proving our capabilities, and then scaling up by working with the next partner or client," Weinberger explained. Adopting advanced supply chain techniques is no longer optional—it's essential for staying competitive. Companies that have already integrated these innovative methods are reaping significant benefits, while those that lag behind risk falling by the wayside, unable to compete with more technologically advanced peers. In the realm of supply chains, efficiency isn't just about speeding up shipping processes. It's about ensuring accuracy and compliance at every step. “Take the food and beverage industry, for example. Proper food certification is a critical part of the supply chain. Companies can't simply decide to ship products without the necessary food certificates. At Morpheus.Network, we incorporate food certification into supply chain documentation, ensuring that everything is handled correctly, especially when dealing with cross-border shipments. “Our approach integrates various elements—food certification, customs documentation, and more—into an automated system. This automation tackles existing inefficiencies, making processes smoother and more reliable,” he says. “It's exciting to engage with companies about their current practices and introduce them to more efficient methods. The biggest challenge, however, is education. Many businesses are not aware that there are better ways to manage their supply chains. Our goal is to show them how these advanced techniques can transform their operations, leading to greater efficiency and competitiveness.” Morpheus.Network's agnostic middleware approach sets it apart from competitors. Instead of replacing existing IT systems, it integrates seamlessly with them, supporting various ERP and TMS systems. This flexibility makes it easier for companies to adopt Morpheus.Network's solutions without overhauling their entire infrastructure. “We enable companies to continue using their existing IT stacks, whether they're utilizing SAP ERP, Oracle ERP, JD Edwards, Sage, Microsoft Dynamics, or other systems. Our middleware seamlessly integrates with various Transportation Management Systems (TMS), such as Magaya and other Cloud-based solutions, without the need to replace any of these systems. “Our middleware sits between these IT systems, embracing the specific technologies companies already use. This approach simplifies the integration of our solutions into their current processes. By being an agnostic middleware, we differentiate ourselves from others who insist on replacing existing systems with their own. Instead, we enhance backend automation based on the current systems companies have in place. “This strategy has proven advantageous. For example, we have successfully integrated our solutions with over 30 different ERPs into a single system. If we had required companies to switch to a single ERP like SAP, it would have involved a multimillion-dollar implementation. Instead, we incorporated the data from their existing systems into their supply chain at a much lower cost.” This approach not only preserves companies' existing investments but also enhances efficiency and integration, making Morpheus.Network a valuable partner in optimizing supply chain management. Currently, the company is expanding its reach to small and medium enterprises (SMEs) with a new product called Speed.supply. This self-managed platform allows SMEs to automate documentation, insurance, and IoT integration, with blockchain ensuring data integrity. Looking ahead, Weinberger sees blockchain as the backbone of data integrity, with AI and machine learning revolutionizing demand forecasting, maintenance, and congestion avoidance. "Making supply chains more efficient is a $2 trillion opportunity," Weinberger notes, emphasizing the importance of technology in driving these efficiencies. “Right now, we're thinking about our kids and their future. When it comes to carbon emissions, there's nothing in this world that emits carbon not even close, as much as the supply chains of businesses. 90% of all carbon emissions are the supply chains of businesses” (a statistic from the EPA (Environmental Protection Agency) Morpheus.Network's success is underpinned by a collaborative and innovative company culture. "We operate with a flat hierarchy," says Weinberger. "Everyone feels ownership of their projects and understands the bigger picture—making supply chains more efficient for the environment and the economy." As Morpheus.Network continues to grow, it remains dedicated to transforming the supply chain industry, proving that technological innovation and sustainability can go hand in hand.

Morpheus.Network: Changing the Face of  Global Supply Chains

Self-driving cars always seem to be just out of reach. Technology improves and people make bold claims about when they will become the norm, only for new setbacks to further delay their inevitable rollout. Autonomous long-haul trucks, however, could arrive earlier. Semis often have relatively straightforward routes. Driverless AI would have an easier time navigating more predictable highway traffic than pedestrian-heavy inner cities. Still, the future of autonomous big rigs in the supply chain is uncertain. Businesses and government bodies should consider the potential consequences — both positive and negative. Positive Consequences of Autonomous Trucks Supply chains would gain a lot from driverless trucking. When this technology becomes reliable enough for logistics professionals to use, it could transform the industry for the better. 1. Improved Safety The most important advantage of autonomous trucks is that once they become accurate enough, they’re safer. As common as driving is, it’s a dangerous profession. That’s largely because humans make a lot of risky mistakes. A whopping 60% of people admit to driving sleepy, slowing their reaction time and making them likely to miss incoming hazards. Drunk and distracted drivers pose even more risks. Robots can’t get tired or intoxicated and don’t text, so they’d eliminate these dangers from the supply chain. Self-driving features can improve driver safety even before fully autonomous semis are a thing. Automated lane assist and braking can fill the gaps when truckers have momentary lapses in judgment. 2. Faster Shipping Driverless vehicles would also make supply chains more efficient. While autonomous trucks won’t necessarily drive faster than humans, they can travel for longer. Truckers can only drive for 11 hours and be on-duty — driving or not — for 14 hours before taking a 10-hour break. This law is an important part of road safety, but it significantly extends shipping times. However, it wouldn’t apply to an autonomous truck. Self-driving vehicles could travel indefinitely, only stopping for fuel. As a result, shipments would reach their destinations in a fraction of the time. Such speed would mean lower operating costs and less disruption for companies, and greater convenience for consumers. 3. Overcoming Worker Shortages Similarly, autonomous trucks would help logistics businesses become more productive. A driver shortage has emerged as e-commerce has boomed, with fewer people entering the trucking sector. Some industry insiders say the nation is short 64,000 truck drivers as of 2023, and almost one-third are 55 or older. Before long, those aging employees will retire, worsening the labor gap. Self-driving vehicles are a convenient solution to this problem. A smaller workforce isn’t a big issue when businesses don’t need as many workers to reach the same level of productivity. Overcoming the trucker shortage lets companies run shipments more frequently. Consequently, delivery timelines would fall even further, and supply chains could prevent disruptions. 4. More Sustainability Driverless semis also bring environmental benefits. It’s no secret that transportation needs to improve its sustainability. The sector consumes 125 million gallons of diesel every day, leading to huge greenhouse gas emissions. While autonomous tech wouldn’t eliminate those numbers, it can reduce them. Trucks waste a lot of fuel through poor driving practices like idling and harsh acceleration. Businesses can program a self-driving big rig to avoid these behaviors, minimizing the diesel they consume. Emissions will fall as supply chains use less fuel to do the same work. Similar programming steps could also stretch electric vehicle ranges. That way, the industry could switch to carbon-free shipping methods without sacrificing productivity. Negative Consequences of Autonomous Trucks As impressive as those benefits are, autonomous trucks also have their fair share of negative implications. The downsides deserve just as much attention for self-driving technology to proceed safely. 1. Safety Concerns Driverless semis will be safer than human truckers once they reach a certain reliability standard. The problem is that they could be more dangerous until they get to that point. Self-driving AI has to anticipate billions of potential situations, and even then, it can only interpret things if its sensors work well. Right now, things like rain, snow, fog, and even reflections pose difficulties, leading to crashes. People can also misread signs and fail to see incoming obstacles, but they’re at least more familiar with common hazards than driverless cars. Traffic involves a lot of unpredictable behavior and subtle nuances people take for granted. AI struggles to understand such complexities, which could lead to devastating consequences in the right situation. 2. Regulatory Complications Autonomous trucks also raise legal questions when events like this happen. Currently, there are no specific laws for determining liability with self-driving cars. Who’s responsible for an accident involving one of these semis? The logistics company? The truck manufacturer? It’s harder to decide without another human party. Insuring a driverless truck may be challenging without concrete regulations on the topic. Consequently, supply chain organizations will hesitate to embrace them before laws catch up with technology. Legislation will eventually adapt, but it will slow adoption before it does. 3. Job Loss As with any type of automation, there are questions about fair employment practices. The transportation industry may face a labor shortage today, but it still employs 3.54 million drivers in the U.S. Self-driving vehicles may threaten these people’s jobs. One would hope that companies would use autonomous semis to fill the gap instead of taking all open positions, but who’s to say they will? The temptation to cut labor costs may lead businesses to automate all shipments. History proves technology creates more jobs than it destroys in the long run. However, these new roles require a different skill set. Consequently, while employment may even out over time, driverless technology could cause some initial job disruption. Self-Driving Trucks Face an Uncertain Future It’s still unclear when autonomous trucking will become a viable option. When it does, businesses have several complications to work through. Driverless vehicles could be a massive help for companies and the customers they serve. At the same time, improper use or regulation of this technology could worsen things more than it improves. Organizations and government agencies should consider these questions today to ensure a clearer, safer future. Self-driving cars always seem to be just out of reach. Technology improves and people make bold claims about when they will become the norm, only for new setbacks to further delay their inevitable rollout. Autonomous long-haul trucks, however, could arrive earlier. Self-driving cars always seem to be just out of reach. Technology improves and people make bold claims about when they will become the norm, only for new setbacks to further delay their inevitable rollout. Autonomous long-haul trucks, however, could arrive earlier. Semis often have relatively straightforward routes. Driverless AI would have an easier time navigating more predictable highway traffic than pedestrian-heavy inner cities. Still, the future of autonomous big rigs in the supply chain is uncertain. Businesses and government bodies should consider the potential consequences — both positive and negative. Positive Consequences of Autonomous Trucks Supply chains would gain a lot from driverless trucking. When this technology becomes reliable enough for logistics professionals to use, it could transform the industry for the better. 1. Improved Safety The most important advantage of autonomous trucks is that once they become accurate enough, they’re safer. As common as driving is, it’s a dangerous profession. That’s largely because humans make a lot of risky mistakes. A whopping 60% of people admit to driving sleepy , slowing their reaction time and making them likely to miss incoming hazards. Drunk and distracted drivers pose even more risks. Robots can’t get tired or intoxicated and don’t text, so they’d eliminate these dangers from the supply chain. 60% of people admit to driving sleepy 60% of people admit to driving sleepy Self-driving features can improve driver safety even before fully autonomous semis are a thing. Automated lane assist and braking can fill the gaps when truckers have momentary lapses in judgment. 2. Faster Shipping Driverless vehicles would also make supply chains more efficient. While autonomous trucks won’t necessarily drive faster than humans, they can travel for longer. Truckers can only drive for 11 hours and be on-duty — driving or not — for 14 hours before taking a 10-hour break. This law is an important part of road safety, but it significantly extends shipping times. However, it wouldn’t apply to an autonomous truck. only drive for 11 hours only drive for 11 hours Self-driving vehicles could travel indefinitely, only stopping for fuel. As a result, shipments would reach their destinations in a fraction of the time. Such speed would mean lower operating costs and less disruption for companies, and greater convenience for consumers. 3. Overcoming Worker Shortages Similarly, autonomous trucks would help logistics businesses become more productive. A driver shortage has emerged as e-commerce has boomed, with fewer people entering the trucking sector. Some industry insiders say the nation is short 64,000 truck drivers as of 2023, and almost one-third are 55 or older. short 64,000 truck drivers short 64,000 truck drivers Before long, those aging employees will retire, worsening the labor gap. Self-driving vehicles are a convenient solution to this problem. A smaller workforce isn’t a big issue when businesses don’t need as many workers to reach the same level of productivity. Overcoming the trucker shortage lets companies run shipments more frequently. Consequently, delivery timelines would fall even further, and supply chains could prevent disruptions. 4. More Sustainability Driverless semis also bring environmental benefits. It’s no secret that transportation needs to improve its sustainability. The sector consumes 125 million gallons of diesel every day, leading to huge greenhouse gas emissions. While autonomous tech wouldn’t eliminate those numbers, it can reduce them. 125 million gallons of diesel 125 million gallons of diesel Trucks waste a lot of fuel through poor driving practices like idling and harsh acceleration. Businesses can program a self-driving big rig to avoid these behaviors, minimizing the diesel they consume. Emissions will fall as supply chains use less fuel to do the same work. Similar programming steps could also stretch electric vehicle ranges. That way, the industry could switch to carbon-free shipping methods without sacrificing productivity. Negative Consequences of Autonomous Trucks As impressive as those benefits are, autonomous trucks also have their fair share of negative implications. The downsides deserve just as much attention for self-driving technology to proceed safely. 1. Safety Concerns Driverless semis will be safer than human truckers once they reach a certain reliability standard. The problem is that they could be more dangerous until they get to that point. Self-driving AI has to anticipate billions of potential situations , and even then, it can only interpret things if its sensors work well. Right now, things like rain, snow, fog, and even reflections pose difficulties, leading to crashes. People can also misread signs and fail to see incoming obstacles, but they’re at least more familiar with common hazards than driverless cars. billions of potential situations billions of potential situations Traffic involves a lot of unpredictable behavior and subtle nuances people take for granted. AI struggles to understand such complexities, which could lead to devastating consequences in the right situation. 2. Regulatory Complications Autonomous trucks also raise legal questions when events like this happen. Currently, there are no specific laws for determining liability with self-driving cars. Who’s responsible for an accident involving one of these semis? The logistics company? The truck manufacturer? It’s harder to decide without another human party. no specific laws for determining liability no specific laws for determining liability Insuring a driverless truck may be challenging without concrete regulations on the topic. Consequently, supply chain organizations will hesitate to embrace them before laws catch up with technology. Legislation will eventually adapt, but it will slow adoption before it does. 3. Job Loss As with any type of automation, there are questions about fair employment practices. The transportation industry may face a labor shortage today, but it still employs 3.54 million drivers in the U.S. Self-driving vehicles may threaten these people’s jobs. employs 3.54 million drivers employs 3.54 million drivers One would hope that companies would use autonomous semis to fill the gap instead of taking all open positions, but who’s to say they will? The temptation to cut labor costs may lead businesses to automate all shipments. History proves technology creates more jobs than it destroys in the long run. However, these new roles require a different skill set. Consequently, while employment may even out over time, driverless technology could cause some initial job disruption. Self-Driving Trucks Face an Uncertain Future It’s still unclear when autonomous trucking will become a viable option. When it does, businesses have several complications to work through. Driverless vehicles could be a massive help for companies and the customers they serve. At the same time, improper use or regulation of this technology could worsen things more than it improves. Organizations and government agencies should consider these questions today to ensure a clearer, safer future.

7 Consequences of Autonomous Trucks in the Supply Chain

Distributed Ledger Technology (DLT) is often paired with the Internet of Things (IoT) to get some interesting and automatic features in the real world, also registered and handled digitally. IoT devices are physical objects designed to connect to the Internet and can also perform effectively on a distributed network. Blockchains weren’t really built to face challenges like high energy costs or lack of needed speed. A Directed Acyclic Graph (DAG) like Obyte could be a better alternative, allowing inexpensive, fast, secure, and highly decentralized transactions or immutable data recording. In this vein, let’s look into some potential use cases for the powerful combination of IoT and Obyte. Track and Verify Assets The journey of any commodity or asset from its origin (manufacturers) to its final destination (common users) is long and complex, and it could be full of issues in the middle. This is especially true when the safety or authenticity of the product is essential for final consumers, and it could be tampered with before it reaches them. Luckily, decentralized networks can be paired with IoT devices to track and verify any product across the supply chain, assuring its final quality. Sensors and IoT devices can report the status of shipments in real time to a DLT, ensuring that all parties have access to accurate and tamper-proof records. This could be particularly useful for monitoring the transport conditions of perishable goods or high-value items, improving accountability, and reducing losses due to theft, fraud, or damage. Consider, for instance, a pharmaceutical product originating from a manufacturing plant. Each product could have an embedded IoT sensor, generating real-time data about its location, temperature, and humidity levels. As the product leaves the factory, the IoT device logs its status onto the Obyte DAG, ensuring an immutable and transparent record every step of the way. If any anomalies occur, such as temperature fluctuations that could compromise the product's integrity, stakeholders are instantly alerted, allowing for swift corrective actions. Upon arrival at the final destination, perhaps a pharmacy, the product's entire journey is readily accessible on the Obyte DAG, and all its journey could be consulted by accessing a simple QR code printed on its tags. Smart Vehicle Leasing and Sharing It’s also possible to implement a system where vehicles, such as electric scooters, bikes, or cars, can be leased or rented using tokens on a decentralized network like Obyte. Users could unlock and operate these vehicles by scanning a QR code and paying with any compatible tokens, or even creating new ones for this purpose. The vehicle's usage data (e.g., duration, distance traveled) would be recorded on the DAG, ensuring transparency and trust. Human-readable smart contracts and Autonomous Agents (acting like digital vending machines) could manage leases, maintenance schedules, and payments. All of this from the same wallet, maybe even with the help of a chatbot, but with no need for extra middlemen being involved. For example, imagine John wants to rent an electric scooter for a quick ride across town. He opens his Obyte wallet, locates a nearby scooter, and scans its QR code. Instantly, the app prompts him to pay the rental fee using Obyte-based tokens. After confirming the payment, the scooter unlocks, and John starts his journey. As he rides, the scooter's IoT sensors continuously track and record data such as distance traveled and time used onto the Obyte DAG. Upon reaching his destination, John parks the scooter and ends the rental via the same app. The smart contract processes the final payment based on the usage data. Additionally, it could automatically update the scooter’s maintenance schedule based on the recorded usage, ensuring it remains in optimal condition. Decentralized Health Monitoring IoT is widely used in healthcare already, and it includes common devices like wearable fitness trackers and medical sensors. If we pair them with a DAG like Obyte, all of our important medical information could be safely registered digitally, ready to be shared with health providers and researchers only if we decide to do so, when we decide to do so. Let’s consider a scenario like that one. Imagine Sarah is using a wearable fitness tracker to monitor her heart rate and daily activity. This device continuously collects health data and securely records it onto the Obyte DAG. One day, Sarah feels unwell and decides to consult a doctor via a telehealth service. Through her digital wallet, Sarah not only can pay for the consultation, but grant her doctor temporary access to her health records stored on the DAG. Then, the doctor reviews the data in real-time, including heart rate trends and activity levels, aiding in an accurate diagnosis. After the consultation, Sarah revokes access, ensuring her information remains private. This system could provide secure, efficient, and controlled sharing of vital health data. Waste Management System Immense waste and inefficient techniques to handle it are another of our big challenges to improve our environment these days. By using IoT sensors and the Obyte ledger, we could create a new decentralized system to address this issue. Sensors placed in waste bins and recycling containers could monitor fill levels and send data to the DAG. Smart contracts could automate the scheduling of waste collection services based on real-time data, ensuring efficient and timely pickups. Additionally, a new customized token could be created to reward users for proper recycling practices, incentivizing environmentally friendly behavior and improving overall waste management efficiency. In a city aiming to boost recycling efforts, a customized token named ‘RecycleCoin’ (RCC) could be created on Obyte. Residents could be provided with IoT-enabled recycling bins that track the amount and type of waste deposited. When someone recycles his plastic bottles, the bin records the data and automatically logs it onto the Obyte DAG. For every kilogram of recyclables, users would earn RCC, credited to their digital wallet automatically. These tokens could be redeemed for rewards, such as discounts at local stores, or they could acquire real value through free market supply and demand. This system would not only incentivize recycling but also ensure transparent tracking of waste management, fostering a more sustainable community. P2P Clean Energy Another way to help the environment through IoT and Obyte, and reduce our electrical bills in the process, could be peer-to-peer (P2P) energy trading. Households or businesses with surplus energy generated from renewable sources like solar panels could sell excess energy directly to other consumers in their local grid. IoT devices would measure the amount of energy produced and consumed, recording this data on the DAG. Smart contracts can facilitate automatic and transparent transactions based on real-time energy usage, ensuring that producers are paid promptly and consumers are charged fairly. This way, we could optimize energy distribution, reduce reliance on traditional energy suppliers, and promote the use of renewable energy sources. **  **If we went to put it into practice, let’s say that Alice’s home, equipped with IoT devices, measures her solar energy production and usage, recording this data on the Obyte ledger. One sunny afternoon, Alice's panels produce more energy than her household consumes. The IoT platform would automatically log the surplus energy onto the DAG and make it available for sale. Down the street, if Mike needs extra energy for his home office, his own IoT system and Obyte wallet could detect the availability and purchase Alice's excess energy via smart contract. The provider would be promptly paid and Mike would be fairly charged. All these examples highlight just a fraction of the immense possibilities that emerge when combining Obyte with connected devices, paving the way for innovative solutions across numerous sectors where they could enhance efficiency, security, and user experience in unprecedented ways. Featured Vector Image by vectorjuice / Freepik Distributed Ledger Technology (DLT) is often paired with the Internet of Things (IoT) to get some interesting and automatic features in the real world, also registered and handled digitally. IoT devices are physical objects designed to connect to the Internet and can also perform effectively on a distributed network. Distributed Ledger Technology (DLT) Blockchains weren’t really built to face challenges like high energy costs or lack of needed speed. A Directed Acyclic Graph (DAG) like Obyte could be a better alternative , allowing inexpensive, fast, secure, and highly decentralized transactions or immutable data recording. Obyte could be a better alternative Obyte could be a better alternative In this vein, let’s look into some potential use cases for the powerful combination of IoT and Obyte. Track and Verify Assets The journey of any commodity or asset from its origin (manufacturers) to its final destination (common users) is long and complex, and it could be full of issues in the middle. This is especially true when the safety or authenticity of the product is essential for final consumers, and it could be tampered with before it reaches them. Luckily, decentralized networks can be paired with IoT devices to track and verify any product across the supply chain, assuring its final quality. Luckily, decentralized networks can be paired with IoT devices to track and verify any product across the supply chain, assuring its final quality. Sensors and IoT devices can report the status of shipments in real time to a DLT, ensuring that all parties have access to accurate and tamper-proof records. This could be particularly useful for monitoring the transport conditions of perishable goods or high-value items, improving accountability, and reducing losses due to theft, fraud, or damage. Consider, for instance, a pharmaceutical product originating from a manufacturing plant. Each product could have an embedded IoT sensor, generating real-time data about its location, temperature, and humidity levels . As the product leaves the factory, the IoT device logs its status onto the Obyte DAG , ensuring an immutable and transparent record every step of the way. Each product could have an embedded IoT sensor, generating real-time data about its location, temperature, and humidity levels Obyte DAG Obyte DAG If any anomalies occur, such as temperature fluctuations that could compromise the product's integrity, stakeholders are instantly alerted, allowing for swift corrective actions. Upon arrival at the final destination, perhaps a pharmacy, the product's entire journey is readily accessible on the Obyte DAG, and all its journey could be consulted by accessing a simple QR code printed on its tags. Smart Vehicle Leasing and Sharing It’s also possible to implement a system where vehicles, such as electric scooters, bikes, or cars, can be leased or rented using tokens on a decentralized network like Obyte. Users could unlock and operate these vehicles by scanning a QR code and paying with any compatible tokens, or even creating new ones for this purpose. The vehicle's usage data (e.g., duration, distance traveled) would be recorded on the DAG, ensuring transparency and trust . Human-readable smart contracts and Autonomous Agents (acting like digital vending machines ) could manage leases, maintenance schedules, and payments. All of this from the same wallet, maybe even with the help of a chatbot, but with no need for extra middlemen being involved. The vehicle's usage data (e.g., duration, distance traveled) would be recorded on the DAG, ensuring transparency and trust Human-readable smart contracts Human-readable smart contracts vending machines vending machines For example, imagine John wants to rent an electric scooter for a quick ride across town. He opens his Obyte wallet, locates a nearby scooter, and scans its QR code. Instantly, the app prompts him to pay the rental fee using Obyte-based tokens. After confirming the payment, the scooter unlocks, and John starts his journey. As he rides, the scooter's IoT sensors continuously track and record data such as distance traveled and time used onto the Obyte DAG. Upon reaching his destination, John parks the scooter and ends the rental via the same app. The smart contract processes the final payment based on the usage data. Additionally, it could automatically update the scooter’s maintenance schedule based on the recorded usage, ensuring it remains in optimal condition. As he rides, the scooter's IoT sensors continuously track and record data such as distance traveled and time used onto the Obyte DAG. Decentralized Health Monitoring Decentralized Health Monitoring IoT is widely used in healthcare already, and it includes common devices like wearable fitness trackers and medical sensors. If we pair them with a DAG like Obyte, all of our important medical information could be safely registered digitally, ready to be shared with health providers and researchers only if we decide to do so, when we decide to do so. all of our important medical information could be safely registered digitally, ready to be shared with health providers and researchers only if we decide to do so, when we decide to do so. Let’s consider a scenario like that one. Imagine Sarah is using a wearable fitness tracker to monitor her heart rate and daily activity. This device continuously collects health data and securely records it onto the Obyte DAG. One day, Sarah feels unwell and decides to consult a doctor via a telehealth service. Through her digital wallet , Sarah not only can pay for the consultation, but grant her doctor temporary access to her health records stored on the DAG. digital wallet digital wallet Then, the doctor reviews the data in real-time, including heart rate trends and activity levels, aiding in an accurate diagnosis. After the consultation, Sarah revokes access, ensuring her information remains private. This system could provide secure, efficient, and controlled sharing of vital health data. Waste Management System Waste Management System Immense waste and inefficient techniques to handle it are another of our big challenges to improve our environment these days. By using IoT sensors and the Obyte ledger, we could create a new decentralized system to address this issue. Sensors placed in waste bins and recycling containers could monitor fill levels and send data to the DAG. Sensors placed in waste bins and recycling containers could monitor fill levels and send data to the DAG. Smart contracts could automate the scheduling of waste collection services based on real-time data, ensuring efficient and timely pickups. Additionally, a new customized token could be created to reward users for proper recycling practices, incentivizing environmentally friendly behavior and improving overall waste management efficiency. In a city aiming to boost recycling efforts, a customized token named ‘RecycleCoin’ (RCC) could be created on Obyte. Residents could be provided with IoT-enabled recycling bins that track the amount and type of waste deposited. When someone recycles his plastic bottles, the bin records the data and automatically logs it onto the Obyte DAG. In a city aiming to boost recycling efforts, a customized token named ‘RecycleCoin’ (RCC) could be created on Obyte. a customized token a customized token For every kilogram of recyclables, users would earn RCC, credited to their digital wallet automatically. These tokens could be redeemed for rewards, such as discounts at local stores, or they could acquire real value through free market supply and demand. This system would not only incentivize recycling but also ensure transparent tracking of waste management, fostering a more sustainable community. P2P Clean Energy P2P Clean Energy Another way to help the environment through IoT and Obyte, and reduce our electrical bills in the process, could be peer-to-peer (P2P) energy trading. Households or businesses with surplus energy generated from renewable sources like solar panels could sell excess energy directly to other consumers in their local grid. IoT devices would measure the amount of energy produced and consumed, recording this data on the DAG. help the environment help the environment Smart contracts can facilitate automatic and transparent transactions based on real-time energy usage, ensuring that producers are paid promptly and consumers are charged fairly . This way, we could optimize energy distribution, reduce reliance on traditional energy suppliers, and promote the use of renewable energy sources. Smart contracts can facilitate automatic and transparent transactions based on real-time energy usage, ensuring that producers are paid promptly and consumers are charged fairly ** **If we went to put it into practice, let’s say that Alice’s home, equipped with IoT devices, measures her solar energy production and usage, recording this data on the Obyte ledger. One sunny afternoon, Alice's panels produce more energy than her household consumes. The IoT platform would automatically log the surplus energy onto the DAG and make it available for sale. Down the street, if Mike needs extra energy for his home office, his own IoT system and Obyte wallet could detect the availability and purchase Alice's excess energy via smart contract. The provider would be promptly paid and Mike would be fairly charged. The IoT platform The IoT platform All these examples highlight just a fraction of the immense possibilities that emerge when combining Obyte with connected devices , paving the way for innovative solutions across numerous sectors where they could enhance efficiency, security, and user experience in unprecedented ways. All these examples highlight just a fraction of the immense possibilities that emerge when combining Obyte with connected devices Featured Vector Image by vectorjuice / Freepik Featured Vector Image by vectorjuice / Freepik Freepik Freepik

5 Ways to Leverage Obyte and IoT Technology for Innovative Solutions

Nvidia has caught lightning in a bottle, and boy, is it making the company filthy rich. Investors eagerly awaiting the company's quarterly results were not disappointed after Nvidia said its sales had more than doubled and its profit was up sevenfold, propelling its valuation to record highs. Nvidia generated $26.04 billion in Q1 revenue, up 262% year over year, while net income of $14.88 billion was a jump of 628% from the $2.04 billion the company had posted in the same quarter last year. The company also said it was increasing its cash dividend by 150% to $0.10 per share. "The next industrial revolution has begun," declared Nvidia founder and Chief Executive Jensen Huang. Indeed, it has. Next quarter, Nvidia plans to generate even more in sales: $28 billion, plus or minus 2%. The kicker? The forecast was above what analysts thought the company would be able to generate: $26.66 billion. Nvidia is basing its revenue forecast on the success of the recently announced Blackwell class of AI chips, which are due to begin shipments this quarter. The company already believes that demand will outstrip supply. "We are poised for our next wave of growth. The Blackwell platform is in full production," Huang said. With so much positive news, it's no wonder the company's stock has hit a record high and crossed the $1,000 a share threshold. At this point, Nvidia's stock is so influential that it helped the technology-driven Nasdaq Composite Index to reach a record high! But that's not all; with yet another jump in the company's stock price, Nvidia is slowly inching towards a market capitalization of $3 trillion — only months after it became a $2 trillion company. The only other company valued at above $3 trillion is Microsoft, but the Windows maker did not achieve that milestone as quickly as Nvidia is. "This still doesn't feel like bubble territory," Derren Nathan, head of equity analysis at Hargreaves Lansdown, told Reuters. There is so much interest in Nvidia stock that the company has decided to make it easier for investors to own a piece of the pie. In its earnings announcement, Nvidia said it would be breaking down its shares at a ratio of 10-for-1 to make stock ownership "more accessible to employees and investors." What a great time to be Nvidia. Sponsored Content: Cash is king 👑 Not long ago, investors were chasing rocketship startups in hopes of a huge payday. Boy, how times have changed. Those overvalued, buzzy startups just aren't as attractive anymore. You know what's cool? Undervalued companies that earn real profit.WebStreet finds these companies, acquires them, improves them, and sells them. (And lets you invest) They buy overlooked businesses already earning money
They improve operations, so they make even more money
They bundle everything into a single, powerful fund that you can invest in. It's like micro private equity on autopilot. Unlike a lot of startups, WebStreet is doing great. Are you an accredited investor looking for passive income and want to invest in businesses providing real value? Join WebStreet’s Waitlist Here. Former OpenAI Employee Spills the Beans on Sam Altman Ouster 🤯 Sam Altman concealed the existence of ChatGPT from OpenAI's board. That's coming from former board member Helen Toner, who recently said in a podcast that Altman had a history of withholding information and lying to its members. The Microsoft-backed startup, which kickstarted the generative AI boom in 2022, went through its share of drama after the release of ChatGPT. Apparently, the OpenAI board only found out about the chatbot's existence after it became public on X, formerly Twitter. "After years of these kinds of things, all four of us who fired him came to the conclusion that we just couldn't believe things that Sam was telling us," Toner said. Worryingly, Sam also apparently gave the board inaccurate information on the safety processes for AI. All of this boiled over into the board deciding to kick Sam out, only for him to return just a few days later with Microsoft's blessing and kicking out the same people who fired him. "We are disappointed that Miss Toner continues to revisit these issues," OpenAI board chair Bret Taylor told the host of the podcast where Toner appeared. Meanwhile, on the safety front, OpenAI said it had formed a committee that would deliver recommendations on "critical safety and security decisions for OpenAI projects and operations." Altman will serve on the three-member board. For their first task, the OpenAI Safety and Security Committee will "evaluate and further develop OpenAI’s processes and safeguards over the next 90 days," the startup said in a statement. Despite the serious allegations, neither OpenAI nor Altman seem to be going anywhere. In fact, the company continues to partner with industry heavyweights such as News Corp to train its popular chatbot while attracting the likes of PwC to resell the enterprise version of ChatGPT. That is some serious backing. In Other News.. 📰 BlackRock Takes the Crown for the Largest Spot Bitcoin ETF From Grayscale — via CoinDesk
AI models have favorite numbers because they think they’re people — via TechCrunch
Prisoners are using VR to prepare them for life after release — via CNN
US court to hear challenges to potential TikTok ban in September — via Reuters
Sam Altman is starting to look a lot like Mark Zuckerberg — via Axios
China’s $47.5 billion chip fund will likely focus on AI amid U.S. export curbs — via CNBC And that's a wrap! Don't forget to share this newsletter with your family and friends! See y'all next week. PEACE! ☮️ — Sheharyar Khan, Editor, Business Tech @ HackerNoon *All rankings are current as of Monday. To see how the rankings have changed, please visit HackerNoon's Tech Company Rankings page. Tech, What the Heck!? is a once-weekly newsletter written by HackerNoon editors that combine HackerNoon's proprietary data with news-worthy tech stories from around the internet. Humorous and insightful, the newsletter recaps trending events that are shaping the world of tech. Subscribe here. Nvidia has caught lightning in a bottle, and boy, is it making the company filthy rich. Nvidia Nvidia Investors eagerly awaiting the company's quarterly results were not disappointed after Nvidia said its sales had more than doubled and its profit was up sevenfold , propelling its valuation to record highs. quarterly results quarterly results sevenfold Nvidia generated $26.04 billion in Q1 revenue, up 262% year over year, while net income of $14.88 billion was a jump of 628% from the $2.04 billion the company had posted in the same quarter last year. The company also said it was increasing its cash dividend by 150% to $0.10 per share. also "The next industrial revolution has begun," declared Nvidia founder and Chief Executive Jensen Huang. Indeed, it has. Next quarter, Nvidia plans to generate even more in sales: $28 billion, plus or minus 2%. The kicker? The forecast was above what analysts thought the company would be able to generate: $26.66 billion . more $26.66 billion $26.66 billion Nvidia is basing its revenue forecast on the success of the recently announced Blackwell class of AI chips, which are due to begin shipments this quarter. The company already believes that demand will outstrip supply. recently announced recently announced "We are poised for our next wave of growth. The Blackwell platform is in full production," Huang said. With so much positive news, it's no wonder the company's stock has hit a record high and crossed the $1,000 a share threshold. At this point, Nvidia's stock is so influential that it helped the technology-driven Nasdaq Composite Index to reach a record high! record high record high so influential so influential But that's not all; with yet another jump in the company's stock price, Nvidia is slowly inching towards a market capitalization of $3 trillion — only months after it became a $2 trillion company. inching towards inching towards $2 trillion $2 trillion The only other company valued at above $3 trillion is Microsoft , but the Windows maker did not achieve that milestone as quickly as Nvidia is. Microsoft Microsoft "This still doesn't feel like bubble territory," Derren Nathan, head of equity analysis at Hargreaves Lansdown, told Reuters. told told There is so much interest in Nvidia stock that the company has decided to make it easier for investors to own a piece of the pie. In its earnings announcement, Nvidia said it would be breaking down its shares at a ratio of 10-for-1 to make stock ownership "more accessible to employees and investors." What a great time to be Nvidia. Sponsored Content: Sponsored Content: Cash is king 👑 Cash is king 👑 Not long ago, investors were chasing rocketship startups in hopes of a huge payday. Boy, how times have changed. Those overvalued, buzzy startups just aren't as attractive anymore. You know what's cool? Undervalued companies that earn real profit.WebStreet finds these companies, acquires them, improves them, and sells them. (And lets you invest) They buy overlooked businesses already earning money They improve operations, so they make even more money They bundle everything into a single, powerful fund that you can invest in. It's like micro private equity on autopilot. They buy overlooked businesses already earning money They improve operations, so they make even more money They bundle everything into a single, powerful fund that you can invest in. It's like micro private equity on autopilot. Unlike a lot of startups, WebStreet is doing great. Are you an accredited investor looking for passive income and want to invest in businesses providing real value? Join WebStreet’s Waitlist Here . Join WebStreet’s Waitlist Here Former OpenAI Employee Spills the Beans on Sam Altman Ouster 🤯 Former OpenAI Employee Spills the Beans on Sam Altman Ouster 🤯 Sam Altman concealed the existence of ChatGPT from OpenAI's board. That's coming from former board member Helen Toner, who recently said in a podcast that Altman had a history of withholding information and lying to its members. recently said in a podcast recently said in a podcast The Microsoft -backed startup, which kickstarted the generative AI boom in 2022, went through its share of drama after the release of ChatGPT. Apparently, the OpenAI board only found out about the chatbot's existence after it became public on X, formerly Twitter. Microsoft Microsoft "After years of these kinds of things, all four of us who fired him came to the conclusion that we just couldn't believe things that Sam was telling us," Toner said. Worryingly, Sam also apparently gave the board inaccurate information on the safety processes for AI. All of this boiled over into the board deciding to kick Sam out, only for him to return just a few days later with Microsoft's blessing and kicking out the same people who fired him. kicking out kicking out "We are disappointed that Miss Toner continues to revisit these issues," OpenAI board chair Bret Taylor told the host of the podcast where Toner appeared. told told Meanwhile, on the safety front, OpenAI said it had formed a committee that would deliver recommendations on "critical safety and security decisions for OpenAI projects and operations." Altman will serve on the three-member board. For their first task, the OpenAI Safety and Security Committee will "evaluate and further develop OpenAI’s processes and safeguards over the next 90 days," the startup said in a statement . statement statement Despite the serious allegations, neither OpenAI nor Altman seem to be going anywhere. In fact, the company continues to partner with industry heavyweights such as News Corp to train its popular chatbot while attracting the likes of PwC to resell the enterprise version of ChatGPT. News Corp News Corp resell resell That is some serious backing. In Other News.. 📰 In Other News.. 📰 BlackRock Takes the Crown for the Largest Spot Bitcoin ETF From Grayscale — via CoinDesk AI models have favorite numbers because they think they’re people — via TechCrunch Prisoners are using VR to prepare them for life after release — via CNN US court to hear challenges to potential TikTok ban in September — via Reuters Sam Altman is starting to look a lot like Mark Zuckerberg — via Axios China’s $47.5 billion chip fund will likely focus on AI amid U.S. export curbs — via CNBC BlackRock Takes the Crown for the Largest Spot Bitcoin ETF From Grayscale — via CoinDesk CoinDesk CoinDesk AI models have favorite numbers because they think they’re people — via TechCrunch TechCrunch TechCrunch Prisoners are using VR to prepare them for life after release — via CNN CNN CNN US court to hear challenges to potential TikTok ban in September — via Reuters Reuters Reuters Sam Altman is starting to look a lot like Mark Zuckerberg — via Axios Axios Axios China’s $47.5 billion chip fund will likely focus on AI amid U.S. export curbs — via CNBC CNBC CNBC And that's a wrap! Don't forget to share this newsletter with your family and friends! See y'all next week. PEACE! ☮️ — Sheharyar Khan , Editor, Business Tech @ HackerNoon Sheharyar Khan Sheharyar Khan *All rankings are current as of Monday. To see how the rankings have changed, please visit HackerNoon's Tech Company Rankings page. *All rankings are current as of Monday. To see how the rankings have changed, please visit HackerNoon's Tech Company Rankings page. *All rankings are current as of Monday. To see how the rankings have changed, please visit HackerNoon's Tech Company Rankings page. Tech Company Rankings Tech Company Rankings Tech, What the Heck!? is a once-weekly newsletter written by HackerNoon editors that combine HackerNoon's proprietary data with news-worthy tech stories from around the internet. Humorous and insightful, the newsletter recaps trending events that are shaping the world of tech. Subscribe here. Tech, What the Heck!? is a once-weekly newsletter written by HackerNoon editors that combine HackerNoon's proprietary data with news-worthy tech stories from around the internet. Humorous and insightful, the newsletter recaps trending events that are shaping the world of tech. Subscribe here. Tech, What the Heck!? is a once-weekly newsletter written by HackerNoon editors that combine HackerNoon's proprietary data with news-worthy tech stories from around the internet. Humorous and insightful, the newsletter recaps trending events that are shaping the world of tech. Subscribe here. Tech, What the Heck!? is a once-weekly newsletter written by HackerNoon editors that combine HackerNoon's proprietary data with news-worthy tech stories from around the internet. Humorous and insightful, the newsletter recaps trending events that are shaping the world of tech. Subscribe here . here here

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