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Usage AI

(AI) has emerged as a game-changer in many industries. Predictive AI technology has helped reshape age-old processes, saving organizations time, money, and frustration. A litany of different organizations have leveraged AI solutions to streamline their operations and ultimately drive productivity, changing industries ranging from art to finance. Artificial intelligence While some have bemoaned the rise of AI, wringing their hands over a possible AI takeover, others have recognized the power of machine learning, algorithms, and computer vision to transform their jobs and allow them to get back to the innovating that truly moves the needle towards progress. AI for Boosting Productivity AI has proven to be a boon for productivity within many organizations. By automating repetitive tasks and allowing employees to focus on the parts of their jobs that carry higher value, AI paves the way for more creativity, innovation, and problem-solving. “By analyzing trends in task completion times and quality and assigning specific team members based on past performance and partnerships, AI encourages a culture of recognition and motivation,” says Brianna Van Zanten, Customer Success Manager at InCheq. “When workers' achievements are acknowledged through data-driven insights, it provides a tangible record of their individualistic abilities.” With more workers taking heed of the message of the Great Resignation and seeking work that is personally and professionally rewarding, utilizing AI to create a better work culture can help companies with talent retention and employee satisfaction, not to mention productivity. With actionable insights from performance data, AI can not only make the workplace better for the employees but also significantly improve the overall performance of the organization as a whole. AI for Content Creation With the rise of AI, many in creative fields have feared that predictive AI creations signal the end of human creativity. However, several organizations have learned to use AI not only to help them be more productive but also to give them the space they need to be more creative. “As a podcast host, I can attest to AI's transformative potential for the podcasting industry,” explains Heidi Moore, host of Wine Crush Podcast. “When we integrate AI into existing podcast workflows, it's not merely an additive process — it’s a paradigm shift. The capability of AI to sift through vast datasets allows it to predict and generate engaging topics that resonate deeply with the audience's preferences and current trends. This predictive prowess is instrumental in crafting content strategies that captivate listeners and foster a loyal audience base.” By automating the routines that take away from the creative process, creative entrepreneurs and leaders can focus more on experimenting and enjoying the fun parts of working within a creative space. If they view AI as a collaborative partner in their creative work rather than a hindrance, they may come by a more efficient process. AI for the Supply Chain As we saw laid bare during the pandemic, the efficiency and health of the global supply chain are critical for business. The introduction of AI has allowed those in the supply chain space to optimize traditional processes and explore technology-informed ways of making things run smoothly worldwide. “AI and RFID technology can be pivotal in transforming supply chain operations, particularly in enhancing the efficiency and sustainability of eco-friendly products,” says Joseph Schlossberg, VP of Global Sales at Sourcing Solutions International. “By integrating RFID's real-time tracking capabilities with AI's analytical prowess, we could significantly streamline supply chain processes, ensuring accurate inventory management and reducing unnecessary waste. This synergy is vital for adapting to rapid market changes and managing resources more effectively.” AI use within the supply chain significantly impacts the recent push for sustainability. “By evaluating extensive data on lifecycle impacts, supply chain practices, and product usage, AI facilitates more sustainable decision-making and innovation,” Schlossberg explains. “It helps us improve product design and predicts the environmental impact of materials and processes that we use.” AI in Finance AI also has a significant role to play in an industry like finance, where accuracy is paramount. “As more and more financial advisors embrace advancements in technology, AI continues to play a larger role,” says Aaron Cirksena of MDRN Capital. With the power to analyze vast data sets and uncover valuable insights for investors, AI can unlock new opportunities within the complex world of finance. “We can use AI in a multitude of ways, whether it is used to manage investments, give predictive AI-driven recommendations, or assist advisors in the day-to-day operations of their firms,” Cirksena notes. “Additionally, more advisors are embracing AI for client communication and assisting them with finding new lead sources.” Financial entities that embrace these technologies within the financial space stand to gain an advantage over those competitors who choose not to evolve or even bend with the changing times. As AI becomes more a part of everyday life, more investors and everyday banking consumers will come to expect the value and efficiency that AI can bring, gravitating towards those organizations that can offer it. AI automation has left its fingerprints in nearly every industry. As we head into the future, the potential for AI in areas from healthcare to the arts promises to reshape the way we work, produce, and innovate. Lead image source

Four Use-Cases for AI Automation in 2024

2024 সালে AI অটোমেশনের জন্য চারটি ব্যবহার-কেস

Vier Anwendungsfälle für KI-Automatisierung im Jahr 2024

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2024 में एआई स्वचालन के लिए चार उपयोग-मामले

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Accessing the dark web on an iPhone can be an intriguing proposition for many users. The dark web is known to be a hub for illegal activity, and it can be difficult to access without the right tools and knowledge. However, it is important to remember that the dark web is not a safe place, and there are many risks associated with accessing it. Before you access the dark web you must be alert and take steps to protect yourself from identity theft. : In this article included an affiliate link to NordVPN. You won’t be charged anything extra for clicking on these links, but you will be supporting me if you do choose to purchase through the link. Thanks! Disclaimers/Notes On AI Usage: AI was used to improve the grammar in this article. What is Dark Web - In-depth Have you ever heard of the dark web? It's a part of the internet that can't be accessed using regular search engines like Google or Yahoo. It's a hidden network of websites and services that can only be accessed with special software or configurations. Unlike the regular internet, which is open and accessible to everyone, the dark web is intentionally hidden and often used for illegal activities like buying and selling drugs, weapons, and stolen data. However, it's important to note that not everyone who uses the dark web is involved in illegal activities. In fact, some people use it for legitimate purposes, such as anonymous communication channels for political dissidents, journalists, and whistleblowers. One of the most well-known ways to access the dark web is through a software called Tor, which stands for "The Onion Router". Tor is a free and open-source software that uses a series of relays to anonymize internet traffic, making it difficult to track the origin or destination of internet traffic. By using Tor, you can can browse the dark web anonymously, without revealing their IP address or location. So while the dark web has a reputation for illegal activities, it's also used for legitimate purposes. It's a complex and fascinating aspect of the internet that's worth learning more about. Here Are The Steps to Access The Dark Web on Your iPhone Step 1: Download a VPN First you need to download a reliable VPN on your iPhone. A VPN creates a secure, encrypted connection between your device and the internet. This is important because it helps protect your online activity from prying eyes. When choosing a VPN provider, it is important to choose a reputable provider with a proven track record of protecting user privacy. The most popular VPN providers for iPhones include ExpressVPN, NordVPN, and Surfshark. I personally use , it's excellent and faster than others. NordVPN Anyway, once you have downloaded and installed the VPN app on your iPhone, make sure to connect to the VPN before accessing the dark web. Step 2: Download the Tor Browser Now, your network work is encrypted and you can download the Tor Browser without anyone's trace. The Tor Browser is a free, open-source web browser that is specifically designed for accessing the dark web, (in one word, TOR browser is the getaway of the dark web). The Tor Browser routes your internet traffic through a series of servers, making it difficult for anyone to track your online activity. To download the Tor Browser on your iPhone, simply search for " " in the App Store and install the app as usual or go through the URL here. Once the app is installed, open it and connect to the server. Tor Browser Remember, do not download or open the TOR browser without a VPN. Step 3: Navigate the Dark Web Safely Now that you have the Tor Browser and a VPN installed on your iPhone, you can safely navigate the dark web. However, it is important to remember that the dark web is not a safe place, and there are many risks associated with accessing it. One of the biggest risks of using the dark web is the potential for identity theft. So make sure to avoid providing any personal information, such as your name, address, or credit card details, while using the Tor Browser. Another risk of using the dark web is the potential for and viruses. To protect yourself from malware, make sure to avoid clicking on suspicious links. malware Step 4: Be alert It is important to use common sense when accessing the dark web on your iPhone. The dark web is a place where illegal activity thrives, and there are many people looking to take advantage of unsuspecting users. Always use a VPN and the Tor Browser when accessing the dark web, and avoid clicking on suspicious links or downloading files. If something seems too good to be true, it probably is a scam. Final Word I hope you enjoyed the article and took note of the security measures mentioned. It's important to remember that you cannot access the dark web through the surface web, which means you can't search for it on Google and expect to find the right resources. If you want to access the dark web on your iPhone, you must need to download a browser like TOR Browser, I2P and FreeNet. Frequently Asked Questions Can I access the dark web on my iPhone? Yes, it is possible to access the dark web on your iPhone, but you will need to use special software or configurations to do so. Is it safe to access the dark web on my iPhone? Accessing the dark web carries a higher risk than browsing the surface web, so it's important to take precautions to protect your identity and devices. Use a virtual private network (VPN) to encrypt your internet traffic, avoid downloading or installing any suspicious software or files, and be cautious when interacting with unknown websites or individuals. Can I access the dark web through a regular browser on my iPhone? No, the dark web cannot be accessed through regular browsers like Safari, Edge or Chrome. You will need to use a special browser like Tor to access the dark web. Is it illegal to access the dark web on my iPhone? No, accessing the dark web itself is not illegal, but many of the activities that take place on the dark web are illegal. It's important to use caution and not engage in any illegal activities while browsing the dark web. Are there any risks associated with accessing the dark web on my iPhone? Yes, accessing the dark web carries a higher risk than browsing the surface web. You may encounter malicious websites or individuals, and your identity or personal information may be at risk. It's important to take appropriate precautions to protect yourself and your device.

The Easiest Way to Access the Dark Web on an iPhone

La forma más fácil de acceder a la web oscura en un iPhone

Le moyen le plus simple d'accéder au Dark Web sur un iPhone

IPhone पर डार्क वेब तक पहुँचने का सबसे आसान तरीका

iPhone でダークウェブにアクセスする最も簡単な方法

A maneira mais fácil de acessar a Dark Web em um iPhone

Cách dễ nhất để truy cập Dark Web trên iPhone

在 iPhone 上访问暗网的最简单方法

Scaling is an important but often overlooked consideration in software and web development. Let’s say that you have plans to make a great product. And let’s also say that after a few months of development, you were able to deploy it successfully. Now, you suddenly have hundreds of thousands of active users. What will you do if the number keeps growing? And how will you handle this huge but sudden change? Do you have enough resources to do so? Will you have to make changes in terms of your tech stack? Scalability is all about having an answer to all these questions. It’s not always easy to scale your product or service properly, and scaling involves a lot of complicated steps. It’s not like there’s a comprehensive and fun way to learn about all this, is there? Thankfully, now there is. On February 22, 2023, from 9:30 a.m. to 3:30 p.m. Central Time, Filestack will be hosting a full-day online conference. The event, titled “Nerd Up: Scale Up," brings together six field experts from across the globe. They will provide you with effective and modern strategies for software and website scaling. The event’s is now open to those who are willing to learn about proper software and website scaling. This article will discuss the basics of the topics that the conference will cover. registration What is the Nerd Up: Scale Up conference about? The event will guide you through the different ways you can prepare for any changes in your application or website. Here are the topics, along with their corresponding presenters, that you will encounter at the conference: OpenAI: Creating Chatbot Applications, Adrian Twarog A Qwik Integration to File Management, Giorgo Boa Designing for Scale: Optimizing Microservices, Chris Bongers IL Classroom and Filestack: Powering LMS, Ian Lotinsky A Design System Story, Gil Fink Using AI to Improve Existing Systems, Patty O’Callaghan Unfamiliar with some of these topics? Don’t worry. We’ll be discussing basic information about them below. And if you are already familiar with them, then you will be learning a lot more when it comes to using them for scaling applications and websites. Let’s start with the conference’s core topic: scalability. What is software or website scalability? There comes a point in every developer’s life when they need to deeply consider software or website scalability. It’s an essential part of adapting to the constantly changing software industry environment. For example, when your website or application starts to grow, you have to prepare accordingly. Similarly, when an unprecedented event (like a pandemic) threatens to topple the stability of an application or website, you have to know how to handle it. Software or website scalability deals with keeping up with any changes in the business environment. Without proper scaling, your software or website might fail to adapt to any major changes. For instance, let’s say that you have software that supports strictly up to 100,000 users due to some constraints. When that software starts growing in popularity or demand, it will be more difficult for you to adapt. The changes you will have to make can include purchasing more servers, changing your software’s structure, and other exhausting tasks. On the other hand, if you make your software scalable from the start, it’s easier to make these changes. There are several factors and ways to make your products scalable. At the Nerd Up: Scale Up conference, our speakers will discuss some important ones to help guide you. So, are you good with scalability? Let’s move on to artificial intelligence, another major topic of the conference. What do you need to know about AI? Artificial intelligence, or AI, is a field of computer science that deals with creating computer systems that can mimic human intelligence to a degree. Formally defining AI is difficult. In fact, in the book “Artificial Intelligence: A Modern Approach," authors Russell and Norvig gathered eight definitions for AI from different studies. But one thing is for sure: AI is one of the most popular and sought-after fields today. This is true not only for scientists and mathematicians but also for businesspeople and modern developers. One increasingly popular topic about AI is OpenAI, an AI research and deployment company. OpenAI provides various APIs that developers can use to create beneficial AI-powered applications. For example, ChatGPT is a model for human-like conversations. It can answer questions, remember conversations, and even admit mistakes, making it perfect for chatbots. OpenAI allows developers to integrate chatbots into their applications quickly. As a result, developers can scale their applications rapidly and meet their users’ needs. Developers can also use AI to improve the quality of existing systems. AI does this by increasing productivity, reducing costs, and improving the user experience. Why we need AI AI for commercial software and websites is one of the best and most popular innovations that we have today It can make our lives easier (with the right guidance and usage) AI is getting more advanced and accurate every day It can help improve existing or old solutions AI functionality is becoming more accessible for developers What is the Qwik framework? Qwik is another topic that the conference will cover, but what is it, exactly? Qwik is a web framework that promotes performance and scalability. Its goal is to minimize the application’s JavaScript executions and downloads. Some of its features include: No hydration (instant interaction with the application even on slow mobile devices) Resumability (No JS downloads/execution before handling user interaction or rendering) Easy lazy loading (load digital assets as needed) Minimal rendering for downloaded and executed code Scalability (The amount of downloaded code is based on user interaction complexity instead of component size) One mental model to follow for both front-end and back-end code Qwik believes that developers shouldn’t worry too much about application size. This is because the industry’s best practices often translate into larger bundles. Furthermore, the Qwik philosophy states that tooling can break down applications into different chunks. Developers can then lazy-load these chunks. This means that the runtime will only download these assets as needed. This view on sizing makes Qwik a helpful tool for scaling websites and applications. Qwik is perfect for many different applications, especially those with file management features. The framework allows developers to rapidly build applications. And when paired with a capable file management service, Qwik also makes handling digital assets much easier. Why we need frameworks like Qwik We can surpass limits set by large application bundle sizes with these frameworks Qwik makes it easy to speed up applications and websites You can follow all the best practices and still have good performance Qwik strikes the balance between an application with less interactivity but high performance and an application with more interactivity but poor performance What is microservice architecture? A microservice architecture is a type of application architecture that developers can follow when building larger applications. The “microservice” part means that the applications that use this application architecture consist of a set of services. These don’t just refer to any services, however. Each service must possess the following qualities: Small, loosely coupled, and independently deployable (i.e., a team can update and deploy their microservice separately from the main application) An independent codebase that is owned by a small team The ability to handle its own data or external state persistence The ability to communicate with other microservices using APIs (details of the other services must be abstracted from one another) The ability to emerge from different tech stacks compared to the other microservices of the application (i.e., every service doesn’t have to have the same frameworks or libraries) By following this application architecture, developers can rapidly develop and frequently update large applications. Microservices also allow businesses to change their tech stack at will, letting them adapt to newer technologies and trends. And because of these characteristics, microservice architecture greatly contributes to an application's scalability. However, there are proper strategies for designing microservices for scalability. You still have to optimize these microservices. This process can include steps like using service meshes and pipelines for testing and deployment. Fortunately, optimizing these microservices is one of the major topics of the upcoming conference. Why we need a microservice architecture Easier management of services (bug fixes, new releases) because of independence More scalability and productivity from smaller teams working on one service (less and faster communication compared to larger teams working on one or multiple services) It’s easier to add or remove features when they’re separate from one another Developers have more control over scaling their application (scale one or some services instead of the entire application every time) Time to nerd up and scale up And that’s it for these interesting topics, at least for now. At the conference on February 22, 2023, you’ll get much more detailed insights about the topics that we’ve discussed above. To register for the upcoming online conference, . click here

Filestack Presents: Nerd Up: Scale Up - A Full-Day Online Conference

Let’s all agree: the pandemic has reshaped the global supply chain. Multiple lockdowns paired with temporary trade restrictions and workforce shortages unveiled vulnerabilities in supply chains that were previously unseen. The drastic change of the landscape forced supply chain executives to up their strategic management game. To do so, some of them have turned to innovative technologies, with supply chain AI leading the race. In fact, while it is a standard practice for enterprises to hold up their digital transformation projects in times of economic uncertainty, the COVID-19 crisis did not stop supply chain decision-makers from turning to . that 92% of the surveyed senior-level executives carried on with their investments. The reasoning? A positive value of AI in the supply chain. artificial intelligence solutions providers A study suggests Below, we look at how artificial intelligence helps supply chains run effectively, investigate the outcomes AI in the supply chain can yield, and share tips on jumping on the digital supply chain bandwagon in a risk-free manner. AI in the supply chain: how it helps hit strategic management targets At the beginning of 2021, Ernst and Young surveyed 200 senior-level supply chain executives to reveal their top priorities for the next 12 to 36 months. Here is what they found: The number one strategic target for supply chain decision-makers is increasing supply chain efficiency The second objective they look to achieve is to gain better visibility into their supply chains Other targets that top off the global supply chain agendas are boosting resilience and optimizing supply chain management costs Artificial intelligence is becoming essential to bringing these strategic transformations to life. As a matter of fact, 95% of the highest-performing organizations . see AI as a cornerstone of their supply chain success Here’s a more detailed look at the use cases of AI in the supply chain that help achieve the targets mentioned above. Use cases of AI in supply chain management that increase operational efficiency Demand forecasting Understanding the sources of demand has never been more challenging. With customer expectations changing quickly and getting more diverse, businesses now rely on AI-powered supply chain tools to glean more demand-related insights — and tune their production strategies accordingly. Integrating available data about each process within the supply chain (even real-time information) and running this data through AI algorithms can help businesses establish a unified view of demand and make more thoughtful decisions. The data for analysis can be gathered from internal sources, such as orders and sales, or external sources, for example, macroeconomic factors, brand sentiment, and the number of COVID-19 cases. As a result of such planning, AI is capable to return a detailed report of potential consumption volumes, broken down by customer and location levels. And with the detailed demand data on hand, businesses can optimize their production volumes, reduce inventory levels, store more goods closer to their customers, and cut down on unnecessary shipments. Laying out best delivery routes Leveraging AI in supply chain management can also help design better delivery routes and optimize fleet utilization. Considering such criteria as supplier and manufacturing sites, storage locations, potential wear and tear of machinery, and fuel usage, AI-based supply chain solutions come up with an optimal route and provide for a speedier flow of items along the supply chain. Last-mile deliveries and driverless cars Driverless cars and last-mile delivery robots (that rely on AI, too) have a chance to transform supply chains by decreasing dependence on human drivers and optimizing delivery routes. Still, according to BCG, merely 10% of trucks will likely operate autonomously by 2030. Delivery drones and bots, in turn, have already won significant popularity. They are increasingly being used to deliver at shorter distances or to places where the ground transfer is not safe, reliable, or sustainable. Hybrid solutions combining delivery vans and drones have recently emerged, too. Amazon, for example, works on a system whereby vans deliver items close to their destination and then send out an AI-controlled drone for the final drop-off. Use cases of AI in supply chain management that provide for better visibility Inventory management Adopting AI in supply chain management can help uncover the performance of inventory across various channels and sellers and identify anomalies, like delays or low inventory levels. With detailed inventory data, enterprises can adjust their inventory strategies to operate more efficiently. Order management AI-powered supply chain platforms facilitate order management and help bring together multiple supply chain players involved in the process. For example, an ITRex helped develop can predict order shipment costs based on up to 60 parameters, process customer requests to eliminate duplicate orders and suggest better carrier matching options, and track shipments from dispatch to delivery. AI-based cargo management platform Use cases of AI in supply chain management that increase resilience Predictive analytics for risk management The pandemic has pushed risk management to the top of every corporate agenda. McKinsey reports that 59% of businesses have adopted a new approach to supply chain risk management over the past year. One typical example of how applying AI in the supply chain advances risk management is optimizing supplier evaluation, flagging suppliers as low-, medium-, or high-risk. For that, an AI solution could weigh out such metrics as the impact on revenues a business is likely to face if a particular source is lost, the time it would take a specific supplier to recover from a disruption, the availability of alternative sources, and other data. Another way of leveraging AI for the supply chain is predicting supply chain disruptions. Feeding off historical operational data, AI could help identify and correct operational inefficiencies in real time, providing an in-depth look into the supply chain performance, opportunities, and risks. Doing so proactively allows supply chain executives to operate at lower costs without sacrificing efficiency. In fact, according to McKinsey, organizations that have adopted AI report a 44% reduction in operating expenses. Digital twins Expanding the reliance on artificial intelligence in the supply chain even further,, businesses can create so-called digital twins — virtual simulations of all corporate assets, warehouses, routes, and materials and product flows. Digital twins help design more resilient and effective supply chains and allow testing out the supply chain performance and foreseeing risks. AI in the supply chain: five real-world examples Let’s look at the examples of companies that have already adopted AI for supply chain management. Amazon The ecommerce giant uses AI-based predictive analytics to power its supply chain and predict demand for products before purchasing and stocking its warehouses. The company says predictive analytics has become a backbone for its supply chain strategy. AI-powered demand forecasting “kicks off the supply chain” and helps the company determine which products, and how much of each, to buy. UPS The company uses AI to manage the flow of packages. The company’s staff gets a bird’s eye view of the number of packages in the delivery network, the expected peaks in the volume of goods en route, as well as potential disruptions. The AI-based supply chain solution relies on historical and real-time information, including weather and traffic data, to devise the fastest and safest ways to deliver packages. DHL The company employs an AI-based tool for predicting air freight delays. The solution analyzes 58 data points and predicts delays or speed-ups a week in advance. The tool also indicates the reasons why the changes to the itinerary might occur. FedEx The delivery service uses Roxo — a robot that relies on AI to automate last-mile deliveries. The robot is designed to be used in a three-to-five-mile radius of storage facilities. It has helped the company satisfy the needs of its customers better and improve its performance benchmarks. Echo Global Logistics The transportation management company builds on AI to ship goods quickly, securely, and cost-effectively. The areas where the company employs AI are manifold — from optimizing the procurement of transportation to carrier management to intelligent shipment tracking. Embarking on an AI-driven supply chain transformation journey About 60% of projects dealing with AI in supply chain management are either delivered late or over budget. We have laid out an AI adoption roadmap to help you overcome AI implementation challenges and ease your supply chain transformation journeys. Step 1. Formulate a business case and think over the strategic aspects of AI adoption Only a third of companies ushering in AI-driven transformation performs a diagnostic audit before rolling out the technology. To make sure you are not missing out on the opportunities of AI, we recommend kicking off your digitization project by identifying and prioritizing the possibilities for value creation across all supply chain segments — from procurement to manufacturing to shipping. With an all-rounded assessment carried out, define the supply chain digitization strategy, and make sure it reflects the findings. It makes sense to start with digitizing one segment of the supply chain that shows the highest value-creation potential to drive ROI faster. And once the base solution is rolled out, you could evolve further, both vertically, expanding the list of available features, and horizontally, extending the capabilities of AI to other supply chain segments. Step 2. Look for an optimal vendor to bring your solution to life Due to the complexity and the multifaceted nature of the supply chains, all of your expectations could hardly be met by a single vendor. So, don’t be afraid to examine what the supply chain technology market has to offer and integrate the optimum offerings into a solution that addresses your specific needs. Another piece of advice is going for a vendor-agnostic integrator, so you prevent technology and solution lock-in. Step 3. Oversee the development and integration of the solution According to McKinsey, only 15% of businesses involved in supply chain management report feeling like their objectives are in line with those of their vendors. To prevent that and ensure a smooth roll-out, map the development process to the initial supply chain digitization strategy and keep in mind the key value you intend to tap into. Prioritizing the value-creation opportunities and dividing the development process into increments according to the set priorities might help navigate end-to-end AI implementation. Step 4. Ensure the solution’s smooth adoption and scale the implemented capabilities Powering a supply chain with AI is a complex endeavor that is more than just rolling out the technology. Digitizing a supply chain also requires comprehensive change management and reskilling. So, before you jump on the AI bandwagon, we recommend laying out a change management plan to help you handle the skills gap and the cultural shift. Start with explaining the value of AI to the employees and educate them on how to embrace the new ways of working. On a final note Over the past years, artificial intelligence has become a vital element of a resilient supply chain. AI-based supply chain management tools are helping organizations speed up the flow of materials and finished products, cut down operational costs, and effectively navigate through changes. If you are looking to tap into the transformative power of AI and digitize your supply chain for better visibility, resilience, and responsiveness, . Their AI experts will answer your questions and help navigate the transformation process with little to no risks. drop ITRex a line

AI is a Cornerstone of a Resilient supply Chain. Here’s Proof

The U.S. startup ecosystem has changed dramatically in the last few months, with persistently high inflation and rising interest rates portending an era of stricter financial conditions. In this new environment, it will be increasingly difficult for startups to raise money from investors. One key way that startups can become more attractive to investors is by reducing their burn rate — the rate at which they are spending money. And one area where startups can make significant cuts is in their cloud costs. Why Startups Fail Every year, thousands of startups launch with the hope of becoming the next big thing. But the vast majority of them fail. Even among venture-backed startups, to return capital to investors. 75% fail The idea of the "burn rate" is key to understanding why startups fail. A startup's burn rate is the rate at which it is spending money. If a startup has a high burn rate, it will run out of money quickly. According to the U.S. Bank, __ __of failed businesses cite cash flow problems as a factor in their failure. A startup can quickly burn through its initial funding if it is not careful. 82% If a startup finds itself in this situation, it has two options: raise more money or cut costs. But neither of these options is easy. Raising more money is difficult, as investors are often reluctant to put more money into a failing company. And cutting costs can be just as hard, as it can mean laying off employees or cutting back on important R&D spending. Why Startups Run Out of Cash According to a 2018 study by Brex, the median burn rate for Series A startups is around , or almost $5 million a year. The average Series A round among top firms was year, meaning that even well-funded startups are burning through cash quickly. $400,000 per month million that $15.7 Tech startups, in particular, face a number of headwinds that can contribute to a cash crunch. For one, they often require expensive hardware and software to get off the ground. They may also need to pay for office space and hire engineers, which can be costly. Cloud costs, too, can quickly eat into a startup's budget. The average SaaS startup (up to 100 employees) spends a staggering the cloud, according to a 2020 study by Harness. year on $1.16 million a Even if a startup is generating revenue, it may not be enough to cover all of these expenses. This is one of the main reasons why startups run out of cash and have to raise more money from investors. Startup Funding is Decreasing Compunding the problem, startup funding is . on the decline Amidst persistently high inflation and rising interest rates, venture capitalists have become more cautious with their investments. After all, major banks are predicting a prolonged downturn in the economy, which could lead to fewer exits and lower valuations for startups. This has led to a decrease in VC funding for startups. In April of this year, venture totals set roughly a 12-month low, following a peak in November of 2021, representing a decline of $5 billion from March to April alone. What's more, the average valuation is , alongside in tech startups seeing sharp selloffs. Lower valuations make it more difficult for startups to raise money from investors, maintain morale, and even incentivize new hires. also declining recent IPOs Startups Need to be More Efficient with Their Cloud Spend In recent years, the costs of infrastructure underlying storage, networking, and computing have dropped significantly. For example, hard drive prices have dropped from around $500,000 per gigabyte in 1981 to less than . $0.03 per gigabyte today While cloud providers have passed on many of those savings, there's still a lot of room for improvement. In fact, a study by Gartner found that many organizations are on their cloud bills. Moreover, cloud providers are even increasing their prices in some cases, with recently. overspending up to 50% GCP doubling some of its fees The bottom line is that startups need to be more efficient with their cloud spend. They need to find ways to optimize their usage and cut costs where possible. Fortunately, there are a number of ways to do this. Startups can use cloud management tools like or to help them optimize their usage and control costs. They can also take advantage of reserved instances and other cost-saving features offered by cloud providers. In one case study, a firm is on AWS costs using flexible reserved instances. Usage.AI AWS Cost Explorer saving $1 million a year And, of course, they can always negotiate with their cloud providers. This is something that more startups should be doing, as it can lead to significant savings. In the current economic environment, it's more important than ever for startups to control their burn rate. And one of the best ways to do this is by reducing their cloud costs. By becoming more efficient with their cloud spend, startups can make themselves more attractive to investors and increase their chances of success.

How Cutting Cloud Costs Can Help Startup Fundraising

Brazil’s Superior Electoral Court approved a new set of rules for the use of . Among the measures are the complete ban on deep fakes and the mandatory warning of the use of AI in all content shared by candidates and their campaigns. artificial intelligence (AI) in elections The country’s next set of elections will take place in October, where voting for local mayors and councilors will take place, and the new AI rules have already come into force. This is the first set of regulations ruled on by the electoral court regarding the use of AI by candidates and political parties. The rules involve prohibiting all types of ; the obligation to warn about the use of AI in electoral propaganda, even if it is in neutral videos and photos; and the restriction of the use of robots to mediate contact with voters (the campaign cannot simulate dialogue with the candidate or any other person, for example). deep fakes According to the rules, any candidate who uses deep fakes to spread false content could lose their mandate if elected. Brazil’s electoral court defines deep fakes as “synthetic content in audio, video or both, which has been digitally generated or manipulated to create, replace or alter the image or voice of a living, dead or fictitious person.” President of the Superior Electoral Court, Alexandre de Moraes, outlined severe punishment for candidates who disrespect the regulation and use AI to harm their opponents and to distort information in order to win elections. “The sanction will be the revocation of their candidate registration and, if they have already been elected, they could lose their mandate,” he said. According to Moraes, Brazil approved one of “the most modern regulations in the world in relation to combating disinformation and the illicit use of AI” in the electoral process. Provisions for Big tech under the regulations The new regulation also provides for the liability of big tech companies, such as and (which owns , , and ), that do not immediately remove content with disinformation, hate speech, Nazi and fascist ideology, as well as anti-democratic, racist and homophobic content. Google Meta Facebook WhatsApp Instagram According to the court, the platforms must provide services “in accordance with their duty of care and their social position.” Therefore, there is a duty for providers to adopt and publicize measures to prevent or reduce the circulation of “notoriously untrue or seriously out of context” facts that affect the integrity of the electoral process. There is also a need for platforms to promote, free of charge, content that informs or clarifies untrue facts. According to Judge Moraes, the measures are necessary to prevent the use of artificial intelligence to harm candidates and especially voters’ choices. “Now, the electoral court has effective tools to combat distortions in electoral advertisements, hateful, fascist, anti-democratic speeches and the use of AI to put something into a person’s speech that they did not say,” he said. This article was originally published by on Tabata Viapiana The Sociable.

Brazil Implements Regulations on AI Usage in Elections

ব্রাজিল নির্বাচনে এআই ব্যবহারের প্রবিধান প্রয়োগ করে

Brasilien führt Vorschriften zum Einsatz von KI bei Wahlen ein

Brasil implementa regulaciones sobre el uso de IA en las elecciones

Le Brésil met en œuvre des réglementations sur l'utilisation de l'IA lors des élections

ब्राज़ील ने चुनावों में एआई के उपयोग पर नियम लागू किए

ブラジル、選挙におけるAI使用に関する規制を導入

브라질, 선거에서 AI 사용에 대한 규정 시행

Brasil implementa regulamentos sobre uso de IA em eleições

Бразилия реализует правила использования искусственного интеллекта на выборах

Brezilya Seçimlerde Yapay Zeka Kullanımına İlişkin Düzenlemeleri Uyguluyor

Brazil thực hiện các quy định về sử dụng AI trong bầu cử

巴西实施人工智能在选举中使用的规定

In today's digital age, where information is readily accessible and opinions spread like wildfire, maintaining a positive online reputation is crucial for businesses and individuals alike. Online Reputation Management (ORM) plays a vital role in shaping how a brand or person is perceived by the online community. In recent years, Artificial Intelligence (AI) has emerged as a powerful tool to enhance and streamline the ORM process. This article explores the growing significance of AI in ORM and its potential impact on managing and safeguarding online reputations effectively. What Is Online Reputation Management (ORM)? Online Reputation Management (ORM) refers to the practice of monitoring, influencing, and managing the online reputation of a brand, company, or individual. It involves a series of strategies aimed at shaping the public perception of an entity in the digital realm. ORM encompasses monitoring online reviews, social media mentions, search engine results, and other online content that may impact the reputation of the entity. The Importance of Online Reputation In today's hyper-connected world, a positive online reputation is critical for success. Consumers heavily rely on online reviews and recommendations before making purchasing decisions. A negative online reputation can lead to lost business opportunities, damaged brand credibility, and a decline in customer trust. Conversely, a positive online reputation can attract new customers, foster loyalty, and drive business growth. Challenges in ORM ORM comes with its set of challenges. The digital landscape is vast, and information spreads rapidly. Negative reviews and comments can quickly gain traction and harm an entity's reputation. Additionally, the abundance of user-generated content makes it challenging to manually track and address every mention. Human intervention alone may not be sufficient to keep up with the dynamic nature of online content. How AI Can Revolutionize ORM AI-driven solutions offer a scalable and efficient approach to ORM. Here are some ways AI can revolutionize the ORM process: Sentiment Analysis AI-powered sentiment analysis tools can automatically assess the sentiment behind online mentions. By analyzing text and social media posts, AI can determine whether the sentiment is positive, negative, or neutral. This enables businesses to identify potential reputation risks and opportunities for improvement. Automated Review Monitoring AI can monitor online reviews across various platforms, allowing businesses to promptly respond to customer feedback. Automated review monitoring helps in addressing issues quickly and efficiently, showcasing a proactive and customer-centric approach. Content Generation and Curation AI can assist in generating and curating content that aligns with an entity's values and resonates with its target audience. From blog posts to social media updates, AI can help maintain a consistent and positive brand image. Personalized Responses AI-driven chatbots and virtual assistants can engage with customers in real time, providing personalized responses to queries and concerns. These intelligent responses create a positive user experience and enhance brand reputation. AI-Driven Brand Monitoring Tools Several AI-driven brand monitoring tools have emerged in the market. These tools offer comprehensive insights into online mentions, sentiment trends, and competitor analysis. Businesses can leverage these tools to stay informed about their online reputation and make data-driven decisions. Leveraging AI in Crisis Management During a crisis or reputation-damaging event, AI can play a crucial role in crisis management. AI tools can quickly detect negative trends, enabling organizations to respond promptly and mitigate potential damages to their reputation. The Future of AI in ORM The future of AI in ORM holds immense promise. As AI technology continues to evolve, we can expect even more sophisticated sentiment analysis, predictive analytics, and AI-driven reputation strategies. This will further enhance the ability to proactively manage and safeguard online reputations. Ethical Considerations in AI-Driven ORM While AI offers numerous benefits in ORM, there are ethical considerations to address. AI algorithms must be transparent and fair, ensuring they do not propagate biases or manipulate public opinion. Striking the right balance between AI automation and human oversight is crucial to maintain authenticity and credibility. AI has emerged as a game-changer in the field of Online Reputation Management. By leveraging AI-driven tools, businesses and individuals can effectively monitor, influence, and manage their online reputations. The ability to analyze sentiments, generate personalized responses, and navigate through the complexities of the digital landscape empowers entities to maintain a positive and influential online presence. FAQs Can AI completely replace human involvement in ORM? While AI is powerful, human involvement remains essential for strategic decision-making and maintaining authenticity in ORM. Are AI-driven ORM tools expensive? The cost of AI-driven ORM tools varies, but they often provide a strong return on investment by safeguarding reputations and driving business growth. Can AI handle multilingual online mentions? Yes, advanced AI algorithms can analyze sentiments and mentions in multiple languages, making them valuable for businesses with a global presence. Is there a risk of AI misinterpreting online sentiments? AI algorithms continue to improve, but there is a slight risk of misinterpretation. Regular monitoring and human oversight can mitigate such risks. How can AI be utilized for personal ORM? AI tools can help individuals monitor their online presence, track mentions, and respond to comments or reviews, thereby improving their online reputation.

AI Usage for Online Reputation Management (ORM)

While artificial intelligence (AI) shows potential to increase profitability across most industries, its adoption is also resulting in a widening global skills gap, making upskilling workforces in AI and machine learning (ML) imperative for progress. A report by KPMG shows that among leading businesses prioritizing technology investment for profitability, a resounding 68% identify AI and machine learning as indispensable to their short-term plans. This means the need for AI skilling is such that it requires employees, employers, business organizations, and educational institutions all to pitch in. In short, building the AI-skilled workforce has to be a truly global effort. Enhancing skills in AI and Machine Learning is no longer optional but a necessity
Ruban Phukan, co-founder and CEO of GoodGist “Enhancing skills in AI and Machine Learning is no longer optional but a necessity,” Ruban Phukan, co-founder and CEO of GoodGist, an autonomous learning startup, told The Tech Panda. And the reason for this necessity, he says, is that AI saves time. “In an era where time is the scarcest resource and the boundaries between work and personal life increasingly blur, leveraging AI to optimize time is one of the most significant steps individuals can take to boost both their professional and personal productivity. This reality underscores the importance of upskilling,” Phukan explains. According to a Slack survey, workplace adoption of AI tools has sped up 24% over the previous quarter, with one out of four desk workers saying they have used AI tools at their work as of January 2024, as compared to one in five as of September 2023. “Upskilling, however, transcends mere familiarity with AI usage. It’s a critical response to the profound shifts in the business landscape and job market triggered by the rapid evolution of technology,” he adds. According to the World Economic Forum, nearly 1 billion people worldwide will need to upskill by 2030, with Korn Ferry warning that failing to do so could result in an $8.5 trillion loss in potential revenue. This is a stark backdrop to McKinsey’s projection that 87% of companies will experience a skills gap in the coming years, making upskilling not just imperative but urgent as time is of the essence here. Job postings for AI are high, but where is the talent? As AI gets integrated into all kinds of sectors, companies are starting to compete for AI talent. AI job postings surged 42% since ChatGPT’s debut, as Big Tech companies like Amazon, Google, Apple, and others like global logistics firm UPS, are beginning to shift resources to channel money into hiring machine learning engineers and data scientists. Companies are actively in search of skilled professionals to fill roles from technical leadership to applied research. These include eBay, Krutrim, Accenture, Dentsu, Gramener and others. According to an AIM report on generative AI salaries in India, large companies are offering INR 1 crore or more annually for senior roles, while startups and mid-size companies are ready to give out approx. INR 30-40 lakh. However, are these companies finding the talent they seek? As per new research, about three in four employers are struggling to hire for the AI skills they seek even though they are willing to boost salaries 43% in marketing and 35-42% across HR, finance, and legal roles. In fact, with the acceleration in AI adoption, companies are beginning to rely on education partnerships and gig work to reach the talent required. This is why skilling programs in AI are afoot. In March, IIM Lucknow and Emeritus launched the “Digital Transformation and AI for Business Leaders” Program to shape the next generation of AI leaders, an 11-month program designed to help leaders gain comprehensive insights into the intricacies of digital transformation and AI. Similarly, Physics Wallah (PW), an Indian EdTech platform, launched PW Institute of Innovation (PW IOI), a four-year residential program in Computer Science and AI to address the critical challenges faced by the Indian software industry, strategically located in Bengaluru, the Silicon Valley of India. The significant increase in the demand-supply gap for skilled AI and data science professionals further highlights the need for a comprehensive transformation in the learning approach
Vishwa Mohan, CIO at PW & President of PW IOI Vishwa Mohan, CIO at PW & President of PW IOI, said, “It is indeed concerning that despite the exponential growth witnessed in the Indian software industry, the employability rate of Indian engineering graduates has remained relatively low, with only marginal improvement over the years. Additionally, the significant increase in the demand-supply gap for skilled AI and data science professionals further highlights the need for a comprehensive transformation in the learning approach.” Employees want AI skilling from employers At the same time, employee expectations are starting to include skilling and training in AI. According to a study by EPAM India, 93% of modern engineers seek upskilling opportunities in AI, Cloud, and other new-age technologies, while 92% look for opportunities to enhance their problem-solving skills to identify and implement the best solutions. Also, 91% of respondents stated that future developmental and on-job training opportunities are their top expectations from their workplaces. Regarding their perspective for the future, 68% and 46% of modern engineers, respectively, believe that Data Analytics and AI will be the demand in the future, enabling enhancing consumer experience and collaboration. Some companies have started working on these expectations in a bid to retain talent. For example, Findability Sciences, an enterprise AI solution has trained over 100 of its data analysts and scientists across its Boston, India, and Japan operations with intensive training in problem formulation and prompt design and engineering skills. Empowering our team with these new skills is a strategic move that will pay dividends for our clients and the company. The future of AI is generative, and we are now more than ready to take it head-on
Mandar Kulkarni, AVP of Pre-sales Mandar Kulkarni, AVP of Pre-sales, said, “Empowering our team with these new skills is a strategic move that will pay dividends for our clients and the company. The future of AI is generative, and we are now more than ready to take it head-on.”?? The aim is to arm its team with the latest skills to cater to the evolving requirements of its existing and incoming customers in the generative AI arena. “This training is more than an investment in our team; it’s an investment in our clients,” says Anurag Srivastava, the Global Delivery Head. In a tech-driven business landscape, AI and machine learning expertise empower professionals to navigate disruption and contribute significantly to short-term viability and long-term success, hence its necessity as a skill is becoming inevitable. Every ecosystem has to pool in resources to meet the AI demand that will only go up in the future. Navanwita Sachdev, Editor, The Tech Panda While artificial intelligence (AI) shows potential to increase profitability across most industries, its adoption is also resulting in a widening global skills gap, making upskilling workforces in AI and machine learning (ML) imperative for progress. artificial intelligence A report by KPMG shows that among leading businesses prioritizing technology investment for profitability, a resounding 68% identify AI and machine learning as indispensable to their short-term plans. report by KPMG This means the need for AI skilling is such that it requires employees, employers, business organizations, and educational institutions all to pitch in. In short, building the AI-skilled workforce has to be a truly global effort. Enhancing skills in AI and Machine Learning is no longer optional but a necessity Ruban Phukan, co-founder and CEO of GoodGist Enhancing skills in AI and Machine Learning is no longer optional but a necessity Enhancing skills in AI and Machine Learning is no longer optional but a necessity Enhancing skills in AI and Machine Learning is no longer optional but a necessity Ruban Phukan, co-founder and CEO of GoodGist “Enhancing skills in AI and Machine Learning is no longer optional but a necessity,” Ruban Phukan , co-founder and CEO of GoodGist , an autonomous learning startup, told The Tech Panda . And the reason for this necessity, he says, is that AI saves time. Ruban Phukan GoodGist The Tech Panda “In an era where time is the scarcest resource and the boundaries between work and personal life increasingly blur, leveraging AI to optimize time is one of the most significant steps individuals can take to boost both their professional and personal productivity. This reality underscores the importance of upskilling,” Phukan explains. According to a Slack survey , workplace adoption of AI tools has sped up 24% over the previous quarter, with one out of four desk workers saying they have used AI tools at their work as of January 2024, as compared to one in five as of September 2023. a Slack survey “Upskilling, however, transcends mere familiarity with AI usage. It’s a critical response to the profound shifts in the business landscape and job market triggered by the rapid evolution of technology,” he adds. According to the World Economic Forum , nearly 1 billion people worldwide will need to upskill by 2030, with Korn Ferry warning that failing to do so could result in an $8.5 trillion loss in potential revenue. This is a stark backdrop to McKinsey’s projection that 87% of companies will experience a skills gap in the coming years, making upskilling not just imperative but urgent as time is of the essence here. According to the World Economic Forum Korn Ferry warning McKinsey’s projection Job postings for AI are high, but where is the talent? Job postings for AI are high, but where is the talent? As AI gets integrated into all kinds of sectors, companies are starting to compete for AI talent. AI job postings surged 42% since ChatGPT’s debut, as Big Tech companies like Amazon, Google, Apple, and others like global logistics firm UPS, are beginning to shift resources to channel money into hiring machine learning engineers and data scientists. AI job postings Companies are actively in search of skilled professionals to fill roles from technical leadership to applied research. These include eBay, Krutrim, Accenture, Dentsu, Gramener and others. According to an AIM report on generative AI salaries in India, large companies are offering INR 1 crore or more annually for senior roles, while startups and mid-size companies are ready to give out approx. INR 30-40 lakh. These include an AIM report However, are these companies finding the talent they seek? As per new research , about three in four employers are struggling to hire for the AI skills they seek even though they are willing to boost salaries 43% in marketing and 35-42% across HR, finance, and legal roles. In fact, with the acceleration in AI adoption, companies are beginning to rely on education partnerships and gig work to reach the talent required. research This is why skilling programs in AI are afoot. In March, IIM Lucknow and Emeritus launched the “Digital Transformation and AI for Business Leaders” Program to shape the next generation of AI leaders, an 11-month program designed to help leaders gain comprehensive insights into the intricacies of digital transformation and AI. IIM Lucknow Emeritus Similarly, Physics Wallah (PW), an Indian EdTech platform, launched PW Institute of Innovation (PW IOI), a four-year residential program in Computer Science and AI to address the critical challenges faced by the Indian software industry, strategically located in Bengaluru, the Silicon Valley of India. Physics Wallah The significant increase in the demand-supply gap for skilled AI and data science professionals further highlights the need for a comprehensive transformation in the learning approach Vishwa Mohan, CIO at PW & President of PW IOI The significant increase in the demand-supply gap for skilled AI and data science professionals further highlights the need for a comprehensive transformation in the learning approach The significant increase in the demand-supply gap for skilled AI and data science professionals further highlights the need for a comprehensive transformation in the learning approach The significant increase in the demand-supply gap for skilled AI and data science professionals further highlights the need for a comprehensive transformation in the learning approach Vishwa Mohan, CIO at PW & President of PW IOI Vishwa Mohan, CIO at PW & President of PW IOI, said, “It is indeed concerning that despite the exponential growth witnessed in the Indian software industry, the employability rate of Indian engineering graduates has remained relatively low, with only marginal improvement over the years. Additionally, the significant increase in the demand-supply gap for skilled AI and data science professionals further highlights the need for a comprehensive transformation in the learning approach.” Employees want AI skilling from employers Employees want AI skilling from employers At the same time, employee expectations are starting to include skilling and training in AI. According to a study by EPAM India, 93% of modern engineers seek upskilling opportunities in AI, Cloud, and other new-age technologies, while 92% look for opportunities to enhance their problem-solving skills to identify and implement the best solutions. Also, 91% of respondents stated that future developmental and on-job training opportunities are their top expectations from their workplaces. study Regarding their perspective for the future, 68% and 46% of modern engineers, respectively, believe that Data Analytics and AI will be the demand in the future, enabling enhancing consumer experience and collaboration. Some companies have started working on these expectations in a bid to retain talent. For example, Findability Sciences , an enterprise AI solution has trained over 100 of its data analysts and scientists across its Boston, India, and Japan operations with intensive training in problem formulation and prompt design and engineering skills. Findability Sciences Empowering our team with these new skills is a strategic move that will pay dividends for our clients and the company. The future of AI is generative, and we are now more than ready to take it head-on Mandar Kulkarni, AVP of Pre-sales Empowering our team with these new skills is a strategic move that will pay dividends for our clients and the company. The future of AI is generative, and we are now more than ready to take it head-on Empowering our team with these new skills is a strategic move that will pay dividends for our clients and the company. The future of AI is generative, and we are now more than ready to take it head-on Empowering our team with these new skills is a strategic move that will pay dividends for our clients and the company. The future of AI is generative, and we are now more than ready to take it head-on Mandar Kulkarni, AVP of Pre-sales Mandar Kulkarni, AVP of Pre-sales, said, “Empowering our team with these new skills is a strategic move that will pay dividends for our clients and the company. The future of AI is generative, and we are now more than ready to take it head-on.”?? The aim is to arm its team with the latest skills to cater to the evolving requirements of its existing and incoming customers in the generative AI arena. “This training is more than an investment in our team; it’s an investment in our clients,” says Anurag Srivastava, the Global Delivery Head. In a tech-driven business landscape, AI and machine learning expertise empower professionals to navigate disruption and contribute significantly to short-term viability and long-term success, hence its necessity as a skill is becoming inevitable. Every ecosystem has to pool in resources to meet the AI demand that will only go up in the future. Navanwita Sachdev, Editor, The Tech Panda Navanwita Sachdev, Editor, The Tech Panda Navanwita Sachdev, Navanwita Sachdev, Navanwita Sachdev, Editor, The Tech Panda

The Talent Quest: Companies' High Stakes in the AI Workforce Race

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