Latest news with #Businesses
CNN
3 hours ago
- Business
- CNN
The US economy rebounded sharply in the second quarter
Economy Donald Trump Tariffs FacebookTweetLink The US economy expanded sharply in the second quarter as businesses dialed back on imports after stocking up earlier in the year to get ahead of President Donald Trump's tariffs. Gross domestic product, which captures all the goods and services produced in the economy, registered an annualized rate of 3% in the April-through-June period, the Commerce Department said Wednesday. That's up sharply from the -0.5% rate in the first quarter, which was the first quarterly GDP decline since 2022. Economists polled by data firm FactSet estimated second-quarter GDP to come in at a 2% rate. The latest GDP report is a key part of an avalanche of economic news this week expected to show how consumers and businesses are weathering Trump's sweeping economic policies. But the tariff-driven buying frenzies in the beginning of the year have made it difficult to asses the underlying health and direction of the world's largest economy. In the first quarter, surging imports took a toll on economic growth, but that trend reversed in the second quarter as businesses drew from their existing inventories instead of importing, in turn boosting GDP. This story is developing and will be updated.
Borneo Post
21-07-2025
- Business
- Borneo Post
Pilot project to smoothen business registration process to kick off Aug 1 in Sibu, Kanowit
(Seated, from left) Sempurai, Tiang, Dr Sim, Hii, Loh and others pose with the thumbs-up gesture during a photo-call. SIBU (July 22): A pilot project to reform the process of starting up a business in Sarawak will be implemented effective this Aug 1, in the districts of Sibu and Kanowit, and will be running for six months. According to Deputy Premier Datuk Amar Dr Sim Kui Hian, the project was spearheaded by the state government through the Sarawak Transformation and Innovation Unit in the Sarawak Premier's Department; Ministry of Public Health, Housing and Local Government; and Malaysia Productivity Corporation (MPC). He said under the pilot project, all business registrations involving business name, trade licence and operating licence applications would be coordinated by one agency, namely the local authorities in Sibu and Kanowit, via one facilitation centre. 'Applicants will only need to fill in one composite form that captures all necessary information for business name registration, trade licence and operating licence applications. 'The pilot project targets a processing time from application to licence collection within 14 working days for low-risk businesses, while high-risk business applications such as sales of gas, entertainment centres, elderly or childcare centres and reflexology centres will be processed within 30 working days,' he said in a press conference here yesterday. Dr Sim added that for applications requiring only the business name and trade licence, the licence could be collected within five working days, while licences for those requiring an operating licence could be collected within 14 working days. 'This means applicants only need to visit the counter a maximum of two times. Studies show that licence processing time for business registration may take up to 60 days or more. 'Through this project, the processing time will be reduced from over 60 working days to only 14 or up to 30 working days.' Earlier, Dr Sim said business registration in Sarawak typically involves three main components depending on the type of business, namely the business name registration, trade licence and operating licence. These are governed by Chapter 64 of the Business Names Ordinance 1958, Chapter 33 of the Businesses, Professions and Trades Licensing Ordinance 1958, Local Authorities Ordinance 1996 and other various regulations and bylaws. 'At present, business registration in Sarawak involves various government departments and agencies such as Inland Revenue Board, District Offices, Divisional Treasury Department and Local Authorities. 'For instance, in Sibu District, the process involves the Sibu District Office, Sibu Divisional Treasury Department, and two local authorities namely the Sibu Municipal Council and Sibu Rural District Council (SRDC). 'On top of the agencies that I have mentioned, there is still approval from agencies that may be required, such as from the Fire and Rescue Department, Land and Survey Department and the Health Department. 'Due to this requirement, applicants are required to deal with multiple agencies at various locations, making the process inefficient and time-consuming. In addition, applicants are required to fill in multiple forms, depending on the business type and licenses applied for,' he said. According to the Deputy Premier, this effort was crucial to stimulate business activities in Sarawak and position the region as a more investor-friendly destination. 'Therefore, Sarawak must act swiftly to seize this opportunity by accelerating and streamlining the investment and business processes. This pilot project is a strategic step in that direction. 'We aim to ensure Sarawak remains competitive as an investment destination that offers administrative efficiency, process certainty, and strong governmental support to the business community. 'I urge all agencies involved to give their full commitment and support to ensure the success of this pilot project, which will serve as the foundation for statewide implementation across Sarawak,' he said. He added that under the Sarawak Digital Economy Blueprint 2030, the Sarawak government had been actively driving digitalisation initiatives for business registration to boost public confidence in transacting with the government via online platforms. 'Existing systems such as e-R&DO and e-LA2 will also be upgraded in the near term to support this digital initiative,' he said. Also present were Deputy Minister of Public Health, Housing and Local Government Sarawak Datuk Michael Tiang, Deputy State Secretary Datu Hii Chang Kee, the ministry's permanent secretary Datu Elizabeth Loh and SRDC chairman Sempurai Petrus Ngelai. business registration Dr Sim Kui Hian lead start-up businesses
Geeky Gadgets
20-07-2025
- Business
- Geeky Gadgets
Why Most AI Apps Fail Before Launch and How to Beat the Odds
Have you ever wondered why so many promising AI applications never make it past the prototype stage or fail to deliver on their potential? Despite the buzz around artificial intelligence, shipping a functional, scalable AI app is far from straightforward. Unlike traditional software, AI applications come with a unique set of challenges: skyrocketing operational costs, safeguarding against misuse, and the constant pressure to meet ever-evolving user expectations. It's a high-stakes balancing act where even small missteps can lead to spiraling expenses or a poor user experience. For developers and businesses alike, the road to deploying AI isn't just bumpy—it's a minefield. App developer Chris Raroque explains the hidden complexities of bringing AI-powered applications to life and uncover strategies to navigate them effectively. From optimizing operational expenses to designing user-centric platforms, you'll gain insights into the real-world challenges that go beyond the hype. Whether it's using multiple AI models to balance performance and cost or carving out a competitive edge with niche-specific solutions, this guide will show you how to overcome the hurdles that make shipping AI apps so hard. Because in a world where innovation often outpaces practicality, success lies in mastering the details that others overlook. AI App Development Challenges Cost Management: Optimizing Operational Expenses AI applications, particularly those powered by large language models, demand significant computational resources, which can lead to high operational costs. For instance, processing lengthy conversation histories or prompts for every interaction can quickly inflate expenses. To manage these costs effectively, consider adopting the following strategies: Shorten prompts to include only the most relevant information, reducing unnecessary data processing. Implement a 'window' technique to limit the conversation history processed by the model, focusing only on recent and pertinent interactions. These methods help minimize resource consumption while maintaining a seamless user experience. By optimizing operational expenses, you can ensure your application remains cost-effective without compromising its functionality or quality. Abuse Prevention: Protecting Your System AI systems are inherently vulnerable to misuse, which can result in excessive costs, degraded performance, or even system failures. To safeguard your application and maintain its reliability, you should implement robust protective measures, such as: Setting limits on message size and user activity, such as daily or monthly usage caps, to prevent overuse. Incorporating a remote kill switch to disable abusive accounts in real time, making sure immediate action against misuse. Using analytics tools to monitor usage patterns and detect anomalies that may indicate abuse. These safeguards not only protect your system from potential threats but also ensure a consistent and reliable experience for all users, fostering trust and satisfaction. The Real Challenges of Deploying AI Apps Watch this video on YouTube. Browse through more resources below from our in-depth content covering more areas on AI application development. Using Multiple AI Models: Balancing Efficiency and Performance Relying on a single AI model for all tasks may seem straightforward, but it is often inefficient and costly. Instead, deploying multiple models optimized for specific tasks can significantly enhance both performance and cost efficiency. For example: A lightweight model can handle basic queries quickly and efficiently. A more advanced model can address complex or nuanced requests that require deeper analysis. By incorporating a decision layer, your system can dynamically select the most appropriate model based on the user's input. This approach ensures that resources are allocated efficiently, reducing costs while maintaining high levels of performance and responsiveness. Platform Optimization: Designing for the Right Environment The success of your AI application depends heavily on how well it aligns with its intended platform. For example, if your application is primarily used on mobile devices, adopting a mobile-first design approach is essential. Features such as voice dictation, quick commands, and streamlined interfaces can significantly enhance usability for on-the-go users. By tailoring your design to the platform, you can create a seamless and intuitive user experience that meets the specific needs of your audience. Framework Utilization: Accelerating Development Building an AI application from scratch can be a time-intensive and error-prone process. To streamline development and improve reliability, you can use existing frameworks like the Versel AI SDK or similar tools. These frameworks offer pre-built functionalities that simplify the development process, including: Streaming capabilities for real-time interactions, enhancing responsiveness. Error handling mechanisms to improve system stability and reliability. Tool integration options to expand the functionality of your application. By using proven frameworks, you can focus on developing core features while reducing development time and making sure a stable, high-quality product. Personalization: Delivering Tailored User Experiences Personalization plays a crucial role in creating engaging and user-friendly AI applications. Allowing users to specify preferences in natural language can significantly enhance their experience. For instance, users might request a specific tone, style, or level of detail in responses, and your application can adapt accordingly. This level of customization not only improves user satisfaction but also helps differentiate your product from generic AI tools, making it more appealing and valuable to your target audience. Niche-Specific Solutions: Carving Out a Competitive Edge In a market dominated by general-purpose AI tools like ChatGPT or Claude, focusing on niche-specific solutions can give your application a distinct competitive advantage. By addressing the unique needs of a specific audience, you can provide a more tailored and efficient experience. For example, an AI tool designed for legal professionals might include features such as legal document summarization, case law analysis, or contract drafting assistance. These specialized capabilities make your product more valuable and relevant to its target users, helping it stand out in a crowded marketplace. Key Considerations for Successful AI Application Development To navigate the complexities of AI application development effectively, keep the following considerations in mind: Monitor costs and usage from the outset to avoid unexpected expenses and ensure long-term sustainability. Use multiple models to balance efficiency and performance, optimizing resource allocation. Design with the intended platform in mind to create a seamless and intuitive user experience. Use existing frameworks to accelerate development and enhance system reliability. Focus on niche-specific solutions to differentiate your product and meet the unique needs of your target audience. By addressing these factors with careful planning and strategic execution, you can create AI applications that are not only functional but also scalable, cost-effective, and user-friendly. In an increasingly competitive landscape, these considerations will help ensure the success and longevity of your AI product. Media Credit: Chris Raroque Filed Under: AI, Guides Latest Geeky Gadgets Deals Disclosure: Some of our articles include affiliate links. If you buy something through one of these links, Geeky Gadgets may earn an affiliate commission. Learn about our Disclosure Policy.
Forbes
16-07-2025
- Business
- Forbes
As Data Breaches Soar, C-Suite Looks to Customer Data Management
Customer data management (CDM) best practices have never been more crucial to today's brands as they face escalating data breaches, which come with severe brand trust, balance-sheet, and customer retention issues. Throw rising competition, increased customer expectations, and a growing need for improved decision-making into the mix, and the need for strong CDM practices makes its own case. Companies need to move, store, and analyze party data so that they can effectively target customers and offer deep personalization. Most importantly, data security is especially critical to brands and businesses today – a data breach can cost companies millions within moments and break customer trust for a lifetime. The complication of data breaches create a heightened demand for corporate accountability related to data security Customers are expected to hand over their data today in most interactions with brands and businesses, but consumer frustrations are mounting as more and more data breaches and hacks occur. The calls for accountability are coming from both the consumers, as well as legislators, with good reason. For many businesses, manual data-gathering efforts using Excel spreadsheets work—up to a point. As the company grows, however, so does the data and the need to make sense of it. This can quickly become unwieldy and unhelpful: Organizations can easily get lost and overwhelmed in large data sets and lose out on potentially valuable insights that help them stand out to their customers and improve the customer journey. That's when it's time for a big change—enter customer data management strategies and solutions. Winding path-to-purchase requires deep customer understanding Unlike past decades, when channels were separate and siloed, today's path-to-purchase is a long and winding road. Multiple touchpoints, both online and off, need to stay connected— including email, CRM, e-commerce, social media, and retail POS. That means it's essential for organizations to deeply understand the customer at every stage. Customer loyalty will soon depend on a company's willingness to protect customer information with the same fervor they pursue revenue. Making sense of the data allows customers to be valued more A range of cloud-based solutions are now commonly used for customer data management that serves as the centralized, beating heart of the effort to improve customer acquisition, satisfaction, and retention; improve customer visibility and targeted communication, and boost data quality. Ultimately, businesses need customer data management to work towards achieving a single customer view that allows them to provide the seamless customer experience that consumers have come to expect, as well as calculate important metrics such as the Customer Lifetime Value (CLV). However, it's not just about the technology: It's about the strategies, policies, and actions that make customer data management an effective effort that helps drive growth. Customer data management best practices: 7 important points brands should consider Following are seven best practices for customer data management: Data needs to be managed with internal standards and policies, to ensure that the organization handles data assets properly throughout the data lifecycle. Make sure the entire company is aligned, across the board, in terms of what data is collected, data points, and how it will be tracked and used. Data protection regulations, such as the European Union's General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) are on the rise. The right customer data management platform should make compliance with customer data regulations easy and straightforward. It's important to determine what specific types of data are most effective to serve your customers and achieve your marketing goals. There are a variety of data categories and industry-specific data to consider, from your customer's identity data, loyalty program information, and online transactional data to demographic information, social media data, and qualitative data about attitudes and opinions. Not only are data leaks and breaches becoming more costly every year—the average cost of a data breach in 2024 was $4.9 million—but these events can also severely impact a company's reputation, as well as its bottom line. If you aren't steering the security ship and communicating your commitment, you run the risk of falling into consumer doubt. After all, customers want to know their information is safe. It's essential to choose a customer data management platform that has the right security standards and practices in place. According to an IBM report, 83% of companies suffer from data inaccuracy. Not only is outdated, inaccurate data not useful, but customer satisfaction and decision-making may suffer and lead to rising costs. The key to good customer data management is making sure customer data is regularly cleaned: That is, validating and updating information including email addresses, phone numbers, and addresses, as well as removing duplicates and deleting unnecessary contacts. Forbes noted that companies now house an average of 15 silos of customer data. It doesn't have to be that way: Don't allow useful data such as call-center information, sales leads, emails, or finance communication to become useless, trapped in department and technology silos. Data needs to be securely shared and accessible, in ways that promote collaboration, problem-solving, and improved decision-making. A complete, omnichannel customer journey includes customer profiles filled out with profile, activity, event, demographic and behavioral data, as well as data related to intent and perception. Getting to that goal requires robust end-to-end customer data management solutions that are highly scalable and can store billions of profile and consent records. It's not enough to have customer data or even a holistic profile. Identity data must be collected and managed appropriately throughout the entire customer lifecycle. That means providing a frictionless customer experience with flexible registration, secure interaction touchpoints, and simplified authentication based on real-time, data-driven insights. The future of customer data is bright—and unified Today's buyers are in control. With a quick click or swipe, they can abandon a brand and make a quick move to the competition, or they can remain long-term loyalists. That means customers —their wants, their needs, their preferences, their expectations—need to be at the heart of every business. Companies have to understand how to gather and analyze the right data in order to collect insights that help them deliver meaningful, seamless experiences to their buyers. This is the promise and power of customer data management best practices: With the right platform that integrates with a company's existing sales and marketing technologies, customer data management helps brands deeply understand their customers through a holistic, unified, centralized, real-time view of data. But organizations also need to follow best practices and prioritize successful strategies in order to make customer data management successful. Effective data management is a promise to customers and an investment in your future. The first step is deciding to take control. You can do that today. This post was first published on The Future of Commerce and is republished here with permission.
CTV News
13-07-2025
- Automotive
- CTV News
Lane restrictions on Dundas Street start Monday
Starting Monday, Dundas Street between Burdick Place and Beatrice Street in the city's east end will have reduced lanes in each direction. According to the City of London, crews will be fixing the road and sidewalks, replacing damaged catch basins, paving new asphalt, repairing water valves and maintenance holes, and upgrading the traffic signals. Sidewalks will be temporarily closed during this time, but all businesses will remain open and accessible. Construction is expected to be finished this fall.
