Whether you’re scanning a QR code to check out a menu, make a payment, or access exclusive content, these simple squares are creating seamless digital bridges all around us. Their growing versatility, especially for businesses and individuals alike, is driving increased demand for easy-to-use tools, such as a qr generator, which simplifies the process of creating these codes.

QR codes offer remarkable flexibility, enabling anyone to tailor them for a wide range of uses. Whether directing users to a website, sharing vital documents, or providing a special discount, QR codes can accomplish these tasks swiftly and effectively.

Practical Ways to Use QR Codes in Everyday Life

QR codes are transforming how we interact with technology by offering fast, contactless solutions to everyday tasks. Their uses are nearly limitless, but here are some of the most practical applications for free QR codes:

• payments – use a qr generator free to create a code that links to a payment gateway, allowing quick and contactless transactions;
• marketing – fusinesses can create free QR codes to promote special offers or direct consumers to their website, maximizing their reach with just one scan;
• education – teachers and institutions can generate QR codes for students to access additional resources, digital handouts, or assignments;
• healthcare – QR codes can be used to provide patients with instant access to their medical records or instructions for prescriptions;
• events – instead of printing physical tickets, organizers can use QR codes for entry, schedules, or maps, enhancing the event experience.

With these simple applications, QR codes are not only saving time but also providing a secure and convenient way to manage personal and business needs.

Why QR Codes Are Becoming Indispensable

The secret behind the growing success of QR codes lies in their adaptability. From contactless payments to marketing promotions, they can serve a wide range of purposes. But what truly makes them a vital part of today’s technology landscape is their user-friendly nature and cost-effectiveness. Anyone can easily create a QR code for free using an online QR code generator, enabling both businesses and individuals to harness the power of this tool without a large financial commitment.

Platforms like me-qr.com have made the process of generating QR codes even simpler. With their free online tool, you can create custom QR codes in just a few minutes. Whether you’re a small business owner looking to enhance customer engagement or an individual wanting to streamline everyday tasks, me-qr.com offers the perfect solution.

Conclusion

QR codes are far from being a fleeting trend—they’ve rapidly evolved into a crucial tool for navigating the digital landscape, enhancing efficiency, convenience, and security in our daily lives. Whether you’re generating a QR code for personal or business use, adopting this technology can open up a world of new opportunities right at your fingertips.

As subscriptions have taken over countless industries, companies have engaged in a plethora of practices aimed at making it almost impossible for consumers to easily cancel. The FTC has been working to address the problem, developing a rule to govern the practice.

“Too often, businesses make people jump through endless hoops just to cancel a subscription,” said Commission Chair Lina M. Khan. “The FTC’s rule will end these tricks and traps, saving Americans time and money. Nobody should be stuck paying for a service they no longer want.”

The agency is particularly focused on “negative option marketing.” In 2009 report, the FTC defined its use of the term.

The FTC uses the phrase “negative option marketing” broadly to refer to a category of commercial transactions in which sellers interpret a customer’s failure to take an affirmative action, either to reject an offer or cancel an agreement, as assent to be charged for goods or services. Negative option marketing can pose serious financial risks to consumers if appropriate disclosures are not made and consumers are billed for goods or services without their consent. With the explosion of Internet marketing over the past ten years, negative option offers are as much a fixture of online advertising as in any other advertising media. The workshop focused particularly on Internet-based negative option offers, because they are relatively new and present distinct issues regarding the form, content, and timing of disclosures.

The new rule will apply to virtually all negative option programs.

The Commission’s updated rule will apply to almost all negative option programs in any media. The rule also will prohibit sellers from misrepresenting any material facts while using negative option marketing; require sellers to provide important information before obtaining consumers’ billing information and charging them; and require sellers to get consumers’ informed consent to the negative option features before charging them.

The agency says the new rule will prohibit sellers from the following:

• misrepresenting any material fact made while marketing goods or services with a negative option feature;
• failing to clearly and conspicuously disclose material terms prior to obtaining a consumer’s billing information in connection with a negative option feature;
• failing to obtain a consumer’s express informed consent to the negative option feature before charging the consumer; and
• failing to provide a simple mechanism to cancel the negative option feature and immediately halt charges.

The agency’s new rules should go a long way toward improving the consumer experience, making it easy to cancel unwanted subscriptions.

As the tech industry continues to evolve, especially with the rise of AI, tech secrets are more valuable than ever, with many even playing a role in national security concerns. According to Reuters, South Korea is cracking down on leaks that threaten its tech companies’ intellectual property.

“We will prevent illegal leaks of advanced technologies to raise the global competitiveness of our companies and strengthen technology leadership,” Finance Minister Choi Sang-mok said.

As Reuters goes on to highlight, South Korea has experienced at 97 attempts to steal its tech secrets in the past five years, with many of those being attempts to steal semiconductor secrets. South Korea has already designated 12 industries as “national strategic technologies.”

While Choi said the South Korean government would introduce stronger penalties for leakers, he did not reveal what those penalties would entail.

Once the only truly competitive hardware platform, x86 has faced growing challenges from Arm, as well as the up-and-coming RISC-V. Intel and AMD want to spur further innovation in the x86 ecosystem, ensuring it remains viable and competitive for years to come.

For over four decades, x86 has served as the bedrock of modern computing, establishing itself as the preferred architecture in data centers and PCs worldwide. In today’s evolving landscape — characterized by dynamic AI workloads, custom chiplets, and advancements in 3D packaging and system architectures — the importance of a robust and expanding x86 ecosystem is more crucial than ever.

The advisory group includes Broadcom, Dell, Google, Hewlett Packard Enterprise, HP, Lenovo, Meta, Microsoft, Oracle, and Red Hat, as well as Linux founder Linus Torvalds and Epic Games founder Tim Sweeney.

“We are on the cusp of one of the most significant shifts in the x86 architecture and ecosystem in decades – with new levels of customization, compatibility and scalability needed to meet current and future customer needs,” said Pat Gelsinger, Intel CEO. “We proudly stand together with AMD and the founding members of this advisory group, as we ignite the future of compute, and we deeply appreciate the support of so many industry leaders.”

“Establishing the x86 Ecosystem Advisory Group will ensure that the x86 architecture continues evolving as the compute platform of choice for both developers and customers,” said Lisa Su, AMD Chair and CEO. “We are excited to bring the industry together to provide direction on future architectural enhancements and extend the incredible success of x86 for decades to come.”

The group’s goals include unifying instruction sets and architectural interfaces to improve compatibility across x86 platforms. The group specifically wants to achieve the following:

• Enhancing customer choice and compatibility across hardware and software, while accelerating their ability to benefit from new, cutting-edge features.
• Simplifying architectural guidelines to enhance software consistency and standardize interfaces across x86 product offerings from Intel and AMD.
• Enabling greater and more efficient integration of new capabilities into operating systems, frameworks and applications.

The group touted the good that can come when Intel and AMD cooperate on standards, despite being competitors.

As vigorous competitors, Intel and AMD at the same time share a history of industry collaboration focused on platform-level advancements, the introduction of standards, and security vulnerability mitigation within the x86 ecosystem. Their joint efforts have shaped key technologies, including PCI, PCIe, Advanced Configuration and Power Interface (ACPI). Both companies also played a pivotal role in developing USB, a vital connectivity standard for all computers regardless of the processor. This advisory group takes this industry collaboration to the next level for the benefit of the entire computing ecosystem and as a catalyst for product innovation.

Government agencies have already been adopting AI across the spectrum, using it for everything from healthcare to improving utilities and infrastructure. Google is hoping to help ease the adoption even more, using its new $15 million grants as a step in that direction.

At Google Public Sector Summit in Washington D.C., Google unveiled the grants to the Partnership for Public Service and InnovateUS.

The first $10 million grant is to the Partnership for Public Service and InnovateUS.

A $10 million grant to the nonpartisan nonprofit the Partnership for Public Service will help establish the Center for Federal AI, a hub launching in Spring 2025 that is dedicated to cultivating AI leadership and talent within the federal government. At the Center, everyone from interns to executives can learn how to use AI responsibly in their government agencies. As part of this, the Center will offer a federal AI leadership program, federal AI internship program, and initiatives to foster a vibrant learning community for federal AI leaders.

“AI is today’s electricity — it’s a transformative technology that is fundamental to the public sector and to our society,” says Max Stier, president and CEO of the Partnership for Public Service. “Google.org’s generous investment will enable the Partnership to expand our current programming and research, and offer innovative new programming to empower agencies to capitalize on AI and better serve the public. We appreciate Google.org’s commitment to effective government, and we are excited to partner with them to launch the Partnership’s new Center for Federal AI this spring.”

The second $5 million grant is to InnovateUS.

An additional $5 million of funding will go to InnovateUS, supported by a consortium of federal, state, and local government partners. This organization has been at the forefront of providing no-cost AI training to public sector workers through at-your-own-pace courses, live workshops, and training programs. InnovateUS has trained more than 40,000 learners and has more than 100 agency partners.

“For government to work better and be more accessible to the people it serves, our workers must have the opportunity to take advantage of the latest tools and technologies,” said Beth Simone Noveck, Founder of InnovateUS and Chief AI Strategist for the State of New Jersey. “By continuing to invest in upskilling programs for public sector professionals offered through InnovateUS, we can improve the effectiveness of how we solve problems while restoring much-needed trust in our government.”

Google says AI is set to play a pivotal role in the future of AI, with these latest grants part of the existing AI Opportunity Fund.

The funding announced today is a part of Google.org’s $75 million AI Opportunity Fund, which aims to help Americans learn essential AI skills. This funding, along with the efforts of organizations like the Partnership for Public Service and InnovateUS, are paving the way for AI to play a central role in improving government services and addressing societal challenges. By investing in AI training and upskilling, we can help ensure the public sector harnesses the full potential of AI to support critical needs such as healthcare access, infrastructure management and public safety, which benefit us all.

According to BleepingComputer, bad actors have been trying to sell data purportedly stolen from Cisco via online forums. The hackers making the claims are the well-known “IntelBroker,” working along with “EnergyWeaponUser and “zjj.”

Tune in as we dive into hackers’ claims of breaching Cisco!

“Compromised data: Github projects, Gitlab Projects, SonarQube projects, Source code, hard coded credentials, Certificates, Customer SRCs, Cisco Confidential Documents, Jira tickets, API tokens, AWS Private buckets, Cisco Technology SRCs, Docker Builds, Azure Storage buckets, Private & Public keys, SSL Certificates, Cisco Premium Products & More!,” reads the post on one hacking forum.

Cisco says it is aware of the hackers’ claims and it is investigating their validity.

“Cisco is aware of reports that an actor is alleging to have gained access to certain Cisco-related files,” a Cisco spokesperson told BleepingComputer.

“We have launched an investigation to assess this claim, and our investigation is ongoing.”

The hackers say they breached Cisco on October 6 and provided samples of the purported stolen data, although they did not provide details on how the hack was carried out.

Tesla has lifted the curtain on a series of major revelations about its upcoming robotaxi, providing a glimpse into its strategic efforts to revolutionize autonomous transport. The recent Tesla event left industry experts and analysts buzzing as Tesla executives discussed everything from the intricacies of the robotaxi’s engineering to its potential market impact.

Jeff Lutz, a seasoned supply chain executive, offered key insights on the Brighter with Herbert YouTube channel, noting that Elon Musk’s recent moves have been “mind-boggling” in their scope and ambition.

Revealing the Cyber Cab

One of the centerpieces of Tesla’s announcement was the unveiling of what insiders are now calling the “Cyber Cab,” a two-seater robotaxi designed to change how people experience urban transport. According to Lutz, this new prototype is more than just a concept vehicle; it represents the future of mass-produced autonomous transport. “They had twenty of these out there, and it wasn’t just for show. We got in them and experienced what Tesla has been working towards,” said Lutz, pointing to the impressive scope of the demonstration.

The design of the Cyber Cab is an embodiment of Tesla’s emphasis on efficiency and purpose-driven features. Lutz highlighted that every element, from the doors to the seats, has a reason behind it. “This isn’t just about aesthetics,” he said, emphasizing the utilitarian nature of Tesla’s choices. “Tesla has always been about pushing boundaries, and here it’s about engineering for functionality and cost-efficiency. This is what will make scaling these vehicles feasible.”

Autonomous Driving & Hardware 3

One of the major questions surrounding the Cyber Cab was whether it would run on Tesla’s existing autonomous technology. During the event, Kim Java interviewed Tesla executives Franz von Holzhausen and Lars Moravy, who confirmed that the Cyber Cab leverages Tesla’s Full Self-Driving (FSD) software, and even older vehicles equipped with Hardware 3 could be made ready for robotaxi duties. “Yes, it’s good to go even with Hardware 3,” Moravy stated, dispelling doubts about the capability of earlier models. This revelation points to Tesla’s broader approach of making its entire fleet adaptable, a strategy that promises to extend the operational life and usefulness of its older cars.

Lutz elaborated on this point, mentioning how Tesla’s steer-by-wire technology is playing a critical role in these advancements. “Tesla is using the Cybertruck as a platform to refine steer-by-wire technology, which is crucial for scaling the Cyber Cab,” Lutz explained. “They’ve figured out how to get it right with the Cybertruck, and now they can scale that to the robotaxi. It’s all about building on existing innovations to move faster.”

Why No Steering Wheel?

Another key feature of the Cyber Cab is the option to remove the steering wheel, an idea that seems counterintuitive but makes perfect sense in Tesla’s grand strategy. “Tesla wants to build a super set that leaves the factory in one way and then adapts to customer needs,” said Lutz. “If a customer needs a steering wheel, it can be added. If they don’t, it stays out, which ultimately reduces manufacturing complexity. Tesla’s objective here is clear—reduce changeover and maintain production efficiency.”

The robotaxi is a two-seater, which some analysts have speculated is part of a plan to eventually evolve the vehicle into a $25,000 mass-market car. Lutz commented, “It makes perfect sense. This is Tesla testing the waters. If they can do this with a robotaxi, then scaling down to a compact model, including options like a steering wheel, is entirely possible.”

Elon Musk’s Long-Term Vision

Lutz believes that Musk’s ambitious vision for Tesla’s robotaxi goes well beyond what other companies have managed so far. “You see companies showing off flashy prototypes that ultimately fail to scale economically. Tesla starts with production solutions—they design for scale from day one. That’s the difference,” Lutz emphasized.

Just unbelievable https://t.co/KpJV3j1W68

— Jeff Lutz (@thejefflutz) October 13, 2024

He also reflected on the significant improvement in AI and hardware integration since Tesla’s AI Day in 2022. “I was there, sitting in the third row. In just 24 months, they’ve gone from a single humanoid walking on stage to an entire army of Tesla Bots interacting and serving drinks,” Lutz said. “The rapid progress they’ve made—both with autonomous cars and robotics—is something no one else in the market has come close to achieving.”

The First Robotaxi Customers: Salesforce?

One of the unexpected revelations during the event was the potential for Salesforce to become one of the first major customers for Tesla Bots. Mark Benioff, CEO of Salesforce, was in attendance and appeared impressed with the capabilities of Tesla’s humanoid robots. Benioff hinted at a future collaboration, posting about using these robots to power Salesforce’s “agent force,” essentially putting Tesla Bots in customer service roles in various sectors.

“Mark knows partnerships,” said Lutz. “He was there for a reason—to see if Tesla’s vision could integrate into Salesforce’s ecosystem. The Bots’ ability to serve drinks and interact with people shows they’re beyond just a concept. It’s a functioning reality. If Salesforce signs on, it’s the beginning of a massive new market for Tesla.”

No $25,000 Compact Car—Yet

Despite speculation, Tesla did not unveil a new $25,000 compact car during the event, and Lutz wasn’t surprised. “Tesla is not going to introduce a lower-cost vehicle until they have the right timing to manage existing inventory and avoid any disruptions in their current supply chain,” he said. “It’s about avoiding what’s called ‘excess and obsolescence’ (E&O). Introducing a new model too soon would create a financial liability in the form of unsold inventory. Tesla is playing the long game, and they’re not going to risk their balance sheet just to satisfy market rumors.”

Lutz pointed out that Tesla’s approach to reducing the cost of the Cyber Cab—from the simple, non-motorized seats to the single-pane side windows—is all part of making autonomous vehicles economically viable. “Elon Musk said it would cost around $30,000, and that likely includes FSD,” Lutz added. “The economics of this vehicle are focused on hitting the price point needed for mass adoption, but not at the expense of Tesla’s production efficiency.”

Scale and Simplicity: The Tesla Advantage

At its core, Tesla’s robotaxi is built for scale. The company has thought through every aspect of the vehicle—from wireless charging to optimized seat designs that facilitate faster cleaning—all with the goal of reducing cost and increasing operational efficiency. “Tesla’s vision isn’t just about putting an autonomous car on the road,” Lutz said. “It’s about an integrated system, including charging, maintenance, and even cleaning—all designed to scale.”

According to Lutz, the absence of a charge port and the move towards wireless charging is a bold step. “Five years from now, wireless charging will be the norm, and Tesla is already building for that future. The reduction in complexity and cost from removing traditional charging components is significant.”

The Bigger Picture: Partnerships and the Future of Tesla

Lutz believes the event served as more than a tech showcase—it was a signal to potential partners that Tesla’s solutions are ready for real-world applications. “In 2022, the event was about recruitment, about showing off Tesla’s engineering prowess,” Lutz explained. “This year, it was about partnerships. There were CEOs and corporate executives everywhere—people who could see firsthand the potential of these robots and autonomous cars to transform their own operations.”

“What people don’t realize is that Tesla isn’t just selling cars anymore,” Lutz continued. “They’re selling solutions—FSD, Optimus, software, and now potentially, robots. The sum of Tesla’s parts is becoming far greater than the whole, and no one’s properly modeling this yet. Tesla is about to fundamentally change the game, and this event was just the beginning.”

Tesla’s robotaxi project is more than just a new model of transport—it’s the embodiment of Elon Musk’s vision for scalable, autonomous solutions. As Tesla navigates partnerships, prepares to scale its production, and explores new applications for its AI and robotics, it’s clear that the company is playing at a different level. Jeff Lutz summed it up well: “Tesla’s not just a car company anymore—it’s a technology company building the future.” As Tesla brings the Cyber Cab closer to reality, it signals the dawn of a new era in transport, manufacturing, and human-machine collaboration, with the potential to disrupt industries far beyond the automotive sector.

Perplexity, which launched two years ago, has positioned itself as an emerging challenger to search giants like Google, offering users AI-generated summaries with selected sources and links. Despite the demand from the New York Times, Perplexity CEO Aravind Srinivas stated, “We are very much interested in working with every single publisher, including the New York Times. We have no interest in being anyone’s antagonist here.”

Tune in for the New York Times vs. Perplexity AI clash!

The Stakes for Publishers

The clash between Perplexity and the Times is not an isolated incident. Generative AI technologies are reshaping the landscape for media and content-driven industries, prompting publishers to recalibrate their strategies in the face of rapid advancements. News outlets, long reliant on advertising and subscription revenue, see both promise and peril in AI. The technology’s ability to analyze data and create content at scale offers efficiency, but it also introduces new risks of misuse and content theft.

The Times has been proactive in protecting its content, and this isn’t the first time it has taken legal action to curb AI firms from exploiting its journalism. The publisher has also filed a lawsuit against OpenAI, the creator of ChatGPT, for alleged copyright infringement. “Perplexity and its business partners have been unjustly enriched by using, without authorization, The Times’s expressive, carefully written and researched, and edited journalism without a license,” the Times wrote in its notice to Perplexity.

The Current Lawsuit Against OpenAI

The New York Times’ legal action against OpenAI further highlights the intensifying struggle between publishers and AI companies over content rights. The lawsuit, filed late last year, accuses OpenAI of using millions of the Times’ articles without permission to train its language models, including ChatGPT. The Times claims that OpenAI’s actions constitute copyright infringement, as its chatbot generates summaries and responses based on the expressive content of the Times’ journalism.

OpenAI, for its part, has denied any wrongdoing, arguing that the data used in training ChatGPT falls under fair use, a defense often invoked by AI companies. The company also contends that some of the Times’ tests in support of the lawsuit were specifically designed to provoke outputs resembling original articles, which OpenAI claims were not representative of typical chatbot responses.

The implications of this lawsuit extend beyond just OpenAI and the Times. If successful, it could set a precedent for how AI companies can legally access and use publisher content, shaping the future of generative AI models and the scope of fair use. This legal battle underscores the broader concerns that media companies have about AI scraping and summarizing their work without appropriate compensation or licensing agreements.

The lawsuit against OpenAI shares many parallels with the current demands made to Perplexity, as both companies have been accused of unauthorized use of copyrighted content. As the generative AI landscape evolves, the outcomes of these legal actions could have significant ramifications for the boundaries between content ownership and technological innovation.

Perplexity’s Response

Perplexity has reportedly assured the Times in the past that it would stop using crawling technology that circumvents website restrictions, but the Times asserts that the company’s assurances have not been honored. The Times asked Perplexity to provide detailed information on how it has been accessing the publisher’s website despite the Times’s preventative measures.

In response, Srinivas emphasized that Perplexity “isn’t ignoring the Times’s efforts to block crawling of its site.” He added that the company plans to address the issues raised in the legal notice by the October 30 deadline. Perplexity has previously struck a handful of deals with publishers, though media companies have described the startup’s terms as less favorable compared to the lucrative licensing agreements that others, like OpenAI, have offered.

Perplexity’s Challenge to Google

Perplexity is backed by Jeff Bezos, and while the company is still a small player compared to Google, it has ambitious plans. In September, Perplexity reported processing 340 million searches, a tiny fraction of Google’s volume but still indicative of growing interest. Perplexity plans to introduce ads under its AI-generated responses later this month, with the company pledging to share up to 25% of the ad revenue with publishing partners whose content it utilizes.

The use of AI-generated search summaries is becoming an increasingly sensitive issue, as traditional publishers worry that users who find information from AI summaries may no longer click through to the full articles. Perplexity is sending some traffic to publishers’ sites, but the volume is still relatively small. According to data from digital measurement firm Similarweb, referrals from Perplexity to the Times’s website increased eightfold over the year ending in August 2024, but they remain a fraction of the traffic driven by Google.

Broader Concerns Across Media

The New York Times is not alone in raising concerns about Perplexity’s practices. Other major media companies, including Forbes and Condé Nast, have accused Perplexity of using their content without permission. Forbes alleged that Perplexity used its content to create stories “extremely similar” to the original reporting. “Any unauthorized use of Forbes’ Intellectual Property is a violation of Forbes’ intellectual property rights, depriving Forbes of those rights and threatening its reputation and goodwill,” Forbes wrote in a notice to Perplexity.

These grievances are part of a larger conversation within the media industry regarding the balance between AI innovation and intellectual property protection. Some publishers have opted to sign licensing deals with AI companies—OpenAI has agreements with media organizations such as News Corp (the parent of The Wall Street Journal), Dotdash Meredith, and Politico owner Axel Springer—that compensate them for the use of their content.

The Complex Dynamics of AI Content Usage

The Times and other publishers have long taken steps to block AI firms from scraping their content without permission. One of the key measures used is the inclusion of specific code in websites that indicates their content should not be scraped, but enforcement remains a challenge. As Perplexity and similar startups continue to gain traction, media companies face the ongoing task of safeguarding their content.

While Perplexity is attempting to carve out its own niche in the competitive search market, the startup is walking a fine line. Its current valuation stands at approximately $1 billion, following a new funding deal earlier this year. Most of its revenue currently comes from a subscription offering priced at $20 per month, which provides users access to more advanced AI capabilities. However, monetizing its AI-generated search through ads—and sharing that revenue with publishers—is a crucial part of its strategy going forward.

A Legal Landscape in Flux

The ongoing disputes between Perplexity, the New York Times, and other publishers highlight the unsettled nature of the legal framework surrounding generative AI. While Perplexity has positioned itself as willing to collaborate with publishers, the path to mutually beneficial agreements is far from straightforward. As Srinivas put it, “We are not interested in being anyone’s antagonist here.” Nevertheless, the tensions around content scraping and copyright issues suggest that the broader fight over content usage by AI is only beginning.

Publishers are finding themselves in a challenging position—embracing technological advancements while safeguarding their core assets. As more media companies weigh legal actions, partnerships, or licensing deals, the industry is grappling with how best to coexist with generative AI firms in a way that preserves both innovation and the value of journalistic content.

The next few months may prove pivotal as Perplexity responds to the Times’s cease-and-desist notice and as other publishers decide whether to follow a similar course. The questions raised by the use of AI in news search—including how to protect original content and fairly compensate creators—remain unresolved, and how these issues play out could define the future relationship between media and artificial intelligence.

The right model can have a major impact on your project’s flexibility, budget, and overall success. So which one is right for you? And how do you know you have made the right choice?  The answer in short is all about your project.  

In today’s blog, I will take the time to cover both models, their strengths, weaknesses and where they work best. Let’s jump in.  

Understanding market trends 

First off, why are we talking about dedicated teams? Globally the IT outsourcing market is on the rise. Outsourcing was valued at $565.43 billion in 2023 and is projected to reach $609.53 billion by 2024.  

North America leads in IT outsourcing, holding a significant share of the market. Meanwhile, Asia-Pacific, especially countries like India and China, is expected to see the fastest growth due to larger pools of teams to hire from. With 56% of global companies now using remote hires, dedicated teams mean quicker access to talent from around the world. This gives companies more choice when it comes to matching solutions to their project’s demands. 

Why does Time & Material work for dedicated teams? 

T&M has one big advantage going for it and that’s flexibility. In short, T&M means you only pay for the hours & resources used. This makes it a great match when the project scope is still evolving. But it’s not the only benefit. Here’s why T&M might work for your project, especially when you look for a  dedicated team to hire in a trustworthy software house company.

T&M offers you flexibility  

T&M contracts are adaptable. This means if your project’s needs change, you don’t have to renegotiate the entire contract. You can adjust the project when needed. When it comes to dedicated teams it’s a great way of bringing on specialized skills. Having this flexibility means you aren’t just tied to one technology or language.  

It gives you transparency in spending 

With T&M, you have a clear view of where your money is going. Regular reports detail how much time has been spent on each task, this is mostly tracked through software like Jira. This can allow you to adjust your budget in real time. This can be a bonus when managing a dedicated team so you can see where their efforts are being spent.  

You are always on board with what’s happening 

T&M projects give you the chance to be hands on. As stated, they’re great for flexibility, so throw yourself into the iterative sprints to share your feedback. This allows you to steer the project as needed and provide input. This model is ideal if you like to stay hands-on and it can help your dedicated team integrate with your in-house team. 

You have a core team  

Since T&M contracts often last for the duration of the project, you get consistency. The same team works with you throughout, meaning your team will develop an understanding of your goals and processes. This can help better align them with the project and development process. 

The problem with a T&M model   

However, T&M projects come with a few potential downsides. The flexible nature of T&M means that final costs can be unpredictable, so if you’re working with a tight budget, you’ll need to keep a close eye on spending. Effective time management is also crucial to avoid project overruns. 

Why does fixed price work for dedicated team projects 

If your project scope is well-defined from the start and you need predictability, Fixed Price could be the right fit. Here’s why you might choose this model, especially when working with dedicated teams. 

You are certain of your budget 

With Fixed-Price projects, you know the total cost upfront. This means predictability, and if you have a strict budget, or that spending stays on track, this can be a valuable bonus. It also makes it easier to get project approval from stakeholders, as you can present a clear financial plan from the start. 

Your project’s scope is clear from the start  

Fixed Price contracts are built around a defined scope and set of deliverables. This means that everyone knows what to expect from day one. This model is a great fit for projects where requirements won’t change, and it allows you to focus on other priorities while your team works on delivering results.  

You can be more hands-off  

With Fixed Price, once the scope is set, you don’t have to be as involved day-to-day. You can leave the execution to your development team, which can free you up to focus on other things. This approach is perfect if you prefer to step back after the initial planning and let your team take control.  

Structured Payment Milestones:  

Fixed-Price projects often have payments tied to specific milestones. For you, this means peace of mind, as you can track progress through these milestones. You can be confident that your project is moving forward, and on schedule. 

Fixed Price doesn’t work in all cases  

That said, Fixed-Price contracts can be rigid. Any changes to the scope after the contract is signed can be costly, as they often require a formal change request and renegotiation. This model also requires detailed upfront planning, which can delay the start of the project if you’re eager to get things underway. You and your software partner will need to create a detailed project plan and you must have an idea about the end product.  

Deciding Between Time & Material and Fixed Price for Dedicated Teams 

Your choice between T&M and Fixed Price will depend on several factors, including the scope of your project, your budget, and how involved you want to be in the day-to-day. Here are some key things to think about 

• Project Scope and Flexibility: if you expect requirements to change, T&M provides the necessary flexibility to adapt as you go. For projects with a stable, well-defined scope, Fixed Price offers predictability and financial security. 
• Budget Constraints: T&M is cost-effective for projects where you want control over spending and can adjust the budget as needed. If you need a set budget, Fixed Price will offer the financial stability you’re looking for. 
• Preferred Level of Involvement: T&M suits projects where ongoing input is beneficial, as it builds collaboration and helps you make adjustments in real-time. Fixed Price is ideal if you want to be hands-off after the initial discovery phase planning, as the project can proceed independently, working to the defined goals and outcomes. 

Using Dedicated Teams with the Right Model 

Using dedicated teams in either T&M or Fixed Price projects provides benefits to your project. With T&M, you can adjust your team on the fly, bringing in skilled engineers for specific tasks as and when. In a Fixed Price setting, you get dedicated resources focused on a single solution, often resulting in faster delivery of the project’s goals. 

Ultimately, whether you choose T&M or Fixed Price will depend on your project’s needs, scope, and budget. Match your objectives to the best outcome you need, you can match the development process that delivers on your goals, whether through the flexibility of T&M or the predictability of Fixed Price. 

1. Identifying Cost-Cutting Opportunities

Bookkeeping provides a granular view of your business’s expenses, enabling you to detect patterns and pinpoint areas where you might be overspending. For example, by regularly reviewing your financial statements, you can identify recurring costs that are unnecessarily high, such as excessive supply orders, inflated utility bills, or redundant software subscriptions. This detailed tracking allows you to make informed decisions about which expenses can be minimized or eliminated altogether.

By staying on top of your expenses, you can negotiate better terms with suppliers, seek out more cost-effective service providers, or reduce waste in your operations. These savings might seem small in isolation, but they can add up significantly over time, leading to improved profitability.

2. Preventing Late Fees and Penalties

One of the most straightforward ways that bookkeeping saves money is by helping you stay on top of payment deadlines. Inconsistent or disorganized financial records can lead to missed payments on bills, loans, or taxes, resulting in costly late fees and penalties. Proper bookkeeping ensures that you are always aware of your payment obligations and deadlines.

For instance, with a good bookkeeping system in place, you can set reminders for important due dates, ensuring that you never miss a tax filing deadline or a payment to a supplier. Avoiding penalties and interest charges on overdue payments not only saves you money but also helps preserve your business’s reputation and credit score.

3. Maximizing Tax Deductions

One of the most overlooked aspects of bookkeeping is its role in maximizing tax deductions. Accurate financial records allow you to claim all eligible business expenses during tax season. Without proper bookkeeping, you might forget or overlook deductible expenses such as travel, equipment purchases, office supplies, or business meals.

By keeping meticulous records of every transaction, your bookkeeper can help you identify deductible expenses that you might not have considered. For example, did you know that home office expenses, certain employee benefits, and even depreciation on business assets can be deducted? Maximizing these deductions can significantly reduce your tax liability, leaving more money in your business.

Furthermore, bookkeepers can ensure that you remain compliant with tax laws, so you don’t face fines or audits that could otherwise drain your resources.

4. Improving Cash Flow Management

One of the biggest challenges businesses face is managing cash flow effectively. Without a proper system in place, it’s easy to lose track of when payments are due or when revenue will arrive, leading to short-term cash shortages. These shortages can force businesses to rely on expensive overdraft fees, short-term loans, or costly financing to cover expenses.

Bookkeeping helps improve cash flow by giving you a clear picture of your accounts payable and receivable. You can anticipate upcoming expenses and income more accurately, making it easier to maintain a healthy cash balance. This reduces the need for emergency loans and helps you take advantage of discounts for early payments. Outsourcing accountancy services can help you get on top of your bookkeeping. Netsuite accounting pricing will more than pay for itself in the added time you gain when handing over finances to an expert. 

Additionally, with good bookkeeping practices, you can identify clients who are consistently late in paying invoices and implement strategies to ensure quicker payments, such as offering incentives for early payments or setting stricter payment terms.

5. Providing Data for Informed Decision-Making

The data gathered through bookkeeping serves as the foundation for making informed financial decisions. By analyzing financial reports, such as income statements and balance sheets, business owners can gain insight into the profitability of different aspects of their business. For instance, you might discover that certain products or services generate more profit than others, allowing you to allocate resources accordingly.

Bookkeeping also enables you to track the financial performance of your business over time. This allows you to identify trends, set realistic financial goals, and adjust your business strategy to reduce inefficiencies and maximize profits. Without accurate financial data, you may be making decisions based on assumptions rather than actual figures, which can lead to costly mistakes.

6. Preventing Fraud and Embezzlement

Fraud and embezzlement are unfortunate realities that can cripple a business’s finances. Poor financial oversight creates opportunities for dishonest employees or vendors to take advantage of weak systems. By maintaining a proper bookkeeping system, you introduce checks and balances that help detect and prevent fraudulent activities.

A well-organized bookkeeping system includes regular reconciliations, which compare your internal records to bank statements, supplier invoices, and receipts. This allows you to catch discrepancies early and investigate any irregularities. Additionally, having multiple people involved in the financial process – such as requiring two signatures for payments – adds another layer of security.

Bookkeepers can also help you spot patterns in your financial data that may indicate fraud, such as unexplained expenses, duplicated payments, or inconsistencies between inventory records and sales figures. Preventing fraud protects your assets and preserves the long-term financial health of your business.

7. Enhancing Efficiency Through Automation

Automation can significantly reduce the time and effort required for bookkeeping tasks, leading to lower labor costs and fewer errors. Many modern bookkeeping software platforms, such as QuickBooks or Xero, offer features like automated invoice generation, expense tracking, and bank reconciliation. By automating routine tasks, businesses can free up valuable time for higher-level strategic work.

Automation also ensures that records are updated in real-time, reducing the likelihood of mistakes that could result in financial discrepancies or missed opportunities. For instance, you’ll have an up-to-date view of your accounts receivable, enabling you to follow up on late payments promptly and maintain steady cash flow.

Investing in bookkeeping software or hiring a bookkeeper who leverages automation tools might seem like an added cost up front, but it often results in long-term savings due to increased accuracy and efficiency.

8. Helping with Financing and Investments

If your business is looking to secure a loan or attract investors, accurate and organized financial records are essential. Banks and investors will want to see detailed reports of your financial performance before offering any funding. Well-maintained bookkeeping ensures that you have this data readily available, improving your chances of securing financing with favorable terms.

Having up-to-date financial statements also allows you to negotiate better interest rates or loan conditions, as it demonstrates financial responsibility and reduces the risk to lenders. This can lead to substantial savings on interest and financing costs over time.

Additionally, clear and accurate bookkeeping can help you make smarter investment decisions, whether you’re investing in new equipment, expanding your workforce, or entering new markets. By understanding your financial position, you can assess whether you have the resources to invest without jeopardizing your cash flow or profitability.

9. Reducing Accounting Costs

While bookkeeping and accounting are closely related, they serve different functions. Bookkeeping is the day-to-day recording of financial transactions, while accounting involves analyzing, interpreting, and reporting financial data. By maintaining well-organized and accurate bookkeeping records, you reduce the amount of work required by your accountant during tax season or financial reporting periods.

Accountants typically charge by the hour, and disorganized or incomplete records will require more time to clean up and interpret. By providing your accountant with accurate financial records, you streamline the process, reducing the hours (and costs) spent on tax preparation and financial reviews. In essence, good bookkeeping can lead to lower accounting fees, which adds to your overall savings.

Conclusion

Bookkeeping is far more than just a task to fulfill tax obligations – it’s a powerful tool that can help businesses save money in unexpected ways. The benefits of well-maintained financial records go far beyond compliance, from identifying cost-cutting opportunities to improving cash flow management and preventing fraud. Whether you’re a small business or a growing enterprise, investing in proper bookkeeping practices can provide substantial long-term savings and help your business thrive financially.

How Artificial Intelligence and Machine Learning Optimizes Marketing

Artificial intelligence (AI), machine learning (ML), and large language models are being used by everyday citizens to connect with each other and make their lives easier. These powerful tools are bringing unprecedented sophistication to digital marketing, from laser-focused personalization to deep data insights. We’re seeing creative applications across the board:

• Email campaigns that feel like they’re crafted just for you
• Smart chatbots that actually understand customer needs
• Ad spending that’s optimized through predictive insights
• Content recommendations that truly resonate
• Social media management that’s both efficient and engaging
• Early detection of emerging trends

What makes AI and ML truly remarkable is their ability to uncover hidden gems in vast seas of consumer data. These tools are able to understand and identify patterns in large amounts of data that would be almost impossible for individuals to find. Their deeper understanding and interpretation of data makes it easier for marketing managers to not only reach audiences but to truly speak and understand their needs. Businesses are able to use these tools to stay ahead of changing consumer needs and to adapt their strategies.

Digital Video Marketing

Video content isn’t just a trend; it’s taking center stage in digital marketing. Short-form video platforms such as TikTok and Instagram reels have given brands an opportunity to reach consumers in an interactive and attention grabbing manner, without having to bore consumers with long stories. Live streaming will allow consumers to feel like they are connected to a brand without having to be physically present.

360-degree videos will allow customers to be consumed by a brand’s content. By putting viewers in control of their experience, these immersive videos are transforming how industries like real estate, tourism, and retail showcase their offerings. The numbers don’t lie; brands that embrace video marketing consistently see higher engagement, better message retention, and stronger conversion rates compared to traditional content formats.

Voice Search and Smart Assistants 

Smart speakers and voice activated devices allow consumers to be connected to a company from within their own home. With recent developments in AI, voice searches and smart assistants have become significantly smarter. AI allows these tools to understand the meaning behind a user’s request resolving users past frustration that these tools are misunderstanding commands.

Forward-thinking companies are developing voice-optimized content and custom skills for virtual assistants such as Siri, Amazon’s Alexa and Google Assistant. With over 25% of 26 to 40 year olds using virtual assistants weekly companies are looking to create seamless experiences that build lasting connections with customers.

Blockchain in Digital Marketing

Blockchain technology is addressing some of the most significant challenges in digital marketing. Ad fraud and data protection can be combated by the decentralized approach of a blockchain. By using blockchain technology digital marketers can measure the effectiveness of their campaign by verifying ad delivery without having to compromise a consumer’s data.

The Path Forward in Digital Innovation

As these technologies converge, they’re creating unprecedented opportunities to deliver experiences that truly resonate with customers. Success in the future digital marketing landscape will rely on the thoughtful integration of these innovations while prioritizing customer needs. Marketers such as KWD, will thrive are those who can harness these powerful tools while maintaining a strategic, customer-focused approach in our rapidly evolving digital ecosystem.

The Imperative of Data-Driven Decision-Making

In today’s digital economy, the ability to harness data effectively is paramount. As Michael Brenner, CEO of Marketing Insider Group, asserts, “Marketing without data is like driving with your eyes closed. You might get somewhere, but it won’t be the destination you intended.” This sentiment underscores the pivotal role that data plays in shaping marketing strategies. Marketers who rely on data are better equipped to understand and predict consumer behavior, optimize campaigns, and ultimately enhance their return on investment (ROI).

The systematic approach to data-driven marketing begins with the collection and analysis of data. By examining customer behavior, market trends, and competitive dynamics, executives can tailor their strategies to meet the specific needs and preferences of their target audience. According to Kristina Jaramillo, a B2B marketing strategist, “Data gives marketers the ability to personalize their outreach and engage with customers on a more meaningful level, which is essential for driving conversions.”

Metrics: The Cornerstone of Effective Marketing

One of the critical aspects of data-driven marketing is the use of metrics to guide decision-making. Metrics serve as the benchmarks against which marketing performance is measured and optimized. The “10/90 rule” highlights the importance of investing in talent over tools, suggesting that 10% of the marketing budget should be allocated to technology and 90% to skilled professionals who can interpret and act on the data. This approach emphasizes the need for expertise in data analysis to ensure that insights are actionable and aligned with business goals.

Josh Collins, VP of Marketing at Clearbit, notes, “The right metrics can reveal powerful insights about customer behavior and campaign effectiveness. However, without the right talent to analyze and apply these insights, even the most sophisticated tools are of limited value.” Metrics such as customer lifetime value (CLV), customer acquisition cost (CAC), and conversion rates are essential for assessing the effectiveness of marketing initiatives and making data-driven adjustments.

Aligning Marketing with Business Objectives

Effective data-driven marketing requires alignment with broader business objectives. Marketing should not operate in isolation but should be integrated with other departments, such as sales and finance, to ensure that all efforts contribute to the company’s overall goals. Data provides a comprehensive view of how marketing activities impact the bottom line, enabling executives to make informed decisions that drive business growth.

As Shama Hyder, CEO of Zen Media, puts it, “Data-driven marketing isn’t just about numbers; it’s about aligning those numbers with strategic business goals. When marketing initiatives are synchronized with the company’s objectives, the results are far more impactful.” This alignment ensures that marketing efforts are not only effective but also strategically relevant.

Practical Applications and Real-World Examples

Implementing a data-driven marketing strategy involves more than just theoretical knowledge; it requires practical application and real-world insights. Successful case studies illustrate how companies have effectively utilized data to achieve their marketing objectives. For example, Netflix’s data-driven approach to content recommendations has been a key factor in its ability to attract and retain subscribers, demonstrating the power of data in enhancing customer experience and driving engagement.

Similarly, Amazon’s use of data to personalize product recommendations has set a benchmark for e-commerce platforms. As Marc Kiven, Co-founder of Zeta Global, observes, “Amazon’s ability to use data for personalization has revolutionized the retail industry. Their approach serves as a model for how data can be leveraged to create highly relevant customer experiences.”

Overcoming Challenges in Data-Driven Marketing

While the benefits of data-driven marketing are substantial, implementing such strategies comes with its own set of challenges. Issues such as data overload, misinterpretation of data, and difficulties in integrating data across platforms can hinder the effectiveness of marketing efforts. Addressing these challenges requires a clear strategy, the right tools, and a skilled team capable of navigating the complexities of data analysis.

As Dave Frankland, Principal Analyst at Forrester Research, points out, “The key to overcoming data challenges lies in having a robust data management strategy and ensuring that the team is equipped with the skills needed to turn data into actionable insights.” Solutions to these challenges involve streamlining data processes, investing in advanced analytics tools, and fostering a culture of data-driven decision-making within the organization.

The Future of Data-Driven Marketing

Marketing is rapidly evolving, driven by unprecedented advancements in data analytics and technology. For enterprise-level executives, particularly Chief Marketing Officers (CMOs), understanding and leveraging these developments is not just advantageous but essential for staying competitive. As we look ahead, several key trends and emerging technologies are poised to reshape the data-driven marketing domain.

Personalization Through AI and Machine Learning

Artificial intelligence (AI) and machine learning are at the forefront of transforming data-driven marketing. These technologies enable a level of personalization that was previously unattainable. “AI is not just a tool for automation; it’s the cornerstone of personalized marketing strategies,” says Annalise Richards, a leading AI strategist at IBM. “The ability to analyze vast datasets and predict customer behavior allows companies to tailor their marketing efforts with unparalleled precision.”

Machine learning algorithms are increasingly sophisticated, offering deeper insights into customer preferences and behaviors. For instance, predictive analytics can forecast future buying behaviors based on historical data, allowing marketers to create highly targeted campaigns. “AI-driven personalization can significantly enhance customer engagement by delivering content that resonates with individual preferences,” notes Sam Levine, Chief Data Scientist at Salesforce. “This not only improves customer satisfaction but also drives higher conversion rates.”

Enhanced Data Privacy and Security

With the rise of data-driven marketing comes the critical need for enhanced data privacy and security. The implementation of regulations such as the General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA) underscores the importance of safeguarding consumer information. “Data privacy is a fundamental concern that cannot be overlooked,” emphasizes Laura Mitchell, Chief Compliance Officer at Oracle. “As marketers harness the power of data, they must also prioritize robust security measures to protect against breaches and misuse.”

Transparency and consent are becoming increasingly important. Companies are investing in technologies that allow consumers to control their data preferences and understand how their information is being used. “Building trust with customers involves not only safeguarding their data but also being transparent about its use,” says Emily Carter, Director of Data Ethics at Microsoft. “A commitment to data integrity and security can enhance brand reputation and foster stronger customer relationships.”

Integration of Multi-Channel Data

The integration of data across multiple channels is another significant trend shaping the future of marketing. With consumers interacting with brands through various touchpoints—social media, email, mobile apps, and websites—integrating data from these diverse sources provides a holistic view of customer interactions. “A unified data strategy is essential for creating a seamless customer experience,” states Michael Wong, VP of Marketing Technology at Adobe. “By consolidating data from different channels, marketers can gain a comprehensive understanding of customer journeys and optimize their strategies accordingly.”

Omni-channel marketing, supported by integrated data platforms, enables brands to deliver consistent and personalized experiences across all touchpoints. “The goal is to provide a cohesive brand experience regardless of where the customer engages with the company,” explains Olivia Grant, Chief Marketing Officer at HubSpot. “A unified approach ensures that marketing messages are relevant and timely, enhancing customer engagement and loyalty.”

The Role of Real-Time Data

Real-time data analysis is becoming increasingly vital for effective marketing. The ability to access and act on data in real-time allows marketers to respond swiftly to emerging trends and shifts in consumer behavior. “Real-time analytics empowers marketers to make informed decisions and adjust strategies on the fly,” says Jason Lee, Chief Analytics Officer at Nielsen. “This agility is crucial in a fast-paced digital environment where customer expectations are constantly evolving.”

Real-time data facilitates dynamic adjustments to marketing campaigns, ensuring that content is relevant and engaging. “Immediate insights allow for rapid optimization of campaigns, enhancing their effectiveness and maximizing ROI,” notes Karen Lee, Head of Digital Marketing at Google. “This capability is especially valuable in competitive markets where staying ahead of the curve is essential.”

Future Trends in Data Visualization

Data visualization continues to advance, providing marketers with innovative ways to interpret and present complex datasets. Emerging tools and techniques are making it easier to translate data into actionable insights through intuitive visual representations. “Effective data visualization is key to making complex data comprehensible and actionable,” highlights David Chen, Lead Data Visualization Specialist at Tableau. “Interactive dashboards and advanced graphics enable marketers to spot trends, identify patterns, and make data-driven decisions with greater clarity.”

The evolution of data visualization tools is enabling more sophisticated analysis and reporting. “As visualization technology evolves, so too does the ability to uncover deeper insights from data,” adds Sophia Robinson, Director of Business Intelligence at SAS. “These advancements are transforming how marketers interpret and leverage data, ultimately driving more effective strategies.”

Mastering Market Intelligence

As data-driven marketing continues to evolve, CMOs and marketing leaders must stay abreast of these advancements to maintain a competitive edge. Embracing AI and machine learning for personalization, prioritizing data privacy and security, integrating multi-channel data, leveraging real-time analytics, and advancing data visualization are all critical components of a forward-thinking marketing strategy. By understanding and implementing these trends, executives can unlock new opportunities for growth and drive superior marketing outcomes.

The future of data-driven marketing is not just about keeping up with trends but leading the way in how data is harnessed to create impactful and resonant marketing strategies.

Looking ahead, data-driven marketing is poised to become even more integral to business success. As technology continues to advance, the capabilities of data analytics will expand, offering new opportunities for marketers to refine their strategies and drive growth. Embracing data as a fundamental aspect of marketing will enable organizations to stay competitive in an increasingly data-centric world.

Mastering market intelligence through data-driven marketing is essential for CMOs and other enterprise-level executives seeking to enhance their marketing strategies and achieve superior outcomes. By understanding and applying data effectively, businesses can transform their marketing efforts, align them with broader business objectives, and navigate the challenges of the digital age with greater agility. Data-driven marketing is not just a trend but a fundamental shift in how marketing should be approached, offering powerful insights and opportunities for those who embrace its potential.

The Rise of Adult Learning

By 2031, over 60% of jobs in Kentucky will require postsecondary education. This is compared to only 55% of Kentucky adults who currently hold a postsecondary credential. Aside from mere job selection, the lack of postsecondary graduates heavily influences the number of households who receive a livable wage. More than 30% of Kentucky households have incomes less than $35,000. Compare that to households with one college graduate receiving a staggering $40,000 more in earnings compared to non-graduate households.

Despite these benefits, college graduates in both public Kentucky universities and the Kentucky Community and Technical College System (KCTCS) have seen a regression in undergraduate students. Overall, there is around a staggering 40% decline through the entire post-secondary system across the decade from 2014 to 2024. The KCTCS specifically saw the sharpest decrease in learners from slightly above 76,000 to just below 50,000, or a 34% decrease in just 10 years. The drop in enrollment isn’t exclusive to the adult learning students, but for the post-secondary education systems in general. Public universities and the KCTCS have seen enrollment rates plummet by tens of thousands of students year after year. But what is driving this rapid decrease in post-secondary enrollment despite the potentially lucrative benefits?

For many, prior commitments prevent college enrollment. Around 48% of adult learners have children, and the limited childcare availability is a major obstacle. Between 2019 and 2021, nearly 16,000 childcare centers closed nationwide. Simultaneously, the average cost of childcare rose to $6,411 per year, or $534 monthly. Aside from childcare, adult workers must cover not only the cost of college, but family expenses and other bills. 58% of full-time undergraduates need to work, and 79% of part-time undergraduates are working adult learners.

However, there are other obstacles to adults in post-secondary education. Many require assistance with coursework in addition to the normal classes due to the years spent out of the classroom. Gateway courses have low success rates in both the public university and KCTCS systems. Adult learners in the KCTCS score less than 25% on English and Math, and learners in the public university system scored 15% on average in both English and Math.

Conclusion

When the financial and academic hindrances combine, they can make adults as much as 4 times less likely to complete postsecondary education. So how can we boost adult learner success in their post-secondary journey? Providing financial assistance and academic support is the best way to help adult learners. Scholarships like the Pell Grant enable learners to finance the costs of college, but also any excess aid covers childcare and other family expenses. This excess aid also provides them with more time to spend studying rather than working. 

“Europe has become less competitive and less innovative compared to other regions and now risks falling further behind in the AI era due to inconsistent regulatory decision-making,” the letter states. This plea echoes the sentiments of Meta CEO Mark Zuckerberg and Spotify CEO Daniel Ek, who recently co-authored a similar letter calling for Europe to embrace open-source AI to remain competitive on the global stage.

Listen to our conversation on Meta’s EU warning. Will Europe miss out on the AI boom?

Fragmented Regulation Stifling Innovation

At the core of the open letter is a stark critique of the EU’s regulatory framework, particularly the uneven application of the General Data Protection Regulation (GDPR). While GDPR was designed to harmonize data protection across Europe, business leaders argue that inconsistent interpretations and unpredictable enforcement are creating a barrier to AI development. The inability of European regulators to reach consensus on how AI should use data is, according to these leaders, hindering the continent’s AI innovation.

“Meta has been told to delay training its models on content shared publicly by adults on Facebook and Instagram—not because any law has been violated but because regulators haven’t agreed on how to proceed,” Zuckerberg and Ek wrote in a previous letter, underscoring the frustration with regulatory ambiguity. This delay, they warn, prevents European AI models from being trained on European data, effectively ensuring that the continent’s AI development lags behind its global competitors.

In the most recent letter, the signatories emphasize the growing urgency, warning that without clear, harmonized regulations, Europe risks missing out on the massive economic potential AI promises. “Research estimates that Generative AI could increase global GDP by 10 percent over the coming decade, and EU citizens shouldn’t be denied that growth,” the letter stresses.

The Role of Open-Source AI in Europe’s Future

A significant portion of the letter focuses on the critical importance of open-source AI models—AI technologies that are freely available for developers to build upon and modify. These open models, the letter argues, offer a way for Europe to level the playing field and reclaim its technological edge by enabling small businesses, researchers, and public institutions to harness AI’s transformative potential.

Zuckerberg and Ek have previously highlighted the role of open-source AI in driving innovation, pointing out that it democratizes access to cutting-edge technology and helps institutions maintain control over their data. “The internet largely runs on open-source technologies, and so do most leading tech companies,” the two CEOs wrote. “We believe the next generation of ideas and startups will be built with open-source AI because it lets developers incorporate the latest innovations at low cost and gives institutions more control over their data.”

The letter emphasizes that Europe is particularly well-positioned to capitalize on open-source AI, noting that the region has more open-source developers than the United States. However, without regulatory clarity and support, Europe risks losing its advantage in this critical area. “Fragmented regulation is holding back developers and preventing Europe from realizing its full potential in AI,” the letter warns.

The Economic Stakes

The business leaders who signed the open letter argue that AI presents an unparalleled opportunity to boost productivity, drive scientific research, and add hundreds of billions of euros to the European economy. However, they caution that the current regulatory environment is deterring investment and innovation, both of which are critical to capturing these benefits.

The stakes are particularly high when it comes to multimodal AI models—advanced systems that can process text, images, and speech simultaneously. These models represent the next leap in AI capabilities and could have a profound impact on industries from healthcare to education. However, without access to the latest models, European businesses and researchers will be left using outdated technology. “These concerns aren’t theoretical,” Zuckerberg and Ek warned in their earlier letter. “Given the current regulatory uncertainty, Meta won’t be able to release upcoming models like Llama multimodal… European organizations won’t be able to get access to the latest open-source technology.”

The letter goes on to argue that Europe’s regulatory environment is not just limiting AI development but actively reducing the continent’s competitiveness. “Laws designed to increase European sovereignty and competitiveness are achieving the opposite,” it says, pointing out that many of Europe’s brightest AI talents are leaving the continent for regions with more supportive regulatory frameworks.

A Call for Harmonization and Clarity

Both the open letter and the previous statement by Zuckerberg and Ek emphasize the need for regulatory simplification and harmonization. Europe’s complex and inconsistent regulations, they argue, are creating a hostile environment for AI development and threatening the region’s ability to compete globally. “Europe should be simplifying and harmonizing regulations by leveraging the benefits of a single yet diverse market,” the executives argue, pointing to the widening gap between the number of homegrown European tech leaders and those emerging from the U.S. and Asia.

The letter concludes by urging EU policymakers to take decisive action and create a regulatory framework that fosters innovation while ensuring privacy and security. “With the right regulatory environment, combined with the right ambition and some of the world’s top AI talent, the EU would have a real chance of leading the next generation of tech innovation,” the letter states.

The Race Against Time

As AI continues to evolve at breakneck speed, Europe faces a critical decision: adopt a regulatory framework that supports innovation and fosters growth, or risk being left behind in the global AI race. “On its current course, Europe will miss this once-in-a-generation opportunity,” Zuckerberg and Ek warned. “Because the one thing Europe doesn’t have, unless it wants to risk falling further behind, is time.”

For now, the message from Europe’s business leaders is clear: the continent’s fragmented regulatory environment is holding back AI innovation, and without urgent reforms, Europe risks missing out on the transformative potential of artificial intelligence. The time to act, they argue, is now.

The World of Prior Authorization

Traditionally, prior authorization is a manual, cumbersome process. It requires checking patient insurance details and medical charts, submitting requests, and following up with insurance companies. This often involves lengthy phone calls, waiting in queues, and navigating complex online portals, leading to an estimated 15-20 minutes spent on each request. If a request is denied, additional documentation or an appeal letter must be prepared, further complicating the process.

In contrast, an automated prior authorization system significantly enhances efficiency. Automated solutions can retrieve essential patient data, validate information, and prepare authorization requests in a fraction of the time. These systems also update medical records automatically and track the status of requests, streamlining workflows considerably.

The complexities and rigidity of the current prior authorization system have profound implications for healthcare. Providers face rising operational costs, with 35% hiring additional staff solely to manage prior authorizations. Manual processes can cost around $11 per authorization, and nearly 93% of physicians report experiencing high administrative burdens related to these requests. The impact on patient care is alarming; delays in authorization can lead to a 100% increase in time to access care, a 25% chance of hospitalization, and even life-threatening events in 19% of cases. Furthermore, 9% of patients risk long-term disabilities due to these delays.

Enter New Innovation

Compounding the issue, many physicians express concerns about the denial rates of prior authorizations. Approximately 27% say their patients’ requests are often denied, while 35% report that the criteria for authorization are rarely evidence-based. In recent years, nearly three in four doctors have noted a significant increase in denials, yet only one in five consistently appeals negative decisions due to time and resource constraints.

In this challenging environment, Orbit has emerged as a transformative solution. The company’s AI-powered prior authorization automation system has demonstrated remarkable effectiveness, saving providers approximately 60% on existing costs and generating an impressive $449 million in savings across the U.S. healthcare industry. Beyond cost reductions, Orbit’s technology enhances patient experiences by expediting care delivery.

Conclusion

By eliminating inefficiencies, Orbit can save provider groups operating with five or more prior authorization team members up to 24 hours of wasted time each day. Processing a patient’s information and scheduling appointments takes just five minutes, a stark contrast to the manual approach. The automated system reduces turnaround times by 55%, saving an average of 11 minutes per authorization. Additionally, it improves accuracy by capturing demographic and insurance data without human error, and decreases the labor dependency, allowing staff to reclaim nearly 12 hours per week.

Overall, Orbit’s automation solution not only addresses the pressing issues surrounding prior authorization but also paves the way for more efficient, patient-centered care in the healthcare landscape.

The Strategic Role of Data in Global Operations

Yum! Brands’ data strategy is not just about marketing or customer engagement—it underpins the entire operational infrastructure of the business. Davies explains, “We look at data from three fundamental perspectives: easy operations, easy experiences, and easy intelligence. The goal is to use data to simplify and improve everything from supply chain management to customer interactions.”

The concept of “easy operations” is critical for a global company like Yum! Brands. Davies elaborates that his team is responsible for helping restaurant operators make data-driven decisions on a day-to-day basis. “We’re leveraging AI and machine learning to determine everything from how much food we should order, to how fast we should cook it, and even how much we should cook in real-time,” he says. This granular use of data has significant implications for reducing waste, improving service speed, and ensuring consistency across thousands of locations worldwide.

The “easy experiences” pillar focuses on how Yum! Brands can use data to improve customer journeys. “Are we remembering your preferences? Are we getting you relevant offers that resonate with your tastes? Are we ensuring that these experiences translate when you move from a digital platform to a physical restaurant?” asks Davies. He stresses that data is at the core of creating seamless, omnichannel experiences for customers, especially as consumer expectations for personalization continue to rise. For Davies, this is where data becomes truly transformational, enabling the company to deliver on the promise of a more connected, convenient, and personalized dining experience.

“Data is not just about operational efficiencies; it’s about enhancing the experience for both the customer and our employees in the restaurants,” says Davies. “The intelligence we derive from our data allows us to anticipate needs, personalize offers, and ultimately, build deeper relationships with our customers.”

First-Party Data: Unlocking a Valuable Resource

Yum! Brands’ journey into data transformation began with a realization about the value of its first-party data. “When you start asking yourself, ‘How much first-party data do we actually have?’ you go in, look, and say, ‘Holy smokes!’” Davies recalls. The amount of customer data across the company’s four major brands—Taco Bell, Pizza Hut, KFC, and Habit Burger—was staggering. This data was not just vast but also unique in its potential to deliver actionable insights.

“Think about it,” says Davies, “when someone orders a pizza, they’re willing to give us a lot of personal information if it means getting their pizza delivered on time and hot. There’s a natural value exchange in our business that is not as prevalent in other industries.” This direct interaction with customers has allowed Yum! Brands to accumulate a treasure trove of data, from purchase histories to location preferences, all of which can be used to enhance customer experiences.

Yet, having access to first-party data is only part of the equation. The challenge, as Davies points out, lies in effectively using that data. “From an operations perspective, we’ve been doing pretty well. But from a forward-thinking, one-to-one digital marketing perspective, we realized that we were not leveraging our data as effectively as we could be,” he admits. This gap between data collection and data activation spurred Yum! Brands to embark on a journey of transformation, focused on optimizing the way it uses customer data to drive personalized marketing and operational efficiencies.

Choosing the Right Customer Data Platform (CDP)

For any enterprise-level organization, choosing the right Customer Data Platform (CDP) is a pivotal decision. It was no different for Yum! Brands, which undertook a rigorous process to select a partner that could meet its unique requirements. “When we started looking for a CDP, it wasn’t just about commercials or functionality. It was about finding a partner who could go on this journey with us,” says Davies. The right CDP partner, according to Davies, is not just a vendor but an extension of the organization’s data strategy, one that can adapt and grow alongside the business.

This philosophy of partnership led Yum! Brands to select Treasure Data as its CDP provider. “There were a lot of good companies out there, but we were looking for something more than just a product. We wanted a partner who understood the complexities of working in a franchisee environment and who could collaborate with us in a meaningful way,” Davies notes. The ability to work closely with franchisees is crucial for Yum! Brands, as the company operates on a decentralized model where individual franchisees often have different needs and challenges. “At Yum! Brands, we like to use the term ‘taking people with you,’ because we can’t just dictate solutions from the top down. We have to bring our franchisees along on the journey,” says Davies.

This approach to collaboration was essential in the decision-making process. Davies emphasizes that the partnership with Treasure Data has allowed Yum! Brands to maintain flexibility while pursuing its long-term goals. “We’ve had to flex, but that’s what a journey is all about—it’s never a straight line. We need partners who are willing to adapt as we move forward,” he explains. This adaptability is particularly important in an environment as dynamic as the restaurant industry, where consumer behaviors can shift rapidly, and operational demands can vary widely by region.

Navigating the Complexities of a Global Franchise

One of the most unique aspects of Yum! Brands’ data strategy is its global franchise model, which introduces an additional layer of complexity when it comes to data integration and utilization. “Operating in a franchisee environment is fundamentally different from a corporate-owned model,” says Davies. “You don’t just implement changes overnight. You have to bring your franchisees along on the journey, helping them see the value of the new data tools and platforms.”

For Davies and his team, this means constant collaboration, both internally and with external partners like Treasure Data. “We call it ‘taking people with you’ because it’s about moving everyone in the same direction. I can’t tell a franchisee to do something—they have to want to do it themselves,” he explains. This collaborative approach has been essential in aligning the company’s broader data strategy with the needs and priorities of individual franchisees.

Davies notes that one of the keys to making this model work is clear communication and flexibility. “It’s not about dictating a solution; it’s about listening, adjusting, and making sure that the strategy we’re implementing works for everyone,” he says. This decentralized approach to data management allows Yum! Brands to be both agile and responsive, ensuring that its data strategy is adaptable to the unique challenges of each market and franchise.

A Data-Driven Transformation

As Yum! Brands continues to build out its customer data strategy, Davies is optimistic about the future. “We’ve come a long way, but there’s still so much potential to unlock,” he says. The company’s focus on first-party data, combined with its commitment to collaboration and innovation, positions it as a leader in the restaurant industry’s digital transformation. “We’ve got some really good data,” says Davies. “Now it’s about using it effectively to deliver on our customer promise and to create better, more personalized experiences for each of our customers.”

For Chief Data Officers at enterprise organizations, Yum! Brands’ journey offers valuable lessons in how to approach data transformation at scale. From the importance of choosing the right technology partners to navigating the complexities of a franchise model, Yum! Brands is demonstrating how a thoughtful, data-driven strategy can drive both operational efficiencies and enhanced customer experiences.

As Davies puts it, “This isn’t just about technology; it’s about leadership. It’s about taking people with you, understanding their needs, and building a strategy that works for everyone.” For Yum! Brands, the journey has only just begun, but with a clear focus on collaboration and customer experience, the company is well-positioned to continue leading the way in the evolving world of data-driven business.

Understanding Kubernetes and Docker Swarm

Before we compare Kubernetes vs Docker Swarm, let’s understand what Kubernetes and Docker Swarm do.

Google developed Kubernetes, managed by CNCF, is an open-source platform for deploying, scaling, and administering containerized apps. Due to its robust architecture and modularity, Kubernetes is known for handling complex multi-container deployments across different environments.

Docker Swarm is Docker’s container orchestration tool. It integrates well with the Docker ecosystem and is more user-friendly, making it a good choice for those familiar with Docker who are looking for a simpler option than Kubernetes.

Kubernetes vs Docker Swarm: Key Differences

When choosing between Kubernetes vs Docker Swarm, it’s essential to consider factors like complexity, scalability, community support, and ease of use. We will now go over some of these important differences below: 

1. Ease of Setup and Learning Curve

When comparing Kubernetes vs. Docker Swarm, it’s essential to consider the learning curve and setup time. Because of its high learning curve, it can be challenging for individuals unfamiliar with Kubernetes. Setting up Kubernetes can be difficult for beginners due to configuring various components such as kubectl, pods, nodes, and services.

Docker Swarm is easier to install and operate than Kubernetes. For users already familiar with Docker, integrating with Docker Swarm is straightforward because it is part of the Docker ecosystem. Setting up a Swarm cluster requires only a few commands, making it an excellent option for those who prioritize ease of use and quick deployment.

2. Scalability

Kubernetes is better than Docker Swarm when it comes to scalability. It supports large, complex applications that work in different settings. Kubernetes can manage workloads automatically with features like auto-scaling, rolling upgrades, and self-healing. Docker Swarm offers fewer scalability options than Kubernetes.It is better suited for smaller applications that don’t need extensive orchestration. However, Docker Swarm’s scalability may be enough for simpler cases.

3. Feature Set and Extensibility

Kubernetes vs Docker Swarm differ in their feature sets. Kubernetes provides many functions, like network policies, secret management, and persistent storage. Users can add functionality with third-party connectors and bespoke plugins because of its flexible architecture. Due to this flexibility, Kubernetes is the preferred choice for complex applications requiring a high level of customization.

Docker Swarm can handle basic orchestration tasks like networking, scalability, and container deployment, but it cannot immediately manage more advanced features. Docker Swarm’s simplicity has a downside – while it makes management easier, it doesn’t offer the same flexibility and extensibility as Kubernetes.

4. Networking

Kubernetes networking is powerful and configurable, but setting it up can be challenging. It provides features like ingress controllers and network policies to ensure secure communication among nodes using pods and services.

Docker Swarm offers a simpler networking model. It uses an overlay network to enable communication between containers on different hosts but lacks Kubernetes’s advanced configuration and security features. While Docker Swarm suits basic networking needs, Kubernetes is better for complex settings with multiple tenants.

5. Community and Ecosystem Support

Kubernetes is the standard for container orchestration, supported by the CNCF and a thriving community. With strong community support, Kubernetes offers numerous third-party products, tutorials, and documentation, making it a leading technology.

Although popular, Docker Swarm lacks the same level of community involvement as Kubernetes. As a result, Docker has lost some of its popularity, with many users switching to Kubernetes. This means that Swarm offers fewer updates, integrations, and comprehensive documentation compared to Kubernetes.

6. Fault Tolerance and Availability

Kubernetes is beneficial because it can handle mistakes and stays available most of the time. It automatically replaces malfunctioning containers and evenly distributes workloads among nodes to prevent resource overuse. Kubernetes also supports stateful applications through features like StatefulSets and persistent volumes. Docker Swarm lacks some of Kubernetes’ more advanced features but still offers essential fault tolerance. While Swarm can replace failing containers, it lacks integrated support for persistent storage and does not provide as precise control over resource allocation as Kubernetes.

Kubernetes vs Docker Swarm: Which One Should You Choose?

Choosing between Kubernetes vs Docker Swarm depends on your needs, experience level, and application complexity:

Choose Kubernetes if:

• Complex systems under your supervision require more sophisticated orchestration features.
• Your team either has experience with Kubernetes or can become proficient in it.
• You need high availability, robust fault tolerance, and much customization.
• You need flexibility to deploy apps across different regions or work in a multi-cloud environment.

Choose Docker Swarm if:

• You already use Docker, so you want a simpler way to manage containers without learning all the details of Kubernetes.
• You don’t need advanced features because your tasks are simpler and less complicated.
• You are drawn to simpler networking models and ease of setup.

Conclusion

Ultimately, your choice should fit your application’s needs and your team’s capabilities. Larger, more intricate systems needing advanced features like auto-scaling, fault tolerance, and extensive customization are best suited for Kubernetes. On the other hand, Docker Swarm is more suitable for smaller-scale applications because of its simplicity and user-friendly setup. If you’re considering implementing Kubernetes but find its complexity intimidating, investing in Kubernetes consulting services can help ensure effective setup and management for optimal performance.

Sutskever was one of several OpenAI board members who led a coup against Altman in 2023, ousting him from the company. Pressure, from both inside and outside the company, ultimately led to Altman’s return, with Sutskever eventually leaving himself.

At the time of Altman’s ouster, reports indicated that Sutskever and the other board members were concerned that Altman was straying too far from OpenAI’s primary goal of safe AI development. The board felt Altman was pursuing profit at the expense of safety, a narrative that has been repeated by other executives who have left the company in recent months.

Hinton is the latest to lend weight those concerns. In a video post following his Nobel Prize win, Hinton touted the students he had over the years, particularly calling out Sutskever.

“I’d also like to acknowledge my students,” Hinton says in the video. “I was particularly fortunate to have many very clever students, much clever than me, who actually made things work. They’ve gone on to do great things.

“I’m particularly proud of the fact that one of my students fired Sam Altman, and I think I better leave it there and leave it for questions.”

Hinton then goes on to describe why Sutskever was involved in firing Altman.

“So OpenAI was set up with a big emphasis on safety,” he continues. “Its primary objective was to develop artificial general intelligence and ensure that it was safe.

“One of my former students Ilya Sutskever, was the chief scientist. And over time, it turned out that Sam Altman. Was much less concerned with safety than with profits. And I think that’s unfortunate.”

Hinton has long been a vocal advocate for need to develop AI with safety concerns front and center. He previously worked on AI at Google, before leaving the company and sounding the alarm over its rushed efforts to catch up with OpenAI and Microsoft.

Since leaving Google, Hinton has warned of the danger AI poses, saying efforts need to be taken to ensure it doesn’t gain the upper hand.

“The idea that this stuff could actually get smarter than people — a few people believed that,” Dr. Hinton said. “But most people thought it was way off. And I thought it was way off. I thought it was 30 to 50 years or even longer away. Obviously, I no longer think that.

“I don’t think they should scale this up more until they have understood whether they can control it,” he added.

Some are lauding the return of X to Brazil as a major win for free speech, but nothing could be further from the truth. Famous journalist Glenn Greenwald pointed out the massive concessions X had to make in order to return.

Not only did X cave on every single demand of the Brazilian government, but the company helped establish a terrifying principle. The Brazilian government now has an established track record of forcing a tech company that purports to support free speech and privacy to betray its users.

It’s safe to say this will not be the last time Brazil flexes its newfound muscle.

Judge Amit P. Mehta ruled Google was an illegal monopoly in August 2024, dealing the company the worst legal blow it has suffered in its history. There are a slew of possible remedies the government may pursue in its efforts to reign Google in, including prohibiting it from entering into exclusionary search deals, forcing it to share data with competitors, and restrict its ability to incorporate AI in its search business. The most extreme option, however, is a complete breakup of the company, forcing it to sell of parts that contribute to Google’s control of the search industry, most notably Android, Chrome, and its advertising business.

In a court filing (courtesy of Vox), the DOJ makes clear it is considering asking the court to do just that, along with a number of other possible remedies.

Accordingly, Plaintiffs are considering remedies that would limit or end Google’s use of contracts, monopoly profits, and other tools to control or influence longstanding and emerging distribution channels and search-related products (e.g., browsers, search apps, artificial intelligence summaries and agents). For example, Plaintiffs are evaluating remedies that would, among other things, limit or prohibit default agreements, preinstallation agreements, and other revenue-sharing arrangements related to search and search-related products, potentially with or without the use ofa choice screen.

Similarly, Plaintiffs are considering behavioral and structural remedies that would prevent Google from using products such as Chrome, Play, and Android to advantage Google search and Google search-related products and features—including emerging search access points and features, such as artificial intelligence—overrivals or new entrants. Such consideration is faithful to the Court’s findings. As the Court recognized, Google’s longstanding control of the Chrome browser, with its preinstalled Google search default, “significantly narrows the available channelsofdistribution and thus disincentivizes the emergenceof new competition.” Mem. Op. at 159. “[T]he Google Play Store is a must-have on all Android devices,” id. at 210; and the Android Agreements are, of course,a ertical tool for Google’s anticompetitive limitations on distribution.

The key words in those paragraphs are “considering behavioral and structural remedies…” That statement makes clear that the DOJ is considering asking for a breakup of the company.

The Google antitrust case is the single biggest case since the US government sued Microsoft decades ago. In many ways, the case against Google is even more high-stakes, given how ubiquitous the company’s products—especially search—are to people around the world.

If the DOJ pushes for a breakup, and Judge Mehta agrees with the recommendation, the result could be a fundamental change to the very nature of search and the internet.