W świecie rozrywki online to często drobne elementy decydują o tym, czy wieczór spędzony przy ekranie zapamiętamy jako zwykłą chwilę, czy jako prawdziwie dopracowane doświadczenie. Ten tekst to mini-recenzja, która skupia się na tym, co wyróżnia nowoczesne kasyna internetowe — nie od strony reguł i strategii, lecz przez pryzmat detali, które sprawiają, że wszystko wydaje się bardziej premium.

Co wyróżnia doświadczenie

Na pierwszy plan wychodzi warstwa wizualna i dźwiękowa: subtelne animacje, responsywne interfejsy i muzyka, która nie przeszkadza, a buduje nastrój. To nie o błysku neonów, lecz o harmonii elementów — kiedy każdy piksel wydaje się dopracowany, korzystanie z serwisu staje się przyjemnością. Warto też zwrócić uwagę na źródła informacji o trendach w branży, na przykład https://curioso.guide/, które opisują zmiany w designie i doświadczeniu użytkownika.

Ponadto ważne są drobiazgi związane z personalizacją: delikatne powiadomienia, system nagród, który nie jest nachalny, oraz możliwość szybkiego filtrowania treści. To one nadają serwisowi charakteru miejsca, do którego chce się wracać, zamiast jedynie traktować je jako kolejny serwis z rozrywką.

Czego można oczekiwać podczas sesji

Sesja w dobrze zaprojektowanym kasynie online przypomina wizytę w luksusowym salonie: wszystko działa płynnie, interakcje są intuicyjne, a czas ładowania minimalny. Gra rozpoczyna się bez zgrzytów, a menu i kategorie są zorganizowane tak, że łatwo odnaleźć to, na co ma się ochotę. To wygoda, która sprawia, że nawet krótkie chwile relaksu stają się przyjemniejsze.

Oprócz płynności warto docenić elementy narracyjne i tematyczne. Motywy graficzne, ścieżki dźwiękowe i krótkie wprowadzenia potrafią nadać rozrywce atmosferę, która przenosi na chwilę w inne miejsce — od glamour kasynowych stołówek po futurystyczne salony gier.

Detale premium, które robią różnicę

To właśnie detale tworzą poczucie ekskluzywności. Poniżej kilka drobnych elementów, które często decydują o tym, że platforma wydaje się dopracowana:

• Subtelne mikrointerakcje — animacje przy najechaniu kursorem, reakcje przy kliknięciu.
• Spójne motywy wizualne — ikony, kolory i typografia dobrane jak w dobrym magazynie.
• Personalizacja przestrzeni — rekomendacje oparte na estetyce i preferencjach, nie wyłącznie na popularności.
• Przejrzystość informacji — czytelne opisy oraz przyjazne dla oka układy treści.

Każdy z tych elementów osobno może wydawać się drobiazgiem, ale razem tworzą kompletną koncepcję, która sprawia, że użytkownik czuje, iż obcuje z produktami na wyższym poziomie niż standard.

Podsumowanie — czego można się spodziewać

Podsumowując, nowoczesne kasyno online, które stawia na detale, oferuje przyjemne sesje, w których każdy element ma swoje miejsce. Nie chodzi tu o spektakularne obietnice, lecz o konsekwentne dopracowanie: design, dźwięk, mikrointerakcje i przyjazny interfejs. To połączenie sprawia, że korzystanie z serwisu przypomina wizytę w dopracowanym klubie — komfortową i bez zbędnego hałasu.

Dla kogoś, kto ceni sobie estetykę i płynność działania, takie miejsce będzie atrakcyjnym wyborem. Nie jest to ocena mechanik czy wyników, lecz odbioru — jak przyjemnie spędza się czas, jak drobiazgi wpływają na odczucia i jak całość łączy się w spójną narrację zabawy.

By Shikhar Mehrotra Prime Day 2026 has real smartwatch discounts, and these seven picks cover every budget and use case.

Source:: Digital Trends

By Sudhanshu Kumar Mangalam Prime Day has dropped prices on some of the best health wearables, including Fitbit trackers, Oura Ring 4, Apple Watch Series 11, Galaxy Watch 8, and more.

Source:: Digital Trends

By Ana Maria Constantin ByteDance unveiled Seedance 2.5 on Tuesday at its Volcano Engine FORCE conference in Beijing, a video generation model that produces 30-second clips at native 4K resolution from a single prompt. The company skipped four intermediate versions entirely, jumping straight from its predecessor to signal what it described as a generational leap. An enterprise beta is […] This story continues at The Next Web

Source:: The Next Web

By Ana Maria Constantin Anthropic is launching Claude Tag in research preview, an “always-on Claude” that lives inside Slack and acts as a persistent AI teammate. The feature lets users tag @Claude to get insights in conversations and assign tasks. It is available to Claude Enterprise and Claude Team customers starting today. Claude Tag is an evolution of Anthropic’s […] This story continues at The Next Web

Source:: The Next Web

China’s e-commerce giant JD.com is preparing for a future where packages are delivered by robots instead of people. The company’s founder and chairman, Richard Liu, expects robots will “sooner or later” take over deliveries from the company’s roughly 700,000 couriers.

“It will definitely be robots delivering packages. But I really don’t want our 700,000 brothers to go without food and without jobs,” Liu said at the Asia-Pacific Economic Cooperation CEO Forum, according to the Financial Times.

He did not provide a more specific timeframe for the change. As part of the transition, Liu said JD.com has entered into agreements with about 120 schools to retrain couriers for new professions, including the repair and maintenance of robots.

The number of gig workers in China — including delivery drivers, chauffeurs, and factory workers on temporary contracts — is expected to reach about 320 million this year, according to Chinese researchers. At the same time, the youth unemployment rate stands at over 16%.

Source:: Computer World

By Shimul Sood Anthropic’s new Claude Tag feature brings Claude directly into Slack channels, where it can handle coding, research, data analysis, and more. Here’s how it works, how to set it up, and why it could change the way teams collaborate with AI.

Source:: Digital Trends

Forty million UK iCloud users could be owed up to $100 (£77) each after a $3.9 billion (£3 billion) class action lawsuit against Apple was cleared for trial — and the company’s problems may be just getting started. 

For Apple, the worry is that this case could snowball to become yet another existential regulatory problem. The action was brought by consumer group Which?, which accused Apple of breaching UK competition law by giving its iCloud storage service preferential treatment and “trapping” customers with Apple devices into using iCloud. 

Trapping happy customers

Apple achieves this by encouraging its customers to sign up to iCloud for storage of photos, videos and other data while also making it difficult for them to use alternative providers to backup key data. The company also squeezes extra dollars out of customers by providing a stingy 5GB of storage for free, while putting important data including messages and photos inside that allocation. Even Google provides 15GB of storage in its free tier.

The problem is that the scale of Apple makes it difficult for competitors to reach customers with alternative solutions, while Apple’s control over the operating system gives it integration advantages third-party competitors don’t get. 

While there may well be justifications for constraining access to some personal data, those privacy and security challenges don’t apply to all of it. 

You are the product

When it originally filed the claim, Which? explained that Apple could resolve the claim without litigation by offering consumers their money back and opening up iOS to allow users a real choice for cloud services. This is unlikely to happen.

This case has been slowly making its way through the Competition Appeal Tribunal, which last week finally gave permission for the case to go to trial.

Apple won’t be looking at a hefty fine just yet. The first available trial date is in October 2028 and the legal fight is expected to last nine weeks, which might, or might not, equate to a Christmas surprise for Apple’s then CEO. There’s no time to sit back, however, as the company must still file its defense papers with the court by the end of next month, July 31.

The snowball factor

The UK is not alone. Italy has launched its own antitrust probe into Apple’s iCloud dominance under the EU’s Digital Markets Act (DMA). The problem with that litigation is that since Italy has commenced the probe, other nations across the bloc might also act.

Italy is looking to see whether Apple has failed to open up its iOS and iPadOS ecosystems to rival cloud services, arguing that third-party providers are unable to access the same system components as iCloud. The DMA insists competitors should enjoy the same degree of access as iCloud because Apple is seen as a gatekeeper, which means it is required to meet a higher set of standards.

Apple, of course, will inevitably — and rightly — argue that customer privacy needs to be protected, and that open, free, access to some of the data its trusted iCloud service can use is not in the consumer interest. 

The company has already proposed one way in which it can provide third-party services with access to confidential data with a trusted intermediary system that anonymizes that information in use. 

Why we need a Trusted System Agent model

That’s precisely what it offered Europe when it proposed a solution called Trusted System Agent — an intermediary that would allow virtual assistants to safely access the same features and capabilities as Siri AI for devices in the EU. Unfortunately, EU regulators didn’t accept Apple’s justification concerning the need to protect customer privacy, which is why Apple Intelligence won’t be available in Europe for a while, if at all.

In the event Apple’s iCloud service falls short of the Italian probe and therefore the DMA, the danger is that if EU regulators take the same evangelically hard-line stance with iCloud services as they have done so far with AI, customers might find themselves losing access to the service. 

First blood

That’s in Europe, of course. But the UK case is likely to get to court long before litigation processes in Europe get going, making the UK action an important test case in which yet another important component of Apple’s offering to consumers is up for trial.

Please join me on social media at BlueSky,  LinkedIn, or Mastodon, even better, please subscribe to The Core for your daily fix of human-curated Apple News.

Source:: Computer World

Ever felt a sinking feeling when your website traffic drops? It makes you question if your efforts are still worth it. Many marketers share this fear, feeling left behind in a digital world that’s always changing. It is easy to feel discouraged when the rules seem to change overnight.

But here’s the truth: search engine optimization is not dead. Billions of people search for answers, products, and services every year. The way they search is just getting more complex.

The real challenge is keeping your visibility in this changing world. You need to move away from old tactics and meet your audience where they are now. By doing this, you can keep your brand trusted in a crowded digital space.

The Paradigm Shift in Information Retrieval

How we use search engines has changed a lot lately. Digital platforms now offer more than just simple searches. They aim to give users quick, accurate answers to their questions.

From Keyword Matching to Semantic Understanding

Before, search engines looked for exact keyword matches. Now, they focus on semantic understanding. They try to understand the real meaning behind a search.

This change means content creators must give detailed answers. They need to show they know a lot about a topic. This way, they meet the user’s needs, even if the search terms are different.

The Rise of Zero-Click Searches

Zero-click searches are becoming more common. Google often shows answers, maps, or summaries right at the top. This makes it easy for users to find what they need without leaving the search page.

This change is good for users but tough for some websites. Sites that share simple facts or definitions might get fewer visitors. But, businesses that offer services are still doing well. They need more interaction or a booking process. Knowing this helps in understanding today’s digital world.

How Generative AI is Reshaping the Search Landscape

Search engines are changing from just indexing pages to creating content for us. This change comes from generative ai. It lets platforms make content instead of just linking to it. This shift changes how we find and use digital info.

The Mechanics of Large Language Models

Large Language Models (LLMs) are at the core of this change. They work by studying huge datasets to find patterns in language. They use probabilistic modeling to guess the next word in a sequence, making responses that make sense.

The process involves several key steps:

• Data Ingestion: Processing billions of web pages to learn context.
• Pattern Recognition: Finding connections between things and ideas.
• Token Prediction: Creating text that sounds like human thought and structure.

Thanks to artificial intelligence, these models can turn complex topics into easy-to-understand formats. This lets search engines give detailed answers to questions that used to need a lot of research.

Integration of AI Overviews in Search Results

Now, search engines show AI Overviews at the top of the page. These summaries are quick and easy to look at. But, the use of automated synthesis has raised questions about how accurate they are.

Many people doubt these summaries, even for important decisions. While artificial intelligence is good at summarizing general info, it can struggle with complex or sensitive topics. So, people often check these summaries against information written by humans to make sure it’s right.

As generative ai gets better, finding the right balance between speed and accuracy will be key. The future of search will depend on whether these systems can keep our trust while being fast enough for today’s users.

The Decline of Traditional Organic Traffic

The classic search journey is disappearing as users find answers without leaving the results page. This change is a big problem for website owners who count on organic traffic to keep their online presence alive. Search engines now focus on speed, making the old way of clicking links to find answers less common.

User Behavior Changes in the Age of Instant Answers

Today, users want answers right away when they search. They often use AI-generated summaries or featured snippets instead of visiting websites. This means they jump between sources to compare before acting.

Since answers are given upfront, the need to visit a specific site is less. This shift in behavior means organic traffic is no longer a sure thing, even for top-notch content. Users are getting faster, but this efficiency hurts publishers.

The Impact on Click-Through Rates for Informational Queries

Informational queries are hit hard by these new search habits. When search engines give a full answer on the results page, users click less. This leads to a drop in click-through rates in many fields.

Creators must now think differently about their content’s value. If answers are free and quick, they need to focus on deeper engagement. Keeping click-through rates up means offering insights that algorithms can’t summarize.

Natural Language Processing and the Death of the Keyword

The rise of natural language processing has made old SEO methods outdated. Search engines now read like humans, focusing on what a query means, not just the words used.

This change means stuffing keywords no longer works. Algorithms now look at the context and details of a search to find the best results.

Moving Beyond Exact Match Optimization

For years, marketers used exact match optimization to get more traffic. But this method often results in stilted, unnatural content that doesn’t engage users or meet search engine standards.

Today, systems can find synonyms, related ideas, and the true purpose of a page. By dropping strict keyword rules, creators can make content that fully answers what users need.

The Role of Intent-Based Content Strategy

A good content strategy now focuses on what the user wants. Whether it’s a quick answer or a detailed guide, your content should match their goal.

Map your content to the user’s journey stages. By answering questions and offering valuable insights, you gain authority that keyword stuffing can’t match.

The aim is to create top-notch content that solves problems. When your content strategy puts the user first, search engines will see your site as a reliable source.

The Economic Consequences for Content Publishers

The digital world is changing fast, hitting traditional ways of making money hard. Content publishers struggle to keep their sites alive as search engines give direct answers.

The Threat to Ad-Supported Business Models

Websites often use ad-supported models to pay for their teams and sites. But when search engines give answers right on the page, people click less.

This drop in clicks starts a vicious cycle for online media. Without enough visitors, sites can’t make money from ads. So, many are looking at new ways to earn money.

Balancing Visibility with AI-Driven Summarization

To stay in the game, content publishers need a new plan. Just making lots of content isn’t enough anymore. They must offer something special that AI can’t match.

By focusing on original research and deep knowledge, sites can attract true fans. While ad-supported models are still around, getting money from subscriptions or special services is key.

In the end, publishers aim to stay seen while knowing search engines aren’t the only way in. They must find ways to capture user interest even when answers are given upfront.

Machine Learning and the Future of Search Ranking

Search ranking has changed from focusing on keywords to a battle of intelligence and predictive modeling. Modern search engines now use machine learning instead of old, rule-based systems. This change lets them understand human language better than ever before.

How Neural Networks Influence Search Quality

Neural networks are at the heart of this change. They work like our brains, analyzing huge amounts of data to find the best results. This way, they understand what we really mean when we search for something.

Thanks to neural networks, search results are not just right but also make sense. As these systems learn more, they get better at ignoring bad content. This means only the best content gets seen by users.

The Shift Toward E-E-A-T in an Automated World

In a world where machine learning can create lots of content, trust from humans is key. Google and others look for E-E-A-T—Experience, Expertise, Authoritativeness, and Trust—to check if info is reliable. These signals help keep out bad content made by machines.

Companies need to show real human insight to stay visible. Just focusing on technical stuff won’t cut it anymore. Brands should aim to build authentic authority that both algorithms and users can trust. By focusing on these human aspects, businesses can succeed as search tech keeps getting smarter.

Deep Learning and the Personalization of Search

Deep learning is changing how search engines understand what we need. They use big data to go beyond just matching keywords. This is a big step forward in how artificial intelligence meets our curiosity.

Hyper-Personalized Results for Individual Users

Today’s search engines use deep learning to create detailed profiles based on what we’ve searched before. When you search, they look at your history to guess what you really want. This makes your search experience more relevant and saves time.

Personalized search has many benefits for us. Here are some key advantages:

• Increased efficiency by needing fewer searches.
• Contextual relevance that considers where you are and what you like.
• Predictive suggestions that guess what you might want before you type it.
• Improved discovery of content that fits your interests over time.

The Privacy Implications of AI-Driven Search

Personalization is convenient but raises big privacy concerns. Artificial intelligence needs lots of personal info to work well. This raises questions about how much data is too much.

People often give up privacy for a better browsing experience. But, having so much personal data can be risky if it gets hacked. Developers must find a balance between using deep learning and protecting our privacy.

The future of search depends on trust. Being open about how data is used is key. As these technologies get better, we must make sure personalization doesn’t risk our safety.

Automated Content Creation and the Quality Crisis

As generative ai tools get easier to use, the web is filling up fast with fake content. This change has made the quality of online info drop a lot. Now, many websites use automated content creation to make more content, but it’s often not as good.

The Flood of Synthetic Content

It’s now easy to make lots of text quickly. Websites can churn out thousands of articles in just minutes. This makes it hard for good, original content to be seen.

To stay ahead, brands need to focus on quality over quantity. Using machines to write content can make it sound fake or lacking in personal touch. Here are some tips to keep your content valuable:

• Use original research and unique data.
• Add expert interviews for real insights.
• Always edit content by hand.
• Think about what users want, not just keywords.

Distinguishing Human Expertise from AI Hallucinations

One big problem with generative ai is it can make up things that aren’t true. These hallucinations can hurt a brand’s image. Only humans can spot these mistakes.

Being an expert means being accountable and having real experience. While automated content creation can help with writing, it can’t replace a real expert’s knowledge. By mixing tech with human review, companies can stay trustworthy and efficient.

Adapting SEO Strategies for the AI Era

To succeed today, you must offer something unique that machines can’t. With generative ai changing how we search, businesses need to update their seo strategies. Old tactics won’t cut it anymore to keep your brand seen.

Focusing on First-Party Data and Unique Insights

Standing out means using data only your company has. Generative ai can mix public info, but it can’t match your unique research or customer stories. By focusing on these, you create a barrier that’s hard for AI to cross.

Using first-party data makes you a key source, not just a secondary one. This boosts your seo strategies by giving search engines the quality info they want. When you share insights no one else has, you become a go-to spot for your audience.

Building Authority Beyond the Search Engine

Just focusing on search rankings is risky in today’s fast-changing tech world. You need to be strong across social media, email, and industry groups. This diversified approach keeps your traffic steady, even when search results change.

Building authority means being a trusted voice that people seek out. When your brand is seen as an expert, you’re not just relying on search for clicks. The best seo strategies build a loyal community that values your knowledge, no matter the search landscape.

The Role of Language Generation in Brand Visibility

Mastering language generation is key for companies wanting to stay ahead in AI-driven search results. Search platforms now favor synthesized answers, changing how we grab attention. To keep your brand seen, you must change how machines understand and show your company info.

Optimizing for AI Answer Engines

Your content needs to be easy for AI to get. Use clear, structured formatting to make sure your insights are picked for AI summaries. Focus on giving direct answers to common questions to get noticed more.

Adding schema markup helps search engines get your data’s context better. This makes your info easier for language generation tools to use, giving you an edge online.

The Importance of Brand Mentions and Entity SEO

Building a strong online presence through entity SEO is also crucial. When your brand is mentioned often on good sites, AI knows it’s reliable. This helps AI link your brand with certain topics and expertise.

Working on brand visibility through quality mentions boosts your authority online. Aim to be seen as a trusted voice in your field by sharing unique insights. When AI sees your brand as a go-to source, you’ll show up in automated answers more often.

The Future of Search Engines and AI Technologies

The digital world is changing fast with ai technologies leading the way. Search engines are becoming more than just gateways to the web. They’re turning into vast knowledge centers. This change makes us think about the future of the open internet.

Will Google Become a Closed Ecosystem?

There’s worry that big search engines might focus more on their own stuff than on linking to other sites. By keeping users inside, they can keep them engaged longer. This could change the digital world a lot.

Several things are pushing this change:

• More use of ai technologies to answer questions directly.
• Less visibility for outside content in search results.
• More time spent inside the search engine for users.

The Emergence of Decentralized Search Alternatives

As artificial intelligence gets stronger, a new movement is starting. Developers are working on decentralized search options. These aim to give back control to users and creators. They use blockchain or peer-to-peer networks for fairness and transparency.

These new platforms offer a fresh view for the web:

• Community-driven ranking to cut down on bias.
• Open-source algorithms for more public oversight.
• Less need for big data centers run by one company.

Even though these decentralized options are just starting, they’re crucial. They stand up to the power of artificial intelligence. The search engine future will be a fight between big, centralized powers and smaller, more open networks. Adaptability will be key for anyone in the digital world.

Conclusion

The world of digital discovery is changing forever. Brands need to stop chasing after algorithm updates. They must find their place in the digital world.

Good search engine optimization means being a true authority. Focus on creating unique insights that AI can’t copy. This builds trust as user habits change.

The future of search is about giving clear, reliable answers. Being the go-to source for answers makes you independent of platform changes. Invest in building a strong reputation that speaks to your audience.

Adopt this change by making your content more human. Becoming the top choice for your readers ensures success, no matter the tech changes. Start building your authority now to succeed in this new world.

By Hisan Kidwai When the BMPS 2026 Grand Finals began in Jaipur, GodLike Esports weren’t the obvious favorites. Teams…
The post How GodLike Won BMPS 2026 Grand Finals And Secured A Spot At The Esports World Cup appeared first on Fossbytes.

Source:: Fossbytes

By Ana Maria Constantin Cloudflare has announced a joint initiative with Mozilla Firefox, Google Chrome, and Microsoft Edge to develop a new internet protocol that verifies whether web traffic is legitimate without tracking users. The protocol, called Private Access Control Tokens, is designed to replace CAPTCHAs and forced logins with anonymous tokens that prove a visitor is human or […] This story continues at The Next Web

Source:: The Next Web

By Ana Maria Constantin Amazon is testing Alexa+ in India with Hindi-language support, the company’s first move to bring its generative AI assistant to a non-Western-language market. The company sent emails to select Indian customers inviting them to join a beta-testing programme, according to TechCrunch, which viewed the invitations. The emails asked users to fill out a form in […] This story continues at The Next Web

Source:: The Next Web

Tech industry experts are urging IT decision-makers to be wary of AI vendor gimmicks such as free tokens, and to adopt a multi-vendor and multi-model strategy to avoid vendor lock-in.

“Don’t be afraid to adopt a multi-vendor approach to get value from different AI tools rather than risk lock-in with a single one,” said Max Goss, senior director analyst at Gartner.

It is unlikely one AI vendor or model will meet an organization’s requirements, Goss said.

The advice comes as more AI vendors are offering cheap tokens subsidized by venture capital in a land grab for customers. The companies are also hiring forward-deployed engineers (FDEs) to push their models to enterprises.

Once companies start developing business processes around specific AI models, they get locked into their ecosystem. “People are adopting hybrid strategies…to cut token costs, and adopting more token-efficient models,” said Jack Gold, principal analyst at J. Gold Associates.

Free and low-cost tokens from AI vendors could incentivize companies to build processes and workflows around proprietary LLMs and agents, said Max Leaming, head of data science and AI solutions at ManpowerGroup.

But as the AI landscape evolves, it’s difficult to predict whether a multi-model or multi-vendor landscape will emerge, said Logan Wolfe, partner of global AI strategy and sovereign transformation at IT consulting firm Kyndryl. “I think it could be multi-model, yes. It really comes down to the use case and the type of implementation that you’re having,” Wolfe said.

Enterprises are still in the midst of moving blue-sky experimentation to a mindset where they see AI as a powerful tool that needs to make sense from a business perspective. With that in mind, IT leaders should ground their AI strategies on use cases as opposed to vendors, Wolfe said.

“If it’s a highly regulated space, if it’s a financial sector, a healthcare sector, then you will be placing a lot more emphasis on safety, privacy, maintaining certain regulations, and so that could prevent you from rapid model switching based on cost,” Wolfe said.

For low-stakes use cases, it would be prudent to have a model-switching approach that doesn’t break the bank. “For a low-hanging fruit use case with varying volume, like a customer support data center, during heavy load times you could switch to the more capable model, then optimize that on evenings and weekends,” Wolfe said.

ServiceNow Chief Digital Information Officer Kellie Romack, who’s worked in IT for 25 years, said companies need to understand how their AI is built. “You can’t have AI built in such a way that you don’t have human beings understanding how it was built…, how to debug, back up, and retrace,” she said.

Romack has also long resisted ripping out one vendor’s platform to replace it with another. “I say, ‘Let’s talk about the technology you already have…, now let’s see the best of breed,’” she said.

After studying what customers already own and where their contracts and plans are headed, Romack looks at options based on architectural principles and the problem being solved, then runs multiple models in-house, such as Anthropic’s Claude and Microsoft’s Copilot, through one LLM gateway.

“We have a lot of different things in-house that people can put their fingers on,” Romack said.

For example, Claude might be better for reading a long Word document, while Copilot might be better for a quick summary.

She is sensitive about internal AI spending. “Every day we look at token spend. I’ll look at an engineer that’s got the same job as another engineer, and I’m like, ‘OK, you spent $10, you spent $10,000. Why?’”

Avoiding vendor lock-in is important for continuity of service. Outages hit AI services from OpenAI and Claude in recent months, and a multi-model approach provides fallback options, Gartner’s Goss said.

“If you are relying on a single provider with a single model, there’s risk there. You can mitigate that risk with a multi-model approach,” he said.

Source:: Computer World

By Shimul Sood Getty Images has announced a new display agreement with OpenAI that will bring its licensed visual content into ChatGPT. The partnership is notable given Getty’s long-running criticism of AI companies over how training data is sourced, marking an unexpected new chapter in the AI industry’s relationship with content owners.

Source:: Digital Trends

By Candace Iverson Prime Day is the perfect time to upgrade. These standout picks deliver practical benefits, thoughtful design, and impressive value.

Source:: Digital Trends

By Shimul Sood My Apple Watch SE 2 still works perfectly. So why does it already feel left behind? Why Apple, why?

Source:: Digital Trends

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Not-yet-profitable AI companies are constructing a vast and expensive global network of server farms to support cloud-based generative AI (genAI) services. Deeply financed by venture capitalists who will one day want to see return on their investments, these centers are consuming enough memory to drive consumer technology prices higher and higher.

Yet, for all the investment now going on, it’s inevitable that new on-device genAI models will emerge. When they do, the AI tasks for which you use cloud services today will be handled on device tomorrow. And at the speed we’re going, tomorrow is not very far away.

We already know it is possible. Just look at Siri AI. To create it, Apple worked with Google Gemini — using the latter to help build and distill Apple’s own AI models, many of which now work entirely on device.

The hidden cost of the AI buildout

This move toward edge AI takes place as the tech industry pours its eggs into the AI basket, with major memory suppliers redirecting manufacturing capacity toward higher-value memory products for AI servers, such as advanced-layer 3D NAND. They’ve done so while failing to invest in additional capacity, prompting a shortage of the kind of general purpose RAM you use in your computer, console, or smartphone.

This is having a dramatic impact. Gartner says the memory shortage will cause PC shipments to drop 10.4% in 2026 and smartphone shipments to decline 8.4%, with prices on those products rising 17% and 13%, respectively, versus 2025 levels.

The AI consumer tech tax

This leaves electronics manufacturers quarrelling over the remaining supply, while shrinking profit margins force them to increase prices. Sony has already raised the PS5 price by $100, Microsoft has raised Xbox prices, and Nintendo has raised the price of its first-generation Switch. Samsung has quietly increased prices across Galaxy smartphones, tablets, and laptops. Analysts also warn that “shrinkflation” is escaping from the supermarket and coming to your tech, an insidious move in which manufacturers quietly reduce the features/performance of their devices to maintain familiar price points. That laptop you purchase could ship with a downgraded display, for example.

Apple is not immune. The iPhone 18 Pro is tipped for a significant price increase in 2026, potentially adding $100 to $150, even before tariffs are considered. Apple CEO Tim Cook recently warned of price increases ahead as a direct impact of demand for memory components.

A business model under pressure

Surely all this investment in AI servers and the increased cost of tech products will be worth it in the end, right? Writer and tech critic Ed Zitron disagrees, pointing out that for $200 a month, a user can burn $8,000 in Anthropic tokens or $14,000 in OpenAI tokens. 

He argues that subsidy at this scale suggests AI economics are already broken, and that the actual value of AI may be inflated, forming a big bad bubble ready to burst once market opinion (and investment) catches on.

By spending billions chasing market share, AI has fundamentally undermined its own value, making it harder to achieve sustainable business success. Costs might well fall in future, of course, but edge AI could be the biggest cost reduction exercise of all.

Make tokens pay

Perhaps AI companies have finally begun turning things around? Maybe not. Less than three months into paying the actual costs of LLM-based services, both OpenAI and Anthropic are considering drastic price cuts, with one Cisco executive stating publicly that AI token costs are far higher than the actual value those tokens are generating at scale.

Even Meta has imposed strict limits on token usage after finding it was on track to spend billions on internal AI alone in 2026. The Times reports that two large banks spent an astonishing $1 billion on AI experiments without seeing any significant return.

That’s the use value, but what about the hardware investment? It is really hard to ignore the irony that billions of dollars are being poured into a server-based infrastructure that might become obsolete before turning any kind of profit. Today’s H200-based servers will need to be upgraded sooner or later, and when they are, where will the money come from? 

Apple has a different approach

Consumer electronics leader Apple clearly sees this. While it has been accused of being behind in AI, perhaps it was just being realistic. After all, the reality seems to be that we’re experiencing something akin to venture capital backed economic socialism in the AI sector, with billions invested for no visible — or, if Zitron is right — possible return. 

At the same time, Apple seems focused on building edge AI as a privacy-preserving, cost-saving alternative to the massive data center buildouts rivals have pursued. 

Rather than squandering billions on a revenue-draining chatbot, Apple worked with others to create its own alternative. As part of its agreement with Google, Apple is using a large version of Gemini to train a smaller, distilled version capable of running locally on Apple hardware.  Siri AI can hold conversations, pull context from a user’s emails, messages, and photos, answer live questions from the web, and act across apps, with much of the work taking place on the device itself.  

These tools are also available to app developers, thanks to Apple’s Foundation Models framework. At WWDC, Apple showed how its devices can work together to run local LLMs using MLX Distributed, which means users can run on-premises, highly private AI models. And the company continues to make strategic acquisitions, such as the recent purchase of on-device AI startup Liquid AI.

On-device or off, the move has caused Apple to break with years of tradition to pack its systems with more and more memory, ironically feeding the same component pricing narrative.

The squeeze isn’t over

Who pays for all this? You do. Memory prices will continue to rise across the year, with TrendForce predicting up to 75% increases on top of the already 100% spike we’ve seen in recent months. Memory suppliers seem unwilling to ramp up supply to help bring costs down, potentially because they don’t want to be left with unused capacity once the AI bubble does burst. That means existing manufacturing is being pointed at the highest value memory components, further feeding price hikes.

When AI leaves the cloud

What happens to investors when AI stops needing a data center to be useful?  The companies that survive this shift won’t necessarily be the ones who built the biggest and most costly clouds. They are more likely to be the ones who identified cloud-based AI as the start of a transition toward more intelligent devices equipped with their own on-device AI. That is precisely what Apple is building toward.

Please join me on social media at BlueSky,  LinkedIn, or Mastodon, even better, please subscribe to The Core for your daily fix of human-curated Apple News.

Source:: Computer World

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Source:: Digital Trends