By Shikhar Mehrotra Alibaba, Tencent, and Baidu are handing out billions in cash and prizes to attract chatbot users, highlighting how fierce China’s AI race has become in 2026.
The post The AI Race is so hot that chatbot users are getting paid in real cash, iPhones, and TVs appeared first on Digital Trends.

Source:: Digital Trends

How much would you pay each month for a Mac, iPhone, iPad, Apple home accessories and a handful of Apple services, including health and home security services? More to the point, how many of Apple’s 2.5 billion users would be willing to pay for the Apple Plus Services suite, and how much would this generate each month in high-yield, high-margin predictable income for the former hardware company?

Apple-as-a-Service? It’s possible

The Apple-as-a-Service idea has hovered at the edge of Apple speculation for years, and while Apple has skirted with the concept (iPhone Upgrade Program), it’s never quite found a way to combine hardware and software in a services-led bundle. But things can change. Bloomberg’s Mark Gurman last year suggested Apple had considered offering a hardware subscription service, but shelved the idea fearing the impact on “normal” hardware sales.

What’s certain at this stage is that it feels as if it would be easier than ever for Apple to pivot its entire business into services, particularly as it has more than 1 billion people using at least one of its services already. Breaking those use patterns down, Apple recently shared some glimpses into the performance of the services segment:

900 million active iCloud+ subscribers.

850 million active App Store users.

58 million Apple TV+ subscribers.

15 million merchants who accept Apple Pay.

Apple News is the number one news app in the US, Canada, and Australia.

The company followed this news up with the introduction of the phenomenal value Creator Studio suite, which unleashes industry leading tools for audio and video production, Final Cut Pro and Logic — along with apps for imagery and productivity — for $12.99 a month. Apps that create opportunity for creative expression are arguably fundamental to the Mac, a purpose that runs deep into Apple’s DNA. 

When it decided to introduce its leading creative apps as a service, Apple moved the needle on both software and services sales, taking a bite out of one segment to benefit a second. The way Apple sees it is that maybe it doesn’t really matter how Apple sells something, so long as the market takes it, and keeps that high margin (c.70%) services segment revenue rolling in. (The segment was worth $30 billion in the just gone quarter.)

The myth of ownership

One argument against hardware-as-a-service is that people like to own their stuff. That’s true. But when you stop to think about it, the truth is that we already use hardware we don’t really own — that iPhone in your pocket you acquired with a carrier deal; the credit card debt you’re paying for your current Mac; the iPads for your field services team you acquired with help from your bridging loan; the Mac you’re about to purchase for a monthly cost direct from the Apple Store.

Even four years ago, “Almost half iPhone owners already finance their iPhone purchase, paying monthly for a new phone,” said CIRP Partner and Co-Founder Josh Lowitz. “And about one-third trade-in their old phone when they buy a new one. So, a significant portion of the user base is accustomed to never owning a phone, instead basically leasing it.”

We use kit we don’t quite own all the time. An Apple hardware-as-a-service offering could accommodate that, offering hardware ownership as one result, after an agreed upon number of payments are made. The second result would be what tempts users though.

Think about how attractive a new Mac upgrade every two or three years and an iPhone upgrade every other year as a basic subscription might be, with AppleCare rolled in. Reflecting that kind of thinking, many already use Apple Trade in, sending their old hardware back to Apple for parts in exchange for money off the next bit of equipment. It’s an ownership model that shows many are already accustomed to treating hardware as if it were a subscription item. 

Improving the experience

But why would Apple abandon hardware sales in favor of services? To build margins, of course, and to develop a predictable income stream, but also to better control the user experience. Not only can Apple then continue to focus on improving its hardware, but because it knows what hardware its customers are running, it can focus improvements in software and services on the hardware.

Think of it as an extension of Apple’s “whole widget” approach, one encompassing hardware, software, services, and silicon with management of the ecosystem itself. 

There are solid environmental reasons for this ecosystem, as it becomes much easier to call in old kit and arrange for it to be recycled, feeding those cannibalized components straight into the circular manufacturing system we know Apple wants to build. It gets a lot easier to build a system like that once you know almost exactly how many recycled components you’ll have to work with in any week; that’s the kind of granular insight a subscription hardware offering might provide.

The numbers game

Would consumers be willing to accept an ownership model like this? To some extent that doesn’t matter. It doesn’t need to be adopted by every consumer to succeed. With 2.5 billion people already one email away from Cupertino, Apple only needs to switch a small fraction of that group over to a hardware/software/services subscription model to generate predictable revenue.

As a thought experiment, imagine if just 1% of those Apple users (25 million) stepped into a services/Mac/iPhone deal at $129/month, that’s $3.2 billion in revenue every month. While I think the cost would be higher (because it’s Apple), that gives you some sense of the revenue the company can raise with the addition of a subscription option when ordering products at the Apple Store.

As a numbers game, Apple starts with the kind of advantage that should make Wall Street nod, in the sense that investors already value tech firms with high recurring revenue more highly than those dependent on cyclical hardware sales.

Who knows, if you could get hold of a Mac and iPhone in such a way for a monthly fee, Apple might find it even easier to upsell consumers to higher specified options through its recently updated Apple Online Store, generating a few more dimes each month with every consensual memory upgrade.

Plus, of course, with user satisfaction numbers in the high 90s, Apple would likely find it even easier to lock its customers into the total Apple experience. That potentially includes a highly secure Apple HomeKit AI-augmented and private home security service with which to protect all this kit, which some believe the company might announce during the year.

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Source:: Computer World

By Shikhar Mehrotra Sony’s next flagship true wireless earbuds may deliver smarter AI audio, improved noise cancellation, fresh design tweaks, and premium pricing, according to a detailed new leak.
The post Sony leak shows a new look for upcoming WF-1000XM6 earbuds and a big audio upgrade appeared first on Digital Trends.

Source:: Digital Trends

Across industries, CIOs are rolling out generative AI through SaaS platforms, embedded copilots, and third-party tools at a speed that traditional governance frameworks were never designed to handle. AI now influences customer interactions, hiring decisions, financial analysis, software development, and knowledge work — often without being formally deployed in the classical sense.

The result is a widening gap between rapid AI deployment and responsible-use protections. Organizations adopt AI faster than they can govern its usage, then scramble to retrofit controls after something goes wrong.

Interviews with five practitioners — each working at a different pressure point of enterprise AI — reveal why this gap persists and what leaders must do to close it before regulators, auditors, or customers force the issue.

Why governance breaks the moment AI hits real workflows

The first problem is structural. Governance was designed for centralized, slow-moving decisions. AI adoption is neither. Ericka Watson, CEO of consultancy Data Strategy Advisors and former chief privacy officer at Regeneron Pharmaceuticals, sees the same pattern across industries.

“Companies still design governance as if decisions moved slowly and centrally,” she said. “But that’s not how AI is being adopted. Businesses are making decisions daily — using vendors, copilots, embedded AI features — while governance assumes someone will stop, fill out a form, and wait for approval.”

That mismatch guarantees bypass. Even teams with good intentions route around governance because it doesn’t appear where work actually happens. AI features go live before anyone assesses training data rights, downstream sharing, or accountability.

What breaks first, Watson said, is data control and visibility. Employees paste sensitive information into public genAI tools, and data lineage disappears as outputs move across systems. “By the time leadership realizes what’s happening,” she said, “the data may already be gone in ways you can’t undo.”

What to do: CIOs must move from model governance to usage governance. You may not control the model, but you can control how it’s used, what data it touches, and where outputs flow. Governance has to be embedded as tollgates inside workflows, not in policy documents that are reviewed after the fact.

Why legacy data governance struggles under genAI

Even where governance exists, it’s often built on assumptions that no longer hold. Fawad Butt, CEO of agentic healthcare platform maker Penguin Ai and former chief data officer at UnitedHealth Group and Kaiser Permanente, argues that traditional data governance models are structurally unfit for generative AI.

“Classic governance was built for systems of record and known analytics pipelines,” he said. “That world is gone. Now you have systems creating systems — new data, new outputs, and much is done on the fly.” In that environment, point-in-time audits create false confidence. Output-focused controls miss where the real risk lives.

“No breach is required for harm to occur — secure systems can still hallucinate, discriminate, or drift,” Butt said, emphasizing that inputs, not outputs, are now the most neglected risk surface. This includes prompts, retrieval sources, context, and any tools AI agents can dynamically access.

What to do: Before writing policy, establish guardrails. Define no-go use cases. Constrain high-risk inputs. Limit tool access for agents. And observe how systems behave in practice. Policy should come after experimentation, not before. Otherwise, organizations hard-code assumptions that are already wrong.

Why vendor AI is where governance collapses

If internal AI governance is weak, third-party AI governance is worse. Richa Kaul, CEO of Complyance, works with global enterprises on risk and compliance management. She sees a sharp divide: while companies are relatively mature in governing AI they build themselves, they are much less prepared when AI arrives embedded in vendor products.

“What we’re seeing is use before governance,” she said. “And it’s often governance by committee — 10 to 20 people reviewing vendors one by one without a shared baseline of questions.” Too often, enterprises ask open-ended questions about AI privacy and accept reassuring answers — what Kaul calls “happy ears.”

Mature governance shows up in specific questions. Is customer data used to train models? Is it reused across clients? Is the LLM accessed via an enterprise deployment or a consumer interface?

“A vendor using Azure OpenAI has a much lower risk profile than one calling ChatGPT directly,” Kaul said.

What to do: CIOs should start with a basic but overlooked step: scrutinize vendor subprocessor lists. Cloud providers are well understood. LLM providers are not. AI has created a second, poorly mapped subprocessor layer — and that’s where governance breaks down.

Why bans fail and incidents repeat

Technology controls alone do not close the responsible-AI gap. Behavior matters more. Asha Palmer, SVP of Compliance Solutions at Skillsoft and a former US federal prosecutor, is often called in after AI incidents. She says the first uncomfortable truth leaders confront is that the outcome was predictable.

“We knew this could happen,” she said. “The real question is: why didn’t we equip people to deal with it before it did?” Pressure to perform is the root cause. Employees use AI to move faster and meet targets — just as they have in every compliance failure from bribery to data misuse.

Blanket bans on genAI do not work. “If you take away responsible use,” Palmer said, “people will use it irresponsibly — in secret, in ways you can’t govern.”

What to do: Shift from awareness training to behavioral learning. Palmer calls it “moral muscle memory,” a scenario-based practice that teaches people to stop, assess risk, and choose a better action under pressure.

Regulators and auditors look for evidence that the right people have received the right training for the risks they actually face. One-size-fits-all AI literacy is a red flag.

Why confidence is not enough when auditors arrive

The final gap appears when organizations are asked to prove their governance works. Danny Manimbo is ISO & AI Practice Leader at Schellman, an attestation and compliance services provider. He sees the same failure pattern repeatedly.

“Organizations confuse having policies with having governance,” he said. “Responsible AI principles don’t matter if they don’t influence real decisions.”

Auditors might start with a simple request: show us a documented AI risk-based decision that changed an outcome. Mature governance leaves fingerprints — including delayed deployments, rejected vendors, and constrained features. Immature governance produces vague assurances.

“The most expensive governance work is the work you try to do after deployment,” Manimbo warned. Walking back data lineage, accountability, and intended purpose is extraordinarily difficult once systems are live.

What to do: Treat AI governance as a management system, not a compliance exercise. Standards like ISO/IEC 42001 work only when they connect risk management, change control, monitoring, and internal audit into a continuous loop.

You can tell governance is working when it changes business decisions, not when it produces documentation.

Closing the responsible AI gap

Across all five interviews, one theme recurs: the responsible AI gap is not primarily a technology failure. It’s a governance timing failure. Controls are being designed for yesterday’s systems while AI is already shaping today’s decisions.

Several of the sources stressed that CIOs should stop framing responsible AI as a future-state program and start treating it as an operational hygiene issue — closer to identity management or financial controls than to ethics committees.

Watson from Data Strategy Advisors emphasized that visibility is the first non-negotiable step. Enterprises that cannot enumerate where AI influences decisions — especially through SaaS tools — are already exposed. “You can’t govern what you can’t see,” she noted, warning that many companies still lack even a basic inventory of AI-affected workflows.

At Penguin Ai, Butt reinforced that point from a data perspective, arguing that inventories must shift from platforms to systems-in-context. An AI feature embedded in HR software and the same feature embedded in marketing automation do not carry the same risk. Treating them as identical is a governance illusion.

Complyance’s Kaul added that the same principle applies externally. Vendor AI governance breaks down when enterprises accept generic assurances instead of mapping where their data actually flows. In her experience, simply forcing teams to trace AI subprocessors exposes risks that executives did not realize they had accepted.

To close the gap, CIOs must:
>
Embed governance where work happens — and before it happens, not after.
Shift focus from models to usage and inputs.
Treat vendor AI as a first-class risk domain.
Replace bans with behavioral training.
Demand governance that provides explanations as to how decisions are made.

The organizations that do these things will not only avoid regulatory trouble, they will move faster — and with more confidence.

Palmer from Skillsoft focused on the human layer that sits underneath all of this. Governance frameworks collapse, she argued, when they assume people will slow down under pressure. “Pressure doesn’t disappear,” she said. “You have to train for it.” Organizations that fail to do so should not be surprised when employees improvise with AI in unsafe ways.

Finally, Schellman’s Manimbo offered a blunt litmus test: if governance has never delayed a deployment, rejected a vendor, or constrained a feature, it probably does not exist in practice. “Governance has to leave fingerprints,” he said. Otherwise, it is indistinguishable from aspiration.

Taken together, the interviews suggest that closing the responsible AI gap does not require perfect foresight or exhaustive policy. It requires earlier intervention and clearer accountability. Organizations that act now — while AI use is still fragmented and informal — have a chance to shape behavior. Those that wait will inherit systems they no longer control and risks they can no longer explain.

At that point, governance is no longer a choice. It becomes damage control.

Related reading:

GenAI in productivity apps: What could possibly go wrong?

Overcome governance and trust issues to drive agentic AI

The trick to balancing governance with innovation in the age of AI

Deloitte’s AI governance failure exposes critical gap in enterprise quality controls

Source:: Computer World

By Ana-Maria Stanciuc Every January, millions take on Dry January, a ritual of restraint and resetting after the holiday season. If that’s the benchmark for kicking off the year with moderation, Europe’s startup ecosystem clearly didn’t get the memo.  In the opening weeks of 2026, the region saw five startups join the unicorn club, crossing the $1 billion valuation mark across sectors as varied as cybersecurity, cloud optimisation, defence tech, ESG software, and education technology.  January was anything but dry for European companies. This burst of activity signals more than a funding spike; it invites a deeper look at what Europe’s innovation identity…This story continues at The Next Web

Source:: The Next Web

By Hisan Kidwai Anime World Tower Defense is a popular tower defense game in Roblox, where players defend their…
The post Anime World Tower Defense (AWTD) Codes (February 2026) appeared first on Fossbytes.

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By Alexandru Stan G2 acquires Capterra, Software Advice, and GetApp from Gartner G2 has completed a major acquisition by purchasing three of the world’s most influential software discovery platforms from Gartner. The move significantly reshapes the global B2B software reviews market and strengthens G2’s position in how companies evaluate and buy software. Noora Saksaa appointed CEO of Slush Slush, one of Europe’s most influential tech and startup events, has named Noora Saksa as its new CEO. The leadership change signals a strategic shift toward expanding Slush beyond its annual event and building a year-round global founder platform. France moves public sector away from…This story continues at The Next Web

Source:: The Next Web

By Alina Maria Stan The software industry is increasingly questioning the growing influence of G2 following its agreement to acquire Capterra, Software Advice, and GetApp from Gartner. The deal, announced in late January and expected to close in Q1 2026, consolidates several of the most influential B2B software discovery platforms under a single owner . How big is G2’s footprint after the acquisition? According to G2’s own disclosures, the combined group will host around 6 million verified software reviews and reach more than 200 million software buyers annually across thousands of categories. Individually, the platforms already commanded significant scale: G2 reports over 3 million…This story continues at The Next Web

Source:: The Next Web

By Varun Mirchandani Researchers develop ultra-high-resolution micro-LED displays (~1,700 PPI) that could enable near-reality visuals in smartglasses and wearable XR.
The post Why your next smartglasses might finally have crisp visuals appeared first on Digital Trends.

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By Varun Mirchandani New thermal diode technology could steer heat one way, preventing overheating and prolonging battery life in phones and other devices.
The post Your phone might stay cool thanks to this new battery breakthrough appeared first on Digital Trends.

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By Allison Steffens Herrera We are all familiar with the subscription economy, and it certainly works as a reminder of the COVID-19 pandemic, when we were all hooked on our TVs watching Netflix or listening to our favorite music artist on Spotify. Despite how modern it seems to be, the truth is that the subscription economy has been around for some time, surprisingly dating back to around 1800, with the first magazine subscriptions, or the subscriptions for fresh British milk, around 1860. Over the years, the of subscription-based companies has turned the subscription model into an ideal business strategy since it provides unique benefits.…This story continues at The Next Web

Source:: The Next Web

Windows developers are now focusing on improving the core experience in Windows 11, with Microsoft reportedly redirecting resources to address the operating system’s performance and reliability issues, according to The Verge.

The move follows criticism of Windows 11 over recurring bugs and performance issues. Many users have also reacted to what they perceive as intrusive ads, bloatware, and unwanted AI initiatives.

“The feedback we’ve received from our community of engaged customers and Windows Insiders has been clear. We need to improve Windows in ways that actually matter to people,” Pavan Davuluri, head of Windows and devices, told The Verge.

“This year, you’ll see us focus on addressing the pain points we hear repeatedly from customers: improving system performance, reliability, and the overall Windows experience.”

Source:: Computer World

It’s easy to fall down the rabbit hole that is the hype surrounding Anthropic’s code agent Claude Code, a hype that really took off during the Christmas holidays and — at least in tech circles — is reminiscent of ChatGPT’s arrival three years ago. Claude Code, already being called both “the new ChatGPT” and “the end of SaaS,” and is considered by many to be the next big step in AI development and AI use.

If, like me, you spend a little too much time online, Claude Code has started to completely dominate your feeds lately. Of course, it “helps” that the algorithms give me “more of what I want,” but both LinkedIn and TikTok are overflowing with people talking about the excellence of Claude Code. AI influencers, ordinary developers, curious IT professionals, and, of course, a steady stream of obscure individuals who want to cash in on all the buzz.

People are vibe-coding everything from entire websites to small personal apps and finding new solutions for their workflows. Ethan Mollick, a professor at the Wharton School of the University of Pennsylvania, wrote about how he had Claude Code build an entire startup. In other circles, there’s talk of Gas Town, an orchestration solution that allows 20 to 30 agents to work in parallel. In San Francisco, it is said, people are letting “Claude swarms control their lives.”

In the last week, Clawdbot (now Moltbot) also jumped on the hype train; it’s a Claude Code-like AI assistant that you give full access to your digital life, if you dare.

It’s all fascinating and often incredibly impressive. Code is seen as the primary use case for generative AI (genAI), and when you see what Claude Code can do, it’s not hard to understand why. I haven’t tested Claude Code myself, even though more than one person has told me that I simply “must.” And I’m not particularly keen to do so (though I will probably get around to it later for purely educational purposes). Let me explain my thinking.

For starters, I’m not a developer and I can’t write code. Now, the point is that Claude Code is supposed to write the code for you, but it’s not quite that simple. The entry barrier is still too high for me, and the road to the really cool stuff is too long. I have a basic understanding of the processes and functions involved in software development, but my knowledge is far from enough.

Anthropic has begun to address this by releasing Claude Cowork, which is described as Claude Code for people who are not developers. That sounds interesting. But here’s the problem: what I’m being asked to do with it, how it’s being sold — it just sounds…boring. For some reason, the first example often highlighted for tools like this is that they can “sort your files on your computer.” That might be a good thing to do, once, if you have a lot of unsorted files on your computer. But it’s hardly a use case that’s worth buying and learning a new tool for.

If you look at what enthusiasts are doing with Claude Code, a lot of it focuses on personal productivity and “optimization,” both at work and in everyday life. That’s something I’m completely uninterested in. Sure, I also read “Getting Things Done” and “The 4-Hour Workweek” 20 years ago, but what I learned above all else was that the deeper you sink into that self-help swamp, the greater the risk you’ll end up spending all your time finding new ways to optimize things. (It’s also sad, but perhaps telling of modern working life, that people need to come up with “hacks” to be able to do their jobs.)

The main reason I’m meh about Claude Code is this: I lack the software perspective. This realization occurred to me recently when I read tech writer Jasmine Sun’s experiences with Claude Code. She points out how people who do parkour over time learn to see a city in ways that the rest of us don’t; they develop a “parkour perspective” where walls and stairs become something completely different from walls and stairs. In the same way, she suggests developers develop a kind of software perspective where all problems can be translated into, and solved by, software.

An ordinary user like me does not have software-related problems. I do not automatically see how something I do can be automated or optimized by a bot. So when I hear that Claude Code can solve my problems, I cannot think of a single one.

I think this perspective says a lot about the use of AI in general and isuseful to keep in mind. That’s true for both super users who hype the new solutions for people who “can’t keep up,” and for companies that are feverishly trying to get their staffers to embrace AI. I don’t think anyone is against a new tool that makes them more productive and facilitates their work, as long as they know what to use it for.

Perhaps companies’ AI training courses should focus less on learning specific tools and more on learning to identify the problems they’re supposed to solve, perhaps even developing a software perspective.

This column is taken from CS Veckobrev, a personal newsletter with reading tips, link tips, and analyses sent directly from editor-in-chief Marcus Jerräng’s desk, each Friday. Sign up for a free subscription here.

Source:: Computer World

By Ana-Maria Stanciuc Apple confirmed this week that it has acquired Israeli AI startup Q.ai in a deal valued at close to $2 billion, making it one of the company’s largest acquisitions ever, second only to the $3 billion purchase of Beats in 2014.  But check your assumptions: this isn’t Beats 2.0. There’s no new headphone brand to flex. Instead, Apple is paying top dollar for tech that might let your devices understand you without you ever saying a word. ​​These days we put our phones on silent so they won’t disturb us; soon the phone will put us on silent so it…This story continues at The Next WebOr just read more coverage about: Apple

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By Paulo Vargas Some blind and low-vision fans will use a Super Bowl tactile device that lets them feel ball movement on a tablet, with live Westwood One audio in headphones to keep every play in sync.
The post Super Bowl tactile device lets your hands follow the ball appeared first on Digital Trends.

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By Manisha Priyadarshini Researchers have developed a flexible AI chip thinner than a human hair that could allow future wearables to run intelligence on their own, removing the need for a constant connection to a smartphone.
The post A flexible AI chip thinner than hair promises smart wearables that work without a phone appeared first on Digital Trends.

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By Deepti Pathak Wobble Displays has recently introduced its latest range of smart TVs in India, including the X Series and…
The post Wobble Launches QLED X Series & 4K K Series TVs in India, Starting at ₹10,999 appeared first on Fossbytes.

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By Shikhar Mehrotra A leaked promo banner appears to confirm Samsung’s Galaxy S26 launch event for late February, aligning perfectly with months of industry rumors.
The post Samsung leak spoils the Unpacked date for Galaxy S26 series launch appeared first on Digital Trends.

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Brotli is one of the most widely used but least-known compression formats ever devised, long incorporated into all major browsers and web content delivery networks (CDNs). Despite that, it isn’t yet used in the creation and display of PDF documents, which since version 1.2 in 1996 have relied on the FlateDecode filter also used to compress .zip and .png files.

That is about to change, though, with the PDF Association moving closer to publishing a specification this summer that developers can use to add Brotli to their PDF processors. The hope is that Brotli will then quickly be incorporated in an update of the official PDF 2.0 standard, ISO 32000-2, maintained by the International Organization for Standardization.

With PDF file sizes steadily increasing, and the number stored in enterprise data lakes ballooning by billions each year, the need for a more efficient compression method has never been more pressing.

The pay-off for using Brotli compression will be smaller PDFs. This will translate into an average of 10% to 25% reduction in file size, depending on the type of content being encoded, according to a 2025 test by PDF Association member Artifex Software.

Unfortunately, for enterprises this is where the work begins. As PDFs written using Brotli compression start to circulate, anyone who hasn’t updated their applications and library dependencies to support it will be unable to decompress and open the new-format files. For PDFs, this would be a first: While the format has added numerous features since becoming an ISO standard in 2008, none have stopped users from opening PDFs.

The most visible software requiring an upgrade to support Brotli includes proprietary PDF creators and readers such as Adobe Acrobat, Foxit PDF Editor, and Nitro PDF. PDF readers integrated into browsers also fall into this category.

Beyond this, however, lies a sizable ecosystem of less-visible open-source utilities, libraries, and SDKs which are used inside enterprises as part of PDF workflows and automated batch processing. Finding and updating these components, often buried deep inside third-party libraries, promises to be time consuming.

If enterprises delay updating, then they risk encountering PDFs created using newer software supporting Brotli that will no longer open on their older, non-updated programs. IT teams will most likely come face to face with this when users contact them to report that they can’t open a file.

Building Brotli support

To kick off adoption, developers need encouragement, said Guust Ysebie, a software engineer with document processing developer Apryse. “Somebody has to jump first and make some noise so other products jump on the bandwagon,” he said.

It’s a challenge because, as he explained in a post about the move to Brotli on the PDF Association’s website, Brotli’s adoption has been slowed because the PDF specification requires consensus across hundreds of stakeholders.

The transition can be eased in three ways, he suggested, the simplest of which is to publicize the need to upgrade across multiple information sources as part of an awareness campaign.

A more radical suggestion is that Brotli-enabled PDFs could be formatted such that, rather than cause older readers to crash, they could show a “not supported” error message encouraging customers to upgrade as a placeholder for the compressed content.

A final tactic is for likeminded developers to take it upon themselves to upgrade open-source libraries. Ysebie said he’s added Brotli support to several libraries, including the iText SDK from Apryse.

“This is how adoption works in real life: Create the feature unofficially, then early adopters implement it, and this causes bigger products to also adopt it,” said Ysebie. The critical moment for adoption of Brotli-enabled software would be its appearance in Adobe Reader. This will happen at some point, but when is still unclear, he said.

The good news is that because there are only a limited number of software libraries to upgrade, adding support to this software should be straightforward, said Ysebie. However, organizations will still have to apply those updated images to their current applications.

As to when Brotli will be added to the ISO PDF 2.0 specification (ongoing since 2015), Ysebie agreed this has a way to go. But the industry had to move on from old technology at some point. “We need to push the ecosystem forward. It will be a little chaotic in the beginning but with a lot of potential for the future.”

Source:: Computer World