[This is a sponsored article with Synology.]

The cloud was supposed to eliminate infrastructure headaches. Instead, some businesses are discovering a new one: invoices they no longer understand.

Storage fees, data retrieval charges, and backup costs are quietly pushing cloud spending higher than many organisations anticipated—and artificial intelligence (AI) is about to make it significantly worse. 

It’s a challenge Taiwanese storage company Synology has been watching closely. 

At Computex 2026 in Taipei last week, the company argued that the economics of cloud-first infrastructure are beginning to shift.

The cloud bill that keeps growing

Businesses that moved enthusiastically to cloud-first infrastructure in the early 2020s are now sitting with bills that look nothing like the ones they signed up for. As costs continue to climb, some are reassessing whether keeping more data on-premise could make better financial sense.

The main catalyst is artificial intelligence. 

AI doesn’t just store data—it constantly accesses, moves, and processes it. Every inference call, every model training run, every search query is pulling data in and out of storage.

Gartner forecasts that more than 80% of enterprises will have deployed AI-enabled applications by 2026. And in a cloud environment, every one of those activities comes with a price tag.

From the start, cloud storage has been largely marketed on a simple figure: storage cost per gigabyte. Amazon Web Services S3 Standard, for example, runs at roughly US$23 per terabyte per month, with Google Cloud and Microsoft Azure in a similar range. 

For many businesses, the math looked straightforward. But what’s less visible is everything layered on top of that base rate.

Every time data is retrieved or moved—something AI workloads do constantly—cloud providers charge additional fees. 

On AWS, data egress starts from around US$0.09 per gigabyte transferred out. At scale, even restoring a 10TB dataset can quietly add about US$700 to the bill, before factoring in anything else.

Add API requests, cross-region replication, and backup-related charges, the total cost can be pushed up to four times the advertised storage rate. 

A Backblaze survey of more than 400 IT leaders found that 95% encountered unexpected cloud storage costs. And according to the Wasabi Global Cloud Storage Index, which surveyed 1,600 IT decision-makers globally, including 525 across APAC, 63% of organisations in the region exceeded their cloud storage budget in 2024. 

Businesses are bringing data back in-house

Amid rising costs, cloud repatriation—bringing data and workloads back from public cloud providers onto private or on-premise infrastructure—has moved from a niche IT discussion to a mainstream business decision. 

A 2025 Barclays CIO survey found that 86% of enterprise CIOs planned to shift at least some workloads back to private or on-premise systems, the highest level recorded. The Flexera 2025 State of the Cloud report similarly shows that 21% of workloads have already been repatriated, even as overall cloud spending continues to grow.

However, it’s important to note that most organisations aren’t abandoning cloud wholesale. 

Instead, they are taking a hybrid approach by keeping cloud platforms for global accessibility and collaboration, while bringing back workloads that involve heavy storage, protection, and processing. Backup and production storage are among the most commonly repatriated, as these are the areas where costs scale most quickly.

For Singapore businesses, there’s another factor at play: regulation. Under MAS Technology Risk Management guidelines and PDPA obligations, companies are expected to know where their data is stored and how it is being accessed.

That becomes harder in large public cloud setups, where data can be spread across multiple regions and servers. On-premise systems, by contrast, make it easier to keep track of exactly where information sits and who has access to it, since everything is managed within a company’s own infrastructure.

What Synology is bringing to the table

Synology is one of the companies building for this shift. 

The firm is best known for its Network Attached Storage (NAS) hardware—physical devices that store data locally while still functioning as a private cloud. 

At Computex 2026, it outlined how it is expanding its NAS ecosystem beyond storage into AI-enabled data management and backup infrastructure.

At the centre of this push is Synology’s next-generation DiskStation Manager (DSM), the operating system that powers every Synology NAS device.

The Taiwanese firm has spent more than two decades building NAS hardware and software. Today, it has shipped over 14 million systems worldwide, managing more than 400 exabytes of data. 

AI that stays in-house

At Computex 2026, the company announced the roadmap for the next generation of DiskStation Manager, DSM Agent 2.0, expanding it from a storage operating system into an intelligent data platform for governed, on-premises AI workflows. The goal is to turn DSM from a storage system into a smarter data platform that can support AI tools running on a company’s own infrastructure.

Instead of sending data to external cloud services, businesses can use their own data, such as files, system logs, and usage data, to power AI tools internally, while keeping everything under their control.

“The next generation of DSM leverages over two decades of expertise to create an AI-ready platform that keeps organisations firmly in control of their data,” said Philip Wong, Chairman and CEO of Synology.

Some AI features available include a conversational assistant for troubleshooting and system management. More advanced AI agents are also in development, designed to handle tasks such as email drafting, formula searches, meeting transcription, and real-time translation, although no release date has been announced yet.

As these capabilities expand, privacy becomes even more important in the age of AI. The system already includes a feature that masks sensitive data such as names, ID numbers, email addresses, and financial information locally before anything is sent to external AI providers like OpenAI or Azure AI. 

Future updates will go further, with support for fully on-premise large language models, where no data needs to leave the organisation’s infrastructure.

Synology’s infrastructure is already at work in Singapore

The value of on-premise data infrastructure is already clear for Singapore businesses using Synology. 

Food chain I Love Taimei, which has 17 outlets in Singapore, uses Synology’s DSM system to manage surveillance footage across all locations. This cuts management time by 65% and also allows the company to run AI-powered customer analysis without sending footage to the cloud.

LASALLE College of the Arts also uses Synology NAS for file storage and 4K video collaboration, allowing students and staff to access large project files easily across Mac computers without compatibility issues or rising costs.

Together, these examples show why some organisations are rethinking the assumption that everything belongs in the cloud.

Cutting backup costs without the cloud

The same push toward more controlled, on-premise infrastructure also extends to backup. At Computex, Synology introduced ActiveProtect Manager 2.0, a centralised backup system that will launch in Q3 2026.

The key issue it addresses is cost. Most backup services charge per server, virtual machine, or device. ActiveProtect instead charges for the hardware, with no extra per-workload fees.

In some cases, customers have seen a lower total cost of ownership. For example, Taiwanese media company Info Times reduced setup costs by 65% and cut storage needs by 75%. Toyota also reduced its backup data by 75% through better storage efficiency.

ActiveProtect 2.0 works with existing systems, so companies don’t need to replace their current setup. It also uses machine learning to detect unusual backup activity and help prevent ransomware infections from being restored. 

And because everything is stored locally, recovery is faster—taking hours instead of days—and there are no cloud data transfer fees.

The bigger picture

Cloud still has an important role to play, whether for global access, extra computing capacity, or supporting teams across different regions.

What’s changing is that businesses are becoming more selective about what they keep in the cloud. Rather than moving everything to a single platform, many are deciding where data should live based on cost, performance, and compliance requirements.

For Singapore businesses that have quietly accepted rising cloud bills as part of the cost of doing business, it may be time to take a closer look at the numbers.

Explore Synology’s solutions here. 

Featured Image Credit: Synology

In context: Anthropic’s latest release is really a story about control, not just capability. The company is offering two versions of the same underlying model: Claude Mythos 5 for a small circle of trusted partners, and Claude Fable 5 for everyone else. The split reflects a core challenge Anthropic is still trying to solve – how to deploy an extremely capable system into the wild without simultaneously handing attackers a new class of offensive tools.

Mythos has already shown what it can do when it is not heavily restricted. Since April, when an earlier preview was sent to about 150 organizations under the banner of Project Glasswing, users have reported more than 10,000 critical security flaws in their own systems. Those same capabilities could also be used by attackers looking to break in, rather than to patch security holes.

For that reason, Mythos 5 is staying behind the glass for now. Anthropic is keeping it in the hands of a “small group of cyberdefenders and infrastructure providers,” along with select biology researchers, and is coordinating with US government agencies as part of the rollout. Access is effectively on a need-to-know basis, with the company signaling that a broader “trusted access program” will come later.

Fable 5 is where Anthropic is testing what a general-purpose release of Mythos-class technology looks like under constraint. Technically, it runs on the same underlying model as Mythos 5, but with hard limits built in. The system is designed to refuse or redirect a long list of requests related to cybersecurity, biology, and chemistry. When those guardrails trigger, the query is silently routed to an older model, Claude Opus 4.8, instead.

Anthropic has also wired Fable 5 to watch for distillation, where a user tries to harvest large volumes of answers to train a smaller model of their own. If the system thinks that is happening, those requests are also redirected to Opus 4.8. In other words, the company is not only trying to control what the model will talk about, but also what others can learn from it.

Anthropic has been wrestling with these decisions for months. Diane Penn, the company’s head of product management, told Wired that testing and feedback since the April preview have helped shape the current strategy, even though it is still far from perfect.

“We’re trying to make improvements in a way that’s beneficial, even if we don’t have the perfect [solution] for every use case to start,” she says. “Out of all the different approaches, this emerged as the most viable and the best one. We just ended up feeling like this was the best product choice for users to get the maximum value out of Fable 5.”

For now, the filters are tuned to err on the side of over-blocking. Penn has acknowledged that some harmless queries will be routed to the older model. Anthropic says it wants to refine its classifiers over time but argues that this level of caution is the only way to justify a wider release at this stage.

The stakes are higher because Fable and Mythos are not just chatbots that respond to prompts and stop. Anthropic says both can run “unattended” for longer stretches than previous Claude models, carrying out sequences of instructions without constant supervision.

That shift toward more agent-like behavior could substantially boost software engineering and other technical work, especially given Fable 5’s stronger code generation and visual capabilities. But it also raises obvious questions about what happens if those capabilities are misused.

Anthropic’s pricing reflects how powerful it believes these systems are compared with its other models. Fable 5 and Mythos 5 cost $10 per million input tokens and $50 per million output tokens, roughly double the company’s other public models but still cheaper than the earlier Mythos Preview. The higher price reflects both the performance gains and the sense that these models are still positioned as specialized systems, not yet just another SKU in a growing catalog.

Around Anthropic, competitors are moving in a similar direction. OpenAI has rolled out its own advanced cybersecurity model to a small circle of partners and convened a working group that echoes Project Glasswing. Both companies are preparing for potential IPOs and are under pressure to show investors they can ship cutting-edge technology without triggering backlash over safety concerns.

Even some of the people watching from the outside say the unease is justified. Canadian finance minister François-Philippe Champagne told the BBC that public concern around Mythos stemmed from “it’s the unknown, unknown.”

Anthropic co-founder Jack Clark has made a similar point from the inside, arguing that the industry has not yet figured out how to slow itself down. “You want the option to be able to take your foot off the gas and put your foot on the brake,” he said. “Right now, it’s like the AI industry has a gas pedal, but it doesn’t have a brake pedal.”

Agent skills have become an important part of real-world AI applications, providing a mechanism — a set of instructions saved in a folder of text-based markdown (.md) files, usually — for models to adapt to specific enterprise use cases and complex workflows.

However, optimizing these skills is a slow process and faulty process, as they cannot be trained in the same way as the parameters of the underlying AI model. Instead, users typically must update them manually by retyping the instructions in each file, playing a “guessing game” as to what changes might improve agentic AI performance and reduce errors.

SkillOpt, a new, open source (MIT Licensed) framework developed by Microsoft, does one better: it introduces an optimizer designed for agent skills, turning the agent’s skill .md document as a trainable object that evolves based on performance feedback.

It uses deep-learning-style optimization to make it possible for the AI to systematically explore modifications to the document and find the best combination of instructions. Most importantly, it accomplishes this procedural adaptation without making changes to the underlying model’s weights.

On various industry benchmarks, SkillOpt outperforms existing baselines, significantly boosting accuracy for models like GPT-5.5 and Qwen. The result is a set of compact, transferable skill artifacts that allow AI agents to adapt to new domains effortlessly.

The challenge of optimizing agent skills

Agent skills package procedural knowledge into natural-language specifications, including domain heuristics, tool-use policies, output constraints, and known failure modes. These skills provide an external interface for agents to adapt to complex enterprise workflows. In practice, agent skills are stored as text documents and inserted into the agent’s context before execution.

One of the key benefits of skills is that they customize the behavior of the underlying model without changing its weights. However, the skill document itself needs to be tweaked and optimized to get the best performance out of the agent.

While deep learning relies on strict mathematical controls for stability, human prompt engineering often relies on trial and error. When attempting to automatically update a skill document based on feedback, the lack of mathematical discipline makes text highly volatile.

Yifan Yang, Senior Research SDE at Microsoft Research Asia, told VentureBeat that the problem is not making changes, but ensuring those changes are mathematically sound.

“The breaking point isn’t whether a team can change a skill, it’s that they can’t guarantee the change is an improvement,” Yang said. “Three failure modes recur: no step-size control, so skills drift; no validation, so a fix that reads as reasonable gets written in and can quietly regress performance; and no negative memory, so the same failed edit keeps coming back.”

To illustrate how easily performance can drop when edits aren’t mathematically validated, Yang noted that “an ungated rewrite pushed GPT-5.5 on SpreadsheetBench from 41.8 down to 41.1.”

According to Yang, these failure modes are amplified in multi-step workflows “because that’s where frontier models are weakest zero-shot. Not on reasoning, but on procedural discipline: format, self-verification, tool policy.”

Before SkillOpt, agent skills were primarily hand-crafted, generated in a single shot, or evolved through loosely controlled self-revision pipelines that could not reliably improve under feedback.

Prompt optimization methods like TextGrad and GEPA treat language artifacts as optimizable objects and use trajectory feedback to evolve prompts, but they focus on single-prompt configurations rather than generating persistent, reusable skill artifacts.

Meanwhile, skill evolution and discovery methods like EvoSkill and Trace2Skill convert agent execution experiences into trajectory lessons to refine skill folders, build domain-specific libraries, or perform evolutionary search.

None of them apply deep-learning-style controls, such as learning rates, validation gates, and momentum, which are necessary to continuously train a single, compact skill document.

Importing mathematical discipline to text

SkillOpt optimizes a text document through an iterative propose-and-test loop that separates the model executing the tasks from the model optimizing the skill. The process unfolds in several steps:

• SkillOpt starts with an initial skill document and a frozen target model (or harness), where the target model runs a batch of tasks to generate execution trajectories that act as the evidence for the current step.

• An offline optimizer model analyzes these trajectories, separating successes from failures into minibatches. Looking at a minibatch helps the model identify systematic procedural errors rather than one-off anomalies. Based on these patterns, the optimizer proposes structural add, delete, or replace edits to the skill document.

• The proposed edits are reviewed to filter out duplicates or contradictions, and the optimizer then ranks these candidate edits by their expected utility.

• Rather than applying all proposed changes, SkillOpt clips the list to a maximum edit budget for that step, generating a candidate skill.

• The candidate skill is evaluated on a held-out validation set using the target model. If the candidate improves the validation score, it is accepted and becomes the new current skill. If it fails, the edits are rejected and sent to a rejected-edit buffer, providing negative feedback so the optimizer knows not to repeat that mistake.

SkillOpt directly addresses the problem of treating text as a trainable object by importing mathematical concepts from deep learning. The creators note that “the deep-learning analogy is operational rather than decorative,” helping the framework avoid the instability issues associated with other optimization techniques.

The edit budget acts as a learning rate. By limiting how many edits can be applied at once, the skill version is prevented from moving too far from its previous state, preserving continuity while allowing new procedures to be acquired. 

Just like checking validation loss in deep learning, the strict held-out examples ensure that plausible-sounding text edits are only kept if they mathematically improve the agent’s actual performance on the validation split.

At the end of an epoch, SkillOpt performs a slow update by comparing tasks under the previous and current epoch’s skills. This acts like a momentum term, carrying durable, long-horizon procedural lessons forward while isolating them from the fast, step-level edits.

SkillOpt in action

To evaluate the technique in practice, researchers tested SkillOpt across different models, ranging from large-scale frontier models like GPT-5.5 to smaller closed and open models including GPT-5.4-mini and Qwen3.5-4B. They also deployed the skills within different execution harnesses, using plain chat as well as complex coding harnesses like the Codex CLI and Claude Code.

The evaluation spanned diverse industry benchmarks including single-round question-answering, multi-round code generation involving tool use, and multimodal document reasoning. SkillOpt was measured against multiple baselines ranging from a default no-skill setting to human-written skills and one-shot LLM-generated skills. It was also compared against advanced prompt-optimization and skill-evolution methods, specifically Trace2Skill, TextGrad, GEPA, and EvoSkill.

SkillOpt dominated across the board, proving highly effective on all 52 evaluated combinations of model, benchmark, and harness. It was particularly effective with frontier models, delivering an average absolute improvement of +23.5 points against the no-skill baseline on GPT-5.5. Furthermore, SkillOpt outperformed a hypothetical oracle baseline that cherry-picks the best competing method for every problem.

Small target models saw immense relative gains, proving that a compact text file can supply procedural knowledge that small models lack in their weights. For example, GPT-5.4-nano nearly doubled its score on multimodal document QA and tripled its score on embodied interaction and sequential decision-making.

These academic benchmarks map to critical enterprise pain points. Zero-shot models often hallucinate formatting or fail to use tools properly in multi-step scenarios. Yang explained that the biggest performance leaps occurred in operations that enterprises historically struggle to automate reliably.

“Document data extraction… exact figures out of contracts, invoices, and forms — AP automation, claims, compliance,” Yang said. “What improves is reliability: precise formatting, self-verification, auditable outputs. And the gains come from learning procedure, not memorizing answers.”

For enterprise practitioners, the true value of SkillOpt lies in its portability, efficiency, and compatibility with existing infrastructure. Experiments confirm that the framework is harness-agnostic. In addition to basic chat, the same optimization loop was successfully integrated into tool-backed execution environments like the Codex CLI and Claude Code with significant gains on industry benchmarks.

Developers can train a skill using one execution loop and deploy it in another. For example, a spreadsheet skill trained entirely inside the Codex loop was moved directly into Claude Code and drove a +59.7 point gain over Claude Code’s native baseline without any further changes.

SkillOpt artifacts also transfer cleanly across model scales. A skill optimized for GPT-5.4 was deployed onto the smaller GPT-5.4-mini and GPT-5.4-nano models with positive gains, proving that the learned procedures encode reusable workflows rather than just exploiting quirks of a specific model’s architecture.

Finally, the framework is highly efficient regarding token usage and context window real estate. Across all benchmarks, the final deployed skills never exceeded 2,000 tokens, with a median length of roughly 920 tokens. This results in highly readable, auditable artifacts that a human practitioner can review and manage in minutes.

Implementation strategies and the enterprise ‘catch’

For enterprise tech leaders, adopting a new framework requires understanding the overhead and limitations. While the research paper notes that training tokens can reach up to 210 million for academic benchmarks, the reality for day-to-day enterprise use cases is much lighter. The high token counts in testing were largely due to re-scoring massive held-out test sets.

“The real upfront work is the verifier and a representative held-out split. The optimizer is light; the evaluation harness is where the engineering goes,” Yang said. He added that for everyday use, “in community frameworks like GBrain, where SkillOpt updates run on Claude Sonnet, training a skill for a single task averages just $1–5.” This optimization cost is a one-time fee that amortizes completely at deployment.

However, the framework requires specific conditions to work effectively, namely a few dozen representative examples and a scorable feedback signal. Teams should avoid applying SkillOpt to open-ended or subjective tasks. “With no clean automatic scorer you have to design a human- or model-based evaluator and watch its stability,” Yang said.

SkillOpt also integrates smoothly with existing orchestration stacks, removing a major adoption hurdle. For instance, developers already using pipeline compilers can run both systems harmoniously. “DSPy is a different, complementary layer,” Yang said. “It compiles declarative LM pipelines and optimizes program structure; SkillOpt optimizes the external skill state a frozen agent loads. You can run them together.”

Looking ahead, open-source developers are already scheduling SkillOpt to run periodically over their agents’ past trajectories, creating a small ecosystem of self-optimizing code-agent plugins. This continuous feedback loop represents a significant shift in how AI systems adapt.

“The valuable version of self-improvement is an agent autonomously discovering knowledge to improve its own behavior and the user experience, under verification and audit,” Yang said. “Skills are the fastest, cheapest, most reversible first step, and the same mindset points toward agents eventually optimizing themselves, all the way down to their own weights.”

Photo credit: iFixit
iFixit engineers tore down the Trump Mobile T1 this week and put every layer to the test. The gold-finished handset drew plenty of early attention for its bold look and branding. What came out during the full examination showed a device that borrows almost everything from an existing model with only light cosmetic updates on top.

Advanced imaging equipment eventually revealed some obvious indicators. Scans of the interior configuration gave us a good idea of what was going on without necessitating disassembly. The inside layout was almost identical to the HTC U24 Pro, including component arrangement and board shape. The camera area received a few small adjustments, but the general design stayed the same. The engineers started by working on the back cover. One of the most significant changes was a larger flex cable for the flash to accommodate the repositioned module, although the rest of the connections, spring contacts, and surrounding hardware remained identical to the original HTC design. The aluminum chassis, on the other hand, had slightly different machined holes for the speaker grill, but the speakers were in the same spot and worked just as well.

Sale

Samsung Galaxy S26, Unlocked Android Smartphone, 256GB, Powerful Processor, Galaxy AI, Immersive Viewing…

• TYPE IT IN. TRANSFORM IT FAST: Enhance any shot in seconds on your smartphone by using Photo Assist¹ with Galaxy AI.² Add objects, restore details…
• MAKE IT. EDIT IT. SHARE IT: Turn everyday moments into something personal with creative tools built right into your mobile whether it’s a special…
• FAST. POWERFUL. AI-READY: Power through your day with AI-accelerated performance from our fastest, smoothest and most powerful Galaxy processor yet…

A deeper inspection of the mainboard revealed the same exact shape, screw positions, and anti-tamper stickers, showing that the entire assembly was identical to the HTC version. Engineers pulled the board from the T1 and installed it in an HTC U24 Pro body, and it simply worked. The opposite was also true: insert an HTC board into the T1 chassis, and everything worked as usual. The only notable difference was in memory, with Micron in one and SK Hynix in the other. Just one of several supply chain alternatives.

Both phones used the same CPU, the Qualcomm Snapdragon 7 Gen 3. On paper, the display sizes differed slightly, but the panels and mounting hardware were fully interchangeable. The wireless charging hardware, ports, and extension features were all carried over intact. However, the battery was a very other story. Capacity had increased to 19.35 watt-hours, but charging speed had decreased to 30 watts. No doubt because the HTC model supports faster 60-watt charging. The new cell features an insignia from the Philippines-based company Newlix Mfg Inc.

The HTC U24 Pro has a repair rating of three out of ten. This was partially due to a lack of official servicing instructions and spare parts. For the time being, the T1 obtained the same rating; however, no service documentation for that model was discovered. However, all of this brought further perspective. The majority of the components were standard off-the-shelf parts obtained from global manufacturers, with a significant amount of Chinese production mixed in. Although some final assembly occurred in Florida, the chassis, display, and the majority of the subassemblies were prefabricated overseas. The T1’s battery was manufactured in the Philippines, which is unsurprising. The device’s labeling indicate that it was manufactured in the United States, but in the end, it appears to be a standard issue device.

Klipsch arrived at High End Vienna 2026 with the kind of product lineup that reminds everyone why the brand still matters after 80 years: big horns, real wood, inspired design, unapologetic efficiency, and enough Heritage DNA to satisfy even a die-hard lover of vintage horn speakers.

Our 80th Anniversary Klipschorn and Klipsch/OJAS kO-R2 preview covered the two biggest attention-grabbers, while our separate Klipsch Rebellion preview focused on the new compact Heritage bookshelf speaker that may end up being the sleeper of the entire announcement.

On paper, all of these products sit in very different parts of the Klipsch universe. One is a tribute to Paul W. Klipsch’s original corner-horn loudspeaker. One is a design-forward collaboration with Devon Turnbull (a.k.a. OJAS). The third is a smaller-format Heritage model based on the rare 1958 H8 “Model H” design.

Seeing (and hearing) them all at the show, the message was pretty clear: Klipsch is not treating Heritage like a museum wing. These are real products that will find their way into real music lovers’ homes this year. They are inspired by the past, but use modern fabrication techniques and crossover designs to bring the performance beyond what was possible with the legacy products.

At around $2,700/pair, the Klipsch Rebellion may be the most interesting of the three from a real-world buyer perspective. It is the first compact bookshelf/stand-mount loudspeaker in the Heritage Series, and Klipsch says it traces its roots back to PWK’s rare 1958 Model H “H8” design, of which only 16 were made.

Paul W. Klipsch designed the Model H as a dedicated center channel speaker to fill in the gap between the company’s other speakers when they were spaced far apart from each other, in order to improve the imaging by providing a rock-solid anchor for vocals. That kind of backstory can become marketing fog very quickly, but the Rebellion has a more practical job: give Heritage fans a smaller horn-loaded speaker that does not require a dedicated listening room, reinforced corners, or a long conversation with a structural engineer.

Standard finish options for the Rebellion include American Walnut and Black Ash. To celebrate Klipsch’s 80th anniversary, a limited-edition Tigerwood finish will also be available (I wonder if the golfer gets a discount?).

At the other end of the room, the 80th Anniversary Klipschorn was pure legacy with new control under the hood. Limited to 280 pairs worldwide, the anniversary model updates the Klipschorn concept with an external active DSP crossover while retaining the essential corner-horn architecture that made the original one of the most recognizable loudspeakers in audio history.

With high extremely high sensitivity, the Klipschorn can be driven from a single ended triode tube amp, so the 125 Watts/Channel of the 80th Anniversary Onkyo Muse Y-50 integrated amp was more than enough to push these speakers to 110 dB+ reference levels with tight, extended bass and effortless detail. The speaker will be available for $25,000-$27,000/pair depending on finish options.

The Klipsch/OJAS kO-R2 pushes in a different direction, taking horn-loaded audio into the design and culture space without abandoning the efficiency and immediacy that made Klipsch famous in the first place. Designed in partnership with artist and noted audio DIYer, OJAS (Devon Turnbull), the kO-R2 was set up in Vienna outside the convention center in its own listening room, built into a storage container. Although that sounds spartan, it was actually a nicely air-conditioned storage container, treated quite effectively with comfy seats and sound treatments to keep outside sounds out (and inside sounds in).

The Klipsch/OJAS kO-R2 is a passive 2-way loudspeaker, featuring the OJAS 1506 Multisectoral horn. The speaker is handcrafted in Hope, Arkansas, by Klipsch artisans, and designed in collaboration with OJAS. The cabinet is built from 13-ply Grade A Baltic birch plywood. It houses the company’s K-33-E 15-inch woofer in a vented enclosure, crossed over at 760Hz to the K-706 high frequency compression driver, which is loaded on an exposed sand cast aluminum multi-sectoral horn. Features of the kO-R2 include anodized aluminum binding posts, anti-vibration rubber feet, an elegant engraved metal ID plate with serial number, and a five-step high-frequency high frequency gain attenuator.

The room had a cool, relaxed vibe as Devon himself spun some of his favorite tunes on vinyl and reel-to-reel tape with mostly home-made amplification gear powering a pair of the kO-R2 speakers. As with any great horn speaker, the kO-R2 produced dynamic, punchy sound that was particularly effective on drums and percussion, but also possessed the finesse to reproduce the delicacy of stringed instruments and human vocals.

The Klipsch/OJAS kO-R2 is available for sale exclusively on ojas.nyc at $11,995.pair. They are taking pre-orders now and expect to beginning shipping the speakers in August or September of this year.

Related Reading:

• TikTok and Instagram Reels now being used to target victims
• “Free” Spotify, Microsoft, Adobe subscriptions targeting cash-strapped users
• Social engineering is still the top vector, but basic account security measures do a lot of the heavy lifting

A new report from ReversingLabs is warning doomscrollers of videos spreading across short-form platforms like TikTok and Instagram Reels infecting users with password-stealing malware.

The videos typically promise free access to subscriptions like Spotify Premium, Windows, Office and Adobe – an instant, telltale sign that things might not be as they seem.

The bill comes months after Australia enacted a similar ban designed to make internet usage safer for young people.

Canada’s government has introduced Bill C-34, the Safe Social Media Act, which will prohibit young people under the age of 16 from using social media, with an exception made for platforms that meet specific safety standards. Another goal of the bill is to make AI chatbots safer by setting up a digital regulator to establish safety standards.

Minister of Health Marjorie Michel said: “Social media platforms and AI chatbots are designed to capture attention. They do not support healthy childhood development and have become a source of anxiety, isolation, depression and a range of other mental health challenges for many young Canadians. 

“The healthy development of our children begins with their physical and mental wellbeing, which is grounded in strong and healthy social connections. This legislation will provide a safer environment for young Canadians and empower them to connect in-person, build friendships, focus in school, and learn real-world skills so they can thrive.”

It could potentially take up to a year for the bill to pass and an additional six months to establish the digital regulator, additionally, the companies that fail to comply with the rules face penalties of 3pc of global revenue, or up to C$10m. 

The proposed legislation will make online services more accountable and transparent by introducing new safety requirements for social media services and AI chatbot services. This will include an age restriction, measures to reduce children’s exposure to certain content and high-risk interactions and regulated services will be required to identify, mitigate and address the risks on their platforms.

Marc Miller, the minister of Canadian Identity and Culture, with responsibility for Official Languages, said, “We have seen the very serious consequences that online harms can have. As technologies evolve, we must ensure our laws keep pace, because parents cannot face these challenges alone. 

“The safety of children cannot be an afterthought. This legislation will introduce stronger responsibilities for online platforms to ensure their services are safe by design and include appropriate measures to keep children safe.”

Canada is not the first region to consider limiting young people’s access to social media. In December of last year, Australia enacted the world’s first social media ban for minors under the age of 16, in a bid to bolster child safety. The ban affects Facebook, Instagram, Threads, X, YouTube, Snapchat, Reddit, Kick, Twitch and TikTok.

Other regions that have considered implementing changes include the UK and France and in November of 2025 the European Parliament proposed an EU-wide minimum age to access social media, video-sharing platforms and AI companions.

Don’t miss out on the knowledge you need to succeed. Sign up for the Daily Brief, Silicon Republic’s digest of need-to-know sci-tech news.

Bluetooth speakers have improved at a breakneck pace in recent years, with features like rugged weatherproofing, stereo pairing, longer battery life, and high-resolution wireless audio moving from premium luxuries to standard expectations. The best part? You no longer need to spend big to get them. Today’s best budget Bluetooth speakers deliver many of the same practical upgrades found in the best Bluetooth speakers you can buy, making great sound, durability, and everyday convenience far more affordable than they used to be.

That doesn’t mean all speakers are created equal, of course. As usual, sound quality is the great divider. What’s the point of saving big on a feature-packed speaker if you never want to listen to it? That’s why I tested every model for our Best Budget Bluetooth speakers list so vigorously, including long-term listening across dozens of models, to ensure the right pick for any scenario or environment. Wherever you go and whatever you’re into, you’ll find the right speaker at the right price below, without sacrificing features or performance.

Best Budget Portable Bluetooth Speakers of 2026

Best Overall: JBL Flip 7 ($150)

JBL’s Flip speaker series has long offered one of the best blends of sound quality, features, value, and sheer indestructibility you can buy, and the Flip 7 is another upgrade to the formula. At just over seven inches wide, it’s supremely portable, yet its 3-inch by 1.75-inch racetrack driver and 0.6-inch tweeter combine with efficient passive radiators on the sides for clear, punchy, and well-balanced sound across the frequency range. JBL has made subtle but effective refinements with each generation, resulting in better instrumental detail and improved clarity on the attack, with minimal distortion, especially with rock and pop.

The Flip 7 doesn’t mess around when it comes to features, offering stereo pairing with a second Flip 7, a companion app for EQ and other settings, up to 14 hours of battery life, or 16 hours with its bass-reducing Playtime Boost, and a drop-resistant design that I’ve thoroughly tested both on purpose and by accident. Upgraded IP67 weatherproofing keeps out dust and water, allowing for a quick dunk with no ill effects, while a quick-release strap and included carabiner provide versatile playback options.

Also new for the Flip 7 is Auracast, which allows it to sync with other Auracast devices and as many of JBL’s latest speakers, like the Charge 6 and Clip 5, as you can handle, though it no longer supports JBL’s Party Mode for connecting with older models. That point aside, the Flip 7’s slick mix of performance, usability, and a price that often falls to $100 or less makes it an easy choice as my favorite budget speaker around.

$149.95 $99.99 at Amazon | Best Buy | Crutchfield

Best Bang for Your Buck: Tribit Stormbox 2 ($80)

Tribit’s Stormbox 2 is the best-sounding portable speaker I’ve tested for the money. The budget brand, which seemed to come out of nowhere, has shown a knack for punching above its weight with multiple models, and the second coming of its baseline Stormbox stands tall with top tubular contenders like the JBL Flip, Ultimate Ears Boom, and others. You’ll find clean treble and impressive midrange gravitas from its multidirectional soundstage, and tapping the bass key ups the ante for a weighty yet controlled lower register. Apart from its tendency to distort more quickly at peak volume than pricier models, there are few reasons to pay more.

The Stormbox 2’s design borrows from the best, including a familiar tubular frame capped by dual passive radiators, grippy acoustic wrapping, and oversized playback keys for simplified control. The Tribit app provides convenient EQ and other controls, while battery life of up to 24 hours bests most speakers in its class. The speaker’s IPX7 weatherproof rating means it has no stated dust protection, so it’s not the best option for the beach, and its build quality feels a little cheap. Otherwise, it’s hard to find much to complain about in a speaker that sounds this good for $80 or less.

$79.99 at Amazon | Tribit

Best Micro Speaker: Sony SRS-XB100 ($65)

Sony’s mighty mini SRS-XB100 is among the most affordable and compact speakers in my Bluetooth arsenal, and I couldn’t imagine living without it. Smaller than a soda can and weighing just over half a pound, the XB100 sounds much bigger than its size suggests. The secret is in Sony’s efficient design, which includes a wide-dispersion driver up top that delivers balanced midrange and treble to fill out small rooms, along with a base-mounted passive radiator to help distribute decent upper bass from surfaces like tables and countertops.

The XB100 has a handy spread of features, including a built-in microphone for calls, IP67 dust and water resistance, one-touch Android connection, and stereo pairing with a second model. But the main reason I keep coming back to this speaker is its packability-to-performance ratio. From Honolulu to the Oregon Caves, I’ve taken this speaker everywhere, even using it on a recent family trip to San Diego as both our hotel soundtrack and the baby’s white noise machine. If you’re after a satisfying mini speaker that goes wherever you do, the XB100 delivers.

$64.99 $43 at Amazon | Best Buy

Best Super Cheap Speaker: JLab Go Party ($50)

JLab’s Go Party doesn’t sound amazing. Its topside light show reminds me of a rainbow version of Kmart’s blue light specials, and its ribbon-like handle feels decidedly budget. So why is this speaker on our list? Because its list price of less than a large pizza at my favorite takeout place makes it an insane deal for everything you’re getting.

While the audio can be inconsistent and fuzzy, choosing EQ3 in the JLab app provides solid balance and punch that’s particularly suited for pop and rock. The app makes it easy to shut down the lights, which extends battery life for up to 16 hours of playtime. Features like audio syncing with other JLab speakers and solid IP56 dust and water resistance help make up for the fact that there’s no charger in the box, and the handy volume dial up top is easier to use than any other speaker on our list. This is a budget model in every sense, but at $35 or less, it’s hardly a dent in your weekly budget.

$49.99 $34.34 at Amazon | Best Buy

Best Clip-on Speaker: JBL Clip 5 ($80)

I used to think most shower speakers were essentially the same, but the Clip 5 bests every budget hanger I’ve tried, including previous Clip models. With uncommonly full bass matched by a warm and detailed upper register, this speaker rises above bathtime fun to provide a solid soundtrack for hotel rooms, camping outings, and other adventures. Its treble could use more sparkle, but you’re still getting plenty of instrumental detail and depth, and when you lay it flat, a diffused rubber backside offers enhanced bass response without table rumble. Its slim design, at less than two inches thick, makes it easy to pack, while intuitive rubberized keys on the front and sides make it simple to control on the fly.

The Clip 5’s carabiner clip is sturdier than those on other models I’ve tested, providing a secure way to attach it in multiple scenarios, from your shower caddy to tree branches and backpacks. An IP67 dust and water resistance rating means it’s equally secure in wet or rugged environments, and you’ll get a decent, but not amazing, 12 hours of playback time at midrange volume. JBL’s app offers EQ and other settings, and Auracast connection lets you sync with an infinite number of newer JBL models, like the Flip 7. You can certainly find cheaper clip-ons, but if you want great sound for your hang, literally, this is the top option around.

$79.95 at Amazon | Best Buy | Crutchfield

Best for Bass: Soundcore Boom 2 ($130)

Soundcore’s Boom 2 mini boombox doesn’t offer the most articulate or cohesive sound for your money, but what it lacks in finesse, it makes up for with sheer gravitas. With up to 80 watts of power pushing a center woofer flanked by dual tweeters, this foot-long speaker gets loud enough to fill a midsize room or ramp up larger outdoor get-togethers. It also pulls more bass from your catalog than any other speaker on our list, especially with its “BassUp 2.0” button engaged, where the sound is at its best. Bass aside, you’ll get solid clarity up top, with surprisingly zippy transient response for rapid-fire percussion and a forward, if sometimes slightly hard-edged, push to midrange instruments like guitar, vocals, and piano.

There are some distinctive design traits here, including an easy-grip handle, a buoyant bottom that keeps the speaker afloat on water, and trendy LED grids on each side, customizable in the app with a rainbow of colors. Like the Tribit Stormbox 2, the Boom 2 offers solid IPX7 water resistance but no stated sand protection. Other features include adjustable EQ, phone charging via its protected USB-C port, an onboard mic for calls, and battery life of up to 24 hours per charge, though that takes a hit when you engage the bass boost and/or light show. This is a fun little budget boombox that isn’t designed for critical listening but provides plenty of power at a nice price, especially on sale.

$129.99 $99.99 at Amazon | Best Buy

Best for iPhone: Beats Pill ($150)

The original Beats Pill never won me over with its muddy, bass-forward sound signature, but following Apple’s acquisition in 2014, the Beats sound has undergone a major transformation while still keeping the hallmarks that made it a hit. That’s utterly evident in the Pill’s second coming, which keeps the brand’s signature brash and vivacious “smile” curve of accentuated treble and bass while providing clear-cut detail and rich instrumental textures for a fun sonic ride. This speaker gets loud, with a low register that rumbles through floors, picnic tables, and other surfaces to spawn mobile dance parties wherever you take it.

While the metallic front screen isn’t as drop-friendly as armored rivals like the Flip 7, as evidenced by the dents I gave it during a ride down the stairs, you’ll get stout IP67 dust and water resistance, features like a built-in speakerphone, high-resolution audio support and device charging over USB-C, and even Find My support with iPhones. Up to 24 hours of battery life keeps you grooving off the grid, and Class 1 Bluetooth provides around 130 feet of range, counted with careful footsteps on my front walk. Without EQ, thanks, Apple, the forward treble is a little overexposed on some tracks, but the Pill’s elegant looks, big sound, and long list of features make it a great buy, especially now that it’s often available for around $100.

$149.95 $99.95 at Amazon | Best Buy

The Bottom Line

Bluetooth speakers have gotten incredibly good at increasingly lower prices. You no longer need to choose between value, quality, and durability; you can get it all in one model. But you’ll still want to choose from well-reviewed options from established brands that put sound and features first.

Other models we tested and considered for this list include the Sony ULT Field 1, Tribit Stormbox Flow, JBL Flip 6 (and the older Flip 5), Ultimate Ears Boom 4 (and older Boom 3), JLab Pop Party, JBL Go 4, Skullcandy Kilo, and Soundcore 3. We also tested our top picks against pricier options like the UE Megaboom 4, JBL Charge 6, and Bose SoundLink Plus.

If you’re only going to pick one speaker, I always point folks to my favorite all-rounder, the JBL Flip 7, first, but there are plenty of reasons to grab something else on our list. At these prices, it’s even worth considering at least one backup, like the micro-sized Sony SRS-XB100, the shower-friendly Clip 5, or a super-cheap model like the JLab Go Party, to throw in your trunk for adventures. The budget Bluetooth category has never been better, so it’s a great time to save big on sound without sacrificing convenience.

Related Reading:

Right on the red carpet at the Toy Story 5 world premiere in Los Angeles, Porsche presented three fully functional one-of-a-kind 911s. Each emerged from the Sonderwunsch special wishes program as a rolling embodiment of a main character from the upcoming film. Porsche worked closely with Pixar designers Bob Pauley and Jay Ward to translate the characters into metal, paint, and leather. This project follows their earlier collaboration on a Sally-themed 911 from the Cars movies.

Porsche picked a 911 GT3 RS with the Weissach package for the Buzz Lightyear vehicle, which was one of the model year’s final specimens and most likely a one-of-a-kind sendoff. The exterior is painted in a brilliant white, but that isn’t the only thing that stands out. Green Yellow and Lizard Green accents occur on the front lid, roof, fenders, door bottoms, and wing endplates, paying reference to the space ranger uniform. The rear wing is almost as fantastic, as it even looks like Buzz’s pop-out wings, with a few white stripes and Fire Red trim on the lower section, as well as sporty Light Sport Grey struts. The wheels have customized centercaps with the Space Ranger logo on a splash of white magnesium, and the custom Goodyear tires have Lightyear written in the sidewall language, along with a few Easter eggs that elegantly tie back into the link.

Sale

LEGO Ideas Disney Pixar Luxo Jr. – Room Decor and Building Set for Adults – Office and Desk Decor for…

• ANIMATE YOUR MEMORIES – Adults, ages 18 and up, can recreate playful Luxo Jr., the iconic lamp character from Disney Pixar’s 1986 animated short…
• LEGO IDEAS EXCLUSIVE – A fan-designed set created by the LEGO community, voted for by passionate fans and produced by the LEGO Group
• FULLY POSEABLE MOVIE ICON – An intricate, articulated design helps builders recreate Luxo Jr.’s unique bouncing, hopping, and rotating movements

Inside, Pebble Grey leather and Arctic Grey Race-Tex dominate the cabin, but there’s also green stitching and Lizard Green seat belts, which are a nice touch. Violeta leather covers the top seat sections. Bob Pauley created a unique Buzz Lightyear graphic for the dash, as well as a one-of-a-kind inscription that defines this vehicle. The options list covers all of the basic factory features, including a front-axle lift, carbon ceramic brakes with black calipers, and an extended-range fuel tank.

Jessie served as the inspiration for Porsche’s second Toy Story 5 vehicle, a 532-hp 911 Targa 4 GTS. They created a new paint color, Jessie White Metallic, which is a pearl white designed specifically to match her western shirt buttons. The bottom sections, front and back fascias, and rockers have been painted 944 Cobalt Blue Metallic to match her clothes. The hood and rear deck lid are painted Atacama Yellow with GTS Red pinstriping along the length of the sides, which is a nice touch. Even the side mirrors get a dose of GTS Red. The red Targa top with light beige piping resembles Jessie’s cowboy hat. The customary writing appears on the rollbar, but it has been replaced with the word “Jessie” in the Porsche typeface, while special gold wheels complete the exterior design.

Inside, they’ve mixed some appealing trim hues, including Dark Night Blue, Bordeaux Red, and Pebble Grey leather. That’s not all; the seat and door panel centers are upholstered in a specially designed denim-look fabric created for both the Jessie and Woody vehicles. The floor mats, with their trendy black-and-white cowhide design, complete the look. The door sill guards light up with “YEE HAW!” writing, and one headrest bears a sheriff symbol, while the center armrest bears a Woody’s Roundup WR emblem. The premium package, night vision aid, PDCC, and heated GT sport steering wheel are all factory extras.

The Woody car features a 911 Carrera T in a one-of-a-kind Dark Sea Blue finish, which Porsche achieved by essentially squishing denim fabric into the paint to create tremendous texture and an old, faded blue jeans impression. The lower trim and rocker panels on the front of the car are Coffee Black, while the front spoiler lip is Aurum, a fancy gold tint. Then there’s the Fire Red pattern that runs around the bottom of the doors, with the “Woody” logo standing out very well. A pair of custom black and gold wheels completes the design and provides some extra oomph.

For the first time, Porsche has used brown vintage leather that has been wrapped all over to offer that timeless, been-around-for-years look. The decor is Dark Night Blue leather with Cognac stitching, and the seats feature small Speed Yellow accents and door panel emblems with a red checkered pattern straight out of a toybox, reminiscent of Woody’s clothing. Oh, and you’ll get the same denim as the front seat centers. The drivers also get floor mats in the same cowhide style as the Jessie car, which is a nice touch. The door sills light up in honor of Woody’s motto, “Ride Like the Wind.” Factory options include an expanded fuel tank, sports exhaust, sports front, front lift, rear seats, Burmester audio system, and memory seats.

Porsche’s Sonderwunsch crew gave each of the three cars their entire attention (with help from Disney and Pixar, no less) to produce these hand-crafted bespoke beauties, which are crammed with all sorts of delightful subtle references for any Toy Story fans who know where to look. How cool is it that all revenues from their sale will support Big Brothers Big Sisters of America, the American Red Cross, and the Starlight Children’s Foundation? Toy Story 5 will hit theaters on June 19, following its global premiere on June 9, 2026.