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There is something poetic about quantum computing.

For decades, it has lived in the realm of possibility, whispered about in academic corridors, hyped in boardrooms, and misunderstood almost everywhere else. It promised to change everything, and yet, for the longest time, changed very little.

Until now.

Not because quantum has suddenly “arrived” - it hasn’t. But because the world around it has finally caught up.

We are, quietly, entering the age of hybrid intelligence, where classical computing, artificial intelligence, and quantum systems begin to work together. And that changes the question from “when will quantum matter?” to something far more interesting: What happens when quantum becomes part of how the world works?

From magic to mechanics

Quantum computing has long suffered from a branding problem.

It was either considered “Magic” because it would solve everything instantly; or a “Myth” because it was perpetually 10 years away!

The reality, as always, is more nuanced and much more powerful.

Quantum computers are not general-purpose machines; they are specialists. They are exceptionally good at specific classes of problems like optimization at massive scale, molecular simulation, cryptographic analysis, complex probabilistic modelling etc.

However, they are also fragile, error-prone, expensive and dependent on classical systems for almost everything else around them!

This leads to a simple but profound insight: Quantum will not replace classical computing. It will collaborate with it.

And that collaboration is where the real revolution begins.

The quiet role of AI

Ironically, the biggest accelerator for quantum computing hasn’t come from within the field itself. It has come from artificial intelligence.

AI has created the conditions for quantum to matter in three critical ways:

1. Made complexity usable - Quantum algorithms are not intuitive. AI helps design, optimize, and even discover them.
2. Improved error correction - One of quantum’s biggest challenges is “noise”. AI is now being used to stabilize and correct quantum systems in real time.
3. Created demand - AI has exposed the limits of classical computing—particularly in energy, consumption, and scale. Quantum is no longer a curiosity; it is a necessary complement.

What’s actually working (and what isn’t)

To understand the current state of the industry, we must separate the signal from the noise. First and foremost, what’s working is “Hybrid Workflows”. The hybrid architectures where classical systems prepare the problem, quantum executes the core computation, and classical systems interpret this result.

This is where real-world use cases are emerging.

Second, progress seems to be very domain specific as quantum is showing promise in areas where complexity explodes – drug discovery, materials science, logistics optimization, financial modelling etc. So, it’s not universal, but selective and meaningful.

Finally, ecosystems are forming. A new stack is emerging. Companies like IBM, Google, and Microsoft are building integrated quantum platforms, while hardware innovators like IonQ and Quantinuum push the boundaries of qubit fidelity.

What’s isn’t working ...yet

Fault tolerance at scale needs to evolve more as we’re still far from fully error-corrected quantum systems. Also, most enterprises are still only experimenting and not deploying quantum solutions at scale.

There is no “Windows moment”, or universal standard for quantum yet; every stack looks different.

And, perhaps most importantly, quantum still requires translation, from physics to business value.

A global race… with no clear finish line

Quantum computing has become a geopolitical priority. The United States is investing heavily through public-private partnerships; China is accelerating both research and infrastructure at a massive scale; and the UK and Europe are focused on Sovereign Quantum capabilities - ensuring they aren’t reliant on foreign stacks for critical security.

They are protecting their intellectual property more fiercely than they did with the internet.

This is not just about computing. It is about economic advantage, national security and scientific leadership.

And yet, unlike previous technology races, this isn’t winner-takes-all. Quantum systems will not exist in isolation. They will exist in networks.

Different players are taking fundamentally different approaches as the hyperscalers are positioning quantum as a “cloud-accessible capability”, as they abstract complexity and integrate with existing workloads.

But, as I have gone around the world talking to CEOs of various quantum companies, I am fascinated by what I call the “Plug-and-Play innovators”:

• Hardware pure-plays: Companies like IonQ and Quantinuum focus on hardware breakthroughs - trapped ions, new materials, and improved qubit fidelity. Their bet is that that “if we solve the physics, everything else follows.”
• The bridge builders: Firms such as Zapata AI and QC Ware are building the bridge between algorithms and applications. Their belief is “Quantum without software is just expensive physics.”

And then there is the gap. No one truly owns the interconnections between quantum and classical systems, nor the orchestration of the hybrid workloads. The missing layer is a neutral ecosystem where these players converge.

That gap will define the next phase of adoption needed for this to truly scale.

What this means for society

Quantum’s impact will not be immediate, but it will be profound.

Healthcare: Simulating molecules at quantum precision could accelerate drug discovery from years to months.

Climate: Optimizing energy grids and materials could unlock more efficient batteries and carbon capture.

Finance: Risk modelling and portfolio optimization could reach entirely new levels of sophistication.

Security: This is my personal passion. While quantum has the potential to break current encryption standards, it is also driving the development of Post-Quantum Cryptography (PQC), making systems more secure in the long run. We must act now to prevent "Harvest Now, Decrypt Later" attacks, where encrypted data is stolen today to be cracked by quantum computers tomorrow.

A slightly uncomfortable truth

Quantum computing will create as many questions as it answers.

• Who gets access first?
• Who controls the infrastructure?
• How do we ensure equitable benefit?

We have seen this movie before with the internet and AI.

The difference this time is that we have the opportunity to design the system more deliberately.

Quantum has been “almost here” for decades. So, why does this moment feel real?

Because AI has created urgency and demand; infrastructure has matured to support hybrid models; and ecosystems are forming, not just technologies.

This is no longer about a breakthrough machine. It is about a connected system of capabilities.

A more human way to think about quantum

Perhaps the simplest way to understand quantum is this:

• Classical computers think in straight lines.
• AI learns patterns from data.
• Quantum explores possibilities simultaneously.

It is less like a calculator and more like imagination. And like imagination, it is most powerful when guided.

So, what should we do now?

For enterprises, start experimenting with hybrid workflows now. Focus on use cases (optimization, simulation), not just the underlying physics, and build internal understanding early.

For policymakers, invest in open ecosystems, prioritize standards and interoperability, and balance competition with collaboration.

For technologists, think beyond silos and design for integration, not isolation. For the rest of us, stay curious.

Quantum computing will not change your life tomorrow, but it will quietly reshape the systems that your life depends on.

Closing thought

We often think of technological revolutions as moments.

In reality, they are transitions. Messy. Gradual. Non-linear.

Quantum computing is not a single breakthrough waiting to happen. It is a shift in how we solve problems; one that will unfold over years, across industries, and in ways we cannot fully predict.

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• Topping has unveiled its new and compact desktop DX1 II DAC
• It's relatively affordable at £119 (about $160, AU$240)
• Multiple inputs and outputs, some clearly designed for gamers

If you've been considering buying one of the best headphone DACs, it's probably because you want to connect them to an audiophile-friendly hi-fi system — or even to your phone or dedicated music player on the commute. But Topping's latest option aims squarely at a very different audience: gamers.

The Topping DX1 II is a new piece of kit which is slowly being released in different regions; it's just been released in the UK from Electromod. It costs £119 (about $160, AU$240), so it undercuts many other options save for models built specifically for smartphones or digital audio players.

The DX1 II seems to have a specific user in mind though. The DAC is designed for all budget-conscious, audiophile-curious buyers, but it does feel aimed at gamers more than most. And that is thanks to a few key considerations that seemingly make it a good pick for enhancing your games' sound.

For example, while the DAC has two headphone outputs (3.5mm and 4.4mm), they're two-way, so you can use headsets with microphones. It can also switch between USB Audio Classes, allowing you to use it alongside the Nintendo Switch and PS5 which are some of the few gadgets only using UAC 1.0.

A DAC is for life, not just for gaming

Despite some gaming features being the headline tools, the Topping DX1 II seems to be a solid all-rounder too — and given how much we loved the larger and more expensive Topping DX5 II, it's well worth taking a closer look.

The DAC can input from USB-C as well as optical, and output to optical, stereo RCA, 3.5mm or 4.4mm. There's support for 32-bit/384kHz PCM and DSD 256, so high-quality audio won't be a problem. There are also EQ tools as well as filter and gain settings.

A built-in amp can deliver up to 1,000mW audio, and since it's quite compact at 10x10x3.2cm, it'll fit into various existing set-ups — and that glossy white casework will make it look right at home next to a PS5.

As a prolific gamer, I'm not sure that I can see a DAC being crucial to a hardware set-up — although I absolutely recommend any one of the best wired gaming headsets. That said, the Topping is still very useful as an affordable entry-level DAC for my music that can get double use for gaming.

While there are several AI image and video generation tools on the market, InVideo differentiates itself by carving out a dedicated niche. Built from the ground up for creative teams, filmmakers, and professionals, InVideo offers the easy-to-use conversational AI Agent One, which helps you create highly professional videos using simple English instructions. This is probably why it's trusted by teams at Netflix, Nvidia, Meta, LinkedIn, and Google.

In this article, we put InVideo to the test to see if it lives up to its claims. Read on as we try out its top features and evaluate its pricing, ease of use, and compare it to the best AI video editors to help you find out if it's the right choice for your needs.

InVideo: Plans and pricing

You can check out InVideo by clicking here.

InVideo offers as many as four individual plans and two plans for teams and enterprises. One good thing about InVideo is that all of its plans come with access to more than 200 AI models, including Seedance 2.0, Veo 3.1, Nano Banana Pro, ElevenLabs Music, and Kling 3.0. Plus, every plan includes all the features that InVideo has to offer, the only difference is the usage limits.

The paid plans start at $17 per month (Plus plan), which comes with 75 credits per month. Here, you get 20 GB of storage, access to 100 iStock assets, and four AI avatars and voice clones. The next plan, priced at $85 per month (Max), comes with 390 credits, 16 AI avatars, 100 GB of storage, and access to 200 iStock assets.

(Image credit: InVideo)

The next two plans let you choose the number of credits you want. For instance, the Generative plan starts with 800 credits per month at $170 per month and goes all the way up to 8,000 credits for $1,700 per month. Here, you can create 40 AI avatars and voice clones, along with 2 TB of storage and access to 1,000 iStock assets (800-credit plan).

Lastly, the Elite plan, meant for individuals with large AI generation and editing needs, starts at 4,250 credits per month for $900 per month and goes all the way up to 42,500 credits per month for $9,000 per month. Here, you can create 200 AI avatars, get 10 TB of storage, and access up to 5,000 iStock assets (4,250-credit plan).

For businesses, there are two plans: Team and Enterprise. The Team plan starts with 160 credits per seat per month at a cost of $40 per month, while you'll need to contact InVideo's sales team and book a demo to receive custom pricing for its Enterprise plan.

As is evident, InVideo is one of the more expensive AI generation and video editing tools out there. Even its Max plan ($85 per month) is significantly more expensive than the highest-tier plans of competitors like Veed, Kapwing, Fliki, and Filmora.

Moreover, InVideo also offers a free plan with limited credits, allowing you to test out the platform's capabilities. However, the free plan is fairly limited compared to competitors like Filmora and is best suited for testing the platform rather than using it on a full-fledged basis.

InVideo: Features

Although InVideo commands a high price, there's a good reason for it. You can generate AI videos and images with InVideo, just like any other AI generation tool. InVideo calls this its Autopilot feature. However, the problem with one-time generation is that the context gets lost after a few back-and-forth edits.

By the time you're on your fifth or sixth edit, your character may have changed entirely, and the scene is nothing like what you initially wanted. This is a problem common to almost all AI generation tools on the market.

This is where InVideo's all-powerful Agent One comes into the picture. Designed for filmmakers and high-end marketing professionals, Agent One is a full-fledged AI assistant that can not only generate images and videos for you, but also remember the context of your scene and create professional, cinematic short videos and even full-length short films (more on that later).

(Image credit: InVideo)

Additionally, InVideo has an extensive collection of workflows, which are templates you can choose from to get started on a new project.

These include explainer videos, animated videos, script-to-video, promos, advertisements, listicle videos, faceless explainers, educational videos, and more.

You can also create animated videos in different styles, such as Disney Pixar-style, claymation, Lego, anime, and more.

(Image credit: Future)

Plus, you'll find a new Trends feature in InVideo that keeps you updated on the latest trends in video creation. This includes camera controls, effects such as Split Self and Drip Flip, as well as motion graphics like Highlight Typography and Glass Motion Graphics. There's also a dedicated Advertising Studio that lets you create high-end professional ad videos for any product of your choice in different styles.

InVideo: Interface and in use

Despite its high-end, professional features, InVideo is surprisingly easy to use, making it beginner-friendly. Its Agent One is as easy to use as a conversational AI.

You first have to provide it with a treatment, which is nothing but your idea, vision, or script, including the context of the video you want to generate. This can include character descriptions, environments, buildings, and a beat-by-beat story timeline.

The heart of Agent One is its Context tab, where you can provide additional details about your project. You'll find various content options under this tab, including About This Project, where you'll add the context of your video, its script, and the ultimate goal.

(Image credit: Future)

Then there's InVideo Rules, where you can enter standing instructions on the pacing or format of your video, along with the tone and specifications of the characters you want to use. There's also a dedicated World Building tab, where you can describe in detail the visual language, settings, and continuity you want to maintain throughout your video.

You can also upload images, references, research, briefs, and scripts in the Inspiration and Knowledge Bank tabs.

Unlike other AI generation platforms, which aim to keep your prompts as short and direct as possible, Agent One encourages you to be as detailed as possible. The more context and detail you provide, the better your output is likely to be.

Besides this, you can also select the layout of the video you want. InVideo gives you many more options than some of its competitors. For instance, you can choose between square, extra tall, portrait, landscape, and more. Plus, you also have a choice of output resolution, ranging from 1K to 4K.

(Image credit: Future)

Overall, the experience is similar to that of a director sitting in a chair talking to a creative team. The only difference is that everything is packed into a single AI agent.

InVideo: How we tested

We reviewed the breadth of InVideo's capabilities. In particular, we tested its Autopilot feature, which lets you create videos with a single prompt. We gave it the same prompt that we used while testing the other AI video editing software:

"A woman in a red coat walks across a rain-soaked city street at night, neon signs reflecting in the puddles, camera slowly tracking alongside her."

One thing to note is that before generating a video, InVideo gives you a lot of options to customize your output. This includes selecting the duration of the video as well as the platform you're generating it for, such as Instagram Reels, YouTube, or TikTok.

(Image credit: Future)

There's also a hidden Additional Options button in the bottom-left corner, where you can customize settings such as visual styles. You also get an option to choose an AI character from InVideo's free AI actors.

When we had everything in order, we hit the Generate button.

Now, InVideo takes arguably the longest time to process a project and generate an output, noticeably longer than the likes of CapCut or Veed. However, the outputs are worth the wait. InVideo created a pretty realistic-looking Instagram Reel of a woman walking on a rain-soaked street.

(Image credit: Future)

Besides this, we also tried using InVideo's Agent One, giving it the same prompt. Although it did create various character options for us in different styles, we couldn't proceed further because it required more credits than the free plan offered.

(Image credit: Future)

However, Agent One's conversational-style editing makes it pretty simple to use. You just have to write down what you're thinking, and Agent One processes your thoughts into a clean script, building each scene bit by bit.

InVideo: Alternatives

InVideo is designed for professional filmmakers or large enterprises that need to create realistic, professional AI videos. If you're looking for a simple video editing software simpler, you could opt for a tool like Veed, which is one of the most complete AI content generation and editing platforms.

With Veed, you also get access to various AI models such as Seedance, PixVerse, and Veo 3.1, which can generate text-to-video, image-to-video, as well as more than 60 diverse AI avatars.

Veed also has one of the best subtitle offerings on the market, keeping up with the latest social media trends. That said, its free plan is a bit limited in what you can do, which is why you'll likely have to upgrade to one of its paid plans, starting at $12 per user per month.

If you're looking for something more affordable, you can go with Filmora. It starts at just $4.17 per month, and even its highest-tier plan costs only $8.33 per month. Filmora is also a professional-level video editing platform that has recently integrated a wide range of AI features into its repertoire.

You get access to more than 2.9 million creative assets, including filters, transitions, effects, music, and stock media. It has also introduced advanced AI features such as AI Audio and Video Extender, which can extend short audio clips and videos for smoother transitions.

There's also Animated Charts and Lens Correction, which come in handy while editing action camera or wide-angle footage. Plus, you get more than 10,000 ready-made templates and over 500 AI-powered effects.

However, Filmora is one of the more difficult tools to use and comes with a bit of a learning curve. Once you get the hang of it, though, it is one of the best tools available for AI-powered video generation and editing.

InVideo: Final verdict

InVideo is a professional-level AI generation and video editing tool designed for filmmakers, advertisers, and professionals working in the creative industry. It offers access to more than 200 AI models, including Veo 3.1 and Nano Banana Pro.

InVideo comes with the powerful Agent One, a conversational AI that not only generates AI videos and images for you, but also works back and forth with you to create highly realistic, cinematic short videos.

Moreover, Agent One is surprisingly easy to use, almost as easy as conversing with a creative director and giving instructions. The best part is that you're not stuck engineering prompts to get the best output. Instead, you can focus on the creative aspects of your project while Agent One handles the rest.

That said, InVideo is one of the most expensive tools out there, with plans starting at $17 per month. If you're looking for something more basic or affordable, you can consider alternatives like Veed, Adobe Firefly, or Filmora.

We've tested a range of video makers and editors, including the best video editing software, the best video editing apps and the best free video editing software.

• Leather jacket belonging to Nvidia CEO Jensen Huang sells for $960k, way above the $40-60k estimate
• Huang's jackets have become a tech sector icon and a staple CEO 'uniform' piece
• The proceeds wil help fund fellowships and more across tech

A black Tom Ford leather jacket worn and signed by Nvidia CEO Jensen Huang has sold at a New York auction for $960,000.

"The response to this sale surpassed even our highest expectations," Sotheby's head of modern collectibles Brahm Wachter explained, with the jacket selling for around $900,000 more than auctioneers had anticipated, given the auction house's estimate of $40,000 to $60,000.

The jacket itself – one of many that the CEO has owned, of course – has become a staple recognized by the entire tech sector, with Huang rarely spotted out in public wearing anything else.

Jensen Huang's jacket sold for $0.9 million

This specific jacket came from Tom Ford's Spring-summer 2023 collection, however the CEO has been wearing similar jackets for years, leading similar examples to have become essential parts of any Nvidia keynote or tech conference.

Huang is one of a growing number of CEOs who have chosen uniformity and simplicity in their clothing – Mark Zuckerberg's blue jeans and grey t-shirt, and Steve Jobs' black turtleneck, also become similarly iconic.

Independent verifiers are said to have confirmed both the jacket's authenticity and the signature's authenticity, revealing that it was worn by Huanh at the 2023 Foxconn Tech Day.

Clearly, it being Jensen Huang's jacket is the core reason why it fetched nearly $1 million at auction. His company, Nvidia, is somewhat of an AI success story, having risen from a valuation of around $300 billion in 2020 to $4.9 trillion today.

At the time of writing, Nvidia is the world's most valuable companies, just a reach ahead of Apple - with the $940,000 cost buying you around 4653 shares in the company at today's market price.

The proceeds are set to help fund Edge Institute, a nonprofit that will support fellowships, grants and residencies across the tech sector.

Via CNBC

The U.S. attacks were the ninth consecutive day of bombing since peace talks between the two countries collapsed in dispute over a memorandum of understanding focused on the Strait of Hormuz.

(Image credit: Atta Kenare)

The “AI” label no longer makes companies special. In today’s world, that is a fact that needs to be accepted.

Even just a year ago, if a business simply mentioned being “AI-powered” it was enough to immediately gather attention and appear innovative. Investors quickly grew excited, and media outlets were quick to pick up the next “hot story.”

Of course, that didn’t always mean that there was truth to such statements. The concept of AI washing — when companies misrepresented or even outright lied about the use of AI tools in their operations — had certainly done its share of damage to this industry while it stayed prevalent.

But today, even without such lies, the effect of AI novelty is disappearing. Every fintech company now has some kind of AI story. Compliance platforms use AI monitoring. Banks and fintechs talk about AI-driven service personalization. Chatbots and AI assistants are utilized practically by every other platform, no matter which industry we look at.

At this point, saying your company uses artificial intelligence feels almost the same as saying you have a website. People have learned to expect it almost by default. And this creates a very different communications environment.

The first wave of AI companies mostly had to convince their audience that the technology was possible. That task has certainly been accomplished. Now, the second wave faces the task of convincing people that their particular implementation of AI is trustworthy, useful, and worth the attention in a market that’s beyond overcrowded already.

That is much harder.

The conversation has changed

AI investment has exploded over the last two years. Enterprise spending on gen AI jumped from $11.5 billion in 2024 to $37 billion in 2025. That’s a whole 220% YOY increase. AI-focused startups continue to dominate venture capital conversations, to the point where nearly every technology company now feels the pressure to position itself as part of this race.

But something else happened along the way: consumers became more educated. If at first, AI sounded like something magical, now people have actually used it. They have seen hallucinations and strange outputs, and they’ve dealt with incorrect recommendations. They’ve had time to realize that AI can be useful, but also that the technology comes with its own frustrations and limitations.

As such, being “AI-powered” is no longer enough to stand out. Consumers have already moved past that stage. One of the biggest mistakes I see today is when companies still assume they have not.

Now, the conversation revolves around a much deeper point: “What does your AI actually improve for me?” For AI-focused companies vying for attention, the benefits of their specific approach are now the key battlefield where they have to win.

This is particularly important for financial and fintech companies, because financial services are built on trust. People may tolerate or even find humor in mistakes from an entertainment app, but they will not be pleased when their money or personal data are put at risk because of AI malfunctions.

The numbers clearly show this trust gap. While AI adoption continues growing, only 13% of consumers truly trust AI systems, and about 30% remain neutral rather than confident. Many people are still uncomfortable giving AI fully autonomous control over important decisions, especially in areas connected to finance or personal data.

At the same time, enterprises themselves also often contribute to the problem of trust by rolling out AI models before building the necessary structures to govern them.

A recent survey by McKinsey discovered that less than 15% of organizations obtain full security and IT approval before deploying AI agents. Or, to put it in other words, the vast majority of these systems come out without proper oversight and responsibility frameworks around them.

This very reality has now become the defining challenge of the next AI adoption phase. The market is no longer asking whether companies can use artificial intelligence. It’s asking whether they can use it responsibly. And that is precisely why I am of the opinion that AI communication from here on out needs to be very different from what we saw during the first hype cycle. It’s no longer about who shouts the loudest.

The main victory condition will be for companies to explain — clearly and realistically — how their systems work and how they benefit their users. And then they will have to continue proving that through sustainable action.

Transparency and governance are now a product feature

One important area to account for is transparency around AI limitations. Now that the broad public already has enough context and experience to understand that AI can fail, pretending otherwise would only damage a company’s credibility.

To earn trust, strong, honest communication is necessary that will openly acknowledge those points of failure. When a business wishes to present its own AI solution, it will need to explain upfront where its model works well and where its shortcomings lie. Customers should have clear expectations and understanding of the risks before they engage with the technology.

Some might think that admitting to shortcomings would be a mistake, a vulnerability. But honesty can yield more results than those people expect.

Clients are generally much more comfortable using services when they understand where the borders are. When they know how decisions are made, that safeguards exist, and that human oversight is still involved in the process, so if something goes wrong, they have someone real to talk to.

This is where competent governance enters the picture.

Be it to partners, clients, or regulators, businesses increasingly need to demonstrate that they are responsible about how they employ AI in operations. Whether decisions can be audited.

A few years ago, these topics were often hidden deep inside technical documentation, if they were brought up at all. Now, explainability of AI models is one of the biggest signals of trustworthiness that a company can project.

And honestly, I think this is healthy for the industry.

By now, AI has stopped being a mere marketing decoration and is leaning more and more toward becoming a full-on infrastructure layer in corporate operations. That means it needs to be properly managed, so that possible mistakes do not create reputational and monetary damage to countless involved parties.

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Veed has quickly carved a name for itself in the AI video and image generation industry. Used by giants like Netflix, Google, P&G, and the BBC, Veed has grown into a full-fledged AI-powered video platform serving over 10 million monthly active users worldwide.

In our Veed review, we put the platform to the test and evaluate its top AI-powered creative features. We evaluate it first-hand, analyzing even its user interface, pricing, as well as how it compares to the best AI video editors available today. Read on to find out if it's the right choice for you.

Veed: Plans and pricing

Veed offers a handy free plan, which comes with around 120 credits, 2 GB of storage, and an upload file size limit of 1 GB. You can export videos up to 10 minutes in length in 720p, with limited AI video generation within the available credits.

Additionally, AI video editing features such as filler removal, background removal, and auto-edits are all available on a try-once basis.

We found the free video editing package to be fairly limited and ideal only for testing out what Veed offers, rather than using the platform long term.

To get the most out of Veed, you'll need one of its paid plans, starting with the Creator plan, priced at $12 per user per month. Here, you can export videos in 1080p quality with 5 GB of storage.

You can check it out by clicking here.

(Image credit: Veed)

A good thing is that there is no upload file size limit, along with unlimited access to auto subtitles and various subtitle styles. AI image generation limits are also increased to 300 images per month, compared to 100 images with the free plan.

Along with this, you get access to all AI video editing features except Text Behind Person, which is still available only on a try-once basis. Subtitle translation and AI dubbing are also limited to a try-once basis. This is also the first plan where you get limited access to Brand Kits and unlimited access to stock templates.

The Pro plan, priced at $22 per user per month, comes with 30,000 credits, enough for creating 6,000 AI videos. Here, you can export videos in 4K quality, along with unlimited AI image generation and access to all AI video editing features. Subtitle translation and AI dubbing also come with higher limits of six hours per year.

Then there's the Studio plan, offering 180,000 credits for $39 per user per month. This plan comes with unlimited storage, along with 12 hours per year of subtitle translation and AI dubbing. You can invite up to five editors, compared to three in all previous plans, along with one reviewer. All other features are limited within the credit allowance that comes with this plan.

Lastly, there's the Enterprise plan for large organizations, where you can customize your credit allowances with unlimited access to almost all features that Veed has to offer. This is the only plan where you get priority support from Veed, along with a dedicated Customer Success Manager, onboarding, and training.

Veed: Features

Veed offers a good mix of both AI generation and video editing features. For starters, you can generate AI videos with simple prompts in up to 4K quality, depending on your plan. You get access to some of the best AI models, including Veo 3.1, Seedance, Halo, Luma Ray, PixVerse 4.5, and MiniMax.

Besides this, there are features like text-to-video, image-to-video, and the ability to create AI avatars. You get more than 60 diverse avatar options, along with support for more than 120 languages. However, unlike Kapwing, most of Veed's avatars are rooted in real-life people and appear more authentic. Besides AI avatars, you can also create custom social media characters, which can be used consistently across future content you create.

The best thing about Veed is the wide range of subtitle options you get. From manual subtitles available in all plans to auto subtitles, there are unlimited subtitle styles to choose from, along with dynamic subtitles that animate with speech. These subtitle options are perfect for modern social media content.

(Image credit: Veed)

Editing features are also plentiful, with options such as Clean Audio, which removes background noise, removing filler words like "uh" and "um," removing awkward silences from videos, fixing eye contact so that your character looks directly into the camera, background removal, and auto-editing.

Another impressive Veed feature is its collaboration and brand management. Depending on your plan, you can use custom Brand Kits to maintain brand consistency across all your videos. Plus, you can invite editors to any project to facilitate real-time collaboration.

Besides this, you also get access to custom templates, which help you get started with pre-built ideas, as well as custom watermarks. The Enterprise plan also allows you to create separate private workspaces, which come in handy for large organizations with multiple teams.

Veed: Interface and in use

Getting started with Veed is pretty easy. Once you create your account, you are taken to the dashboard, where you'll need to enter your first prompt to generate an image or video.

In the workspace, you can see your recent videos in the central pane, along with Brand Kits and the Asset Library on the left. To create a new image or video, you'll need to click New Project from the toolbar at the top.

(Image credit: Future)

Once you're on the edit screen, you'll see all the editing options on the left-hand side, such as Audio, Images, Subtitles, Text, and more. There are plenty of stock videos and images to help you get started with any new project.

There is a horizontal editing bar at the bottom of the edit screen. However, many editing features, such as effects, detaching audio, opacity, and filters, are hidden – you'll need to click the three dots in the center of your dashboard to access them.

(Image credit: Future)

A lot of the edits need to be made after the initial AI video has already been created, such as editing the script, choosing between voice-only and character-driven videos, or adding subtitles or music.

We would have liked to see these options before generating the video, as that would have resulted in more accurate output.

Overall, editing in Veed is pretty smooth, although it takes a bit of time to get the hang of the platform.

Veed: How we tested

To test out Veed's capabilities, we used its free plan, which allows up to 120 credits. We then gave it the following prompt:

"A woman in a red coat walks across a rain-soaked city street at night, neon lights reflecting in the puddles, camera slowly tracking alongside her."

(Image credit: Future)

Veed took a bit of time to interpret the prompt and generate the results, longer than Kapwing and Fliki. That said, the results were pretty satisfactory, and Veed stuck to the prompt word for word.

Another peculiarity of Veed is that it can create both character-driven and voice-only videos. This means it can convert the same script into a story narrated by one of its many characters or create an AI video with only voiceovers.

That said, exporting a single AI-generated video around five seconds in length can take anywhere between 40 and 50 credits. This means the free plan lets you export only around one AI video, which is certainly not enough for everyday use.

After this, we tried creating an AI image with Veed. One thing we liked is that it lets you choose the AI model before generating the content. For instance, the image we generated cost around 20 credits with Google Nano Banana Pro, whereas the same image cost only five credits with the FLUX.2 Pro model.

(Image credit: Future)

We used the following prompt for image generation:

"A weathered sea captain with a salt-and-pepper beard, wearing a vintage naval coat, painted in the style of a classical oil portrait."

You can also choose the image orientation – landscape or portrait – and the number of image variations you want (one, two, three, or four). There's also a pretty handy option to enhance your prompt, which comes in handy when you're short on creativity but need accurate results.

(Image credit: Future)

Veed created four images as requested. Each image has a built-in option to edit, download, or add to an existing project on the platform.

Veed: Final verdict

Veed is one of the most complete AI image and video generation and editing platforms you can opt for. You get a wide range of features, such as text-to-image, text-to-video, script generation, auto subtitles, dynamic editing, and more.

Using Veed is also pretty easy, making it ideal for beginner video editors, especially compared to a more complex platform like Filmora. Besides this, if you want to generate social media content, Veed offers one of the best ranges of subtitle styles available. It also offers one of the most culturally and geographically diverse selections of real-life AI characters.

That said, its free plan is pretty limited, allowing you to create only one or two AI videos, which isn't enough for regular use. However, its paid plans are in line with the industry standard and are comparable to Invideo or Kapwing.

Veed: Alternatives

Veed is certainly very good, but depending on your needs, there are a few alternatives you can consider.

The first is Fliki, which gives you a lot of control over the kind of content you want to generate. For instance, you can choose from various templates and video formats, along with the type of character you want in the video. Additionally, there's the option to add captions, choose an AI avatar, or add a voiceover before you generate the video.

Many of these editing options are also available with Veed, but only after the video has been generated, which can be a bit time-consuming. However, Fliki can export videos only up to 1080p quality, whereas Veed supports up to 4K quality.

If you're looking for something more affordable than Veed, you can consider Adobe Firefly, which starts at just $8.49 per month. It has one of the most generous free plans, with daily image and video generation limits that allow you to use it for a longer period.

Firefly also comes with infinite-canvas mood boards, which come in handy for teams looking to generate new content ideas. There's also a professional range of stock assets, such as images, videos, and templates.

That said, many of its features, such as AI avatar generation and video editing, are still in beta, leaving plenty of room for improvement.

We've tested a range of video makers and editors, including the best video editing software, the best video editing apps and the best free video editing software.

For years, identity security has been designed to secure an organization's human users. But as agentic enterprises take shape, the identity equation is shifting. Artificial intelligence (AI) agents and AI-powered builders – software tools used to develop websites and applications without coding – are increasingly participating in how access is configured, governed and used.

AI agents are effectively new digital employees, so organizations need a way to know they exist and control what they do throughout their lifecycle. They are becoming operators, helping to administer and secure identity environments through machine-native interfaces.

To add another layer of complexity, desktop agents and AI assistants are also beginning to interact with enterprise applications and resources on behalf of users.

For an agentic enterprise to succeed, these agents need trusted access to do useful work but should not be given direct exposure to secrets they have no meaningful reason to access. To achieve this, organizations need a unified, AI-first identity model, centered on end-to-end visibility, governance and controls which strike a balance between security and appropriate access.

AI agents are reshaping identity

AI has created a new category of digital identity. Like human employees, autonomous agents must be discoverable and managed and governed so organizations can understand what systems and data they can access and who is responsible for their actions.

Traditional identity and access management (IAM) systems relied on static, one-time verification methods in response to access requests made by humans. But in the agentic enterprise, requests also come from autonomous software acting on behalf of human users. Organizations therefore need to know exactly who or what is accessing a system continuously, and if they have the correct permissions to access given information.

At the same time, AI is increasingly managing identities and access. Machine-native interfaces allow agents to help manage human users’ access, troubleshoot issues and support security workflows. While these capabilities can help organizations cut costs and improve efficiency, they are only successful when strong access guardrails are put in place.

AI has created a new category of digital identity. Like human employees, autonomous agents must be discoverable and managed and governed so organizations can understand what systems and data they can access and who is responsible for their actions.

Traditional identity and access management (IAM) systems relied on static, one-time verification methods in response to access requests made by humans. But in the agentic enterprise, requests also come from autonomous software acting on behalf of human users. Organizations therefore need to know exactly who or what is accessing a system continuously, and if they have the correct permissions to access given information.

At the same time, AI is increasingly managing identities and access. Machine-native interfaces allow agents to help manage human users’ access, troubleshoot issues and support security workflows. While these capabilities can help organizations cut costs and improve efficiency, they are only successful when strong access guardrails are put in place.

Building a unified identity model for AI

Mechanisms for securing AI cannot simply be bolted onto identity systems designed for humans. It requires a complete rethink of the identity management model, where human and machine identities are governed through a single framework to prevent tool sprawl and unintentional security blind spots.

As organizations adopt AI tools throughout multiple operational layers, enterprise identity needs to evolve and become easier to manage and automate. Identity can no longer rely solely on human administration.

Tools designed specifically for autonomous agents, such as AI-first headless interfaces, allow builders and AI alike to perform identity-related tasks. Autonomous operators must also be trained to configure access, troubleshoot workflows and apply governance controls within approved policies and guardrails.

Visibility and governance across the entire AI agent lifecycle are also critical. As more agents are deployed, businesses must have complete visibility into their agents and actions.

Every AI should be treated as a first-class identity, with a designated human owner, as well as clear policies and full auditability throughout its entire lifecycle. As these agents operate across the enterprise, their actions should be traceable to a human user responsible.

Finally, AI agents need trusted ways to interact with enterprise resources without being given direct access to the credentials or secrets that enable them. Coding and desktop agents increasingly interact with systems on behalf of users, but exposing them to credentials or long-lived secrets creates unnecessary risk. Instead, access to enterprise resources should be brokered through just-in-time privileged controls.

This allows enterprises to maintain oversight of how permissions are granted, governed and audited without exposing the underlying secrets behind that access. Together, these capabilities create a unified identity model which extends governance across human and AI identities without creating a parallel identity stack.

The future of the agentic enterprise

AI agents cannot operate as intended and deliver meaningful value without access to enterprise systems. But granting unrestricted access or exposing sensitive information creates an entirely new risk to organizations.

The future of the agentic enterprise depends on maintaining governance, visibility and control across both human and digital identities. This means identity must become programmable, AI agents should be governed throughout their lifecycle and agent access needs to be given without unnecessary exposure to sensitive data.

A unified identity strategy provides the means to operate AI agents more safely and efficiently while maintaining centralized governance, accountability and control.

We've featured the best endpoint security software.

This article was produced as part of TechRadar Pro Perspectives, our channel to feature the best and brightest minds in the technology industry today.

The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/pro/perspectives-how-to-submit

Complex computer systems that decide whether people get Medicaid benefits have a history of errors. Now changes to comply with Trump's tax and domestic policy law are inundating those systems.

(Image credit: Kate Wells for KFF Health News)

Real Skills for Real Life: A DBT Guide to Navigating Stress, Emotions, and Relationships.'/>

A clinical psychologist shares effective strategies to quickly de-escalate stress and anxiety. That includes dunking your head into a bowl of ice water to trigger your mammalian dive reflex.

(Image credit: Jesse Finkelstein/Sonya Barlas/NPR)

Recent evidence shows that energy cost pressures and a power grid capacity crunch risk becoming a bottleneck on the growth of the UK’s digital economy.

A report by Oxford Economics for the Nuclear Industry Association warns that growing grid capacity constraints and uncompetitive industrial electricity prices could drive data center developers overseas.

This comes as data center energy demands could increase fivefold by 2035 and data center operators face growing pressure for more sustainable energy in line with climate targets.

This is driving many data center developers to explore alternative supply sources such as flexible contracts and Corporate Power Purchase Agreements (CPPAs) which offer affordable, secure long-term power.

Yet many data center developers lack the resources to navigate these complex contracts or meet the high credit requirements.

There is an urgent need for creative new solutions to provide affordable sustainable power for our digital economy.

The energy chokepoint for the AI economy

The Government aims to make Britain the fastest AI-adopting country in the G7 and this will require accelerated data center expansion with AI data centers being prioritized for new demand connections to the grid. While this is welcome, demand-side connections will not alleviate the supply-side challenges from rising electricity costs to network capacity constraints.

Data centers have build times of 12-14 months yet large new renewable energy projects can face waits of 12-14 years to come online at a time when Britain faces rising non-commodity electricity costs such as Transmission Network Use of System (TNUoS) and Nuclear Regulated Asset Base (RAB) charges to fund new electric grid and nuclear energy infrastructure.

Ofgem has warned that data center power consumption could significantly exceed Britain’s current peak electricity consumption, risking rising energy costs.

The move towards flexible contracts

Flexible electricity contracts that allow companies to buy energy in chunks offer a potential solution to this by allowing data centers to tailor energy costs to their consumption.

Crucially, flexible contracts can be adjusted to hedge against fluctuating energy consumption for facilities such as AI data centers which have more variable patterns of energy use. This would also help avoid penalties for ramping up energy use to take on major new customers.

While fixed-price contracts can lock in long-term energy costs to offer certainty, flexible contracts enable data centers to take advantage of price fluctuations to secure cheaper power.

For example, we have a dedicated pricing team monitoring market movements round the clock. This could help facilities partially hedge against the risk of rising prices, setting a price for a portion of their consumption, while buying the rest when required to take advantage of favorable prices on the spot market.

For example, we implemented a flexible contract for an energy-intensive industrial chemicals company which included a cash-out arrangement, enabling them to lock in prices when costs are low and buy power in batches days or even months ahead as needed.

There are various kinds of flexible contract options based on the degree to which companies can forecast their energy consumption. For example, ‘tolerance banding’ which guarantees a set price within a certain range or ‘band’ of electricity consumption, can provide certainty amidst unpredictable, fluctuating costs.

As data center operators become more confident in forecasting energy consumption, this can create even cheaper options such as contracts that enable them to buy every kilowatt-hour above or below expected demand.

The CPPA model

Other contracts such as CPPAs could offer data centers a secure, sustainable, affordable power supply directly from suppliers at stable cost. Private-wire PPAs involving onsite generation could enable data centers to sell surplus power back to the grid, transforming energy from a cost into a revenue stream. On site generation could also help avoid the non-commodity costs for grid electricity such as TNUoS charges that comprise 60% of electricity bills and are set to increase to fund new infrastructure.

With targets to reduce operational emissions from buildings by 76%, CPPAs also help facilities meet climate targets by providing traceable green power. As large consumers with a relatively stable long-term demand, data centers are perfectly placed to tap into this market. Amidst growing energy price volatility and security risks, fixed-price CPPAs offer the chance to lock in power prices and supplies, providing certainty and security.

The barriers to alternative contracts

Yet there are many barriers to flexible contracts and CPPAs market for smaller entities such as data centers. These contracts can be highly complex, contain stringent credit requirements and often require 10-15 year agreements. The Contracts for Difference (CfD) scheme, which gives renewable developers a government-backed route to market through fixed long-term price support, can also act as a competing route to market for generators.

In some cases, this can make long-term corporate offtake agreements less attractive, particularly where developers can secure greater certainty through the CfD mechanism. For smaller customers seeking greener electricity, however, this route can offer an alternative when a direct CPPA may be harder to access.

Many data center projects are run by startups or smaller entities that lack the resources for such long-term commitments or credit requirements. Data centers also present a slightly higher credit risk than other facilities because their revenue streams are not based on a few large, long-term customers but split among many customers across the digital economy.

Opening the market to data centers

There is an urgent need for creative solutions to lower barriers to entry to the flexible contract market for smaller entities such as data centers. Security deposits or bank guarantees can help some firms meet the stringent credit requirements.

Other potential solutions include parent-company guarantees where a parent company makes a commitment to cover the cost in the event of a default or intercompany guarantees where large data center customers such as Amazon offer guarantees.

There are also solutions to simplify adoption and help CPPAs slot into existing energy use. For example, PPA import sleeving contracts, where energy is pre-purchased from a generator or utility and supplied directly to a facility through the grid, can help alleviate energy costs and security risks.

Tailoring contracts to specific energy needs

Independent partners can also help data centers optimize contracts for their specific energy needs and financial situation. Independent brokers can consolidate the process of negotiating with generators, suppliers and investors, speeding up and de-risking adoption.

Brokers can also help negotiate and monitor contracts suited to the precise profile of each data center. For example, cloud computing data centers with relatively steady, predictable demand may prefer fixed contracts whereas AI data centers processing huge amounts of data for many clients have a more variable, ‘peaky’ pattern of consumption and require flexible contracts.

Data centers can also work with partners to get live market intelligence on changing regulations or market movements. For example, we offered one client an early warning service so that they were able to minimize costs during the winter triads, half-hour periods of peak demand during the winter season.

Towards a new model of data center energy

Britain’s ability to compete in the accelerating AI race increasingly hinges on the ability to mitigate the risk of rising energy costs.

Energy security will also be critical to building truly sovereign AI capabilities for the UK. Lowering the barriers to the flexible contract market could create new opportunities at both ends, providing secure, sustainable and affordable power to unlock data center growth while unlocking vital investment in new renewable energy capacity.

Yet this will require tailored, adaptable contractual models from bespoke flexible contracts to PPAs and new ways of lowering barriers to entry including reducing complexity and stringent credit requirements. This could help provide secure, sustainable and affordable long-term power to fuel our digital economy.

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This article was produced as part of TechRadar Pro Perspectives, our channel to feature the best and brightest minds in the technology industry today.

The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/pro/perspectives-how-to-submit

The U.S. carries out a wave of strikes against Iran, as fighting between the two escalates, Congress faces long to-do list as August recess approaches, Andy Burnham becomes U.K.'s 7th prime minister.

In a transition of power presided over by King Charles, Andy Burnham has replaced Keir Starmer as the United Kingdom's prime minister. Both are from the center-left Labour Party.

(Image credit: Kirsty Wigglesworth)

Improve your brand’s visibility and overall GEO with a lifetime subscription to BeeSeen for almost $400 less.

The post Know How AI Platforms See Your Brand with BeeSeen for Life for $99.99 appeared first on TechRepublic.

Here are some hints and the answers for the NYT Connections puzzle for July 20, No. 1,135.

Qualcomm's been at the heart of chipmaking for smartphones and mobile devices for years, with its line of Snapdragon chips powering Android smartphones throughout the 4G and 5G era. With 6G set to roll out in the 2030s, the jury's still out on its potential impact. Qualcomm's CEO Cristiano Amon, however, has painted a curious vision.

Every step you take

Amon, who's been in charge of the American semiconductor manufacturer since he was promoted in 2021, outlined how he sees 6G shaping future hardware in an interview on Fox Business.

Quote of the day

This article is part of TechRadar Pro's QOTD project to provide an insight into the minds of the brightest and most recognized figures in the technology industry today and in years gone by. Read the full series here.

The CEO is bullish on smart glasses hitting the mainstream, suggesting that the cameras built into these devices will be continuously streaming video and capture data in real-time (including audio) to feed a user's personal AI.

Where does 6G come into the picture? The technology permits far faster top speeds compared with today's 5G networks. Theoretically, future mobile networks can reach 1Tbps by taking advantage of the sub-terahertz spectrum. This comes alongside minimal latency.

Through the looking glass

Smart glasses have been out of vogue for many years – especially since Google's clunky Google Glass debut. Recently, however, they've found a new lease of life thanks to improving display technology as well as more intuitive and ergonomic form factors.

One of the best examples of this is the longstanding collaboration between Meta and Ray-Ban. Although these glasses look the part, the camera functionality has received plenty of backlash, with some owners even refraining from wearing them in public.

Although the technology might be there with 6G mobile networks, there are still plenty of obstacles in the way of the number of people happy to wear smart glasses for the new form factor to really take off.

To celebrate Evil Dead Burn coming out in theaters this month, I've put together the ultimate quiz to test fans of the popular horror franchise.

Ever since The Evil Dead was released in 1981, the series has been a favorite among genre fans and is widely recognizable, but have you been paying attention to it? I bet you won't be able to get a perfect score on my quiz, so now's your chance to prove me wrong!

Don't worry if you haven't seen Evil Dead Burn yet, because this quiz only covers the previous movies, meaning you won't find any spoilers for the new movie lurking in here.

But there's plenty of trivia about the rest of the franchise, from the original release to the 2013 remake. These horror movies are among the most fascinating, from the scripts all the way to what happened on set.

Feeling brave? Scroll down to try out the quiz now, and see if you can survive to the very end.

How did you do? Let me know your score in the comments below, and if you're hungry for more horror trivia, why not check out my Resident Evil movie quiz ahead of Zach Cregger's adaptation, which arrives later this year.

Or we've got an ultimate Walking Dead quiz for fans of the hit zombie series. If you think you're a superfan, join other quizzers and prove your knowledge.

For more horror streaming recommendations, I've got you covered too. Take a look at the best horror movies streaming on Netflix, Prime Video, Shudder, and more in July 2026 to find something good to watch.

With President Trump in attendance, an all-superstar lineup that included Madonna, BTS, Justin Bieber and Burna Boy felt a little more political than it might have otherwise.

(Image credit: Mauro Pimentel)

Here are some hints and the answers for the NYT Connections puzzle for July 20, No. 1,135.

Here are hints and the answer for today's Wordle for July 20, No. 1,857.