Artificial Intelligence

Why Apple is playing it slow with AI

Published

1 week ago

July 22, 2025

Apple is taking its time with AI. While most tech companies are racing to push out AI features as fast as they can, Apple is doing the opposite. Its big announcement – Apple Intelligence – won’t arrive for most users until 2026. That’s a long delay in a market where speed seems to matter more than quality. But maybe that’s the whole point.

At this year’s WWDC, Apple showed off new AI features tied to Siri, writing tools, and app suggestions. It called the bundle “Apple Intelligence,” but those tools won’t be widely available any time soon. For now, they’re limited to beta users on select devices in the US. The rest of the world will have to wait. According to Macworld, even early access to Apple Intelligence is expected to be restricted, and many users may not see the features until iOS 18.4 (at the earliest) in 2025. A wider release could slip into 2026.

Not falling behind – just not rushing in

To some, the delay looks like Apple falling behind. OpenAI has already rolled out GPT-4o, Google is squeezing Gemini into Android, and Microsoft has pushed Copilot into Office, Windows, and pretty much everything else. Compared to that, Apple seems slow.

Apple tends not to ship bad software. It delays when things aren’t working. The company has a long history of waiting until something is polished before pushing it out. That kind of caution can be frustrating, but it also avoids something worse: giving people tools that don’t work properly.

Meanwhile, competitors ship bugs

Plenty of companies don’t seem to care about quality. Microsoft’s Copilot, for example, often gives wrong answers, makes up citations, or produces junk text. ChatGPT has its own set of problems, from hallucinating facts to giving inconsistent results. Even tools like Claude or Gemini, which show promise in short bursts, tend to fall short on long-term tasks or anything that needs precision.

Ask developers what it’s like using AI to write production code, and you’ll often hear the same message: it works fine for code snippets or boilerplate, but it’s more work than help when it comes to complex projects. Fixing AI-written code often takes longer than writing it from scratch.

Apple’s delay might be the smarter play

An opinion piece from TechRadar captured the consumer viewpoint. The author said they were glad Apple delayed Siri’s AI overhaul, arguing that the current generation of AI isn’t good enough. They said we often have the AI discussion backwards – we assume the tech is ready, and criticise companies for being too slow. But what if the tech just isn’t there yet? Apple’s delay might not be a flaw; it might be the only rational move.

Apple seems aware of this, making a lot of noise about being “excited” by AI, but it hasn’t forced it into every product, flooding iOS with half-baked tools. It hasn’t promised that Siri will be your new work assistant, for example. And while it may talk up the potential, it’s also been quiet about timelines.

Playing the long game

Some would call that playing it safe, but there’s another way to look at it. Maybe Apple doesn’t actually believe the current wave of AI is ready? Maybe it’s not convinced the technology will hold up under real pressure. So it’s watching the chaos from a distance.

And there’s plenty of chaos to watch. Companies are rolling out AI products that don’t work as advertised. Security issues, bad output, and inflated expectations are becoming common. Behind the scenes, many AI companies are burning through cash trying to make their models useful. If the bubble bursts, Apple gets to say it never went all-in.

Wait, watch, then act

That might not be a bug in the company’s strategy or problems in production: It might be the company’s strategy.

If users grow tired of AI that doesn’t deliver, Apple comes out looking smart for not jumping in too fast. If the tech improves and becomes reliable, Apple can still step in with a product that feels stable and is reliable.

This kind of delay has worked for Apple before, not launching a smartwatch until years after others tried. In the tablet market too, it wasn’t the market leader, but ended up setting the standard once involved.

With AI, Apple might be trying the same thing. Let everyone else test the limits, hit the walls, and suffer the backlash. Meanwhile, Apple learns from their mistakes, avoiding rushing out tools that make headlines for all the wrong reasons.

No rush required

It also helps that Apple doesn’t need to hype itself to stay relevant. It already controls the hardware, the OS, and the app store. It can roll out AI when it wants, how it wants, without chasing investor attention.

Of course, there’s always a risk in waiting too long. If AI tools do become reliable and useful across the board, Apple might miss the shift, but as of now, that shift hasn’t happened, with tools out there still struggling with accuracy, nuance, and consistency.

Getting it right beats being first

So maybe Apple is right to wait. Maybe the smartest move in this hype cycle is to do less.

“If Apple’s slow and cautious AI rollout results in something actually useful, that’s a win,” TechRadar says. And if it doesn’t? At least Apple didn’t spam the market with tools that waste everyone’s time.

In a tech cycle full of broken promises and half-working products, doing nothing might be the boldest move Apple could make.

(Photo by appshunter.io)

See also: Apple loses key AI leader to Meta

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Artificial Intelligence

Zuckerberg outlines Meta’s AI vision for ‘personal superintelligence’

Published

2 hours ago

July 31, 2025

Hrishi

Meta CEO Mark Zuckerberg has laid out his blueprint for the future of AI, and it’s about giving you “personal superintelligence”.

In a letter, the Meta chief painted a picture of what’s coming next, and he believes it’s closer than we think. He says his teams are already seeing early signs of progress.

“Over the last few months we have begun to see glimpses of our AI systems improving themselves,” Zuckerberg wrote. “The improvement is slow for now, but undeniable. Developing superintelligence is now in sight.”

So, what does he want to do with it? Forget AI that just automates boring office work, Zuckerberg and Meta’s vision for personal superintelligence is far more intimate. He imagines a future where technology serves our individual growth, not just our productivity.

In his words, the real revolution will be “everyone having a personal superintelligence that helps you achieve your goals, create what you want to see in the world, experience any adventure, be a better friend to those you care about, and grow to become the person you aspire to be.”

But here’s where it gets interesting. He drew a clear line in the sand, contrasting his vision against a very different, almost dystopian alternative that he believes others are pursuing.

“This is distinct from others in the industry who believe superintelligence should be directed centrally towards automating all valuable work, and then humanity will live on a dole of its output,” he stated.

Meta, Zuckerberg says, is betting on the individual when it comes to AI superintelligence. The company believes that progress has always come from people chasing their own dreams, not from living off the scraps of a hyper-efficient machine.

If he’s right, we’ll spend less time wrestling with software and more time creating and connecting. This personal AI would live in devices like smart glasses, understanding our world because they can “see what we see, hear what we hear.”

Of course, he knows this is powerful, even dangerous, stuff. Zuckerberg admits that superintelligence will bring new safety concerns and that Meta will have to be careful about what they release to the world. Still, he argues that the goal must be to empower people as much as possible.

Zuckerberg believes we’re at a crossroads right now. The choices we make in the next few years will decide everything.

“The rest of this decade seems likely to be the decisive period for determining the path this technology will take,” he warned, framing it as a choice between “personal empowerment or a force focused on replacing large swaths of society.”

Zuckerberg has made his choice. He’s focusing Meta’s enormous resources on building this personal superintelligence future.

See also: Forget the Turing Test, AI’s real challenge is communication

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Artificial Intelligence

Google’s Veo 3 AI video creation tools are now widely available

Published

1 day ago

July 30, 2025

Hrishi

Google has made its most powerful AI video creator, Veo 3, available for everyone to use on its Vertex AI platform. And for those who need to work quickly, a speedier version called Veo 3 Fast is also ready-to-go for quick creative work.

Ever had a brilliant idea for a video but found yourself held back by the cost, time, or technical skills needed to create it? This tool aims to offer a faster way to turn your text ideas into everything from short films to product demos.

70 million videos have been created since May, showing a huge global appetite for these AI video creation tools. Businesses are diving in as well, generating over 6 million videos since they got early access in June.

The real-world applications for Veo 3

So, what does this look like in the real world? From global design platforms to major advertising agencies, companies are already putting Veo 3 to work. Take design platform Canva, they are building Veo directly into their software to make video creation simple for their users.

Cameron Adams, Co-Founder and Chief Product Officer at Canva, said: “Enabling anyone to bring their ideas to life – especially their most creative ones – has been core to Canva’s mission ever since we set out to empower the world to design.

“By democratising access to a powerful technology like Google’s Veo 3 inside Canva AI, your big ideas can now be brought to life in the highest quality video and sound, all from within your existing Canva subscription. In true Canva fashion, we’ve built this with an intuitive interface and simple editing tools in place, all backed by Canva Shield.”

For creative agencies like BarkleyOKRP, the big wins are speed and quality. They claim to have been so impressed with the latest version that they went back and remade videos.

Julie Ray Barr, Senior Vice President Client Experience at BarkleyOKRP, commented: “The rapid advancements from Veo 2 to Veo 3 within such a short time frame on this project have been nothing short of remarkable.

“Our team undertook the task of re-creating numerous music videos initially produced with Veo 2 once Veo 3 was released, primarily due to the significantly improved synchronization between voice and mouth movements. The continuous daily progress we are witnessing is truly extraordinary.”

It’s even changing how global companies connect with local customers. The investing platform eToro used Veo 3 to create 15 different, fully AI-generated versions of a single advertisement, each customised to a specific country with its own native language.

Shay Chikotay, Head of Creative & Content at eToro, said: “With Veo 3, we produced 15 fully AI‑generated versions of our ad, each in the native language of its market, all while capturing real emotion at scale.

“Ironically, AI didn’t reduce humanity; it amplified it. Veo 3 lets us tell more stories, in more tongues, with more impact.”

Google gives creators a powerful AI video creation tool

Veo 3 and Veo 3 Fast are packed with features designed to give you the control to tell complete stories.

Create scenes with sound. The AI generates video and audio at the same time, so you can have characters that speak with accurate lip-syncing and sound effects that fit the scene.

High quality results. The models produce video in high-definition (1080p), making it good enough for professional marketing campaigns and demos.

Reach a global audience easily. Veo 3’s ability to generate dialogue natively makes it much simpler to produce a video once and then translate the dialogue for many different languages.

Bring still images to life. A new feature, coming in August, will let you take a single photo, add a text prompt, and watch as Veo animates it into an 8-second video clip.

Of course, with such powerful technology, safety is a key concern. Google has built Veo 3 for responsible enterprise use. Every video frame is embedded with an invisible digital watermark from SynthID to help combat misinformation. The service is also covered by Google’s indemnity for generative AI, giving businesses that extra layer of security.

See also: Google’s newest Gemini 2.5 model aims for ‘intelligence per dollar’

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Artificial Intelligence

Forget the Turing Test, AI’s real challenge is communication

Published

2 days ago

July 29, 2025

Hrishi

While the development of increasingly powerful AI models grabs headlines, the big challenge is getting intelligent agents to communicate.

Right now, we have all these capable systems, but they’re all speaking different languages. It’s a digital Tower of Babel, and it’s holding back the true potential of what AI can achieve.

To move forward, we need a common tongue; a universal translator that will allow these different systems to connect and collaborate. Several contenders have stepped up to the plate, each with their own ideas about how to solve this communication puzzle.

Anthropic’s Model Context Protocol, or MCP, is one of the big names in the ring. It attempts to create a secure and organised way for AI models to use external tools and data. MCP has become popular because it’s relatively simple and has the backing of a major AI player. However, it’s really designed for a single AI to use different tools, not for a team of AIs to work together.

And that’s where other protocols like the Agent Communication Protocol (ACP) and the Agent-to-Agent Protocol (A2A) come in.

ACP, an open-source project from IBM, is all about enabling AI agents to communicate as peers. It’s built on familiar web technologies that developers are already comfortable with, which makes it easy to adopt. It’s a flexible and powerful solution that allows for a more decentralised and collaborative approach to AI.

Google’s A2A protocol, meanwhile, takes a slightly different tack. It’s designed to work alongside MCP, rather than replace it. A2A is focused on how a team of AIs can work together on complex tasks, passing information and responsibilities back and forth. It uses a system of ‘Agent Cards,’ like digital business cards, to help AIs find and understand each other.

The real difference between these protocols is their vision for the future of how AI agents communicate. MCP is for a world where a single, powerful AI is at the centre, using a variety of tools to get things done. ACP and A2A are designed for distributed intelligence, where teams of specialised AIs work together to solve problems.

A universal language for AI would open the door to a whole new world of possibilities. Imagine a team of AIs working together to design a new product, with one agent handling the market research, another the design, and a third the manufacturing process. Or a network of medical AIs collaborating to analyse patient data and develop personalised treatment plans.

But we’re not there yet. The “protocol wars” are in full swing, and there’s a real risk that we could end up with even more fragmentation than we have now.

It’s likely that the future of how AI communicates won’t be a one-size-fits-all solution. We may see different protocols, each used for what it does best. One thing is for sure: figuring out how to get AIs to talk to each other is among the next great challenges in the field.

(Photo by Theodore Poncet)

See also: Anthropic deploys AI agents to audit models for safety

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