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Apple loses key AI leader to Meta

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Apple is nursing a fresh wound this week after losing one of its most crucial AI leaders to Meta. Ruoming Pang, the executive who oversaw Apple Intelligence, has jumped ship to join Meta’s new Superintelligence Labs.

Pang wasn’t just any Apple employee. He led a 100-strong army of engineers crafting the language models that make your iPhone summarise texts, generate those Genmoji, and prioritise your notifications. Now he’s traded the Apple Park spaceship for Meta’s Menlo Park headquarters, becoming the latest big name to answer Mark Zuckerberg’s call.

The leading exec’s departure is a gut punch to a company that’s been scrambling to prove it can play in the AI big leagues. The timing couldn’t be worse, either.

Just last month, Pang’s right-hand man, Tom Gunter, had already packed his bags and left. Pang’s departure was reported by Bloomberg and the outlet’s sources suggest Apple is losing the talent it desperately needs.

Apple spent years building up its AI chops, focusing on that privacy-first approach that’s supposed to be its secret sauce. However, many believe that focus has led to the company falling behind in AI with many Apple Intelligence features yet to roll out. The haemorrhaging of talent isn’t going to help with efforts to catch up.

Meta’s cheque book diplomacy for AI talent

Meanwhile, Meta’s playing the talent acquisition game like a Premier League club during transfer season. Word on the street is that they’re throwing around signing bonuses that would even make a footballer blush, and frankly, it’s working.

Since last April, there’ve been whispers about Meta’s shopping spree through Silicon Valley’s AI departments. Apple hasn’t been the sole target, with talent at OpenAI and Google also receiving tempting offers as top companies fight to recruit (and retain) expertise.

It’s not subtle, and it’s certainly not cheap. Critics are calling it market manipulation, but you can’t argue with the results. Meta’s managed to hoover up some of the brightest minds in AI, all in service of their grand vision for artificial general intelligence.

The creation of Superintelligence Labs isn’t just corporate restructuring—it’s a declaration of war. Meta’s essentially saying they’re going toe-to-toe with OpenAI and Google’s DeepMind, and they’re backing it up with serious cash. That $14.3 billion they dropped on Scale AI? That’s not play money, it’s a statement of intent.

Back at Apple, the mood isn’t exactly celebratory. Sources are whispering about teams feeling a bit rudderless and questioning whether the company actually knows where it’s heading with AI. It’s a far cry from the confident Apple many have become accustomed to.

The current reliance on OpenAI for key Apple Intelligence features has apparently ruffled some feathers internally. There’s a growing sense that Apple’s becoming too dependent on others’ innovations rather than cooking up its own breakthroughs. For a company that built its reputation on doing things differently, that’s gotta sting.

Broader implications for the AI industry

The movement of talent between major technology companies reflects the competitive nature of the AI landscape. As companies race to develop increasingly sophisticated AI systems, the recruitment and retention of top-tier research talent has become a vital competitive advantage.

Meta’s success in attracting personnel from Apple, Google, and OpenAI demonstrates the company’s commitment to AI leadership and its willingness to invest substantially in human capital. The establishment of Superintelligence Labs, combined with strategic acquisitions and aggressive recruitment, ensures Meta remains a formidable force in the race towards artificial general intelligence.

For Apple, the challenge extends beyond simply replacing departed personnel. The company must address underlying strategic questions about its AI direction while competing for talent in an increasingly expensive and competitive market. The success of Apple Intelligence features will likely depend on the company’s ability to maintain its technical capabilities whilst developing a clear vision for its AI future.

As Meta continues to consolidate AI talent and Apple grapples with strategic challenges, the outcomes will likely determine which companies emerge as leaders in the next phase of technological evolution.

(Photo by Garin Chadwick)

See also: Tencent Hunyuan3D-PolyGen: A model for ‘art-grade’ 3D assets

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

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Artificial Intelligence

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

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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

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

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

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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’

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

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

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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

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

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