A report by the Wall Street Journal said Meta had repeatedly delayed plans to make the API available to developers and, as of Tuesday, had not set a launch date. The report cited people familiar with the matter.

However, Meta disputed suggestions that the project had stalled. A company spokesperson said on Wednesday that testing is already underway with a group of early partners and that the company still expects to release the API later this month.

“The muse spark API will be coming soon,” Meta AI Chief Alexandr Wang announced in a post on X in April.

Meta AI Unveils Spark to Power Next-Gen AI across Platforms

The API would allow developers to integrate Muse Spark into their own software and services. An API, or Application Programming Interface, is a software bridge that enables different systems to communicate and work together.

Meta introduced Muse Spark in April as the first model developed under its Superintelligence Labs initiative, which was created to strengthen the company’s position in the competitive AI market.

The model is designed to narrow the gap between Meta and competitors including OpenAI, Anthropic and Google.

While Muse Spark is already available to consumers through Meta’s applications, users can currently access it only through built-in modes such as Instant, Thinking and Contemplating. Developers still do not have access to a public API, and Meta has yet to release documentation, pricing details, rate limits or eligibility requirements.

The lack of information has created apprehension among developers hoping to build products around the model. Without a public timeline, waitlist or technical documentation, companies interested in integrating Muse Spark are unable to plan deployments or assess costs.

The delays also come at a sensitive time for Meta. Investors have been monitoring the company’s AI strategy as it spends heavily on infrastructure, talent and product development.

Questions about execution have grown following reports of an Instagram security incident involving Meta’s AI-powered support system, which exposed weaknesses in automated account management processes.

Earlier on Wednesday, Meta unveiled a new AI agent designed to help businesses handle day-to-day tasks, showing that the company is going beyond consumer chatbots and into enterprise services.

The launch highlights Meta’s goal to compete more directly with OpenAI, Anthropic and Google across multiple areas of the AI market.

Muse Spark is expected to bolster that strategy. It is the first in what Meta has described as a new generation of advanced models from its Superintelligence Labs unit.

However, the repeated postponements have left analysts, developers and investors waiting for evidence that the company can translate its AI investments into products that are ready for global use.

Access is still currently limited to a small group of testing partners, while the developer community is waiting for Meta to open the platform to the public.

This is one of the first big exits since Mark Zuckerberg reorganised Meta’s AI division under Superintelligence Labs.

LeCun, a Turing Award laureate and one of the pioneers of deep learning, is reportedly in early discussions with investors to raise funds for his new venture, which will centre on developing “world models”, AI systems designed to simulate and understand the real world more deeply. 

This approach aims to create machines that can learn and reason with a closer resemblance to human cognition.

His departure comes at a time when Meta is enhancing its drive to compete with OpenAI, Google DeepMind, and Anthropic in the superintelligent systems space.

Mark Zuckerberg recently consolidated Meta’s AI research under Superintelligence Labs, placing Alexandr Wang, the former CEO of data-labelling firm Scale AI, in charge of the division.

This reorganisation meant that LeCun, who had long reported to Chief Product Officer Chris Cox, was reassigned to report directly to Wang, a move that, according to sources cited by the Financial Times, may have influenced his decision to leave.

LeCun’s planned exit reveals both a generational change in leadership and a potential divergence in vision between academic research and the dynamic, product-driven approach of Meta AI.

Meta, the parent company of Facebook and Instagram, has yet to comment publicly on the reports. LeCun, too, has not issued an official statement.

Since joining Meta (then Facebook) in 2013, Yann LeCun has helped in promoting convolutional neural networks (CNNs) and self-supervised learning, two techniques that underpin today’s large-scale AI systems. 

His next startup could represent a return to the more exploratory and research-oriented roots that first defined his career.

In an attempt to bolster Meta’s superintelligence initiative, the company has been dangling compensation packages of over $100 million to lure top AI researchers, particularly from OpenAI and Google DeepMind. 

This is tied to an internal drive led by Alexandr Wang, the former CEO of Scale AI, now spearheading Meta’s advanced AI team from an office reportedly just steps away from Zuckerberg’s.

Despite the high figures involved in the Meta AI hiring initiative, the campaign has largely hit a wall.

OpenAI CEO Sam Altman, speaking on the Uncapped podcast with his brother Jack Altman on Tuesday, confirmed the reports and offered his own assessment.

“[Meta has] started making these, like, giant offers to a lot of people on our team. You know, like, $100 million signing bonuses, more than that [in] compensation per year […] I’m really happy that, at least so far, none of our best people have decided to take him up on that.”

Meta’s targets reportedly included high-profile figures like OpenAI’s Noam Brown and DeepMind’s Koray Kavukcuoglu, but both declined the offers. 

The failure to secure these names leads to questions about the effectiveness, and ethics, of Meta’s recruitment tactics in what is quickly becoming a high-stakes talent competition.

Altman didn’t stop there as he used the podcast as a platform to criticise Meta’s approach to innovation, drawing a line between OpenAI’s mission-oriented culture and what he sees as Meta’s cash-first strategy.

“I don’t think they’re a company that’s great at innovation,” he said, doubling down on his view that simply catching up isn’t enough in the AI game. Companies, he argued, must genuinely lead.

Beyond recruitment, Meta has poured billions into its AI bets, including a $14.3 billion investment in Scale AI, the company’s second-largest acquisition after WhatsApp. 

It’s already brought in Google DeepMind’s Jack Rae and Johan Schalkwyk from Sesame AI, among others. However, according to Altman, it will take more than star hires to change a transformative AI journey.

He credits OpenAI’s retention strength, reportedly one of the highest in the industry at 67%, to its focus on a collective mission: achieving artificial general intelligence (AGI).

The underlying message is that for OpenAI’s top engineers, purpose trumps pay; so the Meta AI hiring approach requires a different direction.

There’s also a growing front in the competition for influence, social media. Altman revealed that OpenAI is exploring the development of a new AI-powered social app designed to serve feeds based not on algorithms, but on user intent. It’s a direct shot at the core of Meta’s business model.

Meta, on its end, is already testing similar waters through its Meta AI app, but user feedback has been rocky, with reports of confusion and some deeply personal AI chat interactions accidentally shared more widely than intended, a potential privacy minefield.

If OpenAI succeeds in rolling out a more intuitive, AI-driven alternative to traditional social media, it could disrupt Meta’s position, and how the internet itself is experienced.

So, not just about who can pay the most or hire the fastest, but who is building up to be a deeper contest between purpose and profit, between foundational innovation and reactive ambition. And while Meta may have the cash, OpenAI, for now, seems to have the conviction.

The Meta CEO is personally building a new team aimed at artificial general intelligence (AGI), machines that can think and operate at or beyond human capability.

At the heart of this development is a covert “superintelligence” unit made up of roughly 50 top-tier engineers and researchers. 

According to multiple reports, Mark Zuckerberg is leading recruitment himself. That includes closed-door meetings with experts at his homes in Lake Tahoe and Palo Alto, strategic restructuring of Meta’s offices to keep the team close, and eye-watering compensation offers ranging from millions to tens of millions of dollars.

The motivation is the frustration over Meta’s perceived stagnation in the AI space. Meta’s flagship large language model, Llama 4, hasn’t produced the breakthrough results the company hoped for. 

In fact, a planned release of a more powerful version, nicknamed “Behemoth”, was recently delayed due to issues about its real-world capabilities. 

Meanwhile, competitors like OpenAI, Anthropic, and Elon Musk’s xAI are thriving hard to expand their influence, drawing talent and investment with growing momentum.

Zuckerberg is determined not to be left behind. Reports from Bloomberg and The New York Times confirm that Meta is in advanced talks to invest over $10 billion in Scale AI, a startup founded by Alexandr Wang. 

Once the deal is sealed, Wang is expected to join the AGI group, which operates separately from Meta’s existing AI research division.

“I heard of at least three instances last week where Meta lost out on AI talent to competitors offering over $2 million a year,” Menlo Ventures partner Deedy Das wrote on X.

Zuckerberg reportedly believes that Meta has the infrastructure, data scale, and financial muscle to match and surpass the progress of others in the AGI arms race. 

If achieved, the technology would likely be embedded into Meta’s ecosystem, impacting everything from WhatsApp and Instagram to the company’s Ray-Ban smart glasses and enterprise AI tools.

However, the plan leaves users questioning. How will this “superintelligence” group integrate with Meta’s existing AI teams? What risks are involved in placing so much responsibility, and expectation, on one internal unit? And is AGI even within reach? 

The field is divided and some experts believe we’re close. Others say we’re decades away, if not longer, with no clear path forward.

Still, for Zuckerberg, this is a mission.