In 2024, Meta allowed more than 3300 pornographic ads – many featuring AI-generated content – on its social media platforms, including Facebook and Instagram.

The findings come from a by , a European non-profit organisation focused on investigating tech platform algorithms. The researchers also discovered an inconsistency in Meta’s content moderation policies by re-uploading many of the same explicit images as standard posts on Instagram and Facebook. Unlike the ads, those posts were swiftly removed for violating Meta’s .

“I’m both disappointed and not surprised by the report, given that my research has already exposed double standards in content moderation, particularly in the realms of sexual content,” says at Northumbria University’s Centre for Digital Citizens in the UK.

The AI Forensics report focused on a small sample of ads aimed at the European Union. It found that the explicit ads allowed by Meta primarily targeted middle-aged and older men with promotions for “dubious sexual enhancement products” and “hook-up dating websites”, with a total reach of more than 8.2 million impressions.

Such permissiveness reflects a broader double standard in content moderation, says Are. Tech platforms often block content by and for “women, femme-presenting and LGBTQIA+ users”, she says. That double standard extends to male and female sexual health. “An example is lingerie and period-related ads being [removed] from Meta, while ads for Viagra are approved,” she says.

In addition to finding AI-generated imagery in the ads, the AI Forensics team also discovered audio deepfakes: in some ads for sexual enhancement medication, for example, pornographic visuals were overlaid with the digitally manipulated voice of actor Vincent Cassel.

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“Meta prohibits the display of nudity or sexual activity in ads or organic posts on our platforms, and we are removing the violating content that was shared with us,” says a Meta spokesperson. “Bad actors are constantly evolving their tactics to avoid enforcement, which is why we continue to invest in the best tools and technology to help identify and remove violating content.”

The report coincides with Meta CEO Mark Zuckerberg announcing that the company will be getting rid of its fact-checking teams in favour of crowdsourced community notes.

“If we want to sound really dystopian – and at this stage given Zuckerberg’s latest decision to remove fact-checkers I think we have reason to be – we can even say that Meta is as quick to strip individual, marginalised users of their agency as it is to take money from dubious ads,” says Are.

Facebook’s parent company, Meta, has used AI to develop a new way of creating concrete which it claims produces 40 per cent less carbon emissions than standard mixtures, and is already using it in its latest data centre. But experts say that concrete mixtures with similar emissions are already in use across Europe, and that constructing new buildings is incompatible with reducing carbon pollution.

Meta is investing heavily in AI research, including building the world’s most powerful AI-specific supercomputer. Its main aims are to develop better speech-recognition tools, automatically translate between different languages and help build a 3D virtual metaverse, but the company is also using AI to work on projects such as concrete production.

The company says that this construction material is a major contributor to its carbon footprint as it builds data centres around the world for its online services. The production and use of concrete is .

Basic concrete is a mix of cement and an aggregate such as gravel, mixed with water. Commercial concrete can contain dozens or even hundreds of ingredients to achieve a desired strength or durability. Cement is responsible for a large part of concrete’s carbon emissions, so alternatives to this component with a smaller but still sizeable carbon footprint such as fly ash, a by-product of burning coal, and slag, which is a by-product of manufacturing steel, are commonly used.

To train an AI model to find the optimal recipe for a given use, Meta researchers used a resource which lists various properties of 1030 different concrete mixtures called the . This includes the strength of each concrete after curing for a week and a month, and its carbon footprint. The AI was then able to compare all possible concrete mixtures and find examples that matched a minimum given strength, but also had the lowest possible emissions .

Meta took the five most promising mixtures and tested them in a laboratory. The company said in a blog post that manually discovering such mixtures would be challenging, but that its AI approach completed the task “within weeks”. In a paper outlining the research, the authors say coming up with such mixtures is “pushing the boundary of human creativity”.

at the Swiss Federal Institute of Technology in Zürich says that the claimed reduction in carbon emissions is calculated in comparison with a concrete made using pure Portland cement produced entirely with fossil fuel energy and no replacement material at all. “I doubt that this is US industry standard today – it would be embarrassing if it were,” he says.

The AI-derived mixtures are certainly effective, but not really novel, says Kaufmann. “In western Europe, concretes similar to the one referenced as ‘industry standard’ in the paper stopped being used 25 years ago. The emissions of the ‘novel’ concretes described in the paper essentially correspond to Swiss average concrete in terms of emissions today,” he says.

One of the new concrete mixtures is being used in limited parts of Meta’s new data centre in DeKalb, Illinois. “Based on a life cycle assessment of our typical data centre design, we have concluded that concrete is a significant contributor to our embodied carbon emissions, and hence the need to find low-carbon solutions for concrete,” says , a researcher at Meta.

at the University of Leeds, UK, says that minimising cement content in concrete has been a goal of manufacturers for some time because it is the most expensive part of the mixture, and that minimising carbon emissions in reality means not creating new buildings.

“You can fiddle around at the edges of cement contents, using a bit less energy and all the rest of it, but at the end of the day, if you really want to decarbonise the built environment, stop building stuff. It’s literally that simple,” he says.

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Facebook’s parent company, Meta, is building the world’s most powerful AI-specific supercomputer to develop better speech-recognition tools, automatically translate between different languages and help build its 3D virtual metaverse.

Although far from complete, the AI Research SuperCluster (RSC) is up and running and has already overtaken Meta’s previous fastest supercomputer. That machine was designed in 2017 and ran on 22,000 powerful graphics processing units (GPUs) which, despite being designed for playing games, are highly effective tools to train artificial intelligence models with.

RSC currently has only 6080 GPUs, but they are more powerful than those in the older machine and it is already three times faster at training large AI models than its predecessor. Its current performance is on a par with the Perlmutter supercomputer at the National Energy Research Scientific Computing Center in California, which is currently placed at

When RSC is complete, it will consist of 16,000 GPUs and be almost three times more powerful than it is now. Meta says that at this point, it will be the fastest AI-optimised supercomputer in the world, performing at nearly 5 exaflops.

Supercomputers can be designed to excel at certain tasks. Meta’s machine is specialised to train and run large AI models. There will be more powerful computers in the world when it is complete, but only a few, and none that shares its exact architecture or intended use.

The cutting edge of AI research has relied on scale in recent years, and ever more powerful machines to train models with. One of the largest neural networks, the Megatron-Turing Natural Language Generation model, has 530 billion parameters, which are roughly equivalent to the connections between brain cells. Meta says its machine will eventually run models with trillions of parameters.

at the University of Sussex, UK, says the proposed computer is “huge” in scale, but may not overcome some of the challenges in AI research. “A system this large is definitely going to let them build larger models,” he says. “However, I don’t think that merely increasing the size of language models will address the well-documented problems of existing models repeating sexist and racist language or failing basic tests of logical reasoning.”