The releases come from Meta’s Fundamental AI Research (FAIR) team which has focused on advancing AI through open research and collaboration for over a decade. As AI rapidly innovates, Meta believes working with the global community is crucial.

“By publicly sharing this research, we hope to inspire iterations and ultimately help advance AI in a responsible way,” said Meta.

Chameleon: Multi-modal text and image processing

Among the releases are key components of Meta’s ‘Chameleon’ models under a research license. Chameleon is a family of multi-modal models that can understand and generate both text and images simultaneously—unlike most large language models which are typically unimodal.

“Just as humans can process the words and images simultaneously, Chameleon can process and deliver both image and text at the same time,” explained Meta. “Chameleon can take any combination of text and images as input and also output any combination of text and images.”

Potential use cases are virtually limitless from generating creative captions to prompting new scenes with text and images.

Multi-token prediction for faster language model training

Meta has also released pretrained models for code completion that use ‘multi-token prediction’ under a non-commercial research license. Traditional language model training is inefficient by predicting just the next word. Multi-token models can predict multiple future words simultaneously to train faster.

“While [the one-word] approach is simple and scalable, it’s also inefficient. It requires several orders of magnitude more text than what children need to learn the same degree of language fluency,” said Meta.

JASCO: Enhanced text-to-music model

On the creative side, Meta’s JASCO allows generating music clips from text while affording more control by accepting inputs like chords and beats.

“While existing text-to-music models like MusicGen rely mainly on text inputs for music generation, our new model, JASCO, is capable of accepting various inputs, such as chords or beat, to improve control over generated music outputs,” explained Meta.

AudioSeal: Detecting AI-generated speech

Meta claims AudioSeal is the first audio watermarking system designed to detect AI-generated speech. It can pinpoint the specific segments generated by AI within larger audio clips up to 485x faster than previous methods.

“AudioSeal is being released under a commercial license. It’s just one of several lines of responsible research we have shared to help prevent the misuse of generative AI tools,” said Meta.

Improving text-to-image diversity

Another important release aims to improve the diversity of text-to-image models which can often exhibit geographical and cultural biases.

Meta developed automatic indicators to evaluate potential geographical disparities and conducted a large 65,000+ annotation study to understand how people globally perceive geographic representation.

“This enables more diversity and better representation in AI-generated images,” said Meta. The relevant code and annotations have been released to help improve diversity across generative models.

By publicly sharing these groundbreaking models, Meta says it hopes to foster collaboration and drive innovation within the AI community.

(Photo by Dima Solomin)

See also: NVIDIA presents latest advancements in visual AI

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.

The post Meta unveils five AI models for multi-modal processing, music generation, and more appeared first on AI News.

Let’s delve into how AI is revolutionising online slot gaming in the UK and what this means for both players and developers.

AI integration in slot machine development

The development of slot machines has come a long way from their mechanical beginnings to the sophisticated digital versions we see today. AI is at the forefront of this evolution, significantly enhancing the creation and functionality of these games.

Enhanced game design

AI enables developers to create more dynamic and visually appealing games. By analysing vast amounts of player data, AI can generate themes, graphics, and narratives that are tailored to the preferences of different player demographics. This means that games can be more immersive and engaging, drawing players into captivating storylines and visually stunning environments that are continually evolving based on player interactions.

Adaptive gameplay

One of the most exciting applications of AI in slot machine development is the ability to adjust gameplay in real-time. AI algorithms monitor player behaviour and adapt the difficulty and features of the game accordingly. For example, if a player is struggling, the game might become slightly easier to keep them engaged, or if a player is doing exceptionally well, the game might present more challenges to maintain excitement. This adaptive gameplay ensures that players remain interested and challenged, providing a more satisfying gaming experience.

Personalised player experience

Personalisation is a key aspect of modern online gaming, and AI is instrumental in delivering a customised experience for each player.

Machine learning for player insights

AI uses machine learning to analyse player behaviour and preferences, allowing for highly personalised game suggestions and promotional offers. By understanding what types of games a player enjoys and how they like to play, AI can recommend new games or bonuses that are most likely to appeal to them. This level of personalisation enhances the player’s experience and increases their engagement with the platform.

Customised in-game experience

Beyond recommendations, AI also customises the gameplay itself. For instance, AI can adjust game mechanics, such as bonus frequencies and difficulty levels, based on individual player data. This means that each gaming session is unique and tailored to the player’s specific preferences, making the gaming experience more enjoyable and engaging.

Enhancing security and fairness

Security and fairness are critical components of online gaming, and AI plays a significant role in ensuring both.

Fraud detection and prevention

AI is highly effective in identifying and preventing fraudulent activities. By continuously monitoring player behavior and transaction patterns, AI can detect anomalies that may indicate fraudulent actions. When such activities are detected, AI can intervene in real-time to prevent losses and protect players and operators alike. This capability is crucial for maintaining the integrity and trustworthiness of online gaming platforms.

Ensuring fair play

Ensuring fair play is paramount in online gaming, and AI enhances this by maintaining the integrity of random number generators (RNG). AI algorithms ensure that the outcomes of slot games are truly random and free from manipulation. This transparency is essential for player trust, as it guarantees that every player has an equal chance of winning based on luck, without any external interference.

AI’s role in responsible gambling

AI is also a powerful tool in promoting responsible gambling practices, helping to mitigate the risks associated with gambling addiction.

Predictive analytics for problem gambling

AI can analyse playing patterns to identify behaviours that may indicate problem gambling. By using predictive analytics, AI can spot early signs of addiction, such as excessive spending or extended gaming sessions. This allows gaming platforms to intervene proactively, offering support and resources to players who may be at risk.

Intervention strategies

Once potential problem gambling behavior is identified, AI can implement intervention strategies. This might include sending notifications to players about their gaming habits, providing self-assessment tools, or limiting the amount of time and money a player can spend on the platform. These strategies are designed to help players maintain a healthy relationship with gambling and prevent the escalation of problematic behaviours.

Future prospects

Looking ahead, the potential of AI in the online slot gaming industry is immense. As AI technology continues to advance, we can expect even more sophisticated and personalised gaming experiences. AI-driven innovation will likely lead to entirely new types of games that we cannot yet imagine, offering unparalleled levels of engagement and excitement.

AI is revolutionising the online slot gaming industry in the UK, offering enhanced game design, personalised player experiences, improved security, and responsible gambling measures. As the technology continues to evolve, the future of online slot gaming looks incredibly promising, with AI playing a pivotal role in shaping this exciting landscape. For players and developers alike, the integration of AI presents endless possibilities for innovation and improvement in the world of online gaming.

The post The impact of AI on online slot gaming in the UK appeared first on AI News.

“Artificial intelligence, and generative AI in particular, represents a pivotal technological advancement,” said Jan Kautz, VP of learning and perception research at NVIDIA.

“At CVPR, NVIDIA Research is sharing how we’re pushing the boundaries of what’s possible — from powerful image generation models that could supercharge professional creators to autonomous driving software that could help enable next-generation self-driving cars.”

Among the over 50 NVIDIA research projects being presented, two papers have been selected as finalists for CVPR’s Best Paper Awards – one exploring the training dynamics of diffusion models and another on high-definition maps for self-driving cars.

Additionally, NVIDIA has won the CVPR Autonomous Grand Challenge’s End-to-End Driving at Scale track, outperforming over 450 entries globally. This milestone demonstrates NVIDIA’s pioneering work in using generative AI for comprehensive self-driving vehicle models, also earning an Innovation Award from CVPR.

One of the headlining research projects is JeDi, a new technique that allows creators to rapidly customise diffusion models – the leading approach for text-to-image generation – to depict specific objects or characters using just a few reference images, rather than the time-intensive process of fine-tuning on custom datasets.

Another breakthrough is FoundationPose, a new foundation model that can instantly understand and track the 3D pose of objects in videos without per-object training. It set a new performance record and could unlock new AR and robotics applications.

NVIDIA researchers also introduced NeRFDeformer, a method to edit the 3D scene captured by a Neural Radiance Field (NeRF) using a single 2D snapshot, rather than having to manually reanimate changes or recreate the NeRF entirely. This could streamline 3D scene editing for graphics, robotics, and digital twin applications.

On the visual language front, NVIDIA collaborated with MIT to develop VILA, a new family of vision language models that achieve state-of-the-art performance in understanding images, videos, and text. With enhanced reasoning capabilities, VILA can even comprehend internet memes by combining visual and linguistic understanding.

NVIDIA’s visual AI research spans numerous industries, including over a dozen papers exploring novel approaches for autonomous vehicle perception, mapping, and planning. Sanja Fidler, VP of NVIDIA’s AI Research team, is presenting on the potential of vision language models for self-driving cars.

The breadth of NVIDIA’s CVPR research exemplifies how generative AI could empower creators, accelerate automation in manufacturing and healthcare, while propelling autonomy and robotics forward.

(Photo by v2osk)

See also: NLEPs: Bridging the gap between LLMs and symbolic reasoning

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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While LLMs like ChatGPT have demonstrated impressive performance on various tasks, they often struggle with problems requiring numerical or symbolic reasoning.

NLEPs follow a four-step problem-solving template: calling necessary packages, importing natural language representations of required knowledge, implementing a solution-calculating function, and outputting results as natural language with optional data visualisation.

This approach offers several advantages, including improved accuracy, transparency, and efficiency. Users can investigate generated programs and fix errors directly, avoiding the need to rerun entire models for troubleshooting. Additionally, a single NLEP can be reused for multiple tasks by replacing certain variables.

The researchers found that NLEPs enabled GPT-4 to achieve over 90% accuracy on various symbolic reasoning tasks, outperforming task-specific prompting methods by 30%

Beyond accuracy improvements, NLEPs could enhance data privacy by running programs locally, eliminating the need to send sensitive user data to external companies for processing. The technique may also boost the performance of smaller language models without costly retraining.

However, NLEPs rely on a model’s program generation capability and may not work as well with smaller models trained on limited datasets. Future research will explore methods to make smaller LLMs generate more effective NLEPs and investigate the impact of prompt variations on reasoning robustness.

The research, supported in part by the Center for Perceptual and Interactive Intelligence of Hong Kong, will be presented at the Annual Conference of the North American Chapter of the Association for Computational Linguistics later this month.

(Photo by Alex Azabache)

See also: Apple is reportedly getting free ChatGPT access

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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Many games are being totally revolutionised by AI stepping onto the scene, so let’s get into the nitty-gritty of which games are changing, what’s happening, and how AI is leaving its footprint on this world of online casino games!

Personalisation in the slots

First up: personalisation. AI really shines when it comes to personalising the slots, because an AI can analyse each player’s individual behaviour and start tailoring what the game shows to match. Imagine you’re playing at your favourite slot, and you get a bunch of free spins come up – but none of them are quite what you wanted and they’re just not doing it for you today. We all know that feeling of disappointment… and honestly, it gets directed at the company, because why don’t they know you better than that? Isn’t marketing meant to be good these days?

Well, AI is changing all that and cutting the frustration that comes with it! It is capable of tracking what bonuses you use and what games you play (and even when and how you play them), and that means that suddenly, casinos can offer much more tailored options when you’re playing on the slots. Free spins for your favourite game ever, just as you sit down to relax on a Friday night? Yes, that’s much more likely now! 

Personalised bonus games? These are also creeping onto the scene, along with game features that are specifically honed to tick your “like” box and give you the best possible gaming experience. And it’s only because of AI that this is becoming possible – sure, casinos tried to offer this kind of personalisation in the past, but it was simply too much for humans to manage.

Of course, you must have been playing the slots for a while for this to work; the AI is dependent on having historical data of how you play and when you play to bring up these offers. The longer you’ve been playing and the more consistent your patterns are, the better the AI will be able to come up with offers that are perfect for you. As this system improves, maybe we’ll see slots that are completely unique for each individual – it could happen! And as AI becomes increasingly accepted and legislation is put into place for it, we’re going to see more and more innovation in this space.

Learning about bluffing in poker

How do you teach a computer to bluff? We’re not going to pretend it’s easy; it’s proven a major challenge for those building AIs, getting a computer to mimic a human’s ability to deceive other players. However, we’re pretty much there, and AIs can now be incorporated into the online world of poker – one of the most popular casino games on the planet.

So, first off, they have created an AI that’s good at poker; there’s been major progress in advancing how the absolute best AI can play, and it’s doing well. However, that’s not actually enough for casinos: they don’t want an AI that can beat human players every time, because who would ever play against that? They need an AI that can understand nuance, make mistakes occasionally, and lose – but in convincing ways that are still satisfying to play against. Now that’s a real challenge!

But if they’re successful, there’s going to be big rewards: some people would much rather play against a computer than other humans, provided the computer makes a satisfying opponent. This is likely to be an ongoing process as the AIs master how to play in each context, but it already looks promising to us! Of course, there are wary about teaching computers how to lie effectively… after all, sci-fi books and films have shown us exactly why that could be a bad idea. For the casino industry, though, it’s looking tantalising. 

Conclusion

AI isn’t “big” in most casino games yet, because it hasn’t had time to infiltrate them… but we’re likely to see it edging in from the fringes and changing more and more things about how we play and enjoy games online as the years come. It’s overly exciting to imagine how it might revolutionise classic games like poker, blackjack, roulette, the slots, and more. However, we’re just going to have to “wait and see” here, because AI is only just unfolding its metaphorical wings and starting to flap.

The post AI in casino games: A whole new world waiting to be dealt appeared first on AI News.

Musk had initially sued OpenAI in March 2024, alleging breach of contracts, unfair business practices, and failure in fiduciary duty. He claimed that his contributions to the company were made “in exchange for and in reliance on promises that those assets were irrevocably dedicated to building AI for public benefit, with only safety as a countervailing concern.”

The lawsuit sought remedies for “breach of contract, promissory estoppel, breach of fiduciary duty, unfair business practices, and accounting,” as well as specific performance, restitution, and damages.

However, Musk’s filings to withdraw the case provided no explanation for abandoning the lawsuit. OpenAI had previously called Musk’s claims “incoherent” and that his inability to produce a contract made his breach claims difficult to prove, stating that documents provided by Musk “contradict his allegations as to the alleged terms of the agreement.”

The withdrawal of the lawsuit comes at a time when Musk is strongly opposing Apple’s plans to integrate ChatGPT into its operating systems.

During Apple’s keynote event announcing Apple Intelligence for iOS 18, iPadOS 18, and macOS Sequoia, Musk threatened to ban Apple devices from his companies, calling the integration “an unacceptable security violation.”

Despite assurances from Apple and OpenAI that user data would only be shared with explicit consent and that interactions would be secure, Musk questioned Apple’s ability to ensure data security, stating, “Apple has no clue what’s actually going on once they hand your data over to OpenAI. They’re selling you down the river.”

Since bringing the lawsuit against OpenAI, Musk has also created his own AI company, xAI, and secured over $6 billion in funding for his plans to advance the Grok chatbot on his social network, X.

While Musk’s reasoning for dropping the OpenAI lawsuit remains unclear, his actions suggest a potential shift in focus towards advancing his own AI endeavours while continuing to vocalise his criticism of OpenAI through social media rather than the courts.

See also: DuckDuckGo releases portal giving private access to AI models

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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The post Musk ends OpenAI lawsuit while slamming Apple’s ChatGPT plans appeared first on AI News.

The service, accessible at Duck.ai, is globally available and features a light and clean user interface. Users can choose from four AI models: two closed-source models and two open-source models. The closed-source models are OpenAI’s GPT-3.5 Turbo and Anthropic’s Claude 3 Haiku, while the open-source models are Meta’s Llama-3 70B and Mistral AI’s Mixtral 8x7b.

What sets DuckDuckGo AI Chat apart is its commitment to user privacy. Neither DuckDuckGo nor the chatbot providers can use user data to train their models, ensuring that interactions remain private and anonymous. DuckDuckGo also strips away metadata, such as server or IP addresses, so that queries appear to originate from the company itself rather than individual users.

The company has agreements in place with all model providers to ensure that any saved chats are completely deleted within 30 days, and that none of the chats made on the platform can be used to train or improve the models. This makes preserving privacy easier than changing the privacy settings for each service.

In an era where online services are increasingly hungry for user data, DuckDuckGo’s AI Chat service is a breath of fresh air. The company’s commitment to privacy is a direct response to the growing concerns about data collection and usage in the AI industry. By providing a private and anonymous platform for users to interact with AI chatbots, DuckDuckGo is setting a new standard for the industry.

DuckDuckGo’s AI service is free to use within a daily limit, and the company is considering launching a paid tier to reduce or eliminate these limits. The service is designed to be a complementary partner to its search engine, allowing users to switch between search and AI chat for a more comprehensive search experience.

“We view AI Chat and search as two different but powerful tools to help you find what you’re looking for – especially when you’re exploring a new topic. You might be shopping or doing research for a project and are unsure how to get started. In situations like these, either AI Chat or Search could be good starting points.” the company explained.

“If you start by asking a few questions in AI Chat, the answers may inspire traditional searches to track down reviews, prices, or other primary sources. If you start with Search, you may want to switch to AI Chat for follow-up queries to help make sense of what you’ve read, or for quick, direct answers to new questions that weren’t covered in the web pages you saw.”

To accommodate that user workflow, DuckDuckGo has made AI Chat accessible through DuckDuckGo Private Search for quick access.

The launch of DuckDuckGo AI Chat comes at a time when the AI industry is facing increasing scrutiny over data privacy and usage. The service is a welcome addition for privacy-conscious individuals, joining the recent launch of Venice AI by crypto entrepreneur Erik Voorhees. Venice AI features an uncensored AI chatbot and image generator that doesn’t require accounts and doesn’t retain data..

As the AI industry continues to evolve, it’s clear that privacy will remain a top concern for users. With the launch of DuckDuckGo AI Chat, the company is taking a significant step towards providing users with a private and secure platform for interacting with AI chatbots.

See also: AI pioneers turn whistleblowers and demand safeguards

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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In May, several high-profile employees departed from the company, including Jan Leike, the former head of OpenAI’s “super alignment” efforts to ensure advanced AI systems remain aligned with human values. Leike’s exit came shortly after OpenAI unveiled its new flagship GPT-4o model, which it touted as “magical” at its Spring Update event.

According to reports, Leike’s departure was driven by constant disagreements over security measures, monitoring practices, and the prioritisation of flashy product releases over safety considerations.

Leike’s exit has opened a Pandora’s box for the AI firm. Former OpenAI board members have come forward with allegations of psychological abuse levelled against CEO Sam Altman and the company’s leadership.

The growing internal turmoil at OpenAI coincides with mounting external concerns about the potential risks posed by generative AI technology like the company’s own language models. Critics have warned about the imminent existential threat of advanced AI surpassing human capabilities, as well as more immediate risks like job displacement and the weaponisation of AI for misinformation and manipulation campaigns.

In response, a group of current and former employees from OpenAI, Anthropic, DeepMind, and other leading AI companies have penned an open letter addressing these risks.

“We are current and former employees at frontier AI companies, and we believe in the potential of AI technology to deliver unprecedented benefits to humanity. We also understand the serious risks posed by these technologies,” the letter states.

“These risks range from the further entrenchment of existing inequalities, to manipulation and misinformation, to the loss of control of autonomous AI systems potentially resulting in human extinction. AI companies themselves have acknowledged these risks, as have governments across the world, and other AI experts.”

The letter, which has been signed by 13 employees and endorsed by AI pioneers Yoshua Bengio and Geoffrey Hinton, outlines four core demands aimed at protecting whistleblowers and fostering greater transparency and accountability around AI development:

1. That companies will not enforce non-disparagement clauses or retaliate against employees for raising risk-related concerns.
2. That companies will facilitate a verifiably anonymous process for employees to raise concerns to boards, regulators, and independent experts.
3. That companies will support a culture of open criticism and allow employees to publicly share risk-related concerns, with appropriate protection of trade secrets.
4. That companies will not retaliate against employees who share confidential risk-related information after other processes have failed.

“They and others have bought into the ‘move fast and break things’ approach and that is the opposite of what is needed for technology this powerful and this poorly understood,” said Daniel Kokotajlo, a former OpenAI employee who left due to concerns over the company’s values and lack of responsibility.

The demands come amid reports that OpenAI has forced departing employees to sign non-disclosure agreements preventing them from criticising the company or risk losing their vested equity. OpenAI CEO Sam Altman admitted being “embarrassed” by the situation but claimed the company had never actually clawed back anyone’s vested equity.

As the AI revolution charges forward, the internal strife and whistleblower demands at OpenAI underscore the growing pains and unresolved ethical quandaries surrounding the technology.

See also: OpenAI disrupts five covert influence operations

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.

The post AI pioneers turn whistleblowers and demand safeguards appeared first on AI News.

Project P.I. leverages generative AI and computer vision technologies to detect issues such as damaged products or incorrect colours and sizes before they reach customers. The AI model not only identifies defects but also helps uncover the root causes, enabling Amazon to implement preventative measures upstream. This system has proven highly effective in the sites where it has been deployed, accurately identifying product issues among the vast number of items processed each month.

Before any item is dispatched, it passes through an imaging tunnel where Project P.I. evaluates its condition. If a defect is detected, the item is isolated and further investigated to determine if similar products are affected.

Amazon associates review the flagged items and decide whether to resell them at a discount via Amazon’s Second Chance site, donate them, or find alternative uses. This technology aims to act as an extra pair of eyes, enhancing manual inspections at several North American fulfilment centres, with plans for expansion throughout 2024.

Dharmesh Mehta, Amazon’s VP of Worldwide Selling Partner Services, said: “We want to get the experience right for customers every time they shop in our store.

“By leveraging AI and product imaging within our operations facilities, we are able to efficiently detect potentially damaged products and address more of those issues before they ever reach a customer, which is a win for the customer, our selling partners, and the environment.”

Project P.I. also plays a crucial role in Amazon’s sustainability initiatives. By preventing damaged or defective items from reaching customers, the system helps reduce unwanted returns, wasted packaging, and unnecessary carbon emissions from additional transportation.

Kara Hurst, Amazon’s VP of Worldwide Sustainability, commented: “AI is helping Amazon ensure that we’re not just delighting customers with high-quality items, but we’re extending that customer obsession to our sustainability work by preventing less-than-perfect items from leaving our facilities, and helping us avoid unnecessary carbon emissions due to transportation, packaging, and other steps in the returns process.”

In parallel, Amazon is utilising a generative AI system equipped with a Multi-Modal LLM (MLLM) to investigate the root causes of negative customer experiences.

When defects reported by customers slip through initial checks, this system reviews customer feedback and analyses images from fulfilment centres to understand what went wrong. For example, if a customer receives the wrong size of a product, the system examines the product labels in fulfilment centre images to pinpoint the error.

This technology is also beneficial for Amazon’s selling partners, especially the small and medium-sized businesses that make up over 60% of Amazon’s sales. By making defect data more accessible, Amazon helps these sellers rectify issues quickly and reduce future errors.

(Photo by Andrew Stickelman)

See also: X now permits AI-generated adult content

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.

The post Amazon will use computer vision to spot defects before dispatch appeared first on AI News.

“We believe that users should be able to create, distribute, and consume material related to sexual themes as long as it is consensually produced and distributed. Sexual expression, visual or written, can be a legitimate form of artistic expression,” X’s updated ‘adult content’ policy states.

The policy further elaborates: “We believe in the autonomy of adults to engage with and create content that reflects their own beliefs, desires, and experiences, including those related to sexuality. We balance this freedom by restricting exposure to adult content for children or adult users who choose not to see it.”

Users can mark their posts as containing sensitive media, ensuring that such content is restricted from users under 18 or those who haven’t provided their birth dates.

While X’s violent content rules have similar guidelines, the platform maintains a strict stance against excessively gory content and depictions of sexual violence. Explicit threats or content inciting or glorifying violence remain prohibited.

X’s decision to allow graphic content is aimed at enabling users to participate in discussions about current events, including sharing relevant images and videos. 

Although X has never outright banned porn, these new clauses could pave the way for developing services centred around adult content, potentially creating a competitor to services like OnlyFans and enhancing its revenue streams. This would further Musk’s vision of X becoming an “everything app,” similar to China’s WeChat.

A 2022 Reuters report, citing internal company documents, indicated that approximately 13% of posts on the platform contained adult content. This percentage has likely increased, especially with the proliferation of porn bots on X.

See also: Elon Musk’s xAI secures $6B to challenge OpenAI in AI race

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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