AI Upload Porn: Understanding the Digital Frontier

At the heart of the "AI upload porn" phenomenon lies the remarkable progress in generative AI models. These sophisticated algorithms, primarily deep learning architectures, possess the ability to create entirely new content—images, videos, audio, and even text—that can be eerily indistinguishable from genuine human-created media. Understanding their capabilities is crucial to grasping how they contribute to this particular digital sphere. For years, Generative Adversarial Networks (GANs) stood as a cornerstone of synthetic media creation. A GAN consists of two neural networks: a generator and a discriminator. The generator's task is to produce data (e.g., images) that mimic real data, while the discriminator's role is to distinguish between real and fake data. Through a continuous adversarial game, both networks improve, with the generator striving to fool the discriminator and the discriminator becoming more adept at detection. This iterative process allows GANs to generate highly realistic, novel outputs. Early applications of GANs demonstrated their capacity to create convincing faces, landscapes, and even short video clips, laying the groundwork for more complex synthetic media. More recently, diffusion models have ascended to prominence, often surpassing GANs in their ability to generate high-fidelity, diverse, and photorealistic images and videos. Diffusion models work by learning to reverse a process of gradually adding noise to an image until it becomes pure noise. Once trained, they can start from random noise and progressively "denoise" it, transforming it into a coherent, high-quality image or video. Their robustness, control, and impressive output quality have made them the preferred tool for a wide range of generative tasks, including the creation of synthetic explicit content. These models can manipulate existing media or generate entirely new scenes and individuals, offering unprecedented control over the visual narrative. The power of these AI models hinges entirely on the data they are trained on. To generate realistic human forms, expressions, and movements, these AI systems are often trained on vast datasets of existing images and videos, including those of real individuals. This fundamental reliance on extensive data creates a paradox: the more comprehensive and diverse the training data, the more capable the AI becomes, but it also raises significant ethical questions about data provenance, consent, and the potential for misuse. When the training data includes explicit imagery, the AI's ability to generate "AI upload porn" becomes a direct, albeit unintended, consequence of its learning process.

The phrase "AI upload porn" points directly to the final stage of dissemination. It's not just about the creation of AI-generated explicit content, but its subsequent distribution through various online channels. This "upload" aspect involves a complex interplay of user intent, platform infrastructure, and the pervasive nature of the internet. For a user to "upload" AI-generated explicit content, they typically interact with AI tools that can be categorized into a few types: * Stand-alone Applications: Software that can be downloaded and run locally, offering extensive control over the generation process. These often require significant computational power. * Web-based Platforms/APIs: Services that allow users to generate content directly through a web browser or by integrating with an API. These platforms abstract away the technical complexities, making AI generation accessible to a broader audience. * Modded or Fine-tuned Open-Source Models: Open-source AI models, like Stable Diffusion, are often modified or fine-tuned by communities to specialize in generating specific types of content, including explicit imagery. These modified models can then be distributed and used by individuals. Once the AI generates the desired content, it exists as a digital file—an image, a video clip, or even an audio file. The act of "uploading" then follows standard internet protocols, similar to sharing any other piece of media. The channels for "AI upload porn" are diverse and ever-evolving, driven by user communities, technological shifts, and the cat-and-mouse game with platform moderation. * Niche Forums and Image Boards: Many smaller, less moderated forums and image boards serve as primary hubs for sharing explicit AI-generated content. These communities often have lax content policies or are specifically designed to circumvent mainstream restrictions. * Dark Web Markets and Channels: For more illicit or specific content, the dark web provides a more clandestine environment, leveraging anonymity networks like Tor to evade detection and censorship. * Private Messaging Apps and Encrypted Channels: Encrypted chat applications and private groups on platforms like Telegram, Discord, or Signal are frequently used for sharing content among smaller, trusted circles, making detection by larger platforms exceedingly difficult. * Decentralized Platforms: Emerging decentralized platforms, built on blockchain or peer-to-peer technologies, aim to offer censorship-resistant sharing, though their user base for explicit content is still niche. * Mainstream Platforms (Evading Detection): While major social media, video, and image-sharing platforms (e.g., X, Reddit, Facebook, Instagram, YouTube) have strict policies against explicit content, users constantly try to circumvent these rules. This often involves cloaking explicit content, using obscure tags, or exploiting loopholes in moderation algorithms. The sheer volume of content uploaded daily makes perfect detection an impossible task, leading to a continuous struggle for platforms to identify and remove such material. The term "AI upload porn" here specifically refers to instances where users successfully bypass filters and disseminate this type of content on platforms not intended for it. The motivation behind "AI upload porn" varies, from curiosity and artistic exploration (albeit controversial) to financial gain, malicious intent (e.g., revenge porn, harassment), or participation in online communities that normalize or even celebrate such content. The ease of access to generative AI tools, combined with the anonymity afforded by the internet, significantly lowers the barrier to entry for creating and distributing such material.

The concept of "AI upload porn" is not theoretical; it is a burgeoning reality that has evolved rapidly in the last few years, particularly with the widespread accessibility of sophisticated generative models. This emergence is marked by several key developments. The term "deepfake" burst into public consciousness around 2017, referring to synthetic media—primarily videos—in which a person's face or body is digitally altered to resemble someone else's. Initially, deepfakes were computationally intensive and required significant technical expertise. Early iterations often involved swapping celebrity faces onto existing pornographic videos without their consent. This specific application, often termed "non-consensual intimate imagery" (NCII) or "revenge porn," immediately highlighted the profound ethical and legal implications of this technology. What began as a specialized skill accessible to a few has rapidly become democratized. The release of open-source AI models like Stable Diffusion in 2022 marked a pivotal moment. These models, coupled with user-friendly interfaces and readily available training data (including illicit datasets), enabled individuals with minimal technical knowledge to generate high-quality explicit images and videos on their own computers. This shift vastly expanded the scale and reach of "AI upload porn" generation. The ability to create virtually any scenario, featuring any desired individual (real or imagined), with remarkable fidelity, represented a significant leap from previous methods. Modern AI capabilities extend far beyond simple face swaps. Generative models can now create entire anatomically correct (or purposefully distorted) bodies, realistic environments, and complex scenes. Users can prompt these AIs to generate specific actions, poses, and narratives, blurring the lines between reality and simulation. The granularity of control means that the AI can craft explicit content that aligns precisely with user desires, making it a powerful tool for niche fetishes, explicit storytelling, or, disturbingly, the creation of highly personalized and abusive content. A significant development contributing to the ubiquity of "AI upload porn" is the rise of prompt-based generation. Users simply input text descriptions (prompts) detailing the desired content, and the AI interprets these prompts to generate the corresponding image or video. This user-friendly interface makes content creation accessible to anyone capable of typing, eliminating the need for traditional artistic or technical skills. This has led to an explosion of prompt-sharing communities where users exchange effective prompts for generating various types of explicit content, further accelerating its creation and spread.

The emergence of "AI upload porn" is not merely a technological novelty; it carries profound ethical implications and generates significant societal ripples that demand urgent attention. The very fabric of trust, consent, and privacy is threatened by the unchecked proliferation of AI-generated explicit content. Perhaps the most egregious ethical violation inherent in "AI upload porn" is the complete disregard for consent. When AI is used to create non-consensual intimate imagery (NCII), it strips individuals of their autonomy over their own digital likeness and sexuality. Victims, predominantly women, find their images exploited in ways they never agreed to, leading to severe psychological distress, reputational damage, and even real-world harm. This form of digital violation is particularly insidious because it can be generated en masse, targeting anyone with an online presence, even those who have never created or shared explicit content themselves. The "AI upload porn" created in this way constitutes a new, more pervasive form of online sexual harassment and abuse. As AI-generated explicit content becomes more sophisticated, it contributes to a broader "fuzzy reality" where distinguishing between authentic and synthetic media becomes increasingly difficult. This epistemic doubt has far-reaching consequences. It can be used to discredit individuals, manipulate public opinion, or even serve as false evidence in legal proceedings. In the context of "AI upload porn," the inability to definitively prove whether an image or video is real or fake can leave victims in a vulnerable position, struggling to defend their reputation against fabricated evidence. It erodes trust in digital media as a whole, making it harder to discern truth from deception. The psychological impact on victims of "AI upload porn" can be devastating. Feelings of violation, helplessness, shame, anxiety, depression, and even suicidal ideation are common responses. The public nature of online dissemination means that the abuse can feel inescapable, perpetually resurfacing on various platforms. Unlike traditional revenge porn, which often uses actual explicit content, AI-generated NCII can target anyone, regardless of whether they have ever taken or shared intimate photos. This makes the threat more universal and the sense of vulnerability more pervasive. A grave concern is the potential for AI to generate child sexual abuse material (CSAM). While some AI models have safeguards against generating explicit content involving minors, malicious actors actively seek or develop methods to circumvent these protections. The ability to create synthetic CSAM poses an unprecedented threat, as it can potentially create an infinite supply of such horrific material without involving real children in its production. This, however, does not diminish the harm; the existence and distribution of CSAM, regardless of its origin, is a profound societal evil that normalizes and propagates child abuse. The "AI upload porn" category extends to these most abhorrent applications, demanding vigilant counter-measures. The pervasive creation and consumption of AI-generated explicit content, particularly that which is non-consensual or exploitative, risks normalizing the dehumanization of individuals. When digital likenesses can be manipulated at will for sexual gratification, it can desensitize users to the real-world implications of consent, privacy, and respect for bodily autonomy. This normalization contributes to a culture where individuals are viewed as objects for consumption, rather than as autonomous beings deserving of dignity.

The rapid advancement of AI's capabilities, particularly in generating explicit content, has left legal frameworks and regulatory bodies struggling to keep pace. Existing laws often weren't designed to address synthetic media, creating significant challenges in enforcement and victim recourse. Most countries lack comprehensive legislation specifically targeting AI-generated non-consensual intimate imagery. Instead, prosecutors often rely on existing laws related to defamation, harassment, identity theft, or child sexual abuse material (CSAM). * Defamation: While "AI upload porn" can be defamatory, proving malicious intent and monetary damages can be difficult, and the legal process is often lengthy and costly for victims. * Harassment/Cyberstalking: These laws might apply if the content is part of a broader pattern of harassment, but they don't directly address the creation or distribution of the synthetic material itself. * Identity Theft: Some jurisdictions might consider the use of a person's likeness without consent as a form of identity theft, but this is a tenuous legal argument in many cases. * CSAM Laws: Laws against child sexual abuse material are robust in many countries. If AI-generated content falls under the definition of CSAM, it is unequivocally illegal. However, the legal definition often requires "real" individuals, leading to debates on how synthetic CSAM should be classified and prosecuted. Some jurisdictions are actively updating their laws to explicitly include AI-generated CSAM. One of the biggest hurdles in combating "AI upload porn" is the challenge of attribution. AI models are often open-source, allowing for anonymous or pseudonymous creation. The use of virtual private networks (VPNs) and sophisticated privacy tools further complicates the task of identifying the perpetrators. Even when a creator is identified, prosecuting them across international borders, especially if the content servers are located in jurisdictions with lax laws, proves exceptionally difficult. Law enforcement agencies face a steep learning curve in understanding the technical intricacies of AI-generated content and tracking its dissemination. There is a growing global consensus that new, specific legislation is needed to address AI-generated non-consensual intimate imagery. Proposed laws often focus on: * Criminalizing Creation and Distribution: Making it a specific offense to create or distribute synthetic explicit content without the depicted individual's consent, regardless of whether a real person was filmed. * Establishing Victim's Rights: Providing clear pathways for victims to request removal of content, seek damages, and have their cases expedited. * Imposing Platform Responsibility: Holding social media platforms, image hosts, and content distribution networks accountable for the rapid detection and removal of such material, perhaps through mandatory reporting mechanisms or fines for non-compliance. * Digital Authenticity and Provenance: Exploring technologies like digital watermarking or content provenance standards to help distinguish AI-generated content from real media. This could help platforms identify "AI upload porn" more effectively. As of 2025, the debate around AI regulation, particularly concerning synthetic media, has intensified. Governments worldwide are grappling with balancing innovation with protection. Jurisdictions like the EU, with its AI Act, are attempting to create comprehensive regulatory frameworks that categorize AI systems by risk, potentially placing generative models under stricter scrutiny, especially when their outputs can cause significant harm. The US is also seeing increased legislative activity at both federal and state levels, but a unified national approach to "AI upload porn" remains elusive due to political divisions and lobbying efforts by tech companies. The legal landscape is a dynamic one, constantly reacting to new technological capabilities.

The generation and "AI upload porn" are not always isolated acts; they often occur within an ecosystem driven by various motivations, including financial gain and community building. Understanding this ecosystem sheds light on the persistence and growth of this type of content. A significant portion of AI-generated explicit content, particularly deepfakes targeting celebrities or public figures, is monetized through subscription-based platforms like Patreon, OnlyFans (though OnlyFans has strict rules against NCII, creators often attempt to circumvent them), or niche adult content sites. Creators offer exclusive access to their AI-generated images, videos, or even custom requests in exchange for monthly fees. This model creates a direct financial incentive for the continuous production and "AI upload porn." Individual pieces of content might also be sold on a pay-per-view basis on specialized forums or dark web markets. Websites hosting large archives of "AI upload porn" often generate revenue through advertising. High traffic volumes attracted by controversial or niche content translate directly into ad impressions and clicks. This model encourages the mass aggregation and accessibility of such content, prioritizing quantity over ethical considerations. Pop-up ads, banner ads, and even malicious ad networks can be found on these sites. The use of cryptocurrencies facilitates anonymous transactions within this ecosystem. For those involved in the creation, distribution, or consumption of illicit "AI upload porn" (such as synthetic CSAM), cryptocurrency offers a layer of obfuscation that traditional banking methods do not, making it harder for law enforcement to track financial flows and identify perpetrators. Beyond direct financial gain, some individuals create and share "AI upload porn" to gain social capital within specific online communities. These communities often value technical prowess in AI generation, the ability to produce highly realistic or novel content, or simply the sharing of forbidden material. Status within these groups can be derived from creating popular deepfakes, sharing large archives, or developing new tools and techniques. This can create a perverse incentive structure where creators are rewarded with recognition and influence rather than monetary compensation. The most problematic forms of "AI upload porn" often reside in the darkest corners of the internet: * Private Forums and Channels: These are often highly curated, invitation-only spaces where content is shared among trusted members. The private nature makes detection and intervention exceedingly difficult for external parties. * Dark Web Markets: Operating outside the indexed surface web, these markets facilitate the buying and selling of all manner of illicit goods, including highly disturbing forms of AI-generated explicit content. The anonymity provided by overlay networks like Tor makes tracking almost impossible. * Decentralized File Sharing: Technologies that enable direct peer-to-peer file sharing, bypassing central servers, also contribute to the difficulty of content moderation and removal. The monetization and distribution ecosystem for "AI upload porn" is thus a multi-layered network, ranging from semi-public subscription sites to highly clandestine dark web operations. The ease of creation, coupled with established and emerging distribution channels, ensures a constant flow of such content, posing significant challenges for regulation and control.

The discussion around "AI upload porn" cannot be complete without directly confronting its most dangerous and destructive applications: exploitation and abuse. While the technology itself is neutral, its misuse enables new forms of harm that leverage the power of synthesis for malicious intent. AI has exponentially amplified the threat of Non-Consensual Intimate Imagery (NCII), commonly known as "revenge porn." Before AI, creating fake explicit images of someone required considerable skill in photo manipulation or access to actual compromising photos. With generative AI, anyone can potentially create hyper-realistic "AI upload porn" depicting any individual, regardless of whether they have ever been involved in explicit photography. This means public figures, colleagues, ex-partners, or even minors can become targets. The ease of creation, coupled with rapid dissemination, makes it a potent weapon for harassment, blackmail, and character assassination. The emotional and professional toll on victims is immense and often long-lasting. The threat of AI-generated content has become a significant tool in sextortion and blackmail schemes. Perpetrators can create highly convincing "AI upload porn" of victims and then demand money, additional explicit content, or other concessions under the threat of public release. The psychological pressure exerted by these deepfakes is immense, as victims often fear the devastating consequences of having such material spread online, even if it is fabricated. This tactic preys on fear and shame, leaving victims in an incredibly vulnerable position. Beyond individual instances, AI-generated explicit content can be weaponized in targeted harassment campaigns. Imagine a group using "AI upload porn" to systematically attack a political figure, an activist, or a journalist, attempting to discredit them, silence their voices, or destroy their reputation. The ability to generate vast amounts of unique, tailored explicit content makes such campaigns more scalable and impactful than ever before. This not only harms the individual but can also undermine public discourse and democratic processes. The most horrifying manifestation of AI's misuse is the creation of synthetic Child Sexual Abuse Material (CSAM). While the debate continues on the legal classification of "virtual" CSAM versus that involving real children, the ethical and societal condemnation is universal. The technology allows for the generation of explicit imagery and videos of fabricated children, or deepfakes of real children onto explicit bodies, without ever involving a living child in a harmful act. However, the existence and distribution of such material, regardless of its origin, is deeply disturbing. It contributes to the demand for real CSAM, normalizes child abuse, and harms society by creating a dark, depraved digital underbelly. The development and deployment of AI models capable of generating CSAM, even with "safety" filters that are often circumvented, represent a profound moral failure for those who develop and distribute such tools. The fight against "AI upload porn" intersects most urgently and tragically with the fight against CSAM.

The destructive potential of "AI upload porn" has spurred efforts from various sectors to develop countermeasures. However, the nature of this challenge resembles an ongoing arms race, where detection methods constantly strive to keep pace with ever-improving generation techniques. Major online platforms (social media, video hosting, image sharing) are on the front lines of this battle. They employ a combination of strategies: * Automated Detection: AI-powered systems are used to scan uploaded content for nudity, explicit acts, and signs of synthetic manipulation. These systems use machine learning to identify patterns associated with "AI upload porn." * Human Moderation: Teams of human moderators review content flagged by AI or reported by users. Human judgment is crucial for nuanced cases and for understanding context that AI might miss. * Hashing and Fingerprinting: Databases of known illicit content (including deepfakes) are maintained using perceptual hashing, which creates a unique "fingerprint" for each piece of media. If an uploaded piece of content matches a known hash, it can be automatically blocked or removed. * Reporting Mechanisms: Users are encouraged to report instances of "AI upload porn" they encounter, contributing to the platform's ability to identify and remove harmful material. * Zero-Tolerance Policies: Most reputable platforms maintain strict zero-tolerance policies against NCII and CSAM, regardless of whether it's AI-generated or not. However, the sheer volume of daily uploads makes comprehensive moderation incredibly difficult. Malicious actors continuously adapt their techniques to bypass filters, creating an endless cycle of detection and evasion. Beyond platform-specific efforts, researchers and companies are developing dedicated AI tools to detect synthetic media. These tools look for subtle artifacts, inconsistencies, or statistical anomalies that differentiate AI-generated content from real media. Techniques include: * Forensic Analysis: Examining pixel-level noise patterns, compression artifacts, or specific rendering characteristics that are unique to certain generative models. * Consistency Checks: Identifying logical inconsistencies in the generated image or video that a human might not immediately notice but are indicative of AI creation (e.g., distorted hands, odd shadows, unrealistic physics). * Deep Learning Classifiers: Training AI models to specifically classify content as real or fake. While these tools are improving, they are often in a reactive state, always playing catch-up to the latest generative models. A new, more advanced generative model can quickly render existing detection methods obsolete. Educating the public about the existence and dangers of AI-generated explicit content is a crucial long-term countermeasure. Promoting digital literacy helps individuals: * Be Skeptical: Learn to critically evaluate media encountered online, especially if it seems too shocking or too good to be true. * Understand the Technology: Grasp the capabilities of generative AI to recognize the possibility of manipulation. * Know How to Report: Be aware of the mechanisms for reporting abusive content on various platforms. * Protect Themselves: Understand privacy settings, be cautious about what they share online, and be aware of the risks associated with public images being used for training data. As discussed, legislative action is paramount. Clear, enforceable laws specifically targeting the creation and dissemination of AI-generated NCII and CSAM are essential. International cooperation is also vital, as "AI upload porn" often crosses national borders, requiring coordinated efforts between law enforcement agencies and legal systems to prosecute perpetrators and remove content. The fight against "AI upload porn" is a multi-faceted challenge requiring a combination of technological solutions, robust legal frameworks, proactive platform policies, and widespread public education. It is an ongoing battle that underscores the critical need for responsible AI development and deployment.

As we move further into 2025 and beyond, the landscape surrounding "AI upload porn" is poised for continued, rapid evolution. Predicting the exact trajectory is difficult, but several trends and potential developments are worth considering. By 2025, generative AI models will likely achieve even higher levels of photorealism, making it virtually impossible for the untrained eye to distinguish AI-generated explicit content from genuine media. Furthermore, the ability to generate such content in real-time or near-real-time will likely become more prevalent, potentially enabling live manipulation during video calls or seamless integration into interactive virtual environments. This would significantly complicate detection efforts and increase the immediacy of potential harm. The rise of AI companions and increasingly immersive virtual worlds (metaverses) presents a dual-edged sword. While these technologies promise new forms of interaction and entertainment, they also open avenues for the creation and "AI upload porn" featuring personalized, explicit AI avatars or characters. Users might be able to interact with AI companions designed to fulfill explicit fantasies, blurring the lines between consensual virtual interaction and problematic, exploitative content, especially if these models are based on real individuals without consent. The arms race between AI generation and detection will undoubtedly intensify. We can expect more sophisticated detection algorithms leveraging novel AI techniques (e.g., adversarial training for detection) and digital forensics. Simultaneously, creators of "AI upload porn" will continue to innovate, developing new methods to obscure AI artifacts, bypass filters, and operate in more decentralized, harder-to-trace environments. This continuous escalation will demand ongoing investment in research and development for countermeasures. By 2025, there will likely be more specific legislation addressing AI-generated synthetic media in various jurisdictions, moving beyond the current patchwork. The debate around platform accountability will also intensify, potentially leading to stronger regulatory pressure on tech companies to implement more robust moderation and removal policies. However, the global nature of the internet means that legal harmonization will remain a significant challenge, creating safe havens for illicit activities in jurisdictions with weaker laws. As the prevalence and sophistication of "AI upload porn" grow, so too will public awareness and demand for accountability. High-profile incidents involving deepfakes or non-consensual AI-generated content will likely spark public outrage and galvanize advocacy groups, leading to increased pressure on lawmakers and tech companies to act. Educational initiatives promoting digital literacy and critical media consumption will become even more vital. The movement towards decentralized web technologies (Web3) and peer-to-peer networks could introduce new complexities. While these technologies promise greater user control and censorship resistance, they also make content moderation and tracking significantly more challenging for authorities and platforms. This could inadvertently provide new avenues for the dissemination of "AI upload porn" that is harder to detect and remove. The future of "AI upload porn" is deeply intertwined with the broader trajectory of AI development and societal responses to its capabilities. It presents a stark reminder that powerful technologies, while offering immense potential for good, also carry significant risks that demand proactive ethical considerations, robust legal frameworks, and a collective commitment to safeguarding individuals and society from harm. The challenge in 2025 and beyond will be to navigate this complex technological landscape with foresight, integrity, and a steadfast commitment to human dignity.

The phenomenon of "AI upload porn" represents one of the most contentious and ethically fraught intersections of artificial intelligence with human society. Born from remarkable advancements in generative AI models like GANs and diffusion models, the ability to create hyper-realistic explicit content, often without the consent of the depicted individuals, poses profound challenges to privacy, consent, and personal autonomy. The ease with which such content can be generated and the myriad channels through which it can be disseminated—from niche forums and encrypted chats to the dark web—create a complex ecosystem that is difficult to monitor and control. The ethical implications are stark: the erosion of consent, the psychological devastation wrought upon victims, the normalization of dehumanization, and the chilling prospect of synthetic child sexual abuse material. These profound harms demand urgent attention and robust responses. While legal frameworks are slowly evolving to address these new forms of digital harm, they often struggle to keep pace with the rapid advancements in AI technology and the global nature of online content distribution. The challenge of attribution and enforcement remains significant, often leaving victims without clear pathways for recourse. Countermeasures are underway, ranging from sophisticated AI detection tools and diligent platform moderation to crucial public awareness campaigns. However, the struggle against "AI upload porn" is an ongoing arms race, with creators constantly seeking to bypass new safeguards. As we look to 2025 and beyond, the technology will only become more sophisticated, demanding a multi-faceted approach that combines technological innovation, strong legislative action, greater platform accountability, and a globally coordinated effort to protect individuals from exploitation. Ultimately, the issue of "AI upload porn" forces a critical societal dialogue about the responsible development and deployment of AI. It underscores the vital importance of embedding ethical considerations at every stage of AI research and application, ensuring that technological progress serves to uplift humanity, rather than becoming a tool for its exploitation and abuse. The digital frontier is vast and ever-expanding, and navigating its complexities requires vigilance, foresight, and a steadfast commitment to human dignity in the age of artificial intelligence.