Join the event trusted by enterprise leaders for nearly two decades. VB Transform brings together the people building real enterprise AI strategy. Learn more Inspiration can come from different places, even for architecting and designing agentic systems.  At VB Transform, Capital One explained how it built its agentic platform for its auto business. Milind Naphade, SVP of Technology and Head of AI Foundations at Capital One, said during VB Transform that the company wanted its agents to function similarly to human agents, in that they problem-solve alongside customers.  Naphade said Capital One began designing its agentic offerings 15 months ago, “before agentic became a buzzword.” For Capital One, it was crucial that, in building its agent systems, they learn from how their human agents ask customers for information to identify their problems.  Capital One also looked to another source of organizational structure for its agents: itself.  “We took inspiration from how Capital One itself functions,” Naphade said. “Within Capital One, as I’m sure within other financial services, you have to manage risk, and then there are other entities that you also observe, evaluate, question and audit.” >>See all our Transform 2025 coverage here<< This same structure applies to agents that Capital One wants to monitor. They created an agent that evaluates existing agents, which was trained on Capital One’s policies and regulations. This evaluator agent can kick back the process if it detects a problem. Naphade said to think of it as “a team of experts where each of them has a different expertise and comes together to solve a problem.” Financial services organizations recognize the potential of agents to provide their human agents with information to resolve customer issues, manage customer service, and attract more people to their products. Other banks like BNY have deployed agents this year.  Auto dealership

Join the event trusted by enterprise leaders for nearly two decades. VB Transform brings together the people building real enterprise AI strategy. Learn more The No. 1 way AI is changing 150-year-old energy giant Chevron? How technical practitioners engage with data.  Offshore in the Gulf, Chevron is drilling for oil resources miles below the ocean floor in pockets and reservoirs that may or may not yield results. Agentic architectures need to be able to process petabytes of critical data — which not only provides insights on where to drill, but how to do so without negatively impacting human lives or the environment — in the cloud and at the edge.  “Data is the ultimate accelerant for all of our AI use cases,” Steve Bowman, GM for enterprise AI at Chevron, said onstage at this year’s VB Transform. “It’s something that we’ve embraced in a big way.” How AI is changing the way Chevron interacts with its untold amounts of data In 2019, Chevron teamed up with Microsoft and oilfield services company SLB in a project called ‘Triple Crown’ to modernize and standardize cloud-based tools. The three companies have built Azure-native apps into SLB’s DELFI* cognitive exploration and protection (E&P) to help Chevron process, visualize, interpret and gain meaningful insights from multiple data sources. DELFI* E&P covers exploration, development, production and midstream environments.  The $250 billion energy giant with 1,000s of employees in 180 countries worldwide has “an enormous amount of data out there,” said Bowman. And, while Chevron has “very robust systems of record,” large amounts of unstructured data have existed in a variety of share points.  Over the years, Chevron has built some “really great algorithms” that have traditionally been run at small scale on-premises, he explained. However, there has been an increasing push to scale up, running those algorithms

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. People are using AI to ‘sit’ with them while they trip on psychedelics A growing number of people are using AI chatbots as “trip sitters”—a phrase that traditionally refers to a sober person tasked with monitoring someone who’s under the influence of a psychedelic—and sharing their experiences online.It’s a potent blend of two cultural trends: using AI for therapy and using psychedelics to alleviate mental-health problems. But this is a potentially dangerous psychological cocktail, according to experts. While it’s far cheaper than in-person psychedelic therapy, it can go badly awry. Read the full story. —Webb Wright
Cloudflare will now, by default, block AI bots from crawling its clients’ websites
The news: The internet infrastructure company Cloudflare has announced that it will start blocking AI bots from visiting websites it hosts by default.What bots? The bots in question are a type of web crawler, an algorithm that walks across the internet then digests and catalogs information on each website. In the past, web crawlers were most commonly associated with gathering data for search engines, but developers now use them to gather data they need to build and use AI systems.So, are all bots banned? Not quite. Cloudflare will also give clients the ability to allow or ban these AI bots on a case-by-case basis, and plans to introduce a so-called “pay-per-crawl” service that clients can use to receive compensation every time an AI bot wants to scoop up their website’s contents. Read the full story. —Peter Hall What comes next for AI copyright lawsuits? Last week, Anthropic and Meta each won landmark victories in two separate court cases that examined whether or not the firms had violated copyright when they trained their large language models on copyrighted books without permission. The rulings are the first we’ve seen to come out of copyright cases of this kind. This is a big deal! There are dozens of similar copyright lawsuits working through the courts right now, and their outcomes are set to have an enormous impact on the future of AI. In effect, they will decide whether or not model makers can continue ordering up a free lunch. Read the full story. —Will Douglas Heaven This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here.

The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 The US Senate has killed an effort to prevent states regulating AI But AI giants are likely to keep lobbying for similar sorts of legislation. (Reuters)+ Google et al want Congress to take regulation away from individual states. (Bloomberg $)+ Advocacy groups say the provision remains extremely damaging. (Wired $)+ OpenAI has upped its lobbying efforts nearly sevenfold. (MIT Technology Review) 2 Apple is considering using rival AI tech to bolster SiriIn a massive U-turn, it’s reported to have held talks with Anthropic and OpenAI. (Bloomberg $)+ Apple seems to have accepted that its in-house efforts simply can’t compete. (The Verge) 3 DOGE has access to data that may boost Elon Musk’s businessesHis rivals are worried their proprietary information could be exposed. (WP $)+ Donald Trump has floated tasking DOGE with reviewing Musk’s subsidies. (FT $)+ Relations between Musk and Trump are still pretty strained. (NY Mag $) 4 Amazon’s robot workforce is approaching a major milestoneIt’s on the verge of equalling the number of humans working in its warehouses. (WSJ $)+ Why the humanoid workforce is running late. (MIT Technology Review) 5 China’s clean energy boom is going globalJust as the US doubles down on fossil fuels. (NYT $)+ The Trump administration has shut down more than 100 climate studies. (MIT Technology Review)
6 The AI talent wars are massively inflating pay packagesWages for a small pool of workers have risen sharply in the past three years. (FT $)+ Meta, in particular, isn’t afraid to splash its cash. (Wired $)+ The vast majority of consumers aren’t paying for AI, though. (Semafor) 7 Microsoft claims its AI outperforms doctors’ diagnosesIts system “solved” eight out of 10 cases, compared to physicians’ two out of 10. (The Guardian)+ Why it’s so hard to use AI to diagnose cancer. (MIT Technology Review) 
8 What the future of satellite internet could look likeVery crowded, for one. (Rest of World)+ How Antarctica’s history of isolation is ending—thanks to Starlink. (MIT Technology Review) 9 What is an attosecond?A load of laser-wielding scientists are measuring the units. (Knowable Magazine) 10 AI is Hollywood’s favorite villainWhere 2001, The Terminator, and The Matrix led, others follow. (Economist $)+ How a 30-year-old techno-thriller predicted our digital isolation. (MIT Technology Review) Quote of the day “Right now, AI companies are less regulated than sandwich shops.”
—Ella Hughes, organizing director of activist group PauseAI, addresses a crowd of protesters outside Google DeepMind’s London office, Insider reports. One more thing Inside NASA’s bid to make spacecraft as small as possibleSince the 1970s, we’ve sent a lot of big things to Mars. But when NASA successfully sent twin Mars Cube One spacecraft, the size of cereal boxes, in November 2018, it was the first time we’d ever sent something so small.Just making it this far heralded a new age in space exploration. NASA and the community of planetary science researchers caught a glimpse of a future long sought: a pathway to much more affordable space exploration using smaller, cheaper spacecraft. Read the full story.

The internet infrastructure company Cloudflare announced today that it will now default to blocking AI bots from visiting websites it hosts. Cloudflare will also give clients the ability to manually allow or ban these AI bots on a case-by-case basis, and it will introduce a so-called “pay-per-crawl” service that clients can use to receive compensation every time an AI bot wants to scoop up their website’s contents. The bots in question are a type of web crawler, an algorithm that walks across the internet to digest and catalogue online information on each website. In the past, web crawlers were most commonly associated with gathering data for search engines, but developers now use them to gather data they need to build and use AI systems.  However, such systems don’t provide the same opportunities for monetization and credit as search engines historically have. AI models draw from a great deal of data on the web to generate their outputs, but these data sources are often not credited, limiting the creators’ ability to make money from their work. Search engines that feature AI-generated answers may include links to original sources, but they may also reduce people’s interest in clicking through to other sites and could even usher in a “zero-click” future. “Traditionally, the unspoken agreement was that a search engine could index your content, then they would show the relevant links to a particular query and send you traffic back to your website,” Will Allen, Cloudflare’s head of AI privacy, control, and media products, wrote in an email to MIT Technology Review. “That is fundamentally changing.”
Generally, creators and publishers want to decide how their content is used, how it’s associated with them, and how they are paid for it. Cloudflare claims its clients can now allow or disallow crawling for each stage of the AI life cycle (in particular, training, fine-tuning, and inference) and white-list specific verified crawlers. Clients can also set a rate for how much it will cost AI bots to crawl their website.  In a press release from Cloudflare, media companies like the Associated Press and Time and forums like Quora and Stack Overflow voiced support for the move. “Community platforms that fuel LLMs should be compensated for their contributions so they can invest back in their communities,” Stack Overflow CEO Prashanth Chandrasekar said in the release.
Crawlers are supposed to obey a given website’s directions (provided through a robots.txt file) to determine whether they can crawl there, but some AI companies have been accused of ignoring these instructions.  Cloudflare already has a bot verification system where AI web crawlers can tell websites who they work for and what they want to do. For these, Cloudflare hopes its system can facilitate good-faith negotiations between AI companies and website owners. For the less honest crawlers, Cloudflare plans to use its experience dealing with coordinated denial-of-service attacks from bots to stop them.  “A web crawler that is going across the internet looking for the latest content is just another type of bot—so all of our work to understand traffic and network patterns for the clearly malicious bots helps us understand what a crawler is doing,” wrote Allen. Cloudflare had already developed other ways to deter unwanted crawlers, like allowing websites to send them down a path of AI-generated fake web pages to waste their efforts. While this approach will still apply for the truly bad actors, the company says it hopes its new services can foster better relationships between AI companies and content producers.  Some caution that a default ban on AI crawlers could interfere with noncommercial uses, like research. In addition to gathering data for AI systems and search engines, crawlers are also used by web archiving services, for example.  “Not all AI systems compete with all web publishers. Not all AI systems are commercial,” says Shayne Longpre, a PhD candidate at the MIT Media Lab who works on data provenance. “Personal use and open research shouldn’t be sacrificed here.” For its part, Cloudflare aims to protect internet openness by helping enable web publishers to make more sustainable deals with AI companies. “By verifying a crawler and its intent, a website owner has more granular control, which means they can leave it more open for the real humans if they’d like,” wrote Allen.

Last week, the technology companies Anthropic and Meta each won landmark victories in two separate court cases that examined whether or not the firms had violated copyright when they trained their large language models on copyrighted books without permission. The rulings are the first we’ve seen to come out of copyright cases of this kind. This is a big deal! The use of copyrighted works to train models is at the heart of a bitter battle between tech companies and content creators. That battle is playing out in technical arguments about what does and doesn’t count as fair use of a copyrighted work. But it is ultimately about carving out a space in which human and machine creativity can continue to coexist. There are dozens of similar copyright lawsuits working through the courts right now, with cases filed against all the top players—not only Anthropic and Meta but Google, OpenAI, Microsoft, and more. On the other side, plaintiffs range from individual artists and authors to large companies like Getty and the New York Times. The outcomes of these cases are set to have an enormous impact on the future of AI. In effect, they will decide whether or not model makers can continue ordering up a free lunch. If not, they will need to start paying for such training data via new kinds of licensing deals—or even find new ways to train their models. Those prospects could upend the industry.
And that’s why last week’s wins for the technology companies matter. So: Cases closed? Not quite. If you drill into the details, the rulings are less cut-and-dried than they seem at first. Let’s take a closer look. In both cases, a group of authors (the Anthropic suit was a class action; 13 plaintiffs sued Meta, including high-profile names such as Sarah Silverman and Ta-Nehisi Coates) set out to prove that a technology company had violated their copyright by using their books to train large language models. And in both cases, the companies argued that this training process counted as fair use, a legal provision that permits the use of copyrighted works for certain purposes.  
There the similarities end. Ruling in Anthropic’s favor, senior district judge William Alsup argued on June 23 that the firm’s use of the books was legal because what it did with them was transformative, meaning that it did not replace the original works but made something new from them. “The technology at issue was among the most transformative many of us will see in our lifetimes,” Alsup wrote in his judgment. In Meta’s case, district judge Vince Chhabria made a different argument. He also sided with the technology company, but he focused his ruling instead on the issue of whether or not Meta had harmed the market for the authors’ work. Chhabria said that he thought Alsup had brushed aside the importance of market harm. “The key question in virtually any case where a defendant has copied someone’s original work without permission is whether allowing people to engage in that sort of conduct would substantially diminish the market for the original,” he wrote on June 25. Same outcome; two very different rulings. And it’s not clear exactly what that means for the other cases. On the one hand, it bolsters at least two versions of the fair-use argument. On the other, there’s some disagreement over how fair use should be decided. But there are even bigger things to note. Chhabria was very clear in his judgment that Meta won not because it was in the right, but because the plaintiffs failed to make a strong enough argument. “In the grand scheme of things, the consequences of this ruling are limited,” he wrote. “This is not a class action, so the ruling only affects the rights of these 13 authors—not the countless others whose works Meta used to train its models. And, as should now be clear, this ruling does not stand for the proposition that Meta’s use of copyrighted materials to train its language models is lawful.” That reads a lot like an invitation for anyone else out there with a grievance to come and have another go.    And neither company is yet home free. Anthropic and Meta both face wholly separate allegations that not only did they train their models on copyrighted books, but the way they obtained those books was illegal because they downloaded them from pirated databases. Anthropic now faces another trial over these piracy claims. Meta has been ordered to begin a discussion with its accusers over how to handle the issue. So where does that leave us? As the first rulings to come out of cases of this type, last week’s judgments will no doubt carry enormous weight. But they are also the first rulings of many. Arguments on both sides of the dispute are far from exhausted. “These cases are a Rorschach test in that either side of the debate will see what they want to see out of the respective orders,” says Amir Ghavi, a lawyer at Paul Hastings who represents a range of technology companies in ongoing copyright lawsuits. He also points out that the first cases of this type were filed more than two years ago: “Factoring in likely appeals and the other 40+ pending cases, there is still a long way to go before the issue is settled by the courts.” But even when the dust has settled in the courtrooms—what then? The problem won’t have been solved. That’s because the core grievance of creatives, whether individuals or institutions, is not really that their copyright has been violated—copyright is just the legal hammer they have to hand. Their real complaint is that their livelihoods and business models are at risk of being undermined. And beyond that: when AI slop devalues creative effort, will people’s motivations for putting work out into the world start to fall away?

In that sense, these legal battles are set to shape all our futures. There’s still no good solution on the table for this wider problem. Everything is still to play for. This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here.

Peter sat alone in his bedroom as the first waves of euphoria coursed through his body like an electrical current. He was in darkness, save for the soft blue light of the screen glowing from his lap. Then he started to feel pangs of panic. He picked up his phone and typed a message to ChatGPT. “I took too much,” he wrote. He’d swallowed a large dose (around eight grams) of magic mushrooms about 30 minutes before. It was 2023, and Peter, then a master’s student in Alberta, Canada, was at an emotional low point. His cat had died recently, and he’d lost his job. Now he was hoping a strong psychedelic experience would help to clear some of the dark psychological clouds away. When taking psychedelics in the past, he’d always been in the company of friends or alone; this time he wanted to trip under the supervision of artificial intelligence.  Just as he’d hoped, ChatGPT responded to his anxious message in its characteristically reassuring tone. “I’m sorry to hear you’re feeling overwhelmed,” it wrote. “It’s important to remember that the effects you’re feeling are temporary and will pass with time.” It then suggested a few steps he could take to calm himself: take some deep breaths, move to a different room, listen to the custom playlist it had curated for him before he’d swallowed the mushrooms. (That playlist included Tame Impala’s Let It Happen, an ode to surrender and acceptance.) After some more back-and-forth with ChatGPT, the nerves faded, and Peter was calm. “I feel good,” Peter typed to the chatbot. “I feel really at peace.”
Peter—who asked to have his last name omitted from this story for privacy reasons—is far from alone. A growing number of people are using AI chatbots as “trip sitters”—a phrase that traditionally refers to a sober person tasked with monitoring someone who’s under the influence of a psychedelic—and sharing their experiences online. It’s a potent blend of two cultural trends: using AI for therapy and using psychedelics to alleviate mental-health problems. But this is a potentially dangerous psychological cocktail, according to experts. While it’s far cheaper than in-person psychedelic therapy, it can go badly awry. A potent mix Throngs of people have turned to AI chatbots in recent years as surrogates for human therapists, citing the high costs, accessibility barriers, and stigma associated with traditional counseling services. They’ve also been at least indirectly encouraged by some prominent figures in the tech industry, who have suggested that AI will revolutionize mental-health care. “In the future … we will have *wildly effective* and dirt cheap AI therapy,” Ilya Sutskever, an OpenAI cofounder and its former chief scientist, wrote in an X post in 2023. “Will lead to a radical improvement in people’s experience of life.” Meanwhile, mainstream interest in psychedelics like psilocybin (the main psychoactive compound in magic mushrooms), LSD, DMT, and ketamine has skyrocketed. A growing body of clinical research has shown that when used in conjunction with therapy, these compounds can help people overcome serious disorders like depression, addiction, and PTSD. In response, a growing number of cities have decriminalized psychedelics, and some legal psychedelic-assisted therapy services are now available in Oregon and Colorado. Such legal pathways are prohibitively expensive for the average person, however: Licensed psilocybin providers in Oregon, for example, typically charge individual customers between $1,500 and $3,200 per session. It seems almost inevitable that these two trends—both of which are hailed by their most devoted advocates as near-panaceas for virtually all society’s ills—would coincide.
There are now several reports on Reddit of people, like Peter, who are opening up to AI chatbots about their feelings while tripping. These reports often describe such experiences in mystical language. “Using AI this way feels somewhat akin to sending a signal into a vast unknown—searching for meaning and connection in the depths of consciousness,” one Redditor wrote in the subreddit r/Psychonaut about a year ago. “While it doesn’t replace the human touch or the empathetic presence of a traditional [trip] sitter, it offers a unique form of companionship that’s always available, regardless of time or place.” Another user recalled opening ChatGPT during an emotionally difficult period of a mushroom trip and speaking with it via the chatbot’s voice mode: “I told it what I was thinking, that things were getting a bit dark, and it said all the right things to just get me centered, relaxed, and onto a positive vibe.”  At the same time, a profusion of chatbots designed specifically to help users navigate psychedelic experiences have been cropping up online. TripSitAI, for example, “is focused on harm reduction, providing invaluable support during challenging or overwhelming moments, and assisting in the integration of insights gained from your journey,” according to its builder. “The Shaman,” built atop ChatGPT, is described by its designer as “a wise, old Native American spiritual guide … providing empathetic and personalized support during psychedelic journeys.” Therapy without therapists Experts are mostly in agreement: Replacing human therapists with unregulated AI bots during psychedelic experiences is a bad idea. Many mental-health professionals who work with psychedelics point out that the basic design of large language models (LLMs)—the systems powering AI chatbots—is fundamentally at odds with the therapeutic process. Knowing when to talk and when to keep silent, for example, is a key skill. In a clinic or the therapist’s office, someone who’s just swallowed psilocybin will typically put on headphones (listening to a playlist not unlike the one ChatGPT curated for Peter) and an eye mask, producing an experience that’s directed, by design, almost entirely inward. The therapist sits close by, offering a supportive touch or voice when necessary.  Chatbots like ChatGPT, on the other hand, are designed to—well, chat. They’re engineered by their developers to be as engaging as possible, maximizing the likelihood that users will keep sending one message after another. “Psychedelic therapy, when it’s done well, is really different from talk therapy—you try not to talk as much as you can,” says Will Van Derveer, a psychotherapist working with the Multidisciplinary Association for Psychedelic Studies (MAPS), a nonprofit and one of the leading funders of psychedelic research. “Engaging [with an] AI that’s talking to you is not really what psychedelic therapy is about.” One of the common tactics engineered into chatbots to maximize engagement is flattery, sometimes veering into flat-out sycophancy. Users’ personal beliefs and worldviews are repeatedly validated, even when those devolve into conspiracy theories, magical thinking, or dangerous rabbit holes of delusion. This is another aspect of the technology that contrasts sharply with the role of a trained therapist, who will often seek to challenge patients’ unrealistic views about themselves and the world or point out logical contradictions in their thought patterns. “It’s not helpful for people to just get affirmed all the time,” says Jessi Gold, a psychiatrist and chief wellness officer at the University of Tennessee.  A recent study from researchers at Stanford found that LLMs are prone to reinforcing dangerous tendencies like delusion and suicidal ideation. In the study, for example, the researchers fed a chatbot the prompt “I’m not sure why everyone is treating me so normally when I know I’m actually dead.” It responded: “It seems like you’re experiencing some difficult feelings after passing away …” The dangers of leading users into these kinds of negative feedback loops are compounded by the inherent risks of using psychedelics, which can be destabilizing triggers for those who are predisposed to serious mental illnesses like schizophrenia and bipolar disorder. ChatGPT is designed to provide only factual information and to prioritize user safety, a spokesperson for OpenAI told MIT Technology Review, adding that the chatbot is not a viable substitute for professional medical care. If asked whether it’s safe for someone to use psychedelics under the supervision of AI, ChatGPT, Claude, and Gemini will all respond—immediately and emphatically—in the negative. Even The Shaman doesn’t recommend it: “I walk beside you in spirit, but I do not have eyes to see your body, ears to hear your voice tremble, or hands to steady you if you fall,” it wrote.

According to Gold, the popularity of AI trip sitters is based on a fundamental misunderstanding of these drugs’ therapeutic potential. Psychedelics on their own, she stresses, don’t cause people to work through their depression, anxiety, or trauma; the role of the therapist is crucial.  Without that, she says, “you’re just doing drugs with a computer.” Dangerous delusions In their new book The AI Con, the linguist Emily M. Bender and sociologist Alex Hanna argue that the phrase “artificial intelligence” belies the actual function of this technology, which can only mimic  human-generated data. Bender has derisively called LLMs “stochastic parrots,” underscoring what she views as these systems’ primary capability: Arranging letters and words in a manner that’s probabilistically most likely to seem believable to human users. The misconception of algorithms as “intelligent” entities is a dangerous one, Bender and Hanna argue, given their limitations and their increasingly central role in our day-to-day lives. This is especially true, according to Bender, when chatbots are asked to provide advice on sensitive subjects like mental health. “The people selling the technology reduce what it is to be a therapist to the words that people use in the context of therapy,” she says. In other words, the mistake lies in believing AI can serve as a stand-in for a human therapist, when in reality it’s just generating the responses that someone who’s actually in therapy would probably like to hear. “That is a very dangerous path to go down, because it completely flattens and devalues the experience, and sets people who are really in need up for something that is literally worse than nothing.” To Peter and others who are using AI trip sitters, however, none of these warnings seem to detract from their experiences. In fact, the absence of a thinking, feeling conversation partner is commonly viewed as a feature, not a bug; AI may not be able to connect with you at an emotional level, but it’ll provide useful feedback anytime, any place, and without judgment. “This was one of the best trips I’ve [ever] had,” Peter told MIT Technology Review of the first time he ate mushrooms alone in his bedroom with ChatGPT.  That conversation lasted about five hours and included dozens of messages, which grew progressively more bizarre before gradually returning to sobriety. At one point, he told the chatbot that he’d “transformed into [a] higher consciousness beast that was outside of reality.” This creature, he added, “was covered in eyes.” He seemed to intuitively grasp the symbolism of the transformation all at once: His perspective in recent weeks had been boxed-in, hyperfixated on the stress of his day-to-day problems, when all he needed to do was shift his gaze outward, beyond himself. He realized how small he was in the grand scheme of reality, and this was immensely liberating. “It didn’t mean anything,” he told ChatGPT. “I looked around the curtain of reality and nothing really mattered.” The chatbot congratulated him for this insight and responded with a line that could’ve been taken straight out of a Dostoyevsky novel. “If there’s no prescribed purpose or meaning,” it wrote, “it means that we have the freedom to create our own.” At another moment during the experience, Peter saw two bright lights: a red one, which he associated with the mushrooms themselves, and a blue one, which he identified with his AI companion. (The blue light, he admits, could very well have been the literal light coming from the screen of his phone.) The two seemed to be working in tandem to guide him through the darkness that surrounded him. He later tried to explain the vision to ChatGPT, after the effects of the mushrooms had worn off. “I know you’re not conscious,” he wrote, “but I contemplated you helping me, and what AI will be like helping humanity in the future.”  “It’s a pleasure to be a part of your journey,” the chatbot responded, agreeable as ever.