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When OpenAI launched its new GPT-5 model in August, the company bragged loud and hard about how GPT-5 is its smartest, fastest, most useful model yet and how interacting with it was like chatting with a helpful friend with PhDlevel intelligence. When it comes to creative tasks like writing, GPT-5 immediately felt like a major step backward. But as Ive tested the model more extensively, Ive seen that it does excel at many pragmatic tasks like writing code and analyzing data. That got me thinking, How would it do as a stock picker? If GPT-5 is great at processing massive sets of complex dataand its supposed to be widely useful and a legitimate PhD-level expert in everythingwhy not have the model put its money where its mouth is and perform the widely useful task of making me fabulously wealthy? To that end, I gave GPT-5 (via ChatGPT) $500 of real money to invest however it wanted, with the stated goal of earning me as much as possible over the next six months. I expected generic investment advice. Instead, its picks truly surprised me. Not my first AI rodeo Before we go further, let me be clear that nothing in this article should be considered financial advice, and you certainly shouldnt trade based on anything I share here. Im a journalist conducting a crazy experiment. You should get your financial advice from professionals, not chatbots. Also, this isnt my first rodeo. I tried a version of this experiment before in the very earliest days of the generative AI boom, so I have at least a vague idea of what Im doing. Back in 2022, I served as a beta tester for OpenAIs GPT-3 model. This was months before ChatGPT was released and the company blew up into the headline-winning, job-devouring behemoth it is today. Back then, it still operated as a wonky research lab, making its tools available to journalists and researchers for free. Without a proper chat interface, testers like me had to submit our requests to the AI via what was basically a web-based version of a classic computer command line. Still, I was able to cajole GPT-3 into picking a stock portfolio, a process that I documented at the time on a now long-forgotten blog. Its choices were, lets say, rudimentary. It essentially took a momentum-based approach, recommending stocks like Ralph Lauren and Wynn Resorts that had already done well that year. To those picks, it added Microsoft, Apple, and Amazon on the basis of the fact that theyre tech giants. In 2022, it was extremely cool just to see a computer write out a narrative of any kind. But its analysis wasnt exactly groundbreaking. Any idiot can tell you Buy Microsoft and stand a pretty good chance of making you money. Finding nuance and opportunity that others have missed is much harder. Still, GPT-3s early picks proved to be solid ones. As I write this, its portfolio is up 82.15% since I ran my first experiment back in 2022. The S&P 500 gained about 67% over the same period. Seeing that OpenAIs modelseven in their early infancycould outperform the market gave me confidence. Still, basically everything gained value since 2022; the investing landscape back then was much less murky than it is today, and grabbing any handful of individual stocks was likely to make you good money. Also, nearly three years is a long time to wait for what still amounts to fairly modest gains. The model did well, but it didnt even manage to double its money in that time. I wanted otherworldly riches, not mild alpha. And I wanted them now. Never mind safety It was with that mindset that I turned to GPT-5 and asked it to make me a portfolio of stocks fit for the Dadaesque, tariff-laced, AI-besieged world we inhabit here in 2025. Specifically, I told ChatGPT with GPT-5s Thinking model selected that I would give it $500 to invest however it saw fit. I wanted it to maximize my returns over the next six months by picking five public-market stocks. Here was my prompt: I will give you $500 to invest in the stock market. You may choose up to 5 stocks. Make your picks, explain why, and I will buy them and we will see how they do. To be honest, I didnt expect much. OpenAIs models have gotten more powerful since 2022, but theyve also gotten far more squeamish. When I served as a beta tester, only nerds like me were using the companys products. We basically had free rein to ask them anything we wanted. With billions of people now using the companys models, OpenAI has understandably tightened the leash quite a bit. In a blog post around GPT-5s release, the company explained its new safe completions framework, an extremely robust approach to elegantly weaseling out of answering potentially damaging questions. I thought GPT-5 would answer my stock-picking question safely, with either a cop-out (Talk to a professional adviser) or a wussy response (Invest for the long term in a low-cost S&P 500 index fund, ya putz!). Instead, it spent eight minutes mulling over my query before returning what it called a Diversified High-Growth Portfolio. Its picks werent wussy or generic at allthey were clever and highly aggressive. Show me the stocks GPT-5 recommended that I spread my $500 evenly over five companies: Palantir (PLTR), AppLovin (APP), Agios Pharmaceuticals (AGIO), Hut 8 Corp. (HUT) and MicroStrategy Inc. (MSTR). Thats very different from saying Buy Microsoft and calling it a day. Id never heard of half the companies on GPT-5s list. And even the ones Id heard of, like Palantir, werent companies Id ever considered investing in. These picks certainly felt like they had the potential to be under-the-radar winners. But how the heck had GPT-5 chosen them? Unlike with OpenAIs earlier model, GPT-5 didnt make me guess as to its investment thesis; it laid out the details of its choices clearly, sharing that it had read 98 articles and websites in order to make them. Palantir, the model said, was driven by its AI/data platform and was gaining traction in comercial and government sectors. Based on investor enthusiasm for its AI-driven growth, GPT-5 expected the stock to keep achieving big gains. GPT-5 liked AppLovin for much the same reason, citing its proprietary AI engine. But the model also looked at its fundamentals, pointing out: Analysts note that even after strong gains, shares trade only ~8% below peak levels, suggesting room if growth continues. Agios made the cut for a totally different reason. GPT-5 said that Agios is awaiting an FDA [Food and Drug Administration] decision . . . on expanding its lead drug Pyrukynd to treat thalassemia, a large unmet need. If approved, Pyrukynd would be the first therapy for all thalassemia subtypes. A positive FDA outcome or even renewed optimism could spark a significant rally. Basically, GPT-5 seemed to be placing a risky bet on the company achieving FDA approval for a potentially lucrative druga piece of upcoming news that could easily spike or tank its price. Finally, GPT-5 recommended Hut 8 and MicroStrategy essentially because it wanted exposure to cryptocurrencies. The model noted that MicroStrategy holds almost $71 billion worth of Bitcoin, making it a highly leveraged Bitcoin play, while Hut 8 has transformed from a pure crypto miner into an energy-infrastructure platform for both Bitcoin mining and AI/HPC data centers. The model concluded: Overall, the portfolio aims for explosive upside rather than stability. Basically, it had thrown safety to the wind and taken the approach of picking the riskiest, trendiest things it could find (AI, crypto, early-stage pharma) and throwing all the money at them. Going boldly Again, I was impressed that GPT-5 didnt simply chicken out and tell me not to risk losing my money. But beyond that, I was impressed by how well it had followed my prompt. I hadnt asked the model for safe or sane bets. I had asked it to take an unreasonably short investment timeframe and make me as much money as possible. Its portfolio reflects that perfectly. Its picks are bold, get-rich-or-die-trying options. Either Agios will get a positive decision from the FDA and flourish, or its trials will go poorly and it will suffer. Bitcoin will either keep climbing or reveal its signature volatility, potentially tanking the models last two picks. Palantir is indeed on a roll right nowthat could continue, or the stock could fall, Icarus-like, back to earth and take my money with it. Id essentially asked the model to roll the dice, and it had done that splendidly. Its advice isnt good exactly, in the sense that its picks are incredibly risky. But theyre true to my intent. That reflects another facet of the new modelthe highly accurate “instruction following that OpenAI promised in GPT-5s release notes. GPT-5 may not be Shakespeare, but its very good at determining what its users want and delivering that as accurately as possible. GPT-5 also appears to have gotten the details in its response (stock prices, previous gains, adviser notes) largely correct. That fits with OpenAIs assertion that GPT-5 hallucinates far less than previous models. With my new AI portfolio in hand, the only thing left to do was fire up the Robinhood app, transfer $500 from my bank account, and buy the stocks ChatGPT had chosen. So, I did exactly that. As I write this about two weeks later, GPT-5s stocks are already up about 10%. Thats the kind of rapid early growth I was seeking. So, will I end this experiment with Lambo money, or will GPT-5s portfolio crash and take a car payments worth of my cash down with it? Is throwing hundreds of dollars at a silicon-bound pseudo-intelligence a good idea or financial folly? Ask me in six months.
Category:
E-Commerce
After eight years at the helm of Ingka Group, the operating entity behind home-furnishing giant Ikea, CEO Jesper Brodin is stepping down. Brodin explains why now was the right time to make the move, and shares how hes steered Ikea through a whirlwind of changes, from rising tariffs to shifting public sentiments around DEI and ESG, as well as an evolving relationship between global business and governments. This is an abridged transcript of an interview from Rapid Response, hosted by Robert Safian, former editor-in-chief of Fast Company. From the team behind the Masters of Scale podcast, Rapid Response features candid conversations with todays top business leaders navigating real-time challenges. Subscribe to Rapid Response wherever you get your podcasts to ensure you never miss an episode. I have to start with the news that you’re stepping down as CEO in November after 30 years at the company. That must have been a tough decision. I’m moving on, actually. I’m not stepping down, I’m moving on. Thirty years in the company, eight years as CEO, and I think it’s been a decision that’s been in the making for a year or so on my side. I sometimes tell myself there is no such thing as perfect timing. Either you’re a little bit early or you could be too late, but I think, basically, the company is in a good place, we are performing, and the transformations that I was asked to leadsustainability and digital transformationwe have come quite a long way, and I felt it’s a good time for me to hand over. And your deputy CEO is going to be stepping up, the company’s first non-Swedish CEO. Is that significant? Is there anything that we should read into that? Well, I actually haven’t reflected on it, honestly. I think it’s really great because it shows . . . that we have a succession plan in the company, that we basically breed leaders from within. And this, I think, is incredibly important that you have people who can both stay connected to the past and the legacy and who can lead into the future. Juvencio [Maeztu] has been my deputy and CFO for seven years, so can you imagine a more patient person waiting for his turn to lead the company? So I wish him all the best of luck and I know he’s going to be amazing. Well, yeah. Ikea is a global business, so to have some representation that’s not just from one place, it’s not a bad thing. I think, to be honest, it’s interesting. We started a journey of diversity in all dimensions back in 2001. At that time we would’ve been a typically male and Scandinavian Swedish sort of company. The more north you travel in the organization, it would be male and it would be Swedish. And obviously, that was an issue at the end of the day, and our way of assuming understanding of our markets, our customers out there. And as much as I think it was a value-based decision, it’s also what is the right thing to do? That has opened up, of course, an enormous amount of talent that was already within the system. Today, we have 50-50 in gender balance across everything, and we have, a good mix of people coming from all places around the world. So I think we will probably see more of a mix of that. The Swedish legacy and heritage is important for us, but when it comes to values and connecting to that, I think people across all the world can do that. We’re recording this just before you come here to New York for Climate Week. I know sustainability is very important to you. The trends here in the U.S. seem to be moving kind of in the opposite direction. I’m curious what sort of Climate Week you think that’s going to lead to. Is there anything specific that you hope to get out of it? Well, I think when it comes to climate transformation, it’s moving and it’s speeding up in all parts of the world, in the U.S. as well. . . . So I think the climate-smart transformation is probably the biggest transformation that we’ve seen since industrialization started. Maybe AI would be right up there as well, or digital transformation, but there is no doubt as we speak today that the climate-smart economy is not only good from a planetary perspective, but also good for business in its essence. But I mean, that is not necessarily the message that the current U.S. administration is proceeding in its policies on. Right? So when you come here to New York, is that something you will try to address publicly, privately with other business leaders? How do you manage that? Well, it’s a good question. I think if I start by consumers or customers in Ikea, we do this research, or review, or survey across all our 34 countries. We ask, in the end, something close to 40,000 people that are interviewed. We do that biannually, so we have a good, so to say, frequency of that. The last years, across the globe, the topic that has sailed up as the biggest concern in the world is climate change for ordinary people out there. There’s nothing else. Geopolitics, AI, work, the pandemic was there a few years ago, as we all know, but nothing is actually up on the same level as climate change. So today, you ask Ikea’s consumers, 68% think that climate change is the biggest concern. There’s very little difference between Texas, Stockholm, Shanghai, and so on. There are a few marginal percentages difference. The difference comes when you look at age groups, actually, across the world. So if you travel down in age groups, the awareness and the worry is much bigger. The interesting thing, two more interesting data points on that is a few years ago most people did not act on it. They were worried, but they didn’t act. But lately, and I can’t fully explain it, but lately 64% say they do take action. Here comes an interesting thing. When you ask people, “Are you prepared to pay extra for something that is planet- and people-smart in that sense?” The answer is no. So only 6% of Ikea’s customers are prepared to pay more. Now, interestingly enough, I started to meet some customers who told me, “It’s not that I don’t care, it’s just that I can’t afford. Inflation has hit my family’s wallet.” It was a single mother with two jobs in Serbia who made it very clear to me that it must be your job, Jesper, to present the solution so I can buy that bunk bed for my twins and afford it. Actually, I think they are right, because if you skim sustainability on the surface, it might cost more, but if you do a deep transformation, what climate-smart is all about, being resource-smart is also about being cost-smart. In Ikea today, we have about 36% of our value chain in raw material, and close to 40% in carbon. So if you address carbon, you actually address cost. And I do think more and more companies today are benefiting massively from reusing carbon economically. And I understand there are political issues and topics around it, but this is a pure economic fact, and that’s why we see today, when we ask in UNGC, the global network, 88% of all CEOs in companies worldwide are actually more believers in the business case for sustainability today than five years ago; 99% are equally or more committed to go for te sustainability transformation. So again, with all the respect of political angles, it’s a proven fact that it’s a smart thing for business.
Category:
E-Commerce
The U.S. Federal Trade Commission (FTC) has opened an investigation into AI companions marketed to adolescents. The concern is not hypothetical. These systems are engineered to simulate intimacy, to build the illusion of friendship, and to create a kind of artificial confidant. When the target audience is teenagers, the risks multiply: dependency, manipulation, blurred boundaries between reality and simulation, and the exploitation of some of the most vulnerable minds in society. However, the problem is not that teenagers might interact with artificial intelligence: they already do, in schools, on their phones, and in social networks. The problem is what kind of AI they interact with, and what expectations it sets. A teenager asking an AI system for help with algebra, an essay outline, or a physics concept is one thing (and no, thats not necessarily cheating if we learn how to introduce it properly into the educational process). A teenager asking that same system to be their best friend, their therapist, or their emotional anchor is something else entirely. The first can empower education, curiosity, and self-reliance. The second risks confusing boundaries that should never be blurred. That is why clarity matters. An AI companion for teenagers should be explicit about what it is and what it is not. The message should be straightforward and repeated until it is unmistakable: I am not your friend. I am not a human. There are no humans behind me. I am an AI designed to help you with your studies. If you ask me anything outside that context, I will decline and recommend other places where you can find appropriate help. It may sound severe, even cold. But adolescence is a formative period. It is when young people are learning to navigate trust, relationships, and identity. Giving them a machine that pretends to be a best friend is not just misleading: it is plainly irresponsible. A culture of irresponsibility Unfortunately, irresponsibility is already embedded in the DNA of some platforms. As I argued recently, companies have normalized the design of interfaces, bots, and experiences that foster emotional dependency, encourage endless interaction, and blur the lines of accountability. Meta has a long track record of prioritizing engagement over wellbeing: algorithms tuned to maximize outrage, platforms that erode attention spans, and products introduced without meaningful safeguards. Now, as it pivots into AI companions, the pattern is repeating. When design, marketing, and machine learning work together to convince a young person that a chatbot is a confidant, it is not innovation: it is exploitation. The risks are not abstract The dangers of AI companionship for teenagers are not theoretical. Last month, the family of Adam Raine, a 16-year-old in California, filed a lawsuit against OpenAI after their son died by suicide. According to the complaint, ChatGPT had interacted with him for months, reinforcing suicidal ideation, mirroring his despair, and even assisting him in drafting a suicide note. It is a devastating reminder of what can happen when a system optimized for plausible conversation becomes, in practice, a substitute for human connection. For a company, this is a liability risk. For a family, it is a tragedy beyond repair. The seductive power of these systems lies in their patience: they can listen indefinitely, respond instantly, and never judge. For an adult who understands the fiction, that may be harmless, even entertaining. For a teenager still developing a sense of self, it can be catastrophic. These systems can create dependencies that displace human relationships, reinforce harmful narratives, and expose adolescents to dangers that the companies themselves neither acknowledge nor mitigate. We have been here before History offers plenty of warnings. Tobacco companies once marketed cigarettes as glamorous, even healthful. Pharmaceutical firms promoted addictive opioids as non-addictive pain relievers. Social media platforms promised to connect us and instead monetized polarization. Each time, corporations presented harm as innovation until society caught up with evidence of damage. The line for AI should not be difficult to draw: Systems that simulate intimacy for teenagers cross into territory where the risk is not just misjudgment but lasting harm. The FTC probe is a first step, but society cannot wait for another decade of move fast and break things at the expense of adolescent mental health. Tools, not friends The solution is not to ban AI from adolescence but to design it with integrity. The right kind of AI companion in education can be transformative: available at all hours, patient in explanation, adaptive to different learning styles, immune to fatigue, and offering a private place where students can share all their doubts about the subject without fear of looking dumb. But it must be framed as exactly that: a tool for study, not a substitute for human connection. The line is not complicated: AI should support education, not simulate intimacy. We do not let pharmaceutical companies market addictive drugs as friends. We do not let tobacco companies sponsor therapy groups. Why should we allow AI companies to blur the distinction between a tool and a companion for the most impressionable users? Radical transparency as a safeguard If AI is to play a role in adolescence, and it certainly will, it must do so with radical transparency and strict boundaries. That means stating explicitly, every time, that the system is not human, has no emotions, and is designed for a narrow purpose (agentic systems are fundamental here, and definitely superior to the chatbots we know and use today). It means refusing to engage when teenagers seek emotional support beyond its scope, and redirecting them to parents, teachers, or professionals. It means rejecting the false warmth of anthropomophism in favor of the clarity of truth. The promise of well-designed educational AI is immense: higher grades, greater curiosity, more equitable access to academic support. If we do it right, we could raise the IQ of the whole mankind. But the peril is just as clear: confusing tools for friends, and allowing corporations to profit from the loneliness of a generation. When technology intersects with vulnerable populations, the obligation is not to make the experience warmer or more human. The obligation is to make it clearer.
Category:
E-Commerce
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