Oct 9, 2026 · 11 min listen · Last updated October 9, 2026
From storyflo. This is your daily audio brief. Theo here. October 9th, tech desk. Five stories from the last twenty-four hours — here's where I'd start. Let's get into it. First, from MIT Technology Review · AI. Roundtables: A Conversation With the Creator of AI-Designed Viruses.
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Daily A.I. Brief · October 9th
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Roundtables: A Conversation With the Creator of AI-Designed Viruses
So, there's this fascinating conversation happening with Samuel King, a PhD student at Stanford, who’s been exploring the idea of using AI to design genetic blueprints for viruses. He’s not creating life just yet, but he’s definitely laying the groundwork for what could be a new frontier in biology. Imagine AI not just analyzing existing life forms but actually proposing new ones. That’s where his work is headed.
In the interview, James O’Donnell, an AI reporter, dives into King’s journey and what it means to be recognized as one of MIT Technology Review’s Innovators Under 35. They discuss how this approach could change our understanding of biology and the ethical implications that come with it. It’s a thought-provoking topic, especially considering how rapidly technology is evolving.
The conversation is set to go live on October 16th, so if you’re curious about the intersection of AI and biology, it sounds like a great opportunity to hear directly from someone at the forefront of this research. It’s a blend of science and creativity that really makes you think about the future.
AI Stock Rankings: What Changes the Top Ten? | EP 001
In this episode, we dive into the intricacies of AI stock rankings, focusing on how different time horizons and sorting methods impact the top ten lists. It’s interesting to note that only six stocks remained consistent when shifting from a one-year to a five-year ranking, and just two held their ground when the focus changed to one-year returns. This highlights how sensitive these rankings can be to the criteria we use.
The research, conducted on a cohort of 383 equities, emphasizes the importance of understanding the context behind these rankings. The dates for the data collection span from September 18 to October 5, 2026, offering a snapshot of how these stocks performed historically rather than predicting future outcomes. So, while the rankings can provide insights, they’re not foolproof indicators of what to invest in next.
The episode encourages listeners to think critically about the metrics that influence these AI-generated lists. It’s a reminder that just because a stock makes the top ten doesn’t mean it’s a guaranteed win. The conversation revolves around the nuances of investment strategies, urging us to look beyond the surface. If you’re curious about how these AI systems work and what factors really matter, this episode is a great listen.
Adobe’s AI Investment Thesis: A Billion Users—Who Pays? | EP 002
Adobe is hitting a major milestone with a billion monthly users, which raises an interesting question about monetization. The crux of the discussion is whether they can convert AI productivity into a consistent revenue stream. They’re looking at various factors, like how they can monetize workflows, the costs associated with AI inference, and the dynamics between user adoption and actual revenue.
In their latest earnings report, Adobe shared that they made $6.76 billion in revenue, with annual recurring revenue hitting $27.5 billion. The growth in AI-focused revenue is impressive, over 150%, but the report doesn’t specify the total size of that segment. There’s also a dated model predicting stock performance, suggesting a potential price increase over the next year, but it's important to note that this is conditional research and not a guaranteed return.
Overall, the focus is on whether Adobe can effectively leverage their massive user base to create sustainable revenue, especially as they continue to invest heavily in AI. It’s a fascinating intersection of technology and business strategy, and it’ll be interesting to see how they navigate this landscape.
AI Investment Forecasts: Where Are the Receipts? | EP 004
In this episode, the focus is on how we can actually verify AI investment forecasts. It dives into the nitty-gritty of what makes a forecast credible—like the importance of having clear records that show when and how predictions were made. They analyzed a metadata audit from October 2026, which looked at 746 public consensus records, but it didn’t go deep into validating every detail or checking the accuracy of those forecasts.
The discussion highlights the difference between missing data and irrelevant data, and how that impacts our understanding of forecasts. They also touch on the tools available for deeper insights, like the iPulse AI research and the Forecast Library, which can help analyze past predictions. But even with these tools, it’s clear that just having a digest of past forecasts isn’t enough to prove investment skill or the accuracy of inputs.
It’s a reminder that while AI can sound convincing, we need to dig deeper to really understand the evidence behind those forecasts.
AI vs Wall Street: What Investment Ratings Hide | EP 003
So, here’s the scoop on how AI is shaking things up on Wall Street. You know those “Buy” ratings? They can sometimes mask a whole bunch of analysts just sitting on the fence, leaning towards a “Hold.” It’s a bit like when everyone in a group chat agrees to go out, but no one really wants to. Companies like Adobe and Tata Consultancy Services are showing us that while AI can give a shiny score, it doesn’t always mean there’s a solid consensus behind it.
What’s interesting is that having fourteen different advisor opinions doesn’t necessarily mean you’ve got fourteen independent forecasts. They might just be echoing each other, which doesn’t help when you’re trying to figure out if a stock will actually outperform in the long run. Plus, those one-year and five-year forecasts? They’re still up in the air, leaving investors in a bit of a fog.
The research dives deep into how these consensus scores are calculated and what they really mean for investors. It’s a reminder that while AI can analyze data at lightning speed, it’s not a crystal ball. So, if you’re looking at those ratings, just know there’s more beneath the surface than meets the eye.
Alphabet is really making strides in the AI space, but there’s a lingering question about how that translates to cash flow. In this episode, they dive into how their core areas like Search, AI, and Google Cloud are performing, especially after the infrastructure bill. It’s fascinating to see how they’re analyzing earnings quality and cash conversion, looking at different scenarios—base, bull, and bear—while also considering various factors that could impact their trajectory.
The episode leans heavily on a recent research batch from iPulse AI, which gives a snapshot of where Alphabet stands as of September 2026. They’re comparing this to earlier forecasts, which adds a layer of depth to understanding their financial health. The quarterly scenario table they discuss averages out different opinions, which is crucial for grasping the broader market sentiment.
What’s particularly interesting is their focus on the “alpha gap” and advisor disagreements. It’s a reminder that even in a booming sector, there’s a lot of debate about the best way forward. They also touch on key upcoming milestones that could shape how investors view Alphabet in the next few quarters. Overall, it’s a thoughtful look at the interplay between innovation and financial performance, and it makes you think about what’s next for them in this rapidly evolving landscape.
So, there’s this interesting discussion about Intuit and its position in the AI landscape. The podcast dives into whether AI can enhance QuickBooks' financial workflow or if it just opens the door for competitors. Over the past five years, Intuit's ranking improved from 7 to 4, which sounds good, but the changes in how they measure things make it hard to pinpoint if the company itself is actually getting better.
The investment outlook is pretty nuanced. The base case hinges on solid accounting practices and smart share buybacks, while the optimistic scenario relies on more businesses adopting their AI tools. On the flip side, there's concern about price wars and customer loyalty, especially as small businesses face challenges. They also break down cash flow numbers, showing a substantial operating cash figure but reminding us that these aren't live valuations.
What’s fascinating is how they separate the AI forecasts from traditional earnings expectations. It’s a reminder that while AI can offer insights, it doesn’t replace the need for real-world data. Overall, it’s a thoughtful exploration of how Intuit might navigate the evolving tech landscape.
In this episode, they dive into gold as a potential safe haven, but with a nuanced view. The discussion hinges on reserve demand versus real yields, exploring how these factors influence gold's value. They highlight a significant shift in forecasts from July to September, with the price anchor at $4,380.92 per troy ounce and projected targets reaching $4,529 in a year and $6,250 in five years.
Interestingly, the opinion mean for five-year forecasts increased from 6.55% to 7.63%, indicating a more optimistic outlook, while the annual mean absolute deviation tightened significantly. They emphasize that these figures are model forecasts rather than guaranteed returns, reminding listeners that mining costs don't necessarily create a price floor for gold.
Key indicators to watch include central bank purchases, ETF holdings, and jewelry demand, all of which can impact gold's trajectory. The episode also touches on the split among advisors regarding gold's future, and the importance of understanding the broader economic context, including real yields and policy decisions from the Federal Reserve. It's a thoughtful examination of gold's role in the market, encouraging listeners to stay informed and cautious.
Nike's facing a pivotal moment, grappling with whether it's on the path to a comeback or just a value trap. The latest analysis dives deep into its investment landscape, weighing channel economics and various scenarios that could play out. They’ve anchored their research to a price of $35.51, with ambitious targets of $42 and $75 over the next one to five years. But remember, these are projections, not guarantees.
The analysis highlights the importance of cash flow and earnings, especially as Nike navigates weak demand and stiff competition. It’s crucial to look at how they manage their cash conversion and operating discipline. The upcoming earnings release on October 1 is expected to shed more light on these dynamics.
Interestingly, the research methodology has evolved since the last consensus snapshot in July, with stronger projected returns now on the table. However, this doesn’t necessarily mean improved accuracy. The discussion also touches on the need for a careful evaluation of margins and cash flow, emphasizing that one quarter's performance shouldn't be taken as the whole picture.
As we look ahead, it’s clear that Nike's situation is complex. The interplay between wholesale and direct economics, alongside their operational strategies, will be key in determining their trajectory. It’s definitely a space to keep an eye on, especially as more evidence comes to light.
Stellantis is navigating a tricky landscape with its famous brands like Jeep and Ram. The recent financials show a significant €22.3 billion net loss for FY2025, alongside unusual charges of €25.4 billion. It’s important to note that not all of these losses are cash outflows; about €6.5 billion in reset charges will impact cash over the next four years. Their Q2 results revealed a revenue of €43.5 billion, but the adjusted operating margin was just 1.8%, and industrial free cash flow took a hit, sitting at negative €921 million.
Looking ahead, management is optimistic about improving cash flow, projecting positive numbers by 2027, but they’re cautious, not guaranteeing outcomes. A key focus will be on North America's operating margin, which needs to exceed 4% to reinforce the recovery thesis. The next big milestone is the Q3 results coming up on October 28, 2026, which could provide more clarity.
Interestingly, the research highlights a mix of AI advisor perspectives, yet it’s worth noting that these aren’t independent analysts, so the consensus might not be as solid as it seems. The landscape is complex, and while there are signs of potential recovery, the path to cash generation remains uncertain.