NVIDIA announced earnings yesterday. In addition to continued exceptional growth, the most interesting observations revolve around a shift from simple one-shot AI to reasoning.
Reasoning improves accuracy for robots - like telling a person to stop and think about an answer before they reply. Here’s an example where I asked Gemini to create a financial projection for NVIDIA for the next five years.
With Salesforce announcing its intent to acquire Informatica & Google’s announced acquisition of Wiz, 2025 is the best year in the last six in terms of M&A value.1
These massive acquisitions, totalling more than $32b propel 2025’s year-to-date number to decade highs - exceeding the fast-money pre-Covid days of 2020.
Only five months in, 2025 has been the year of stablecoins. A Fireblocks survey of banks conducted in May underscores how quickly the market is moving.
Why are so many banks and payment processors aggressively moving to adopt stables?
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“Now with LLMs, a bunch of the perceived quality depends on your prompt. So you have users that are prompting with different skills or different level of skills. And the outcome of that prompt may be perceived as low quality, but that’s something that is really hard to control.”
Loïc Houssier, VP Product at Superhuman, shared this perspective on a recent podcast. AI products differ from classic software in that the experience is in large part determined by the user.
What if every software spoke English? We asked this question about two years ago but now they do - with AI we can retrofit existing apps to speak English.
I don’t want to have to figure out any particular menu to find a setting or understand how a product manager or designer intended me to use the product.
I just want to talk to my computer and tell it what to do.
AI agents are increasingly outperforming humans in various tasks, yet they typically cost 70% to 80% less.
Will they ever be able to charge a premium?
Waymo has reduced accidents by 82 to 92 percent in San Francisco. Waymos monitor more sensors, don’t fatigue, and react more quickly than humans. But, Waymo is often 13-33% cheaper than alternatives.
Within medicine, recent studies suggest AI can be at least as accurate as human doctors, in the evaluation of rashes from smartphone photos, estimating longevity, and diagnosing medical case histories, scoring 90% accuracy compared to human doctors who averaged in the mid-70s.
Nobody wants to read your stuff.
Writing is about the reader - the infinitely busy reader who has a thousand things to do & three goals to accomplish by the end of the quarter. What will attract the reader? What sentence will propel them to the next phrase to the end?
In the past, great content marketers have segmented readers into personas, written witty hooks to entice visitors to dwell.
The blocky charts. The ability to solve a hard test problem. The hidden game of Snake. My graphing calculator was a 7th grade miracle.
AI is this generation’s graphing calculator. With about 2 years’ of studies, we can draw some conclusions on its impact. A meta-analysis published in Nature showed a medium to large impact on students.
ChatGPT’s Select Impact on Higher-Order Thinking
| Condition/Scenario | Effect Size1 | Significance (p-value) |
|---|---|---|
| Overall Effect | 0.457 | < 0.001 |
| Type of Course: STEM and related | 0.737 | < 0.001 |
| Learning Model: Personalized learning | 0.718 | < 0.001 |
| Learning Model: Mixed | 0.719 | < 0.001 |
| Duration: 4-8 weeks | 0.654 | < 0.001 |
| Role of ChatGPT: Intelligent tutor | 0.945 | < 0.001 |
| Role of ChatGPT: Intelligent learning tool | 0.428 | < 0.001 |
| Area of Application: Tutoring | 0.478 | < 0.05 |
The higher the Effect Size, the greater the Effect. 0.3-0.5 is considered a medium sized effect. Above 0.5 is considered a large effect.
With models rapidly commoditizing in performance, we are seeing different strategies for keeping users on the same models.1
Ultimately, personalization & applications are likely to be the two vectors by which foundational model companies compete.
A model remembering your name, optimized to your codebase, having a knowledge of your previous work & refashioning itself to the way you work : those are reasons for loyalty, even if the model isn’t state of the art. Like airplane reward programs, personalization & memory introduce switching costs that may outweigh the benefits of state-of-the-art models.