AI Summary
5 min readTom Wigg, head of specialties in the Americas at Morgan Stanley, interviews Steven Byrd, global head of thematic and sustainability research at the firm, on the shift from linear to exponential improvements in AI frontier models. Byrd argues that non-linear advances expected this spring and summer will enable models to handle a much greater share of economic activity at higher accuracy and low cost, reshaping industries and business models.
AI Scaling Laws Driving Capabilities
Byrd highlights a clear scaling law from recent years: increasing training compute by 10x roughly doubles model capabilities. This relationship suggests unprecedented non-linear gains ahead, as new models emerge with underappreciated abilities across industries. Rather than uniform disruption, AI will support or enable some businesses while upending others, with certain models proving immune. Investors must assess each case thoughtfully, as these models could perform tasks economy-wide at low cost, amplifying effects on stocks in all sectors.
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What you'll learn
- 1 (00:30) **Reframing AI Progress** - Host Tom Wigg introduces shift from linear to exponential AI improvements
- 2 (00:39) **Introducing Steven Byrd** - Global Head of Thematic Research shares obsession with non-linear frontier model gains
- 3 (01:33) **AI Scaling Laws Explained** - 10x compute increase yields 2x model capabilities
- 4 (02:06) **Industry Disruption Implications** - AI to enable or disrupt business models selectively
- 5 (02:33) **Model Performance Forecast** - Spring/summer models handle more economy at low cost/high accuracy
- 6 (03:23) **CapEx ROI and Hyperscaler Concerns** - Addresses bearish hyperscaler stocks and spending cuts
- 7 (04:02) **Token Economics Model** - Hyperscalers see excellent returns even fully loading data center costs
+ Full timestamped outline available in the app
Show Notes
Original Release Date: April 28, 2026
Tom Wigg and Stephen Byrd discuss the accelerating pace of AI breakthroughs, the forces driving them and why the next phase of development may look very different from anything we’ve seen so far.
Read more insights from Morgan Stanley.
----- Transcript -----
Tom Wigg: Welcome to Thoughts on the Market. I’m Tom Wigg, Head of Specialty Sales in the Americas at Morgan Stanley, and a sector specialist in Technology, Media and Telecom.
We wake up every day to new AI product releases, so it’s easy to lose sight of the unprecedented non-linear improvement in AI capabilities. But things are about to get weird.
It’s Tuesday, April 28th at 8am in New York.
The market has been thinking about AI in linear terms. But we need to reframe that assumption of only incremental improvement and think about exponential improvement.
That was my takeaway from a conversation with Stephen Byrd, Global Head of Thematic and Sustainability Research at Morgan Stanley. In our conversation, we zeroed in on Stephen’s bull case for broader AI model improvements.
Tom Wigg: First, I want to talk about one obsession that you’ve been writing about for the last several months – is this idea that we’re going to see nonlinear improvements in the frontier models coming out this spring.
Stephen Byrd: Yes.
Tom Wigg: There’s been, you know, some big headlines around new models, benchmarks coming out publicly. Is this, you know, your bull case playing out on these models? And what are the implications?
Stephen Byrd: Yes! Absolutely, Tom. So we have, to your point, we are obsessed. And I know I’m not shy about that – with the nonlinear rate of AI improvement. It is the most important impact to so many stocks that I can think of in the sense that it can impact all industries, all business models. So, what we’ve been saying for some time is, if you look back over the last couple of years at the relationship between the amount of compute used to train these LLMs and the capabilities, we have a very clear scaling law.
And approximately the law is, if you increase the training compute by 10x, the capabilities of the models go up by 2x. Now, as you and I’ve talked about this a lot; just meditate on that for a moment. I think things are about to get weird in the sense that on the positive side, we’re going to see all kinds of underappreciated capabilities across many industries. So this disruption discussion, I think, is going to spread, but it’s also going to require investors to, kind of, be more thoughtful about what they do with that concept. Meaning you can’t sell everything. In the sense that AI will disrupt some businesses.
I actually think t
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