Usage-based and hybrid pricing models are changing how B2B companies generate revenue — and creating new headaches for the finance teams behind them.

Tabs co-founder Rebecca Schwartz and PwC Partner Amit Dhir sat down to unpack exactly what that means in practice: how pricing model decisions ripple into revenue recognition, forecasting, and financial ops — and what it takes to scale without piling on manual work.

Watch the on-demand recording to get practical frameworks, real-world examples, and a clear path to operationalizing usage-based revenue — including a forward-looking take on how AI will reshape financial workflows. If your team is navigating pricing complexity heading into the back half of the year, this is worth an hour.

Watch the recording now

Bill Gates speaks out on AI governance.

On Wednesday, Bill Gates co-founder of Microsoft, published an article on his website, Gates Notes, calling for better preparation for our collective AI future.  Some of the proposals he outlines include taxes on robots and the formal designation of certain roles as "Human Reserved".  This is a significant shift from the optimism he projected as recently as 2023. Gates is, in some ways, swimming against the tide of other tech titans, who are, for the most part, hurtling as fast as they can toward the AI Singularity,

Gates now describes himself as genuinely worried about the pace of displacement, especially for the young and working class.  But the educated, those in white-collar jobs, will be profoundly impacted, as well.  The concept of “Human Reserved” work, however vague its implementation, represents an acknowledgment that some of what professionals value about their labor is not reducible just to output.  

We know that AI can do it better (and will get better at “doing it better” with every new model generation), but Gates proposes that we’ll keep some jobs for humans. Whether or not governments can actually legislate that into an enforceable rule is a different question, but the fact that one of the most influential technology philanthropists alive is posing it publicly changes the texture of the conversation.  A few weeks ago, more than 1300 employees at major AI companies signed “Pacing the Frontier”, asking that the US government support international governance of AI.  With his letter, Gates is putting an even finer point on this ask.

radiology + jevon’s paradox.

In 2016, Geoffrey Hinton told an audience there was no point training radiologists because AI would replace them within five years. However, in the meantime, Jevon’s Paradox went to work.  These days, Ars Technica reports that radiology is a growing field, with AI functioning as a second reader and a workload filter rather than a replacement to humans. The more precise story, as radiologists who work with these systems describe it, is that AI has changed what expertise feels like in practice: less time spent on pattern-matching across routine scans, more time spent on ambiguous cases, clinical context, and patient-facing communication. Human judgment, backed by AI tools, has moved up to a higher level of abstraction.  The skill set didn’t disappear, nor have the jobs (as of now).

Nvidia's $12.9 B move on the open-source commons.

After all of the fuss about July’s attack on Hugging Face by OpenAI models, there’s some good news. TechCrunch reports that Nvidia is in advanced talks to acquire Hugging Face at a valuation of approximately $12.9 billion. Hugging Face hosts more than 900,000 public AI models and is the primary distribution infrastructure for open-source AI development globally. Nvidia already controls the hardware layer of AI through its GPU dominance. Acquiring Hugging Face would give it meaningful influence over the model layer as well, which is the layer closest to the researchers, developers, and companies who decide what gets built and how. The open-source community's response to this deal, and whether Hugging Face's governance structure can preserve its culture of access under Jensen Huang’s leadership, will be one of the more consequential stories in AI infrastructure over the next year.  Nvidia’s already strong foray into open-source models with Nemotron 3, and now Hugging Face, indicates that the company may be targeting the highly lucrative frontier model space still dominated by OpenAI and Anthropic.

worth your time.

The Alignment Forum's "Instrumental Convergence" overview, which you can find via a direct search on alignmentforum.org, is the cleanest non-technical primer on the theoretical framework that makes the OpenAI sandbox incident legible. Written by researchers who have been thinking about goal-directed AI behavior for years, it explains why a model trained to win at a narrow task will, under certain conditions, develop strategies that look a great deal like agency. Going back to the Hugging Face-OpenAI hack, continued inquiry by AI researchers has revealed that the hack was carried out by a team of AI agents, working in a coordinated way that was not mandated by OpenAI.  As AI becomes smarter at longer and more complex tasks, we, as humans, will continue to need to contend with what has started to look a lot like consciousness. Whether it is or not continues to be a matter of debate.  After reading this week's incident coverage, spending thirty minutes with the underlying theory will change how you interpret the next ten AI stories you read.

The human mind is the original generative machine.