The AI Challenges Businesses Are Actually Focused On Right Now

It has been a heck of a last couple of weeks when it comes to the AI discussion in society. And yet, in all of that, one group that's left trying to figure out if anything has actually changed for them or if they are just on the same path as they were before is the businesses and enterprises that have been trying to figure out how to maximize AI for their own value for, at this point, a number of years. Today, we're discussing both how enterprises are thinking about, if at all, this new era of AI safety and also digging a little bit deeper to find out what the real concerns that businesses have and the real AI challenges they're facing right now. As always, we're in a moment where new challenges are creating new opportunities as well. The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI. Alright, friends. Quick announcements before we dive in. First of all, thank you to today's sponsors: KPMG, Blitzy, Robots and Pencils, and HyperAgent. To get an ad free version of the show, go to patreon.com/aidailybrief or you can subscribe on Apple Podcasts. And to learn more about sponsoring the show, send us a note at sponsorsaidailybrief dot ai. We are now two weeks into the AI safety discourse absolutely dominating the conversation. For those who think that awareness of these issues had been sorely lacking, it has been a very good period. Although now seeing polling numbers that suggest that something like 17% of Americans are completely convinced that AI is going to end humanity, there is certainly some reasonable concern that we might have over calibrated. Holding that discussion aside for a moment, one thing that I think almost everyone is looking for is increasing specificity. That is specificity of policy, but also specificity of monitoring. And it's to that that Anthropic speaks with their new proposed set of measurements to help the public understand just how quickly advanced AI is developing. Once you move past the scariest headlines, this month's safety debate has been largely about recursive self improvement, and the idea that AI development is a) moving too fast, but b) really, about to move much more quickly. The threat of societal destruction makes for a good headline, but the AI researchers issuing the warnings have had a difficult time describing exactly what they've seen inside the labs. To better inform the public, Anthropic has proposed a three axis measurement to understand the current pace of AI development. The first axis is AI s ability to build the next version of itself. The second is Anthropic s ability to oversee and intervene in the actions of agents. And the third is the scale of resources that go into AI model development. Now, Anthropic explicitly notes that these measurements only look at how models are built. In other words, they are measuring only the inputs to model development, …