Overhyped
Overhyped
Search & AI, "Productivity", and Innovations that weren’t
👋 On time for your weekend: a round-up of this week’s remarkable stories at the intersection of technology, business, design, and culture.
Three articles and three podcasts wrestled from this week’s relentless algorithmic chop shops and icky click-bait chum. No fluff, just stuff⚡️
📚 Reading
Pundits Have It Backwards: Search Is A Threat To AI:
If I can download models that can reliably answer questions about their training data, why do I need to visit a Microsoft- or Google-hosted website and type queries into their text box? If I want recipes from my favorite recipe site, maybe I visit their site, instead and talk to their model. If I want the current NYT or WaPo consensus on Ukraine, why won’t I just go to those sites and chat with their bots? Why does a Microsoft or a Google need to be involved in any of this?
Jon Stokes—Return | 7 minutes
Productivity:
The next productivity wave can not be found in mass production but in services and experiences, but companies still only measure their business based on mass-production paradigms [..] We have peaked in mass production efficiency, and more investment in that productivity increase will not succeed. We mass produce the components, but services act as a layer that keeps re-shuffling better and better ways of organising and adjusting those components.
Marcus Kirsch—Medium | 8 minutes
Overhyped and never delivered: A brief history of innovations that weren’t:
In the grand scheme of things, improving what we know and making it universally available might bring more benefits to more people in a shorter period of time than focusing overly on invention and hoping that it will bring miraculous breakthroughs [..] a plea for a better balance between the quest for (perhaps, but not assuredly) stunning future gains and the deployment of the well-mastered but still far from universally applied understanding of achievements.
Vaclav Smil—Big Think | 8 minutes
🎧 Listening
Why We're Not Ready for AI:
We're seeing this split in the ecosystem today of a bunch of folks building their own kind of closed-source companies [..] This small community of about 100 folks that really know how to train these large models [..] Separetdly you're seeing folks in the open-source world, a ton of different people contributing models that are pretty good on the large language model and image generation side.
Jacob Effron—The Logan Bartlett Show | 70 minutes
Power and Prediction:
We don't quite know what the organization of the future looks like. There are reasons to think for many industries it might take a long time [..] for it to show up in the productivity stats [..] I'm a little more optimistic [..] We know from past technologies, and business leaders know from past technologies [..] that it requires some system-level change. And we now have the toolkits to think through, how do you build system-level change without destroying your company?
Avi Goldfarb—🚀 Faster, Please! | 25 minutes
The AI Moment:
Let's have the intellectual honesty to say that we don't understand what consciousness is, and we don't understand the thing that really gives us agency [..] We need some kind of science of agency, of consciousness before we're able to say that we can build these things. To recruit enormous amounts of value in the world requires a lot of planning [..] I'm not sure we can build that just yet.
Amjad Masad—Cognitive Revolution | 32 minutes
🏘️ Next Door
In Scenius Mag this week, a few tales of greater diversity at lower prices brought forward by individuals and their new tools for creation, acquisition and distribution.