The Lindahl Letter

You might well be aware that multimodal machine learning (MMML) is a slice of the machine learning universe. Even typing the title of this post was challenging. I really wanted to type multi model vs. modal with an “E” before the last “L” instead of an “A” like the actual wording requires in this case. The definition of multimodal is really direct and does not include a ton of mystery. The word is used to describe something with more than one mode. You might end up quickly running down the path of

Let me start with a quick update on something Substack related. Throughout the last month I attended an invitation-only weekly forum hosted by Substack called Substack Go where writers were brought together to help encourage each other. For me writing on Substack is generally a solitary activity that happens mostly on Saturday morning. That effort is followed by a Sunday morning of editing and expansion. Finally the rest of the week is spent tinkering to get to a final post that goes out on Friday

This is the third week of including audio integration as a part of the weekly Substack post for The Lindahl Letter. Recording a reading of the first section of the post that contains the main content is easy enough to achieve using Audacity with a basic use of both the noise reduction and loudness normalization effects. Between those two effects it will keep a noise floor in place to keep anything from being too loud during the recording. For those of you who are curious to complete the recordings

This topic has been added to my list of academic papers that I need to one day complete. Beyond that scholarly realization the core of this topic really has me conflicted about how to approach consideration about what a national AI strategy really entails. I’m fundamentally questioning what the trajectory of the strategic action would be for the different players involved. Within that conflict I have to wonder if the corporate players within a nation taking action would be inclusive of the strategy

Considering this topic really involved taking things in two different directions. First, I started to really try to understand the world and landscape of machine learning patents. Second, it became abundantly clear that acquisitions have fueled a lot of change in the machine learning space. A history of machine learning acquisitions could be a topic one day. That will probably happen in week 78. Some of that acquisition has been about bringing talent to internal teams and some of it has been about