We have mentioned our technology focus from time to time and what motivated our thinking. On the first topic, we have had several posts this year. Here is a sampling: Year to date, 2023; Knowability; Technology thoughts. For the second focus, we have had seveal posts about the Gairdner Group of Canada.
Our topics of a technical level would relate to computing and its growing basis operationally plus the impacts that we see and will see. But, there is a lot involved, hence we will do a series of posts relating to different aspects of technology via computing.
Code is (has been) how we govern what computers do. Much code is outside of our influence. In cases where we can actually influence things, the scope is limited. And, the approach is not trivial nor to be taken lightly. Of late, we see emphasis on generating code via what is known as AI.
As one would expect, code needs management. Per common themes, libraries have been defined for such a purpose. Libraries functions included storing code, keeping track of changes, and much more. One of the utility functions would be version control. There are other functions and utility programs developed over time to provide access to functions while providing some track record of events relate to code change.
A popular project was Git which came to fore in 2005. Before then, there were many others which are still around. But, we picked Git due to its lack of earlier involvement. Too, it came to be around the time of Linux and was done by the same programmer.
Then, that 2005 timeframe was when the US GSO noted that government agencies could use the cloud. Of late, there are several of these services offered. Companies, and people, ponder the benefit and negative effects of taking that turn. The TGS, Inc. server is a shared host, though we use other means that are cloud-based. We have been researching architecture options from the beginning. For us, the concern was expressed as the balancing of content versus configuration.
We might be said to have gone full circle. Our intitial thrust was on Microsoft's Office Live (need to check the name - we started in the 2009 timeframe). But, we used blogger, too, which was picked up by Google. Then, we have ties to other facilities. Since our focus at the time that Microsoft went to Office 365 was historical and genealogical research which was new to us. Too, we were working on minimal budget by choice.
We self-funded, and John has worked pro-bono on this and other projects since the beginning. That gave us freedom to study when and where we thought there was something of interest. Of course, we followed the machine learning work, as our interest is truth engineering. John will explain the particulars. That work was done independently. Except, all along, the 400 years of generational change in the U.S. very much has analogs in what we see (or have seen) with computation. That is a topic needing some discussion.
So first, this bullet points to Microsoft's project's repository collection. They have been doing this for several years now.
As an aside, GitHub works with OpenAI (publisher of ChatGPT) to support a "Copilot" project in which people use the xNN/LLM approach to help them with coding tasks. We are skirting that discussion, for now; be assured, we will get back to that. Then, Microsoft has supported OpenAI and has tied its Bing to some level of the ChatGPT system.
Now, back to Microsoft, a team related to the company has been using the new ways in pursuit of market analysis which goes with the new modes of algorithmis trading. Besides value that might relate to successful trading, however that might be defined, we have to look at concerns of many of natures, many of which would have been purely academic had these new ways not created a means to observe. And, so whole new approaches to busyness and its modes are now reachable, albeit not as easily as the reports may get one to consider.
- Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions.
Code generation is found everywhere now. In terms of the interfaces, we like Bard though it suffers from the same problems as do the others. A huge discussion going forward will be how to balance the dynamics of the new way which we have seen generates many reactions from maniac dreaming to angst of machine dominanc.
Our intent is not to lessen the seriousness of the different view nor to argue that we do not know enough to make good decisions. One factor being overlooked is that the underpinnings of the operational truths deal, for the part, with applied mathematics having found a home on the computer, partly has this happened because of design changes. The motives for progress largely was gaming and trying to enhance the illusory experience.
Well, we got that now many fold.
Remarks: Modified: 10/30/2023