Ohio Notes

Hey hi! You’re wrong that the Web site you cannot connect to at all is down as an irrelevant out-of-date cache of a downtime indicator said it was online several days ago!” (Gemini’s output in a nutshell)

Google Gemini is not a good tool for much (nor is it good at much), but it is incredibly bad when it comes to any real-time things.

We all know that GNU’s going to eventually bring everything back on-line. Then Google will update its search index to reflect that it’s offline and Gemini will confidentially declare that GNU’s not reachable for several days afterwards at a minimum.

There are problems though.

No search engine should have an “AI overview” deciding what is and isn’t accurate when you search for things. That would be best done by the Web sites in the search results. Plus, you’d avoid embarrassing potentially harmful-to-at-least-someone contradictions like this one here.

Now, will Google (and the rest of the pseudo-“agentic” search engines, like Bing and Bing-based DuckDuckGo, which is, in fact, a proudly AI-first search engine) do the right thing, or does someone need to start building their replacement that isn’t just some existing search engine scraper or crypto “currency” tool? I sure would like a reasonable search engine that just focuses on search and nothing else.

Your move, search engine companies.

GitHub claimed over 50% of code was now being done with LLM tools. Further information shows that is not exactly the full story.

The Vervint article in the introduction there says: “GitHub’s own data shows that while Copilot might suggest code for 35-40% of what a developer types, only about 26% of those suggestions get accepted. Furthermore, we have far less data on how much accepted code actually survives code review, testing, and makes it to production unchanged.” It continues saying: “Context matters enormously. For example: A junior developer working on backend CRUD operations of an app might accept 40% of AI suggestions, while a senior engineer architecting complex distributed Agentic AI systems might accept less than 10%. The type of project, programming language, and company culture all dramatically impact these numbers.”

A comment reply to a news.ycombinator.com submission I made for a Techrights article makes a point that I’ve made before in discussions. People with the means to actually do so may try using the LLM to write a new GNU/Linux like OS without the GPL. Whether it will work is something we should have doubts on, as it likely won’t even reach the sloppy slopped bootloader when tested.

We know why IBM and RedHat, Canonical, Microsoft, Oracle, Google, and the rest of big tech and big FOSS are doubling down on LLM slop: they want to find people to give free money as a shareholder. But, like Roy wrote: “It cheats the shareholders, but for how much longer?”

What I can say now, at least, is that it sure would be horrible to have to have no way to easily get away from constant slop articles, slop posts, slop code, and blatant slop promotion. Consider news/information sources and software sources that do more than just LLM slop. What a bad time to be in (or going into) a tech industry right now.

There are the “tech optimists”, which are the people who believe that technology is great, and it will make the world a better place. There are also people known as the “tech pessimists”, which are people who believe things ranging from “technology was good but now it’s bad” to just a flat-out and extreme “technology is a mistake”.

If all technology is a mistake, does that include technologies for travel? How about assistive technologies? Are those also mistakes?

Being overly optimistic does not help either, especially if it leads you to claim things like “everything will be on the cloud and we will be happy!” and “crypto[currencies] and NFTs are good actually… no, really!” With the data breaches, lack of privacy, and all of the other issues that come with cloud computing, and the enormous waste of electricity that comes with cryptocurrencies and mass-produced images that sell for too much money, you can’t really blame the people who say “technology is a mistake”.

Perhaps the flaw in that view is with how broad of a term “technology” is.

Technology has its uses for sharing information, like what I do with my personal web site and blog.

It has its use for letting people communicate with each other over short or long distances, as many have done over the decades with Internet Relay Chat (IRC), AOL Instant Messenger (AIM), MSN Chat, and even nowadays with Discord, Skype, Slack, and for still quite a large amount of people: IRC.

It has its uses for various medical things, and medical devices have drastically changed healthcare for many through innovations.

It also has its uses with assistive technology, which even the UN considers to be life-changing.

Further yet, it has its uses in education for engagement, participation, feedback, and connection to content and real-world experiences, with things such as D2L Brightspace, Zoom, and Microsoft Teams now being seen in many schools and universities worldwide.

But the same technologies can be used for horrible purposes that can do more harm than good. Big tech companies pull tons of data from their users to sell for various purposes such as advertising, so they know how to target us with ads for new products or political wins that will favor them, sometimes even if you thought your custom settings disabled it.

But with how bad the technology can be, it can always get better, and it could always be worse. We all have roles that we can play in tech, no matter if you are designing a program, writing the code, performing quality control, using the finished product, or even if you are doing multiple or all of those things at once. Since all technologies are a mix of good and bad, there is no logical reason to be completely optimistic or pessimistic about technology.

The line between good and evil is not a solid one, but rather a very elaborate and blurry one. It is not even just a smooth transition between “here is the good, here is the nice smooth linear transition, and here is the evil.” What is good for some people is evil for others, and what is evil for some is good for others. So, the examples given in this article describing good and bad things can be the exact opposite for some people!

For marketing purposes, collecting data is great since it gives insights into information and groups of people whom they want to target a product or service to.

Would a marketer be a marketer if perse was not marketing to the correct markets? Yes, but per job would almost always be done incorrectly. The same goes for software developers. As people, we want to know how our programs and products are performing compared to others that do the same thing, so in this case, data collection can be seen as justifiable.

For many students as well as professors and teachers, Zoom and Microsoft Teams are nowhere close to replacing the more immersive and involved environments that in-person classes offer to people.

These virtual meeting programs are just horrible attempts at so-called substitutes that cannot truly replace in-person meetings/classes. Likewise, people working in an actual office or at least a physical building were more productive, and they got more done with in-office work than their work-from-home counterparts.

So, while there are benefits to technology, the negatives can sometimes overshadow the positives, and in other cases, the positives will overshadow the negatives. Frequently in tech optimism, all tech is seen as good, and in tech pessimism, all tech is seen as bad.

With all this being said, can we truly group tech into groups of “good and bad” without having tons of overlap or people pointing out how their thoughts make yours wrong?