Idk how I feel about this. I think this is only an appropriate solution if you are 100% capable and can take complete ownership of patching said dependencies.
I get how there is risk associated with a supply chain attack, but what are you going to do when you don't understand a vulnerability and need to fix it?
Most problems aren't impossible to solve of course, but those who've been working with a codebase for a long time probably have a more intimate knowledge of how it works.
I don't know the answer to your question, but have often thought the same thing. I used to have this saying - at some point you have to take the tinfoil hat off and just "live a little." My thoughts is I'd never make a name for myself if people didn't know who I was. Now at almost 34, I just straight up don't care anymore. I'll never "be someone" and I'm too old in tech to be taken seriously by the movers and shakers.
Not sure where I'm really going with this other than I fully understand opsec, the hacker mindset, cyber security, etc, but I've never really cared to stay private because I wanted to be known. Now that I'm likely as good as I'll ever be, it doesn't really matter lol. If someone finds something I said in poor taste, I'll apologize and hopefully have learned from it and move on.
Definitely try out fancyzones from powertoys if you're on Windows. For Linux I'm not really sure, not much of a Linux desktop environment type, but I'm sure there's something for gnome. Lg makes a software I think it's called screen split, but fancy zones is better in my opinion. I run six 34 inch 2k ultrawides. I use the "edges" for stuff on the back burner - main content goes in the middle. It you have the right monitor some ultrawides can split inputs if you have multiple machines/ sources. That could be useful for dual os or work & personal setups.
You mean open ai put out a model and people stopped using search? Or Google?
What Open ai offers currently can't really compete with search - I understand the data it's being fed gets newer and newer, but it's not really real time like the search engines are. Indexing and presenting data is so different than NLM. Even if it is fed data that's new it's going to have to infer a lot because of a lack of history. It might be able to summarize recent events I guess. Way dumbed down here, but I consider chatgpt like a really smart encyclopedia that can search fast and stay in context across "searches."
If you meant Google, that's sort of what I'm saying - they wouldn't release something that could blow open ai out of the water. But I suspect what open ai offers as a product is something Google could've built long ago, or maybe did and couldn't figure out how to monetize it. They've instead invested in ai to make their products and services better, not as much to offer ai as a service.
What I meant by bard not working out so great was that Google quickly dusted off or slammed together some shenanigans to be relevant, even though what openai is doing doesn't appear to be a part of their master plan.
well my thought is that they 'whipped it up' real quick to attempt to downplay it a bit. Did that backfire? Yeah, I think so. But personally, I think people are missing where the real money is. OpenAI will do great for awhile until every damn product and service is using it, and then it's a race to the bottom. But that's just like my opinion...
I'm probably way too late for this thought to get any traction / discussion - but I have this weird feeling that openai screwed up and showed it's "cool new thing" too early, and publicly.
As much as it pains me to say this, I don't think the real money is in making this a service, or "the product." I think the real money is in using AI internally as a puzzle piece of your backend - ie. the secret sauce behind xyz product.
I'm being very narrow here, but you can only do so much integrating what openai has built into your products - eventually "everything" providing data from the same model brings "everything" to the same level. In contrast if you train and create your own models to make xyz do something specific, nobody knows how it was done, or it surely makes it a lot harder to kang.
I have zero proof, but I suspect Google for instance has models that would literally obliterate what openai has shown capability wise. They're probably not necessarily language models though. Again, nothing to stand on here but I doubt their search and analytics for example are driven by hard coded algorithms these days.
Bard may have been released sort of as a "psh, we've been there done that" when in reality they didn't, because they never planned to make the models they were/are working on "publicly" available to use. It makes me wonder if this is how Google has lead for some long with some areas - now openai sort of screwed it up for everyone by making it a service that can be integrated / adopted by nearly anyone.
The only people I guess that are really going to know are the devs working for these big orgs, and I'm sure that lock and key knowledge.