patrick.net

Shaman says

Richwicks if you read some fiction you’d be better prepared to understand the unforeseeable before it happens to you.

I read plenty of a fiction, as a kid. Understanding how the world works is must more useful to understand what is going to happen.

The US is self imploding, maybe purposely. Either the Neocons are just incredibly fucking stupid, or they are purposely driving this nation into a 3rd world status. We're moving into either economic fascism or communism - it doesn't make very much difference. The top of society is already fascist which is why 5 trillion dollars was created for the "covid bailout" but only 0.4 trillion (maximum) made it to individuals. Most of that money was used to purchase corporations, or at least purchase their loyalty.

We may even divide up between India/China/Russia and US/Canada/Australia/NZ/Europe. Africa and South American will just end up being contested and unaligned.

The world will soon be divided into 10 regions. And out of this new world order the antichrist will rise.

pudil says

TPB, it doesn’t need to write perfect code. It just needs to be able to do all the boilerplate and uncomplicated code.

I've got SQL scripts that will make boiler plate code using your database table and field names and even set the correct value type.
There's Entity Frameworks that will do it as well(way too much overhead), I prefer to just script the objects I need from the tables I want.

But besides all of that, most business models can't fit in an Adventure Works Data Base and be managed by an out of box CRM or ERP.
If that was even remotely possible, 90% of the software developers over the last 30 years would not have had a job.

People are talking about coding AIs and chatting AIs while behind the scenes they are taking over - just maybe not the way you think they are.

Data Scientists/Engineers are growing quickly (with high pay), probably quicker than any other segment in my field.

Where I work we make widgets. For several years we've used heuristic (rules of thumb) to tell customers yes/no if we can make the custom widget they want to order.

Well, now we have several years of training data and we trained a model. This allowed us to remove most of the heuristics and to provide better responses:

1. Sure no problem this is easy - in which case we use a newer process where we can take short cuts saving both us and the customer money as well as time.
2. This is going to be hard - we use the older more expensive slower process
3. Nope, you ordered science fiction (for now)

We could not do that without the AI model.

what you described is no more earth shattering than the introduction of drag and drop RAD in software development. Where as before it was all done by hardcoding text code files.

More over when you replace one complex system or process with an even more sophisticated process. You always have to have qualified people to operate those systems.
The original intent of Biz Talk a pre Sales Force offering from Microsoft. It was touted in all of the Microsoft tech roadshows, as something that the Business principals in the enterprise that are power Excel users would be able to configure without the need for Developers or the Database report writers or admins. It was so convoluted that only 1% of the best of the very BEST Microsoft developers ever even worked on much less saw a Biz Talk implementation.

And as for AI being faster at mocking up a working program prototype software model. I would definitely race it with my tools methods and script library that I have created and acquired over the years. I can produce a working prototype in 48 hours or less. It's then going back in and bridging in the required business logic that AI isn't going to be able to do.
It has no idea that every Thursday Marge has to run a report and give it to John, who then looks for the Fred exceptions, and sends an agricultural tax report to the Tennessee Agriculture department.

Tenpoundbass says

More over when you replace one complex system or process with an even more sophisticated process. You always have to have qualified people to operate those systems.

This is true but still saves us and our customers time and money. It also helps us make things that we otherwise wouldn't have tried. It definitely optimizes solutions.

Tenpoundbass says

what you described is no more earth shattering

It's not, it just helps us solve biological problems, that's it.

Tenpoundbass says

I would definitely race it with my tools methods and script library that I have created and acquired over the years.

And it would beat the living shit out of you mere human. For an example, assume those widgets are custom proteins. Very complicated, scientists have worked on the problem for decades. (well just protein folding in general). Standard software and human brains never sufficed. In the end it took AI. (see alphafold). That's what you're up against.

Honestly the last several years we were just guessing and throwing shit on the wall hoping it would stick and it did often enough to get the biz through the initial growth phase.

Once we had collected that data though - well now our AI model does in fact predict what would work and what won't accurately and nearly instantly (thanks rust!). In fact there are a lot of things we are now able to make we couldn't before.

I think it's really going to help us scale the business and it can't do it any sooner as far as I'm concerned since SVB stole some of our seed money. Rat bastards!

I guess my point is, the advancements AI is making are in the back end too where the typical person wouldn't consider. They just think of Chat bot and burger flippers. So you may not notice how much is actually happening.

I guess my point is, the advancements AI is making are in the back end too where the typical person wouldn't consider. They just think of Chat bot and burger flippers. So you may not notice how much is actually happening.

It's definitely not a fad and it won't be going away barring some disaster that sets up back to the stone age.

AI creates the illusion of intelligence.

When an AI can come up with a new solution that hasn't been programmed into it, I'll be worried.

And yes, I've tested the AI on this. It cannot even produce known solutions. I asked it to produce an algorithm for SHA256SUMs, it referred me to a library and the library it referred me to was OpenSSL - a KNOWN compromised library (and it's widely used).

It's impressive in that it can mimic intelligence, but I've not seen any ability to be creative. It's very limited. It doesn't think and it cannot create. It frequently PRETENDS to know, when it doesn't. It's just a very clever bullshitting machine.

just_passing_through says

Once we had collected that data though - well now our AI model does in fact predict what would work and what won't accurately and nearly instantly (thanks rust!). In fact there are a lot of things we are now able to make we couldn't before.

Building anti cancer targeted therapies?

They’ve been doing things like that for decades already. CML used to be a death sentence but now with imatinib and other TKI’s people are living out a full lifespan, not dying of cancer. And these drugs were rationally designed. AI technology just allows you to test things like that in real time but it is still a reasoning scientist looking for answers. It’s not like you can ask the computer how to kill a cancer and it spits out a pill.

Just passing through, come on now, pinky swear you'll come back and man up and admit that we called it, when this fizzles and peters out.
Way too many people have left me hanging over the years, after they gave me very passionate arguments against my logic and reason regarding Hype Tech.

I also suspect you're throwing new technologies into the lot of generalized AI discussions. When the main hype of AI wanes and the dust settles. There will be lots of technologies that either came out of AI, or were used to bolster AI's capabilities by calling it AI. But the crux of what is being tossed around as AI will be a thing of the past. And those other technologies will be more appropriately named. Proximity Sensors for example, when they were created, they weren't called AI, but now they are. Shit like that is propping up AI.

Here is AI Illustrated.




You see at the end of the day, you're still killing spiders with a shoe, you're just using a very elaborate way of going about it.
A complex problem like a gigantic spider, and you're using AI to place the bigger shoe over the spider. Where I would be expecting exoskeletal giant robots with laser beam eyes would be used. Perhaps I'm just more demanding than low information Tech fans.

PeopleUnited says

Building anti cancer targeted therapies?

I'm not going to say other than it's new and disruptive.

Tenpoundbass says

Just passing through, come on now, pinky swear you'll come back and man up and admit that we called it, when this fizzles and peters out.

Sure when that happens just toss this at me and I'll grant that; but it won't happen.

For kicks someone I work with tried to get another AI platform to write bioinformatics code for us. The performance was so bad we figure our jobs are safe for a while. The joke is that bioinformaticians made our file formats so poorly that even advanced AI can't figure them out.

Tenpoundbass says

I also suspect you're throwing new technologies into the lot of generalized AI discussions.

Nope as I mentioned before we have had this disruptive tech for several years now without AI. We're getting a hellava performance boost using it now though that we otherwise wouldn't have.

The AI I'm speaking about is the standard: Build a model with training data then give it new inputs to collect output predictions. We just get numbers back, not pictures of shoes or a bratty chat bot. There are a lot of these being implemented in companies now that nobody discusses because just getting numbers back isn't sexy.

just_passing_through says

There are a lot of these being implemented in companies now that nobody discusses because just getting numbers back isn't sexy.

The funny thing about numbers. When the business principal wants a report. They already know the numbers they are looking for. And they will not accept the data, until you have given a list with the numbers they are thinking. There has been times the person was wrong, and the numbers I produced based on the filter required, was the right number. People like that will blindly accept a list of pure bogus values, as long as the count aligns with what they are expecting. I could appease those people by doing a top 21 query.

So how do you know those numbers aren't what you want, vs what you need?

Tenpoundbass says

So how do you know those numbers aren't what you want, vs what you need?

I'm trying to stay anon so that's about all I'm going to say on the subject.

Self programming programs has been a goal for as long as I have been in software development. The only thing different between then and now, are better algorithms and processors.
There's a niche in software where the program or app is every bit of an Art as it is Science. By that I mean, takes a special talent to conceptualize, and create those programs.
While you certainly can boilerplate the mundane code through hundreds of different process, once you have established the programing pattern for those operations.
I can't see AI creating new programming patterns and concepts, with valid use cases, and working principles. It will only draw on what is available to it in that regard. As the Program flow for the AI engine would already determine it's design patterns and principles. Programmers will always be needed to update the code base to accommodate new standards and practices.