While it’s true, this argument should not being used to defend people who don’t even consider Africa people as “real” human.
In fact, it’s probably the same people (few generations earlier but with the same mindset) who jumped on boat to create the slave routes, kill people for lands and ressources… You know the people that don’t consider we are all the same.
Because the chips in question for AI are made in Taiwan and nowhere else. The fabs you see on US or EU soils are few generation behind. It will takes decades to be back (if possible) at the same level than Taiwan. And it cost a lot of investment. Ask Intel, they started that many years ago and still constructing the Fab as we speak. And it’s not even the latest generation Fab.
Making headlines is not a proof of quality. It’s just the latest buzz word. You should be less influenced by trends but more by real results.
Btw, I’ve participated to this kind of summit, even as speaker. These events are more a marketing and lobbying tool for consultant firms than being a real breakthrough event on the technology.
They did the same for the sovereign cloud years ago. Lot of money (our taxes) given, fancy events, fancy speeches. Concrete results: still waiting.
And yes, this ML training already show it’s limitations (hence the thing of the past remark). Until recently, you could improve the quality of the answer by providing more training data. But now, they’ve reached the limit as no more data can be given.
It’s just a matter of time before the bubble explode.
Sorry but no.
It’s good when what you are trying to do has been done in the past by thousand of people (thanks to the free training data). But it’s really bad for new use case. After all it’s a glorified and expensive auto-complete tool trained on code they parsed. It’s not magic, it’s math.
But you don’t get intelligence, creativity from these tools. It’s math! Math is the least creative domain on earth. Since when being a programmer is just typing portion of code from boilerplate / examples from internet?
It’s the logical thinking, taking into account all the parameters and constraints, breaking problems into piece of code, checking it, testing it, deploying it, supporting it.
Ok, programming goal is to solve a problem. But usually not all the parameters of the problem can be reduced to its mathematical form.
IA are far from being able to do that and the ratio gain/cost is not proven at all. These companies are so committed to AI (in term of money invested) that THEY MUST make you use their AI products, whatever its quality. They even use a marketing term to hide their product bad answer: hallucinations. Hallucination is just a fancy word to not say: totally wrong.
Do you find normal to buy a solution that never produces 100% good results (more around 20% of failure)?
In my industry, this IA trend (pushed mainly from managers not knowing what really is programming and of course “AI”) generate a lot of bad quality code from our junior devs. And it’s not something i want to push in production.
In fact, a lot of PoC around ML never goes from the R&D phase to the real production. It’s too risky for the business (as human life could be impacted).
For a company, the choice are today: AWS or Microsoft. I would prefer an EU version (of being spied). It was pitched as the next big step, like this IA initiative today… Still waiting…