I do not believe so, at least not to any significant degree. Rather I believe businesses are adjusting to global inflation and the global economic current and soon to be changes.
This will be a wildly unpopular opinion right now but I believe most of the talk around AI is just that. Machine Learning and Big Data have been rebranded with new window dressing. I suspect people will tire of it quickly once they realize it has no ability to show it's work and is just the next algorithmic evolution beyond the tools used in social media using tailored data-sets and easy to manipulate algorithms. What people are calling AI is impressive however until such a time this AI has truly open source code with completely open obfuscated data-sets and can be self hosted with easily reproducible outcomes then history has taught me to distrust the great and powerful Oz.
A very small nuanced clarification that you might or might not agree with, but I'd argue that it was the reaction to Covid, and not Covid itself, that led up to the issues we face now and will face for years.
For example take Microsoft last week:
https://www.fool.com/earnings/call-transcripts/2023/01/24/mi...
Read through the comments on how they see the current AI shift.
> So, that's sort of fundamentally how we view it. And then the other aspect I'd also say is simultaneously investing in this new AI trend because I don't think any application start that happens next is going to look like the application starts of 2019 or 2020. They're all going to have considerations around how is my AI inference performance, cost model is going to look like. And that's where we are well positioned again.
> So, that's how I view it. The market, you all are better readers of, quite frankly, what's happening out there. We can tell you what we see. What we see is optimization and some cautious approach to new workloads and that will cycle through, but we do fundamentally believe on a long-term basis, as a percentage of GDP, tech spend is going to go up.
What is called "AI" today is just brute force machine learning. There is no intelligence, as ChatGPT has amply demonstrated, just blind regurgitation of a black-box statistical analysis of data.
True AI, i.e., the kind of AI in movies, is still several decades away. It's actually further away now than it was 10 years ago, as the brute-force method has pushed AI research into a local maxima that will be difficult to get away from without starting over.
The problem is that the hill "AI" is currently climbing is just the hill of blind statistics; this method of AI will never be capable of developing understanding.
GPT puts words together based on structure and statistical analysis of what were seems like it is most likely to come next. But GPT doesn't understand the prompt, so the result is frequently nonsensical: it looks structurally sound (and is, because grammatical structure is easy), but most of the time the output doesn't mean anything.
True AI, i.e., "intelligence" will understand contexts and semantics. But it's not something you can get to with brute force.
What makes you think our brains do anything other than "blind statistics"? What is a human brain if not a multi-trillion parameter statistical machine, trained on a vast amount of data, implicitly over the billions of years of evolution, and explicitly over decades of individual lifetime? It's actually amazing that a completely randomly initialized model like GPT can be so rapidly trained to communicate effectively - using just text as training material!
GPT still fails on many occasions, such as ignoring context or simply not knowing enough about the world, but these are not fundamental limitations. It can and will be trained to pay attention to context, to query external data sources, and to construct a better world map. It will be trained using multiple data types, like audio and video inputs in addition to text, that way it will learn a lot more about how the world works, physics, etc.
People are constantly redefining "true intelligence" as whatever these ML models can't do yet. That definition has changed a lot in the last ~20 years.
ChatGPT does not communicate effectively; it communicates quite poorly. It simply does a good job of hiding the lack of substance in its output. ChatGPT is syntactically correct, but it's rare to get something that is semantically correct, or meaningful, for anything but the simplest prompt.
To put it bluntly: AI isn't intelligent until it can reason, and that's not something that can be learned from statistics. ChatGPT can say the sky is blue, and regurgitate a Wikipedia article about it, but it will never understand why the sky is blue, or be able to use that knowledge to answer a question that for which the answer isn't already in its dataset. That's not intelligence. That's just a very good search program paired to a wiki.
Many of my answers - including most of this one - are regurgitation of information I learned previously. Many, if not most people just follow established patterns when communicating, with no deep understanding involved. Even that deep understanding is also pattern matching, where patterns are simply more complex.
You can easily find examples of an ML model performing multi step reasoning to answer a complex question, just like a human would. I can google those examples for you if you like.
I don't appreciate gaslighting, so I'll be withdrawing from this conversation and you're free to continue your fantasy about ML taking over the world, like VR, blockchain, and big data before it.