Navigating the fall of AI in the Tech Industry
It’s 2019. From 2016 onward AI has gotten lots and lots of hype. However it seems that after all it is very likely that we enter a new AI Winter. In this piece, I want to explore the hypothetical implications of an AI Bubble burst and it’s impact on the tech industry. First, let’s begin by admitting that they are telltale signs of an AI Winter coming up.
Here’s a few examples:
AI circus, mid 2019 update
Introduction It’s been roughly a year since I posted my viral ” AI winter is well on its way” post and like I promised…
China’s AI industry is tanking
In Q2 2018, Chinese investors sank $2.87b into AI startups; in Q2 2019, it was $140.7m. It’s part of a massive slowdown…
It’s pretty much obvious that AI is a marketing term. We were never close to even achieve AI in the first place. What was years ago refered to Artificial Intelligence is now referred as General Artificial Intelligence. The thing is that we don’t even have an intelligence to begin with. Deep Learning is just an approach to Neural Nets and Neural Nets is just a tool. What is commonly referred today as “AI” is just statisitics (linear regression).
Don’t get me wrong, Deep Learning is useful but not for everything. Deep Learning is hammer and not everything is a screw. However, the current hype isn’t about that at all. It’s about reaching singularity making fully autonomous vehicules and etc… Back in 2016 I fell for it because I didn’t know much about the topic.
However what is interesting to me is how the current tools we developed under the umbrella AI are going to change the Tech Industry.
The Fall of AI, The Direct Consequences
When the public at large will realize that the AI hype was not real it’s obvious that AI research will lose funding. They probably will have to rebrand themselves to something less sensational. Alot of people who specialized in machine learning will start losing their jobs. Python might become a forgotten language. We will start hearing less and less about AI. Data Science might become less in demand for a while. However in the case of Data Science it really depends on how society will decide to regulate the access of the consumers data.
“AI” Just A Tool In The Software Engineer’s Toolkit
Even thought it was all hype they where still impressive innovations brought to the table. Just not enough to justify the hype. Those innovations will just become tools that are used when needed to solve real world problems. So the Tech Industry will still be revolutionized but not by the AI companies or researchers but more by the regular software engineer who will include some of those innovations when needed inside an app for example.
What people wanted to be an AI revolution will just become a seamless evolution of technology in our everyday life. Enhanced photo processing on phones, Ray tracing in movies and games, Deep Fakes are all examples of this sublte movement.
Deep Fakes Is Exactly What I’m Talking About
You see deep fakes have become more and more sophisticated. Just look at how they deep faked Keanu Reeves.
DeepFakes weren’t the goal of Artifial Intelligence. It’s just random software engineers who decided to use GANs for this purpose. Now even video editing professionals use it. What we’re likely to see is that the deepfakes techniques may become more and more prevalent in the movie industry. Therefore making movies more and more advanced and visually pleasing I guess.
DeepFakes are also used for nefarious reasons which if they would continue to advance technologically wise we wouldn’t be able to use video as evidence in court anymore. However, neural nets are also being trained to detect deepfakes therefore this might not be an issue after all
This unexpected development that stems from our pursuit of AI is really typical of technology. It develops in unexpected ways. After the AI bubble burst no one would refer to deepfakes as being part of AI.
We would just say that deepfakes are created using GANs and not as deepfakes are created using AI.
At the end of the day deepfakes are just one of the many examples of how tools invented in the pursuit of AI are used in a more concrete daily setting that is far from the big promises of Artificial Intelligence.
The Data Scientist
Data scientist have benefited from the AI hype which got them really high salaries. After the bubble burst data scientist might experience loss in salary or in demand in the short term. However in more long term view of things, Data scientist will also have machine learning techniques as tools in their toolkit and is not going to be defined by AI. Today when you think Data Scientist you think AI. Tomorrow, when you think Data Scientis you will think Data.
At Then End Of Day, Technology Is All About Pivoting
The AI industry will merge into the current Tech Industry and become synonymous with tools that are used with a cunjunction of other tools in order to solve problems. Nothing more nothing less.
This really makes you think about how this pivoting nature is typicall of Tech. Holo lens is pivoting from an AR for everyone to AR for blue collar professionals. Instagram was the result of a pivot from burbn. Youtube was a pivot from a dating website.
Tech always pivot.
Thanks for reading, don’t forget to follow me for more content on Tech!