By Wladimir Hinz, RIC Centre Tech Blogger
What does it really mean to create something intelligent?
There are those who consider Artificial Intelligence (AI) to be the future of technology. Others regard it as something unethical and outrageous that can be dismissed as yet another narcissistic manifestation of people trying to attribute Godlike powers to themselves.
The idea that our own existence can be reduced to that of a complexly evolved computer implies that we are only “useful” until a more efficient machine comes along. This frightens and offends many people, generating friction when trying to apply this technology in real life. The implications are quite subtle but meaningful.
At First there was Darkness
When discussing AI, a very introspective analysis of the human condition usually arises. In general, AI refers to something more than just mimicking human behaviour. There needs to be a similar input-output relationship in a programmable process.
In short, scientists are trying to figure out whether or not a psychological process can truly be generated and applied by a computer when it’s analyzing a problem. There’s a big difference between being able to handle a substantial amount information and actually having a cognitive system (a.k.a. the essence of humanity).
Sparks of Life: Manmade Evolution
Can we create a machine to solve all of our conflicts and end all drama? Some startups certainly think so.
No startup out there is claiming to be creating life – yet. They mostly think of themselves as automating human tasks that are intelligence-intensive, putting them somewhere between smart devices and actual intelligence.
The reason for this is that there are still barriers that need to be broken. “Machine learning” isn’t really intelligence. Pattern recognition and data-driven predictions may very well be precursors of a proto-brain, but there’s more to being human than just that. For example, understanding human language is one big barrier that needs to be breached before we can genuinely interact with a machine.
Following the Herd
Big companies like Google, Twitter and Facebook are clearly looking for fresh AI technology. They have each respectively acquired DeepMind Technologies, Whetlab and Wit.ai. AI startups are being sought after like never before. (Oh, and Apple has also just acquired Vocal IQ).
VC companies are also investing heavily in this technology. Even though investment rounds are still fairly small, as most startups are in their early stages, the trend is quickly picking up and startups are receiving plenty of attention. Just last year, VC investments grew 300% compared to 2013, reaching US$ 309.2 million. And for this year, even higher numbers are estimated.
It’s true, investors usually follow a herd-like mentality when they believe they have found the next big idea. However, the vast variety of projects that need funding is the main reason behind these multimillion dollar flows of capital.
The current scenario is similar to the early years of Big Data. The term “AI” doesn’t denote one specific technology, it denotes a broad approach to solving different problems in a wide range of industries. Like Big Data, it has numerous valuable applications.
A Splendor of Creation
AI technology will surely flourish in environments where there’s a lot of data to be analyzed and impossible to be processed by humans. That said, it will surely thrive not as a standalone technology, but as a process that interacts with other systems.
This is where the richness of applications of AI comes from. Like Big Data, it’s more likely to see a future in healthcare, finance, security and e-commerce.
The analogy of Big Data works particularly well when one thinks of this technology as a process that runs behind an easy-to-use interface, providing useful insights to a massive amount of information that’s constantly being decoded and interpreted. To illustrate this point, here are a couple of startups in the AI business:
- MetaMind launched almost a year ago with USD$ 8 million in funding. They have created an algorithm for image recognition technology that is capable of identifying what is inside of a picture. They have also developed a deep learning sentiment analysis tool that can tell if text has positive, negative or neutral content.
- Enlitic is also a startup that focuses on developing image recognition algorithms, but for the Healthcare sector. Their deep learning computer analysis tool looks to help healthcare professionals diagnose maladies based on images such as X-rays, CT scans, etc.
- Sentient Technologies has built one of the biggest AI systems that exists right now and offers a Darwinian-evolution-based deep learning system that adapts to the needs of the user. They emphasize their scalable process that can run on several computers to deliver faster and better results than the competition.
- ai and X.ai provide personal assistants that can perform a variety of tasks that will surely enhance the way that everybody works.
A Dystopian Future?
Will machines rebel against humankind? This is actually a very serious question. It’s impossible to say right now, as all the arguments are pretty much theoretical. While we are not yet at that stage, it is, nevertheless, an important concern that has Stephen Hawking, Elon Musk and Bill Gates warning scientists not to give moral responsibilities to robots or AI.