3 Trending Topics in AI Right Now

Connecting AI to the IoT- AI is inexplicably linked to the IoT. I can’t go a day without discovering something new related to the research being done on the connections between these two technological fields. Take platforms like Fetch.ai, for example, which are still developing. If groups like Fetch are successful in their efforts, the AI space will forever be linked up with the Blockchain and the IoT at the same time. Even if the blockchain doesn’t remain a part of this group forever, it’s reasonable to expect that AI and the IoT will lead the way into the future, hand in hand. How else will our machines learn how to share data with each other to drive continuous improvement without human involvement? As of now, one of the key issues with driving the development of and scaling of platforms related to these three technologies is how to contend with what will likely be the world’s largest amount of computing power ever used for one project. With this in mind, it’s important to remember the utility of projects like the Golem Network, which we have mentioned before. If the Golem Network is ever truly adopted at scale, then we’ll have the world’s largest distributed supercomputer. Since the network already relies on spare processing power from its’ participating nodes, their supercomputer is accessible by anyone.

2. Anything that Google Does with AI- We’ve spoken time and time again about Google’s involvement in the Artificial Intelligence industry and there’s a reason for that. The Silicon Valley Tech Giant is doing so much for the space, that there’s always something new to bring to light. Most recently, besides being embroiled in issues related to their proposed ethics board and involvement in controversial AI-related projects, they’ve created what is being called “an end-to-end AI platform.” If you’re wondering what this means, you can check out their site below. In the interest of brevity, I’ll simply say for now that on the surface, Google appears to have launched the most powerful AI development platform in history, simply due to the fact that it is backed by Google’s cloud services. Below the surface, however, lies what is arguably a troubling possibility. Given that Google is trying to sign all sorts of AI teams up, en-masse, for its’ in-house development platform, who’s to say this is not another big data play by a tech giant? In other words, what sorts of data can Google access via the back-end of their new AI platform? Can they use it to see what AI teams are focusing most of their efforts on? If so, does this extend to gleaning proprietary info on what sorts of algorithms these teams are relying on? Likely, the answer is no and yet the question remains as to what Google’s incentive is in releasing this platform. Why would a for-profit tech company with a history of making a killing from advertising partners want to suddenly go open-source? On one level, Google has already “gone open-source,” along many lines. It has a website dedicated to open-source activities, as well as a history of creating programming languages and frameworks that become widely adopted across the software development community. With this in mind, there’s no reason to suspect a selfish aim behind their new AI platform, at least not until it is tested on the open-market for a long period of time.

3. AI and Ethics- As AI continues to develop and arguably, move closer to the time in which we will have fully autonomous systems, ethical issues will, in turn, become the most important topic of discussion in the field. Why do I believe this? Until we solve the issue of whether or not we can make AI ethical in some way, while still allowing it to develop autonomously, we’ll continue to worry about all of the things that could go wrong with it, with good reason. Just think about all of the questions that need to be answered for us to come to a conclusion on whether we can create ethical AI for a moment. Should we embed a particular moral code in our AI systems? If so, who determines what this is? Will it be a sort of amalgamation of many religious and social traditions? Should religion be factored into the process at all? Will what makes an AI “ethical” be different depending on what country a development team is working in? The list goes on and on. Beyond this group of questions involving how to embed a code of ethics into an AI system lies the question of what sort of behavior should be considered unethical. For now, in my experience, it appears that no one is even close to answering any of these questions. Still, deciding how to deal with ethics in the AI space has never been more important, which is why articles continue to be published on the subject. With that in mind, it’s impossible to say when the question of Ethical AI won’t be a trending topic in the industry.

Keep in mind that this list was compiled in no particular order. These are topics that consistently come up across many different sources. Still, none of them are measurably more important than anything else, along any obvious dimensions. Furthermore, 3 topics represent a truly small cross-section of everything that’s currently being researched in the AI industry. In the future, we’ll offer more lists as different issues come to the forefront. Until then, check out our resources below for a deeper dive into the topics we’ve just discussed. If you’re also interested in more of an overview of how our future might look on a technical level, you can also check out George Gilder’s seminal work, “Life After Google,” below.