Artificial intelligence is one of the most exciting scientific developments in human history. Only a decade ago, AI was a far-fetched fairy tale. Advancements in deep learning have propelled AI enthusiasts’ wildest dreams into reality.
In fact, artificial intelligence is already a part of our everyday lives, whether it be in the form of your email app that learns what messages you frequently trash or the digital assistant tracking your speech patterns.
AI is more than a passing fad or unfortunate bubble. It’s the future.
1. The market is on the rise
Machine learning, deep learning and big data analysis are booming with no signs of slowing down anytime soon. As these technologies progress so does investing interest. AI took a hearty five percent chunk out of the nearly $50 billion invested in the venture capital market in 2015, and those percentages are on a continual uptick. Just last month, Microsoft pledged to back promising AI startups with their own AI venture fund. This isn’t limited to tech giants, either. Citi Ventures, an investment arm of Citibank, is pouring cash into machine learning in hopes to better protect against fraud.
2. The technology is progressing rapidly
Machine learning could only take artificial intelligence so far. Deep learning has made robust AI a reality. Deep learning is based on our understanding of the human brain. Its software is built upon a neural network that chops large amounts of data into tiny slices, passing analyses through layers of the network. Google’s AI Go player, AlphaGo, famously used a neural network to beat top Go players, a feat previously thought impossible.
Until quite recently, an artificial neural network was impossible to implement because of hardware constraints. But now, thanks to GPU computing, it’s very possible.
3. It’s burgeoning
The market is currently booming, and there’s plenty of room for expansion. Unlike many other technologies, the applications of one specific AI technology are endless. Developers have the unique advantage of their product reaching further than their target. Investors are scrambling to back the latest artificial intelligence technologies, which gives developers a wonderful opportunity to focus on a niche.
4. There’s a wealth of resources to take advantage of
OpenCog is an open-source artificial intelligence framework with virtually unlimited applications. This is just one of the many GNU-license projects developers can utilize.
Python offers an overabundance of open-source machine learning libraries to choose from. PyBrain, for example, is completely free and makes creating your own artificial neural network much simpler.
If you and your team aren’t ready to utilize open-source projects, there are a great deal of educational resources at your disposal. Introductory courses are available from the online open-education website Udacity. More traditional institutions, such as Stanford, offer elementary AI courses, online and completely free, too.
5. The industry could have an enormously positive effect on society
Many fear a frightening future in which AI has destroyed the job market. Some fear the worst: a dystopia where humanity is dominated by hyper-intelligent AI systems. This doesn’t have to be the future.
Self-driving cars could save countless lives, having proved to be much less prone to error than human drivers. It could do away with drunk and distracted driving completely. Artificial intelligence could make our sensitive data more secure, causing the rate of identity theft to plummet. These are just a few small examples of what AI could do for our society.
Larger applications, like healthcare, could be streamlined, too. Healthcare could be automated for underdeveloped nations, and could even be improved for the developed world. MYCIN, an early healthcare AI system, identified deadly bacteria and blood clotting diseases in patients, and provided acceptable therapy 69% of the time. That was just the beginning. Technologies like MYCIN could be expanded and improved upon, reaping great rewards for the healthcare industry and for society at large.
AI is on its way. Google’s self-driving car project, Waymo, already boasts one billion simulated miles, and that’s just the tip of the iceberg. Amazon is making incredible strides with its big data analysis. Microsoft’s intelligent personal assistant, Cortana, gets smarter by the second.
With each passing day, our world becomes more deeply connected with AI. 2017 is the perfect time to enter AI development. The market is surging, the technology is progressing and there’s an abundance of free resources your new project could utilize. With ample funding and learning opportunities, there’s no reason to hesitate to join the rise of AI.
Ellie Martin is co-founder of Startup Change group. Her works have been featured on Yahoo!, Wisebread, AOL, among others. She currently splits her time between her home office in New York and Israel. You may connect with her on Twitter.
This is a guest blog and may not represent the views of RE•WORK. As a result some opinions may even go against the views of RE•WORK but are posted in order to encourage debate and well-rounded knowledge sharing, and to allow alternate views to be presented to the RE•WORK community.
Upcoming Summits Include:
View the full events calendar here.
22 November 2017, London
Leading minds in healthcare and machine intelligence will come together for an evening of networking and keynote presentations around tools & techniques set to revolutionise healthcare applications, medicine & diagnostics. Join us for a three course meal to support and showcase women in Healthcare and Machine Intelligence.
23 January 2018, San Francisco
Leading minds in machine intelligence will come together for an evening of networking and keynote presentations. Join us for a three course meal to support women in AI and Machine Intelligence.
25 January 2018, San Francisco
The Deep Learning Summit is the next revolution in artificial intelligence. The increasingly popular branch of machine learning explores advances in methods such as image analysis, speech and pattern recognition, natural language processing, and neural network research. This summit will explore how deep learning algorithms and methods are being applied to solve challenges in industries including healthcare, manufacturing, transport, security and communications.