Does your business have a game plan for Machine Learning (ML) and Artificial Intelligence (AI) this year?
All Analytics published a report full of quotes from industry experts on how to prepare for AI and ML. We combed through it for you and found some of the best points that small businesses can focus on for 2018 coupled with questions you may have asked.
- What are areas where I can apply ML? Rich Wagner, CEO of Prevedere, said, “In the next 12 months we should start seeing major business processes that incorporate ML. For example, supply and demand planning, marketing spend decisions, and assessing patient symptoms by analyzing them across millions of others for proper diagnosis.”
- What if I’m not the first one to adopt this in my industry? Josh Bloom, CTO, Chairman, and Founder of Wise.io, said, “adoption appears to be on the slow uptake. There are so many impediments that have nothing to do with the technology itself, like the existence of ‘good enough’ approaches already in production and the inertia of getting access to the right data within existing security and privacy constraints… what I think we’ll see is a sort of speciation where some small number of platforms emerge as the de facto standards for doing certain types of ML (like reinforcement learning, or learning on low-power, low-RAM devices).”
- What are some of the exciting things AI and ML have already accomplished? Omer Trajman, Co-founder and CEO of Rocana, said, “machines are learning to drive and driving for us; they’re figuring out our tastes and shopping for us… voice-based computing has brought AI into our living rooms as Google Home and Alexa take on more manual tasks like shopping…”
- Where should I look first for ways to implement AI and ML? James McCaffrey, Senior Research Scientist at Microsoft Research, said, “the biggest development I suspect will be coming over the next 12 months is the use of ML/AI to pluck relatively low-hanging fruit to make IT systems smarter, and start the process of an enterprise’s IT organization becoming a strategic part of revenue generation… examples include sophisticated sales projections, IT system anomaly detection, and enhanced network security systems.”
- Can I afford the infrastructure for AI? John Akred, CTO of Silicon Valley Data Science, said, “With Google providing GPU-based compute coupled with ML capabilities like TensorFlow, in a market with AWS, Microsoft, and others making similar moves, the kind of infrastructure to deliver AI capabilities is now available at very low cost.
And our favorite quote from the entire paper came from Nvidia’s CEO, Jensen Huang: “Software is eating the world, but AI is going to eat software.”
Similarly to a post we published a few months back, “5 Ways AI Affects Your Small Business,” we continue to see that adoption and understanding are some of the most common hurdles for businesses of all sizes with ML and AI adoption. There will be a ton of advancements this year and things will only pick up steam. We’d love to be your partner in jumping on and running with these exciting technologies!