Buying or selling a dwelling is a major financial and emotional undertaking. In our digital era, these processes can be addressed differently than before – with more consideration, accuracy, and automation into them. Though real estate has traditionally been slow to embrace the recently emerged tech trends, it's high time to start. Such technologies as Artificial Intelligence & Machine Learning can bring tangible benefits to all parties involved – sellers and renters, buyers and tenants, as well as to real estate brokers, agents, and other professionals. Artificial Intelligence (AI) is such a broad concept and is so much talked about that it may cause misunderstandings about what it exactly means.
This article is based on a presentation originally given by Daniel Faggella, CEO & Founder at Emerj (formerly TechEmergence) to a group of real estate executives at a Grupo4s "Future of Real Estate" event in San Francisco, in March of 2018. The real estate market in the US is currently a seller's market, with demand outstripping supply, and housing affordability going down steadily for 2018 (Source: Gallup, May 2018). As more efficient means of buying and selling properties are being made possible with the help of machine learning, other AI-based applications are creeping their way into maintenance, energy management, and more. In the article below, we'll explore the applications of machine learning in real estate. We'll examine the buying and selling process, in addition to a more in-depth look at facilities management and building automation systems. We'll also examine other industries that might serve as a proxy for future real estate innovation, helping executives to imagine future possibilities before they impact real estate itself. To help business leaders find the real estate applications and ML insights that matter most to them, we've broken this article out into the following sub-sections: Our interviews with hundreds and hundreds of ML researchers (for our AI in Industry podcast, and elsewhere) show that they agree on very little in terms of big-picture dynamics of ML. There is no consensus on which industries will be transformed first, no consensus about AI risks in the coming 20 years, and no consensus on a definition of artificial intelligence. However, the one thing they do agree on is that AI will change a lot of how business is done in the coming decade or two, as the Internet did in the past two decades.
Our comprehensive guide to how chatbots will develop in 2020 and beyond. Artificial intelligence is the hottest talking point for business users looking to improve their efficiency, deliver new ideas and take the next steps in the transition to a digital enterprise. AI and chatbots are helping democratise business, empower startups and help build new partnerships, something that every organisation needs to prepare for. "Every business is a technology business" was one of the mantras of the decade just concluded. Every company across every vertical and market started working and communicating with smartphones, using cloud services to open up their data and adopted as-a-service solutions to reduce the cost of doing business and broaden their business base and the opportunities for workers. Ten years ago, specialists were needed to manage databases and build websites. Now anyone with a plan can build an entire company out of off-the-shelf parts, sell across the world without leaving their desk. They can pick advice from a huge range of sources to grow the business and partner with a massive range of organisations to deliver whatever they sell. Now as we move into the 2020s, enterprises and startups alike are taking the next step, adopting AI and bringing smart services into their organisations. It has already started with chatbots and analytics tools, but is already expanding to business-enabling technology, using a mix of machine learning, deep learning, computer vision, natural language processing, machine reasoning (MR), and deep or strong AI. Companies will continue to deploy AI for intelligent robotic process automation, computer vision tasks, and machine learning applications.
Even though Artificial Intelligence (AI) has been around as an academic and scientific discipline since the 1950s, the proponents of AI have never been as hopeful as they are in the present times. It's needless to mention that the current surge in AI research, investment, and real business applications is unprecedented. Market Intelligence firm IDC in their New IDC Spending Guide, September 19, 2018, predicted that the worldwide spending on cognitive and Artificial Intelligence systems would reach $77.6B by 2022. Similarly, Gartner projects the business value created by AI at $3.9T by 2022. While the philosophical debate on the ethical concerns around AI continues in several circles, we have seen myriad business applications of AI.
Me: "Alexa, tell me what will happen in 2020." Amazon AI: "Here's what I found on Wikipedia: The 2020 UEFA European Football Championship…[continues to read from Wikipedia]" Me: "Alexa, give me a prediction for 2020." Amazon AI: "The universe has not revealed the answer to me." Well, some slight improvement over last year's responses, when Alexa's answer to the first question was "Do you want to open'this day in history'?" As for the universe, it is an open book for the 120 senior executives featured here, all involved with AI, delivering 2020 predictions for a wide range of topics: Autonomous vehicles, deepfakes, small data, voice and natural language processing, human and augmented intelligence, bias and explainability, edge and IoT processing, and many promising applications of artificial intelligence and machine learning technologies and tools. And there will be even more 2020 AI predictions, in a second installment to be posted here later this month. "Vehicle AI is going to be ...