A big investor in artificial intelligence has dropped a warning about what's on the horizon in terms of AI development and how it will affect everyone. A new op-ed published in the Financial Times details a recounted conversation between AI investor Ian Hogarth and a machine learning researcher that told Hogarth that engineers have already reached the point where they are close to developing Artificial General Intelligence (AGI). The machine learning researcher said, "from now onwards," we are nearing AGI, and for those that don't know, AGI can be simply understood as creating an AI that is capable of performing or learning how to perform every task that a human can do. Despite these warnings from the machine learning researcher, Hogarth admits that these views aren't widely held and that estimations for when humans will achieve AGI vary from a decade to more than half a century. Hogarth recounted the conversation with the machine learning researcher and said that if what he was saying is true and that humans could be on the verge of creating something that is truly dangerous, doesn't he have a responsibility to warn people?

Eight years ago, John Deere unveiled Farm Forward, an ambitious campaign aimed at adopting AI in all of its equipment to build autonomous farms of the future. They've effectively become first movers in the agricultural space. Tractors would drive themselves and calculate optimal herbicide applications on the fly. Besides machinery, John Deere is developing data-driven practices for farm management designed to increase efficiency. The company's Intelligent Solutions Group believes computer vision and machine learning are a natural fit for agriculture. To that end, the company purchased Blue River in 2017.

The rise of Artificial Intelligence (AI) is a trend that will have significant implications for your portfolio. Machine Learning (ML) is ground zero for unleashing the potential of AI for businesses, governments, and consumers. Industries and Institutions vary, but the fundamentals stay the same. We'll look to the Joint Artificial Intelligence Center (JAIC) publication, "Understanding AI Technology" by Greg Allen to get a better understanding of Machine Learning. "AI is not an elixir.

Every day, roughly 60 percent of all market trades are made by computer. When the market turns volatile, this can climb to as high as 90 percent. Robo-advisors are increasingly making this process available to the consumer, saving them time and money as a result. With humans no longer in the transaction chain, fees are slashed. Undercutting the typical 2 percent cut of profits (not to mention 20 percent incentives) charged by a wealth manager, most robo-advisors take around 0.25 percent.

China's support and focus for the emerging AI industry, as well as its goal of becoming a world leader in artificial intelligence by 2030, comes from a source that the country takes very seriously -- government policy. Thus, China's possible domination of the AI sphere within the next 12 years could be the result of the nation using its strengths and weaknesses as a means to propel itself into the forefront of intelligent tech. Kai-Fu Lee, an AI investor that helps tech startups get off the ground through his $1.8-billion dual-currency venture fund Sinovation Ventures, recently noted in a statement to WIRED that China's goal of becoming the world leader in AI-driven solutions by 2030 is achievable because the target is literally a policy from the state. According to Lee, China's government has the capability to implement policies that are followed to a fault by both the country's citizens and its business sector. The AI investor also noted that this system is difficult to replicate in other countries trying to dominate the AI field, such as the United States, due to the West's democracy-driven nature.

Investing in AI is not an easy job: AI technologies are black boxes and unless you are able to dig into lines of code they may be inscrutable. Simply looking at proof of concepts might not be enough to really understand the underlying stack behind specific applications, and this represents a big barrier for investors to efficiently allocate their capitals. Generalist investors found then alternative ways to discern investable companies from the pile of tech-driven companies out there. AI specialists are luckily not that naive, but they are able to go much deeper and look behind the veil. I then compiled a list as extensive as possible of every investor I read or bumped into over the past months. A final remark: there is a fund which does not make AI investments, but it is an AI investor.