According to the Financial Times, Facebook is working on producing artificial intelligence (AI) chips for a virtual assistant to be smarter than Apple's Siri or Amazon's Alexa Facebook is working with Intel, other tech giants and semiconductor makers to make this goal come true. It's goals in developing a more specialized and powerful AI chip is so that a digital assistant will have enough'common sense' to communicate with a human on any subject as well as making it a practical tool in regards to controlling its social network; for instance in the area of monitoring videos and deciding what content should be allowed on its service. Facebook has in the past been known to make its own hardware when necessary and is currently developing its own custom'application-specific integrated circuit' (ASIC) chips which would be a particular kind of transmission protocol designed to specifically work with the company's AI programs. Yann LeCun, Facebook's chief AI scientist and one of the pioneers of modern AI, says there is a need for more specialized AI chips to speed up tasks at lightening speed but with lower power consumption. He says that the company is doing anything and everything it can do in this area especially in monitoring videos flowing through their site in real time but that it will essentially require neural designs which are computer systems modeled on the human brain and nervous system.

In previous columns, I've explained that there's a lot of hype surrounding the incremental improvements of the decades-old programming techniques collectively identified under the marketing buzzword "Artificial Intelligence" aka "AI." What's NOT hype is that those programming techniques (pattern recognition, neutral nets, ect.) have gotten incrementally more effective than they were in the past at playing games and performing speech recognition, automated translation, and so forth. What IS hype are the all-too-common and all-too-visible claims that AI will soon be able to perform complex tasks that involve anything resembling common sense, such as negotiating business deals, customer support and selling products. Well, maybe you'll believe a team of AI experts at Stanford University that is measuring the progress of AI. "Computers continue to lag considerably in the ability to generalize specific information into deeper meaning, [while] AI has made truly amazing strides in the past decade... computers still can't exhibit the common sense or the general intelligence of even a 5-year-old." As you're probably aware, AI is very good at playing games like poker, GO, and (most famously) chess.

Five years ago, researchers made a sudden leap in the accuracy of software that can interpret images. The technology behind it, artificial neural networks, underpins the recent boom in artificial intelligence (see "10 Breakthrough Technologies 2013: Deep Learning"). Yann LeCun, director of Facebook's AI research group and a professor at New York University, helped pioneer the use of neural networks for machine vision. That's what would allow them to acquire common sense, in the end.

Five years ago, researchers made a sudden leap in the accuracy of software that can interpret images. The technology behind it, artificial neural networks, underpins the recent boom in artificial intelligence (see "10 Breakthrough Technologies 2013: Deep Learning"). Yann LeCun, director of Facebook's AI research group and a professor at New York University, helped pioneer the use of neural networks for machine vision. That's what would allow them to acquire common sense, in the end.

Five years ago, researchers made a sudden leap in the accuracy of software that can interpret images. The technology behind it, artificial neural networks, underpins the recent boom in artificial intelligence (see "10 Breakthrough Technologies 2013: Deep Learning"). Yann LeCun, director of Facebook's AI research group and a professor at New York University, helped pioneer the use of neural networks for machine vision. That's what would allow them to acquire common sense, in the end.

Siri: Okay, from now on I'll call you "an ambulance." Apple fixed this error shortly after its virtual assistant was first released in 2011. But a new contest shows that computers still lack the common sense required to avoid such embarrassing mix-ups. The results of the contest were presented at an academic conference in New York this week, and they provide some measure of how much work needs to be done to make computers truly intelligent. The Winograd Schema Challenge asks computers to make sense of sentences that are ambiguous but usually simple for humans to parse.

David Siegel, a quantitative hedge fund pioneer, issued a warning to investors: Artificial intelligence lacks common sense. Siegel, who has used AI to build his Two Sigma Investments into a 37 billion hedge fund firm, said algorithms are limited by the scant amount of training data available to instruct them on how to identify everything from objects in images to trading opportunities. Hedge funds are embracing a form of AI called machine learning years after Two Sigma deployed the technology and as stock and bond pickers struggle to outperform markets. A unit of the firm, called Two Sigma Ventures, seeks to invest in companies focused on data science, machine learning, artificial intelligence and advanced hardware.