CBInsights has prepared a list of the major AI trends to follow in 2018. Let’s have a look at the 13 trends In AI that will have a huge impact in years to come.

Robotic workforce

It is no more a closely guarded secret that in the future much of the labor-intensive work in assembly lines of factories would be done by AI programmed robots and not workers. This would bring down the cost of hiring workers and also reduce outsourcing and offshoring.

Recently, a Chinese T-shirt manufacturer Tianyuan Garments Company signed a Memorandum of Understanding (MoU) with the Arkansas government to employ 400 workers at $14/hr at its new garment factory in Arkansas. Operations were scheduled to begin by the end of 2017. Tianyuan’s factory in Little Rock, Arkansas, will use sewing robots developed by Georgia-based startup SoftWear Automation to manufacture apparel.

In Japan, by 2025, more than 80% of elderly care would be done by robots, not caregivers.

Ubiquitous Artificial Intelligence

Artificial Intelligence impacts multiple fields, even those that we least expect it to. Machine learning, a crucial component of AI, refers to the training of algorithms on large data sets so that they learn how to identify desired patterns better at their tasks.

The functioning of AI is getting more versatile with each passing day.

UK’s IntelligentX wants to introduce the world’s first AI brewed beer; DeepFish in Russia is using neural networks to identify fish, and Sweden’s Hoofstep is raising VC money to bring deep learning-based behavioral analysis to horses.

Uncle Sam vs The Dragon in the realm of AI

China is all set to prove its prowess in AI and outshine the US and other western countries. The Chinese government is investing a lot in this futuristic technology.

The Chinese government is promoting an intelligence plan. It includes everything from smart agriculture and intelligent logistics to military applications.

In 2017 China’s artificial intelligence startups took 48% of all dollars going to AI startups globally in, more than that of the USA. In deep learning also China publishes six times more patents than the US.

The US is also, seemingly, losing its preponderance in AI startups to China. In technologies like face recognition, China has poured in billions.

In July 2017, the Chinese government said it planned to reach the level of United States in artificial intelligence by 2020 and become the world leader by 2030. One government-backed project is to create a chip that has 20 times the performance and energy efficiency of NVIDIA’s GPUs. Chinese company Cambricon is pledging to make one billion processing units in the next three years and is developing chips specifically for deep learning.

Battlefields in the age of AI

The wars of the future will rely on smart technology like never before. Drones are just the beginning. With the increasing convergence of conventional defense, surveillance, and reconnaissance with cybersecurity, the need for algorithm-based AI only expands.

Cybersecurity is a real opportunity area for AI since attacks are constantly-evolving and the main challenge is new forms of malware. Prima facie, AI would have an extra edge here given its ability to operate at scale and sift through millions of incidents to identify aberrations, risks, and signals of future threats.

The market is mushrooming with new cybersecurity companies trying to leverage machine learning to some extent.

A total of 134 startups have raised $3.65B in equity funding in the last 5 years. About 34 of them raised equity for the first time last year to compete in a market still dominated by larger companies like Cybereason, CrowdStrike, Cylance, and Tanium.

Voice Assistants

Voice-enabled computing was all over at the Consumer Electronics Show in 2018. Barely any IoT device was without integration into the Amazon Echo or Google Home.

Samsung is also working on its own voice assistant, Bixby. It wants all of its products to be internet-connected and have intelligence from Bixby by 2020.

LG made all of its appliances in 2017 WiFi-enabled.

AI to throw the gauntlet before professionals

Skilled professionals — including lawyers, consultants, financial advisors etc —will face the heat of artificial intelligence as much as unskilled and semi-skilled workers.

For instance, artificial intelligence has huge potential to reduce the time and improve efficiency in legal work. As AI platforms become more efficient, affordable and commercialized, this will influence the remuneration structure of external law firms that charge by the hour.

Decentralization and Democratization

Artificial Intelligence isn’t only limited to powerful supercomputers and big devices; it is also becoming a part and parcel of smartphones and wearable devices and equipment. Edge computing is emerging as the next big area in AI.

Apple released its A11 chip with a neural engine for iPhone 8 and X. Apple claims it can perform machine learning tasks at up to 600B operations per second.

Another case for edge AI would be training your personal AI assistant locally on your device to recognize your unique accent or identify faces.

Capsule Networks

Neural networks have myriad architectures. One of the most popular one in deep learning these days is known as convolutional neural networks. Now a new architecture, capsule networks, has been developed and it would outpace the convolutional neural networks (CNNs) on multiple fronts.

CNNs have certain limitations that lead to lack of performance or gaps in security.

Capsule Networks would allow AIs to identify general patterns with less data and be less susceptible to false results.

Capsule Networks would take relative positions and orientation of an object into consideration without needing to be trained exhaustively on variations.

Dream salaries in AI talent hunt

As per a recent report, the approximate number of qualified researchers currently in the field of AI is 300,000, including students in relevant research areas. Meanwhile, companies require a million or more AI specialists for their engineering needs.

In the US, a Glassdoor search for “artificial intelligence” shows over 32,000 jobs currently listed, with several salary ranges well into the 6 digits. Companies are more than willing to pay handsome emoluments to intelligent AI experts.

 Bigwigs of enterprise AI

As tech giants like Google, Amazon, Salesforce, and Microsoft improve their enterprise AI capability, it would be very difficult for the smaller players to sustain themselves.

Google released Cloud AutoML. Customers can bring their own data to train the algorithms to suit their specific needs.

Amazon began selling AI-as-a-Service with “Amazon AI” under its AWS banner. Amazon AI‘s goal is to serve big.

AI medical diagnostics

Regulators in the US are looking forward at approving AI for use in clinical settings. The advantage of AI in diagnostics is early detection and better accuracy.

Machine learning algorithms can compare a medical image with those of millions of other patients, picking up on nuances that a human eye may otherwise miss.

Consumer-focused AI monitoring tools like SkinVision — which uses computer vision to monitor suspicious skin boils — are already in use. But a new wave of healthcare AI applications will set the ground for machine learning capabilities in hospitals and clinics.

Recently, AstraZeneca, an Anglo–Swedish pharmaceutical and biopharmaceutical company, declared a partnership with Alibaba subsidiary Ali Health to develop AI-assisted screening and diagnostics applications in China.

GE and Nvidia have also joined hands to bring deep learning capabilities to GE’s medical imaging devices. Because of open source software libraries, hundreds of APIs and SDKs, and easy assembly kits from Amazon and Google, the barrier to entry in AI could not have been lower. Google launched an “AI for all ages” project called AIY (artificial Intelligence yourself).

Its first product was a voice recognition kit for Raspberry Pi that enabled the users to give any voice they desired to their personal voice assistant.

Point of no return for Machine Learning?

First was big data, and then came cloud, then the machine learning frenzy. We reached peak machine learning in 2017. Last year investors pumped in over $15.2B in funding to AI startups across multiple industries. It was a 141% spike in funding from 2016. Over 1,100 new AI companies have raised their first rounds of funding since 2016. And that’s more than half the historic number of AI startups that have ever raised an equity round.

The normalization and mainstreaming of machine learning will make investors picky about the AI companies they fund.

Featured Image: Google.com

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An excellent article by Frank Holmes, CEO and Chief Investment Officer, U.S. Global Investors at forbes.com.

Stop buying Iranian oil or face the music. That’s the message the U.S. government shared with the world this week, giving importers until November 4 to cut their consumption of Iran’s crude to zero—or expect sanctions. The threat comes a month after President Donald Trump withdrew the U.S. from the Obama-era nuclear deal.

West Texas Intermediate (WTI) responded by adding more than $6 to the price of a barrel this week alone, to end above $74.

Other drivers included supply disruptions in Canada and Libya, as well as a sharp, more-than-expected decline in U.S. crude inventories. Nearly 10 million barrels were drawn in the week ended June 27, the most since September 2016. Crude is now up an eye-opening 70 percent from the same time last year, contributing to the inflationary pressure that’s pushed consumer price growth to a six-year high.

And there could be more upside, should supply crunches continue along with Trump’s ongoing geopolitical efforts to isolate Tehran. Ready to see $90-a-barrel oil? That’s the forecast from Bank of America Merrill Lynch analyst Hootan Yazhari.

“We are in a very attractive oil price environment,” Yazhari told CNBC this week,“and our house view is that oil will hit $90 by the end of the second quarter of next year,” or 12 months from now.

Even if this prediction ends up overshooting the mark, I believe there could still be money to be made in the energy space on tightening supply and strong global demand. For more, I urge you to watch this brief video outlining the six factors that matter when picking energy stocks.

Bull Market May Have Just Hit a Trade War Wall

The U.S. market is mere days from hitting a milestone that some investors might not have anticipated in the business-friendly era of Trump. Both the S&P 500 Index and Dow Jones Industrial Average have been stuck in correction mode since early February of this year, when inflation fears and concerns of a global trade war triggered a monster selloff.

Today marks the 99th day both indices have been in correction, and according to MarketWatch, if they stay sideways another 10 trading days, it will become the longest such stretch since 1984.

Stocks managed to recover then, but as I see it, unless Trump softens his stance on trade, they will have a difficult time doing the same today. Stiff retaliatory barriers are scheduled to be raised by China, Canada and other key markets, and Canadian consumers have already started boycotting American-made goods. U.S. exports of steel, soybeans and other products are down from a year ago because of friction over the tariffs, which are essentially regulations that could jeopardize the positive work Trump has done in cutting red tape in other areas.

Below is the Dow’s performance so far this year, not including today, annotated with some key moments in the Trump trade war. I chose the Dow specifically because it includes the very largest U.S. exporters, some of which do tens of billions of dollars in sales in China alone. As the biggest U.S. exporter, Boeing delivered more than 200 aircraft to the Asian country last year, accounting for a quarter of the plane maker’s global sales. Apple generated around 20 percent of its revenue in China, or the equivalent of $44.7 billion.

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The question now is whether we’re headed for a recession, and how investors can prepare—though I believe the market is oversold, as I explain in the most recent edition of Frank Talk Live. The last nine years have been extraordinarily profitable, but every bull market must come to an end—not from age, remember, but from changes in monetary or fiscal policy.

Trade war friction has strained international relations in other ways than just trade, of course. Among those is foreign direct investment (FDI), essential for global economic growth.

Chinese FDI in the U.S. Just Fell 92 Percent

China’s tech industry is exploding. Last year, gross output value of Chinese tech firms hit 20 trillion yuan, or about $3 trillion, for the first time ever. Nine of the world’s 20 biggest tech firms now call China home, beginning with Alibaba, valued at a half a trillion dollars. And for the past several years, China has filed far more patent applications than the U.S. on an annual basis. (I should mention, though, that the U.S. still has more patents overall, having just issued patent number 10 million.)

The Asian country, in fact, has more unicorns—or startups worth $1 billion or more—than any other nation on earth. Chinese unicorns account for more than half of the global total, and 66 percent in terms of valuation, according to the World Economic Forum (WEF).

Just look at the top 10 Chinese unicorns. Ant Financial, formerly known as Alipay, ranks first with a valuation of $145 billion. That’s about twice the value of the number one U.S. unicorn, Uber.

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It’s very likely even more capital will flow into these firms this year and next. That’s because Chinese FDI in the U.S. fell an eye-opening 92 percent in the first half of 2018, as the government cracks down on capital flight. The decline is also likely in response to the U.S. government’s increased scrutiny of Chinese acquisitions.

According to economic research firm Rhodium, Chinese investors have sold $9.6 billion worth of U.S. assets, including office buildings in New York, San Francisco, Chicago and Los Angeles. That’s after making only $1.8 billion in investments. What this means is that the country’s net U.S. FDI is negative $7.8 billion so far this year.
And regarding a possible rebound in Chinese investment activity, “looming U.S. policies present substantial headwinds,” writes Rhodium’s director of research, Thilo Hanemann.

So where will all this capital go?

I don’t think anyone can say for sure, but my guess is that this will be a huge windfall for the already fast expanding Chinese tech industry.

Only Half of China Is Online

There are even more reasons to be optimistic about the Chinese tech industry, including the fact that only a little over half of the country’s population is online. At 772 million people, the user base is massive—more than twice the size of the entire U.S. population—but penetration is only 54.6 percent, according to UBS. That’s well behind the U.K. (94.8 percent), Japan (93.3 percent) and the U.S. (87.9 percent).

This means, of course, that the country’s tech and internet industries still have much room to grow.

China is already number one in mobile payments, having surged to a whopping $9 trillion in 2016, compared to only $112 billion for the U.S. The Asian giant is rapidly becoming cashless—so much so that a friend of mine recently had a hard time using paper money to make a purchase in a Chinese convenience store. In fact, a number of unmanned, fully-automated stores—most notably BingoBox and Alibaba’s Tao Cafe—have sprung up all over the country. Transactions are made simply by scanning your smartphone on a designated counter or plate before leaving the store.

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