Analysing images of gravitational lensing has historically been an extremely painstaking and time-consuming procedure for astrophysicists.

It's how images of astrological objects can be distorted by gravity, and the phenomenon can reveal fascinating new information about our universe. However, the analysis of a single image can take several weeks — and require expert knowledge and techniques.

But now, researchers at the Kavli Institute for Astrophysics and Cosmology (KIPAC) have discovered an alternative: Using artificial intelligence (AI) to analyse the images.

And it's quicker by an order of magnitude, they wrote in a paper submitted to the journal Nature— a staggering 10 million times faster. (We saw the news via MIT Tech Review.)

The researchers trained a neural network using half a million images of gravitational lenses. It can now analyse new images with a comparable accuracy to traditional methods, in a fraction of the time: Up to 100 systems in a single second.

"The amazing thing is that neural networks learn by themselves what features to look for,” paper co-author and KIPAC staff scientist Phil Marshall said in a statement. "This is comparable to the way small children learn to recognize objects. You don’t tell them exactly what a dog is; you just show them pictures of dogs.”

Lead author Yashar Hezaveh added: "It’s as if they not only picked photos of dogs from a pile of photos, but also returned information about the dogs’ weight, height and age."

"Analyses that typically take weeks to months to complete, that require the input of experts and that are computationally demanding, can be done by neural nets within a fraction of a second, in a fully automated way and, in principle, on a cell phone’s computer chip,” said postdoctoral fellow Laurence Perreault Levasseur, another of the paper's authors.

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I activated my Amazon Echo for the first time in December 2015. It's since become one of my favorite tech gadgets ever.

Amazon's family of Echo speakers are some of the most popular gifts right now, so many people are activating their Echo units for the first time.

Here's what you need to know: These speakers, which can respond to either "Alexa,""Amazon," or even "Computer" (for those "Star Trek" fans out there), are extremely quick to respond, and understand your commands far better than any other device I've used.

Thanks to its excellent audio system, with seven microphones for listening and a 360º omni-directional audio grille for speaking, Amazon Echo works exceedingly well wherever I am in my home. I can hear it — and it can hear me — almost perfectly.

Amazon Echo has completely transformed the way I live in my apartment. There's just so much you can do with Echo. Take a look.

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"Alexa, what time is it?"

Honestly, the best use cases for Amazon Echo are the simplest ones. With the Echo, I don't need to bother searching for my phone just to get the time — you can ask for the time from anywhere in your house and get the answer immediately. It's a small thing, but it totally makes a difference when you're rushing in the morning.

"Alexa, how's the weather outside today?"

Again, it's a simple task, but it's way quicker and better than pulling out your phone and opening your favorite weather app. Amazon Echo will not only tell you the current temperature, but also the expected high and low temperatures throughout the day, and other conditions such as clouds and rain.

"Alexa, set a timer for 10 minutes."

Amazon Echo is the perfect cooking or baking companion because it's totally hands-free. When the timer's up, a radar-like ping will sound until you say "Alexa, stop."

Russian president Vladimir Putin believes that in the future, the country that leads in artificial intelligence (AI) could dominate the world.

According to a report by Russian state-funded organisation RT (which we first saw via The Verge), Putin told students that "artificial intelligence is the future, not only for Russia, but for all of humankind."

"It comes with colossal opportunities, but also threats that are difficult to predict," he said.

"Whoever becomes the leader in this sphere will become the ruler of the world."

That's why Russia will share its know-how in artificial intelligence with other nations. "It would be strongly undesirable if someone wins a monopolist position," Putin said.

Currently, AI is being used by companies like Google, Facebook, Microsoft, and Apple to power some of their cutting-edge software and services. But technological advancements in the military field means that AI-powered weapons might be the next step in the evolution of warfare.

The Russian President believes that, as CNBC first reported, drones will be at the forefront of the battlefields in the future. "When one party's drones are destroyed by drones of another," he said, "it will have no other choice but to surrender."

Putin's claims also prompted Tesla CEO Elon Musk, to warn about the risks of "competition for AI superiority", which he believes could "most likely cause" a third world war.

More than countries' leaders, Musk worries that AIs could initiate a war by themselves. That, in his opinion, could happen "if [an AI] decides that a preemptive strike is [the] most probable path to victory".

Musk is a believer in AI, but he has warned about its potential dangers in the past, even picturing nightmare scenarios with robots "going down the streets killing people". More than anything else, he advocates for regulation. "AI is a rare case where I think we need to be proactive in regulation instead of reactive," he said in a recent interview.

"I think by the time we are reactive in AI regulation, it’s too late."

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Elon Musk, the billionaire entrepreneur who cofounded companies like PayPal, Tesla, and SpaceX, has once again warned that artificial intelligence (AI) poses a threat to humanity's existence.

This time he tweeted that competition for AI could lead to the third world war after Russian president Vladimir Putin told a group of students last week that the country with the best AI will be "the ruler of the world."

Musk tweeted out a story on Putin's comments and added: "Competition for AI superiority at national level most likely cause of WW3 imo."

Musk has repeatedly warned about doomsday AI scenarios despite the fact no one really knows how advanced the technology will become or who will look to harness it and how.

The smartest self-thinking machines today are still unable to perform more than one task and they still have limited use. An AI might be able to learn how to play a board game, for example, but the same AI can't learn how to spell or how to perform an operation. This is one of the major limitations with AI at present.

Several AI experts, including Google DeepMind CEO Demis Hassabis and Skype cofounder Jaan Tallinn, believe that machines will eventually learn how to excel at a number of tasks, outsmarting humans and becoming "superintelligent" in the process. But the timescale for this varies wildly from around 30-50 years right up to over 100 years.

Musk has over 12 million followers on Twitter and there's a risk that his comments could lead result in policy makers putting the brakes on AI development just as it's starting to take off. That would be a shame given AI has enormous potential to improve our lives. Companies operating in the field believe that it can harnessed to make new life-saving drugs and cut the amount of energy used across entire nations.

It's fair to say that there are a number of far more pressing issues that humanity needs to contend with, including the prospect of a nuclear war on the Korean peninsula and mitigating the effects of climate change, which is already claiming thousands of lives through major weather events.

There are efforts underway to ensure that AI remains safe and of benefit to humanity. The Partnership on AI, for example — a collaboration involving Microsoft, Amazon, Google, DeepMind and others — is working together to try and determine things like whether it's possible to programme an AI with a set of ethics (and what those ethics should be) and how to prevent AI from being exploited by terrorists and other groups.

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Artificial intelligence can't understand meaning or emotion just yet, but it can write a pretty good essay on 17th-century maritime trade.

At the 2017 TED Conference this past April, AI expert Noriko Arai gave a talk presenting her Todai Robot, a machine that has been programmed to take the entrance exam to Japan's most prestigious university, Tokyo University.

While Arai discovered Todai didn't pass muster to gain acceptance, the robot still beat 80% of the students taking the exam, which consisted of seven sections, including math, English, science, and a 600-word essay writing portion.

But it wasn't necessarily cause for celebration, Arai said. "Instead, I was alarmed."

When Arai thinks about all the evidence claiming machines will replace huge swaths of the global workforce — first in manufacturing and low-skill jobs, and then perhaps in white-collar professions — she sees it as an indication that education is flawed.

Instead of absorbing meaning from their studies, Arai has observed children behaving more like her Todai robot. They ingest facts and spit them back out, without comprehension. The problem is, Todai and other forms of AI will inevitably surpass human memory and cognition at some point, research has suggested. The human brain can never compete with the rote fact-checking power of a computer.

Humans excel at pattern recognition, creative projects, and problem solving. We can read and understand. As Arai notes repeatedly in her talk, computers cannot — at least, so far.

Sometimes Todai makes mistakes. Even with 15 billion sentences in its repertoire, Arai's robot failed to grasp a multiple choice question whose answer would have been obvious even to young children. But as Arai found in her follow-up tests, in which one-third of middle schoolers couldn't answer a simple reading comprehension question, easy questions can also beguile human minds.

"So we have to think about a new type of education," Arai said, one in which kids are taught not just to deposit facts, but also to analyze and think critically about them. "How we humans will coexist with AI is something we have to think about carefully, based on solid evidence. At the same time, we have to think in a hurry because time is running out."

Watch the talk below:

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Amazon will open an R&D hub in Barcelona in early 2018 that will specialize in machine learning research, VentureBeat reports. Machine learning drives many of Amazon’s capabilities, so investing further in this nascent tech makes a good deal of sense for the e-commerce titan.

Here's how the new hub could benefit Amazon's machine learning efforts across its business:

• Amazon’s product recommendations are largely driven by machine learning, as the company utilizes its huge database of consumer purchases to predict what specific items customers would be interested in. As the company extends its business into other areas, via its Whole Foods acquisition, for example, it will need machine learning algorithms that can parse increasingly diverse data sets.
• Machine learning and natural language processing (NLP) are at the core of Amazon’s digital assistant Alexa. The new R&D lab could help improve Alexa’s functionality, which is especially important as its accuracy currently lags behind Google Assistant’s.
• Amazon's logistics business is heavily reliant on machine learning. There are thousands of factors in each individual order fulfillment, so employing artificial intelligence (AI) that can reroute, change delivery arrival times, and make other adjustments accurately and efficiently is extremely valuable. Additionally, Amazon’s interest in drone delivery is well known, and machine learning is what enables drones to fly autonomously. As such, further research in the area could bring Amazon closer to employing a fleet of drones.

Amazon may be trying to make machine learning its new competitive advantage. Amazon’s patent on one-click payments is set to expire this year, meaning the company will lose exclusivity on one of its earliest features that drove it to prominence, but machine learning could provide Amazon with a new advantage. In fact, Amazon has filed a number of machine learning- and AI-focused patents recently. If these prove nearly as valuable as one-click has been, they could help Amazon fend off competition from retailers deploying one-click options. Additionally, the company may even be angling for a new revenue stream, as it has discussed making its machine learning and AI available to other companies through Amazon Web Services (AWS).

One of retailers' top priorities is to figure out how to gain an edge over Amazon. To do this, many retailers are attempting to differentiate themselves by creating highly curated experiences that combine the personal feel of in-store shopping with the convenience of online portals. 

These personalized online experiences are powered by artificial intelligence (AI). This is the technology that enables e-commerce websites to recommend products uniquely suited to shoppers, and enables people to search for products using conversational language, or just images, as though they were interacting with a person. 

Using AI to personalize the customer journey could be a huge value-add to retailers. Retailers that have implemented personalization strategies see sales gains of 6-10%, a rate two to three times faster than other retailers, according to a report by Boston Consulting Group (BCG). It could also boost profitability rates 59% in the wholesale and retail industries by 2035, according to Accenture. 

Stephanie Pandolph, research analyst for BI Intelligence, Business Insider's premium research service, has written a detailed report on AI in e-commerce that:

• Provides an overview of the numerous applications of AI in retail, using case studies of how retailers are currently gaining an advantage using this technology. These applications include personalizing online interfaces, tailoring product recommendations, increasing the relevance of shoppers search results, and providing immediate and useful customer service.
• Examines the various challenges that retailers may face when looking to implementing AI, which typically stems from data storage systems being outdated and inflexible, as well as organizational barriers that prevent personalization strategies from being executed effectively.
• Gives two different strategies that retailers can use to successfully implement AI, and discusses the advantages and disadvantages of each strategy.

To get the full report, subscribe to an All-Access pass to BI Intelligence and gain immediate access to this report and over 100 other expertly researched reports. As an added bonus, you'll also gain access to all future reports and daily newsletters to ensure you stay ahead of the curve and benefit personally and professionally. >>Learn More Now

You can also purchase and download the full report from our research store.

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When Steve Jobs introduced the first iPhone over 10 years ago, he said that it was so advanced that it was "literally five years ahead of any other mobile phone."

Jobs was wrong.

It actually took a good eight years before the rest of the industry caught up.

These days, though, it's become fashionable to argue that Apple is either falling behind the competition or soon will. Many flagship Android phones now offer designs, capabilities, and software that match or best those of the latest iPhones. And the tech industry is moving into new technologies such as machine learning, and artificial intelligence where Apple has historically been weak. 

But I wouldn't count Apple out. It has some under-appreciated strengths that are likely to keep it on top for years to come. 

New phone, new tricks

Apple's future will likely be a topic of discussion this week as it gets set to unveil its tenth-anniversary iPhone on Tuesday. Assuming the numerous leaks are accurate, the device will have a brand-new design and advanced features like facial recognition, wireless charging, and an improved, nearly borderless screen.

Critics are likely to complain that the innovations the new phone offers where seen first on other devices. It's likely to do well regardless. Apple has become a master smartphone maker over the last 10 years, and the release of a new phone — even one like this with a revamped look — is something the company knows how to do well.

But to keep its edge as it moves into the second decade of the iPhone era, Apple will have to learn some new tricks. It will have to become an expert in cutting edge technologies such as machine learning and artificial intelligence, and will likely have to beef up its media effort. Apple's success over the next 10 years will likely be less dependent on new iPhone hardware and more about what new experiences the company can deliver to iPhone users.

"Apple needs to be able to sell on the experience of the software and added services they have," said Carolina Milanesi, a tech analyst at Creative Strategies. "Customers will have to say, 'I'll buy it because I want to buy something like [augmented reality] not the new iPhone.'"

The good news for Apple is that the iPhone is the perfect vessel to offer those new services and innovations. Because Apple controls the phone's hardware and software, it will be able to offer those experiences in a cohesive way that its biggest competitors won't be able to match.

Augmenting Apple's advantages

AR is the perfect example of Apple's hidden strengths. Many experts think AR headsets will one day replace smartphones. But right now, the foundation of AR is being built on and for smartphones, not other devices.

A key new feature of iOS 11, the upcoming version of the operating system that underlies the iPhone and iPad, is a set of programming tools designed by Apple that allow developers to tap into the sensors and cameras in Apple's mobile devices to create high-quality augmented-reality experiences. When Apple releases iOS 11 later this month, the operating system will become the largest augmented-reality platform in the world overnight. Programmers have already started building AR apps for iOS 11, and we've seen a lot of clever uses so far.

Apple's impending launch of its AR-powered operating system demonstrates one of its big advantages going forward. Because of the massive number of people using its devices that are running the latest version of its operating system, Apple can quickly achieve mass adoption of new, advanced technologies. That's something its competitors struggle with.  

Last week, for example, Google announced its own AR development tools for Android, but initially those will only be available for a handful of phones. To be able to use Google's version of AR, all the various Android phone makers will have to design their devices to meet Google's requirements, a process that's likely to take at least a year, which will leave the Android alliance struggling to catch up with Apple yet again. 

A Siri-ous edge

AI and digital assistants could be another area where Apple has an edge. 

At first glance, it might appear that Apple is trailing in that area. While Siri has improved a lot over the years and is great for controlling your phone, it feels limited compared with its chief rivals, Google Assistant and Amazon's Alexa. It isn't as good at answering questions as Google Assistant. And unlike Google and Amazon, which have been encouraging developers of all stripes to create apps for their assistants, Apple has severely curtailed the kinds of apps and tasks with which Siri can interact.  

But thanks to hundreds of millions of iPhones in use, Siri is already on far more devices than those assistants. And it's expanding its reach. It's now on every other major Apple product, including the Apple Watch, Apple TV, and the Mac. This December, Siri is coming to Apple's new connected HomePod speaker, where it will be able to tap into a wealth of music knowledge to help play the tunes you want when you ask.

And while Apple's approach to Siri may seem slow and measured compared to the competition, it's also, arguably, offering a better experience. Apple has placed a lot of emphasis on making sure new Siri feature work well, make sense and are appropriate for controlling with voice commands. Siri may not be able to order a Domino's pizza for you on command like Alexa can, but you probably won't care — it's just not something you'll likely want to do very often. 

Media is likely to be another big piece of Apple's future — and yet another place where it has an advantage over rivals. Apple's first two original TV shows may have been critical duds, but overall it's taking video seriously. The company recently hired two top Sony executives to lead its efforts in Hollywood. On top of that, it reportedly wants to spend $1 billion on video production next year. And it's even looking at moving its original content folks into a legendary movie studio that would serve as its Hollywood headquarters.

With all the talk about Apple having its own video studio, it's easy to forget that the company already has a ready-built audience for those videos in the form of its millions of iPhone users. The device represents the perfect platform to experiment with video and convince a generation that grew up binge watching Netflix shows or worshipping YouTube stars to pay a little extra to get the shows they want.

It's all about scale

The big thing that gets overlooked when people charge that Apple is behind its rivals is the fact that it operates at a massive scale. Sometimes that scale — which involves manufacturing and distributing tens of millions of devices each quarter and making sure they all work reliably — means it may be slower than its smaller rivals to incorporate the latest innovations into its devices. 

But that scale also works in Apple's favor, because no one can match it. When Apple adopts or builds in new innovations, it's able to deliver them to a mass audience much faster than the competition. 

So, the iPhone models we'll see over the next decade may not always seem like they're breaking new ground, but they will likely will be the devices that popularize new technologies, because they'll be distributed at a scale that other companies won't be able to match. 

"They need to make sure they can deliver 400 million units of a single thing, and do it in a manner that will scale and maintain the quality of what Apple wants to be," said Andy Kleinman, the CEO of Wonder, a startup that's working on a specialized smartphone targeted at gamers. "What I always like about Apple, they're not necessarily inventing new things, but building a better experience for what people wanted."

SEE ALSO: AR is going to be everywhere soon

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A Stanford University professor who went viral last week after publishing a study that suggested artificial intelligence (AI) can tell whether a person is gay or straight based on photos believes AI will also be to determine a person's IQ and their political leanings, simply by looking at their face.

Michal Kosinski is cited in The Guardian saying that sexual orientation is just one of the many things that AI will be able to determine in the coming years by looking at our faces.

He predicts that self-learning algorithms with human characteristics will also be able to identify:

• a person's political beliefs
• whether they have high IQs
• whether they are predisposed to criminal behaviour
• whether they have specific personality traits
• and many other private, personal details

It's possible to infer a lot amount of information by looking at someone's face.

"The face is an observable proxy for a wide range of factors, like your life history, your development factors, whether you're healthy," Kosinski reportedly said.

When AI-powered computer programmes are given access to photos of lots of faces they can learn how to distinguish certain traits.

Kosinski's "gaydar" AI, which has not been released to the public, was trained on a relatively small database of online dating photos. After processing the photos, it was able to correctly identify someone's sexual orientation 81% of the time for men and 74% of the time for women.

Two prominent LGBT groups, Glaad and the Human Rights Campaign, said an AI that can infer someone's sexual orientation was "dangerous" and dismissed the study as "junk science".

Samim Winiger, a Berlin-based AI researcher, told Business Insider that the "gaydar" research is "flawed on so many levels."

"For one, I'm sure there is heavy data-set bias at work here. But since this is all not open code/data (surprise surprise), It's hard to tell. Secondly, the research makes definitive, binary statements about human sexuality - negating a very large cultural component in the *spectrum* of human sexuality."

Winiger said that it's even more ludicrous to suggest that AI can tell a person's IQ from just photos.

Despite having obvious concerns about the research, Winiger said he wouldn't be surprised if the NSA buy into it given how much money is going into "predictive policing".

The social applications of facial detection technology are likely to raise complex ethical questions relating to privacy and the misuse of AI.

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For Russia and Vladimir Putin, it is clear that planetary domination and artificial intelligence (AI) are inextricably intertwined.

“Artificial intelligence is the future, not only for Russia but for all humankind,” he said via live video feed as schools started this month. “Whoever becomes the leader in this sphere will become the ruler of the world.”

Putin isn’t an outlier in his thinking; he is simply vocalizing to match the intensity a race that China, Russia, and the US are already running, to acquire smart military power.

Each nation has formally recognized the critical importance of intelligent machines to the future of their national security, and each sees AI-related technologies such as autonomous drones and intelligence processing software as tools for augmenting human soldier capital.

“The US, Russia, and China are all in agreement that artificial intelligence will be the key technology underpinning national power in the future,” Gregory C. Allen, Center for a New American Security fellow, told WIRED. He is the coauthor of a recent report, commissioned by the Director of National Intelligence, that concluded: “As with prior transformative military technologies, the national security implications of AI will be revolutionary, not merely different. Governments around the world will consider, and some will enact extraordinary policy measures in response, perhaps as radical as those considered in the early decades of nuclear weapons.”

Becoming 'the front-runner'

The State Council of China released a detailed strategy in July with the stated goal of making the country “the front-runner and global innovation center in AI” by 2030.

Among the policies outlined by the government are pledges to invest in AI and related R&D that will “through AI elevate national defense strength and assure and protect national security.” According to a recent report from Goldman Sachs, China now has most of the drive, government support, and resources it needs to become an AI world power.

China also has the experience of directing its AI inward, to manage its own population — something the US has far less experience with, based on its different style of governance.

For example, Chinese authorities are exploring the use of AI technologies, such as facial recognition and predictive analytics, to help prevent crime in advance based on behavioral patterns. This will likely mean that Chinese AI systems have more specialized surveillance experience, and other training that translates well to military applications.

China’s AI strategy also directly connects commercial AI developments to defense applications, another trait influenced by its strong central government. For example, Baidu, China’s leading search engine, runs a national machine learning lab with the operational goal of making China more competitive.

Beihang University, a leading military drones center, is also part of China’s machine learning project, and notably the university has been barred by the US Department of Commerce from exporting certain items for reasons of national security.

Russia on the rise

Russia still trails China and the US in the realm of AI.

However, the military modernization program they started in 2008 is triggering massive expansions and new investment in AI. The Russian Military Industrial Committee has set a target of making 30 percent of military equipment robotic by 2025.

With a smaller tech industry than either China or the US, it needs to set — and achieve — these kinds of ambitious goals to stay competitive. Russia does benefit from a strong academic tradition in technology and science, however, and an efficient deployment of the tech that it already has.

Center for Naval Analyses research analyst Samuel Bendett pointed out to WIRED that despite having cheaper drones with shorter ranges, Russia has been able to deploy them very effectively in Ukraine and Syria. Allen added that Russia appears more willing to put AI and machine learning to work as part of its already impressive propaganda, intelligence, social-media, and hacking campaigns.

Like China, the Russian government is far more centralized and holds more power over the ways that AI will develop in the country. This suggests that it will probably be directed more toward military and intelligence applications.

AI in the US

Although the US has at least so far been generally recognized as the global center for advanced AI development, that development has been almost totally focused in the private sector, and the government has lagged far behind with strategy and R&D.

It was not until October of 2016 that the White House released a report on AI, although the Pentagon has been developing its “Third Offset” strategy for several years and monitoring AI and machine learning developments in China in particular.

Yet the US government cannot order the private tech sector to cooperate as the Chinese and Russian governments can, and how much cooperation it receives varies with the political climate. Experts indicate that in some important ways, the US government is behind China and Russia in its use of AI.

That’s partially because authoritarian regimes in those countries depend on intelligence, and the ability to detect and eliminate domestic subversion, for survival; they can also apply the technology without regard to privacy or civil rights. And while the American CIA — whose mission is ostensibly foreign, and not domestic— is using AI to collect social mediadata, whose data is up for grabs is a matter of some dispute.

The bottom line

The AI race between China, Russia, and the US is different from any arms race before, in that the technology also has obvious and immediate commercial applications.

The same technology that makes Facebook so good at tagging you in photos can help government agencies find suspects and spies.

Autonomous cars require the same kinds of technologies that autonomous drones and military land vehicles need. Private companies are in effect conducting military research, whether they intend to or not.

One silver lining from Putin’s fairly ominous speech, however, was his recognition that leveling the AI playing field makes the whole world safer. This is the basic nuclear deterrence argument: if we have nuclear weapons on both sides and our mutual destruction is assured, we won’t use them.

As the Allen paper points out, AI will be changing things so fundamentally that population size will no longer be as important for national power; smaller countries that gain an AI edge “will punch far above their weight.”

And perhaps our AIs — if we train them ethically— will themselves see international collaboration and sharing of resources as an optimally advantageous strategy.

SEE ALSO: High-tech China-US arms race threatens to destabilize East Asia

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Not enough people are talking about artificial intelligence.

At least, that's the thinking behind Evercore's massive price target increase for Nvidia on Friday. The firm upgraded their price target for Nvidia from $180 to $250, implying that Nvidia should be worth about $45 billion more than its current market cap.

"[Nvidia] management believes that investors still severely underestimate the impact of AI and the size of the potential market ('Every PC/Server will have AI in the future')," C.J. Muse, an analyst at Evercore, wrote in a note to clients on Friday. "We are only at the cusp of AI’s growth potential and Nvidia is creating THE AI computing industry standard."

Artificial intelligence is one of the most promising areas in the tech industry, but few people are talking about it. While augmented reality might give you directions to your favorite coffee shop overlaid on the sidewalk in front of you, artificial intelligence could realize that you are on your way, brew up your favorite order, and automatically charge your account as soon as you pick up your latte.

Nvidia's graphics processing chips are ideal for powering the processing intensive AI systems, and Nvidia is entirely responsible for finding that huge new market for their chips. The company's culture of innovation led to a search for new uses for their graphics cards back in the 90s and the development of their CUDA parallel processing platform in 2006.

Since then, people have been using CUDA to speed up specialized computing tasks like video game rendering. As artificial intelligence systems began becoming more prevalent, Nvidia's chips and CUDA programming platform became the perfect pair for developing the next generation of computer intelligence.

"Nvidia has created an industry standard for AI systems that will be nearly impossible to replicate. NVDA dominates Training today, and looks to be the leader in Inference tomorrow," Muse said.

Nvidia's traditional market dominance has come from PC gamers hoping to fight zombies at faster frame rates. The company is doubling down on its data center business recently, and Muse thinks it could be even bigger than the gaming business very soon.

Nvidia recently released its Volta architecture for chips and has already seen increased adoption in major data centers like Amazon's huge Amazon Web Services platform, Muse said. The business is set to be one of Nvidia's largest in the "near term" according to the company's leadership.

Another hot area of tech, autonomous driving, will be a big factor in Nvidia's long term growth. Companies making headlines for their self-driving cars, like Tesla, are using Nvidia's "Drive" platform to process visual data from the road and translate that into decisions on how to drive the car.

AI is everywhere and will grow to be a part of nearly every computer of the future, according to Nvidia's management. As the AI industry explodes, Nvidia is set to grow its earnings by a similar measure. Muse thinks the company will be announcing earnings of $10 a share within the next 3-5 years. Nvidia posted earnings of $2.65 in its most recent fiscal year, so $10 would be an improvement of 277.36%.

Muse summed up his sky-high valuation:

"Considering the strong first mover advantage NVDA has in AI coupled with the CUDA ecosystem that is becoming the de facto standard for AI globally, we suspect the company’s multiple will remain elevated for some time as growth investors will be willing to project beyond 2020-2022, where earnings power should continue to grow in double digits as AI proliferates globally."

Nvidia's stock is up 4.95% shortly after Muse released his updated price target. Nvidia has grown 74.49% so far this year, including Friday's jump.

Click here to watch Nvidia's stock price move in real time...

SEE ALSO: Nvidia is set to dominate the '4th tectonic shift' in computing

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We live in a world of cheap, low-quality food where the crowning achievement in taste and convenience is the Dorito.

But it doesn't have to be this way, according to Matias Muchnick, the CEO and co-founder of a startup called NotCo (The Not Company) that aims to replace foods made with unhealthy animal products with vegetable-based ones that taste the same.

The Chilean company currently sells an eggless mayonnaise called "Not Mayo" in several countries in South America and plans to launch in American stores including Walmart in 2019.

The startup also has plans to roll out its next products, which include vegetarian yogurt ("Not Yogurt"), cream cheese ("Not Cheese"), and milk ("Not Milk") in the next few months.

"We want to change the way we make the food we love, rather than changing the food we love," Muchnick told Business Insider at a demo day in San Francisco organized by biotech accelerator Indie Bio. The accelerator picks out promising startups and helps provide them with the training and funding they need to bring their products to fruition.

With that in mind, I tasted samples of three of their offerings — yogurt, chocolate mousse, and three kinds of eggless mayo.

First up was the mayonnaise, NotCo's flagship product. They offered three samples — spicy (slightly orange in color and pictured below), regular, and garlic (off-white) — in giant, gooey globs.

I'm not typically a fan of mayo — especially not when it's served like sprayable cheese — but this stuff was delicious. It tasted very similar to the regular stuff, but a bit lighter. As someone who usually mixes their mayo with Sriracha, the spicy flavor was, not surprisingly, my favorite.

Surprised by how tasty the vegetable-based product was, I picked up a bottle of the stuff to see what was inside. The chief ingredient was garbanzo beans. The mayo was also pretty healthy, judging by its nutrition label. Roughly 70 calories per tablespoon with a small amount of fat and some protein. I had to ask Camila Sepúlveda, NotCo's head of innovation, what made their product different from the eggless mayo made by Hampton Creek.

"It's healthier," she said. "It's made from real ingredients that are good for you, not fillers and artificial things."

In comparison to NotCo's Not Mayo, whose chief ingredients are garbanzo beans, water, and salt, Hampton Creek's mayo is produced with canola oil, water, and lemon juice from concentrate. Hampton Creek's mayo also has more fat than NotCo's and no protein, something NotCo's product likely gets from the garbanzo beans.

Next, I tried the yogurt, which isn't for sale yet.

It had a nice, sweet vanilla flavor, but didn't quite taste like yogurt to me — more like a creamy dessert topping of some kind.

Clearly, deciding on the right mix of vegetable ingredients to put into a product that seeks to resemble the original, which is made from animal products, is tough work. This is where NotCo employs a technique called machine learning, a programming method where algorithms "learn" from data sets. The more data you feed the algorithm, the more knowledge it builds and the more the product adapts to your desires — at least in theory. NotCo has a name for its machine. He's called Guisseppe.

"We wanted a fun name, and then we found this artist who paints images using only vegetables," Karim Pichara, the company's co-founder, told Business Insider. "His name was Guiseppe."

Next up was NotCo's chocolate mousse, which also isn't available in stores yet.

This stuff exceeded my expectations. It was rich, sweet, and creamy — exactly what I'd expect in a chocolate mousse. There's no way I'd be able to distinguish this from a non-vegetarian mousse. I wished I could have taken some home.

While NotCo hasn't released the ingredients of all of its products (since they're still in the testing phase), Guisseppe selected mushrooms, coconut, and quinoa for a chocolate product it was creating last year.

"We take milk, break it down molecularly, and use Giuseppe to predict which plant-based ingredients will result in something that tastes identical to the animal-based food," said Muchnick.

As it turns out, that process is very similar to a technique that Hampton Creek appears to be using. Last week, the company received a patent for its method of using artificial intelligence, a proprietary plant database, and something called "predictive modeling" to scan and pick out the plant proteins it uses to make its products, according to a filing with the US Patent Office.

Both companies are responding to a growing appetite among millennials and other people for healthier and more sustainable alternatives to animal-based products, which often produce large amounts of waste.

Hampton Creek has raised more than $120 million since it was founded in 2011. After soaring to become the third-largest mayo producer in Chile within five months, NotCo is currently in the process of raising $4 million for its first seed round, which is expected to close in the next few days.

When it comes down to it, "tasting is believing," Muchnick said.

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In late 2016, the Obama administration publishedthreereports that shared an extraordinary conclusion: advances in machine learning, a technology that allows systems to learn and improve without explicit programming, are enabling a revolution in Artificial Intelligence (AI).

As AI systems become increasingly capable of not only routine tasks like driving a car, but also complicated ones like designing car engines, AI technology will be the driving force behind transformations across both the economy and national security.

If imitation is the sincerest form of flattery, then the authors of the Obama administration reports have received a heartfelt compliment from their Chinese counterparts. With China's July 2017 Next Generation Artificial Intelligence Development Plan, the country has announced that it, too, sees AI as the transformative technology that will underpin future economic and military power.

China's plan calls for exceeding all other nations in AI by 2030, but the checklist for China's ambitious agenda is strikingly similar to the policies prescribed by the Obama administration's reports. Greatly increase long-term investment in AI research and development (R&D)? Check. Promote collaboration on AI between the private tech sector and the government? Check. Develop a pipeline of top AI talent? Check. Invest to mitigate AI's potential risks and societal disruptions? Check. The similarities go beyond such high-level objectives, even including many specific policy details and recommendations.

A reader of both documents would be forgiven for concluding that the Chinese strategy's authors had copies of the White House reports on their desks as they wrote. Unlike a college term paper, however, there are no extra points for originality in governance. All that matters is to have the right policies and to implement them effectively.

Unfortunately, there is plenty of reason to worry that China may have an edge in implementing policies practically cribbed from the United States.

The Obama administration sought to increase support for AI R&D, since annual federal funding for all computer science and mathematics R&D is less than half of what Google alone spends. Rather than boosting those levels, the Trump administration's budget calls for cutting AI research at the National Science Foundation by 10 percent, to a mere $175 million.

China, meanwhile, has demonstrated a willingness to spend jaw-dropping sums on technology when there are strategic national interests at play. For instance, in 2014, the Chinese government announced a 1 trillion RMB ($150 billion) investment fund to turn the Chinese semiconductor industry into a global powerhouse.

Those figures are not merely hype. By 2017, the government had already made a third of that sum available. Similarly, China's new plan foreshadows massive increases in funding for AI R&D.

One might think that US government support for AI R&D is not terribly important, so long as US companies lead the way. Perhaps that's true in sectors like health care, but the US companies with the best AI technology are often considerably less willing to invest in national security applications.

When Google acquired DeepMind, arguably the world's leading AI R&D organization, DeepMind required Google to prohibit the use of their research for military and government surveillance purposes. When Google acquired a leading military robotics developer, Google announced that the firm would no longer accept military contracts. And Google is far more cooperative with the national security community than most tech companies.

Chinese firms are less reluctant to make these distinctions. As China pursues a strategy of "military-civil fusion" in AI, it wields a range of policy mechanisms to incentivize industry cooperation. This summer, Tsinghua University — considered "China's MIT"— announced plans to establish a Military-Civil Fusion lab that will provide a platform for dual-use advances in AI.

Also this year, China established its first national deep-learning laboratory under the leadership of Baidu — often called "China's Google"– and in partnership with the Chinese Academy of Sciences, Tsinghua University, and Beihang University. (Beihang University also happens to be a leader in the development of Chinese military aerospace technologies, including autonomous systems and robotics.)

No Chinese company has more enthusiastically embraced AI technology than Baidu. Despite lagging its US and Chinese competitors in the mobile era, Baidu is reinventing itself around AI. Under the leadership of AI pioneer Andrew Ng, who until this March served as Baidu's chief scientist and head of AI R&D, Baidu's 1,300-person AI team achieved impressive results, developing better-than-human speech recognition software a year before Western companies and building out Baidu's well-respected machine-learning cloud-infrastructure team.

Ng's departure was a significant setback, but Baidu remains focused on AI. Qi Lu, a former Microsoft executive and a leading AI specialist, has joined Baidu as chief operating officer.

Overall, Chinese tech companies are not as far behind as many in the West assume. This year, nearly all of the top-performing teams in the ImageNet Challenge, an influential AI competition, were from China. iFLYTEK, a Chinese AI startup, currently ranks second in the reading comprehension tasks measured by the Stanford Question Answering Dataset leaderboard, besting teams from Microsoft and Google, among others.

While not yet the overall leaders in AI technology, Chinese researchers have proven their ability to catch up quickly and produce genuine innovation.

As China and other nations increasingly approach parity with the US in key military technologies such as precision guided munitions and stealth aircraft, the Department of Defense hopes that AI will enable it to maintain military technological supremacy well into the 21st century.

That's a worthwhile goal, but achieving it will require that the United States not merely have a strategy, but also implement it better and faster than other countries. The Defense Department has sought to deepen ties with Silicon Valley to bring cutting-edge AI tech to the Pentagon, but even Defense Secretary James Mattis acknowledges that thus far the Pentagon has been challenged in these efforts.

Here too, China is embracing and implementing America's strategy. Ng led Baidu's AI efforts from the firm's Silicon Valley campus. Since his departure, Baidu has announced plans to add a second site in the area. Tencent, the Chinese social media giant that both Facebook and Snapchat have confessed to imitating, has also moved in.

Chinese companies believe that by rotating Chinese staff to Silicon Valley and American staff to Chinese campuses, they can accelerate the timeline for reaching parity with the United States in AI technology and depth of talent. At present, however, the size and experience of China's AI workforce remains dwarfed by that of the United States.

Half of the top 10 employers of AI talent in China are US firms, including IBM, Intel, and Microsoft, who may thus be integral to the development of China's human capital in AI.

China's copying of America's homework could be a positive development if it deepens our understanding of the risks brought about by the rise of AI and how to mitigate them. The 2016 White House report addressed the workforce challenges of AI head on.

Larry Summers, who served as Obama's first director of the National Economic Council, predicts that the rise of AI in the economy could bring about "a third of men between the ages of 25 and 54 not working by the end of this half century." Such an unemployment rate would be higher than that endured by Germany during the Great Depression when the Nazi Party came to power.

China's AI plan likewise shows a clear understanding that increased automation is likely to reduce demand for labor across many sectors, putting societal stability (and perhaps the legitimacy and survival of the Communist Party) at risk. That why China's strategy includes a call for a new regulatory focus on the ethical, security, and governance challenges of AI, including workforce displacement.

Like the Obama plan, the Chinese plan also calls for government action to mitigate the economic pain and social instability of worker displacement. China's government-led transition of hundreds of millions of laborers from agriculture to manufacturing shows that it has experience in this area, but for now its AI-related efforts remain at the planning stage. With official GDP growth rates still above 6 percent, China's near-term problem is actually a labor shortage.

Unfortunately, the United States is no longer attempting to plan for these challenges. The current US Treasury Secretary, Steve Mnuchin, has stated that AI workforce issues are "not even on our radar screen." The White House Office of Science and Technology Policy (OSTP), which was instrumental in leading AI policy work during the Obama administration, has been essentially depleted of staff, with more than 70 out of 100 positions unfilled. The current administration has effectively deprived itself of critical expertise and insights on AI.

Without a recognition of the historic challenges of artificial intelligence — or a focus on preparing workers, soldiers, and diplomats for the future — will the United States be able to withstand AI's disruptions or maintain competitiveness?

Though China's success in implementing its highly ambitious AI strategy remains to be seen, China's actions are a clear indication of governmental commitment to this agenda at the highest levels. At this point, the United States is failing to implement the sensible and ambitious AI policy that the Obama administration left behind. Meanwhile, China is using the Obama playbook to stride boldly forward into the AI revolution.

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Nvidia hit an all-time high of $190.08 on Monday after another Wall Street bank took notice of its huge advantage in artificial intelligence.

AI is the hottest area of tech right now, and Nvidia is crushing its competition. Last week, Evercore analyst C.J. Muse said that not enough people are paying attention to Nvidia and AI right now and Vivek Arya of Bank of America Merril Lynch agrees.

Arya said Nvidia's transition to a chip maker and AI powerhouse is "underappreciated,"according to a CNBC review of Arya's comments.

Muse also thinks the company is underappreciated and expects AI to be the main driver to $45 billion of growth at Nvidia. He said every computer will eventually have some AI component, representing a huge opportunity for chip makers like Nvidia.

Nvidia has the chance to dominate the competition because of its impressive graphics processing units. Their chips are the best for artificial intelligence work. Intel and AMD are Nvidia's strongest competitors, but their technology is behind Nvidia's, Markets Insider previously reported.

Nvidia's newest "Volta" chips are extremely powerful chips aimed at the data center market where a lot of AI processing power will live. The company is highly focused on this segment of its business, and BAML thinks it could grow 21% in 2018, according to CNBC, citing Arya. Nvidia started working on its AI programming platform in 2006, while other players have started their AI tech developments much more recently.

Shares of Nvidia are up 85.33% this year.

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Over the past several years, e-commerce giant Amazon.com has become one of the leaders in the emerging field of artificial intelligence (AI).

The company uses AI technology in a host of ways behind the scenes for things such as improving search results, offering better product recommendations, and enhancing its forecasting and inventory management. The more public face of Amazon's AI effort is Alexa, the voice-activated digital assistant at the core of its market-leading Echo family of smart speakers.

Given how much it has riding on the technology, it should come as no surprise that Amazon has announced plans to expand its AI research by building a new R&D center in Barcelona, Spain.

Shortage of AI talent

As businesses far and near awaken to the transformative potential of AI, they have been snapping up all the available talent from the relatively small pool of scientists and technicians trained in artificial intelligence, and its sub-disciplines, machine learning and deep learning. As the scarcity of people with the requisite knowledge and abilities has deepened, those companies have been looking to tech centers outside Silicon Valley to fill the void.

Earlier this year, Alphabet Inc, a pioneer in the AI revolution, revealed that it would launch Google Brain Toronto, its second such research facility in the Great White North. A previous location in Montreal was announced last year. These tech hubs are found near major universities that have courses of study in AI, providing convenient access to scientists and researchers, not to mention those soon to graduate.  

Doubling down on AI research

Amazon has revealed plans to build a new AI research hub in Barcelona, Spain, which will be located in the city's 22@ start-up district, and plans to hire more than 100 scientists and software engineers to staff the facility over time.

Facilities such as these are key to Amazon's plans to evolve its use of the technology. Using software models, algorithms sift through large amounts of data and extract patterns in order to make more accurate predictions or assessments. Amazon uses AI and machine learning as the foundation of many of its customer recommendations, logistics capabilities, and smart speakers, so expanding on its AI capability is a key competitive advantage.

This isn't the only geographic move Amazon is making in an effort to bulk up its AI staff. Earlier this year the company expanded its research and development center in Cambridge, England, by adding a 60,000-square-foot facility to house over 400 "machine learning scientists, knowledge engineers, data scientists, mathematical modelers, speech scientists, and software engineers" according to a press release. 

These moves are indicative of just how serious Amazon is about the field and the geographic lengths the company is willing to go to have access to AI talent.

What is all this AI worth, anyway?

Amazon CEO Jeff Bezos has been quite clear about his opinions regarding the future transformative influence of AI:

I think it's gigantic. ... It's probably hard to overstate how big of an impact it's going to have on society over the next 20 years. ... It has been a dream since the early days of science fiction to have a computer that you can talk to in a natural way and actually ask it to have a conversation with you and ask it to do things for you. And that is coming true. 

Beyond the intangible benefits that Amazon realizes from its AI research, some believe that its Echo family of smart speakers powered by Alexa represent the greatest quantifiable opportunity. Mark Mahaney and Jim Shaughnessy of RBC Capital Markets revealed that 50% of Echo owners use the device daily and 17% have placed orders on Amazon's website using the device. The analysts make the case that the Alexa-based devices could contribute as much at $10 billion to Amazon's top line by 2020.

That's not chump change.

Suzanne Frey, an executive at Alphabet, is a member of The Motley Fool's board of directors. Danny Vena owns shares of Alphabet (A shares) and Amazon and has the following options: long January 2018 $640 calls on Alphabet (C shares) and short January 2018 $650 calls on Alphabet (C shares). The Motley Fool owns shares of and recommends Alphabet (A shares), Alphabet (C shares), and Amazon. The Motley Fool has a disclosure policy.

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Brands are dead, or they might be in the future.

According to Aaron Shapiro, the CEO of the marketing firm Huge, brands will take a backseat as technology like artificial intelligence and machine learning become more prevalent.

"As machines start to take more decisions for people it makes it harder for marketers to figure out how to enter into that equation and how to influence consumer behavior," Shapiro told Markets Insider. "It's very disruptive for many companies."

Artificial intelligence powers technology like Apple's new face-recognition unlock tool and Google's smart assistant. AI is in its infancy, but it already is showing up in users' lives in a big way, which could be a big problem for marketing firms like Shapiro's.

Shapiro says to understand AI's impact on brands, picture a futuristic smart fridge. The fridge has cameras to track the food inside, and it sees that your milk is running low. Because it's connected to your credit card and your preferred online grocery store, it automatically orders new milk based on data it has gathered about your previous shopping habits. The fridge already knows which kind of milk you prefer based on what it's already seen you buy, so you don't have to pick the brand or even type of milk to reorder.

"You're already locked into your preferences, and you're done," Shapiro said. "You're not even deciding what food you want to buy anymore."

That exact fridge may not exist yet, but it could soon. A Samsung smart fridge already can track your food and can offer recipes based on what's in your fridge. Visa has said it expects all fridges in the future to be connected to your credit card and have built-in food-delivery capabilities.

But AI won't just affect your snacking habits. Shapiro said Amazon's Alexa assistant already let you order products without being too specific.

When asking for more soap, for example, Amazon will pick a soap it thinks you will like based on its algorithm, and while it has you confirm that choice, Amazon already is able to sort through hundreds of brands and pick a soap for you.

"Most of the internet up until today has been about more options," Shapiro said. "Now with machine learning, it's not about everything — it's about the perfect product just for me."

Shapiro says this means the companies that own the most successful versions of these AI-equipped systems will wield immense power in the future.

That's probably why Google is working so furiously on its smart assistant. As Shapiro noted, Google's business today is ad-supported; it sells brands spots at the top of search results. If users stop searching for the best types of soap and instead rely on algorithms to pick out soap for them, Shapiro said, soap brands will stop buying those ads and Google will lose its biggest source of revenue.

When asked what the future of advertising looks like in a world dominated by smart fridges and voice assistants, Shapiro says he doesn't know but is excited to find out.

"I love technology that makes things simple and more powerful for people," Shapiro said, alluding to AI. AI, he said, is "both very exciting and really scary if you're trying to market."

To see the companies most likely to benefit from the AI revolution, click here ...

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A recent report asserts that the artificial intelligence (AI) industry will reach a compound annual growth rate of 17.2% by 2023. The market is set to swell to a whopping $14.2 billion over the next six years, up from just $525 million in 2015.

Natural language processing technology is set to be a huge contributor to this growth. This tech is being adopted rapidly, particularly by financial institutions, because it can carry out customer service transactions and answer common questions in the place of human employees.

As for geography, North America is expected hold the majority of the AI industry’s market share by 2023, but Europe and the Asia-Pacific region will see significant growth thanks to the rapid pace of urbanization in some areas, increasing use of smartphones, and robust automotive sectors.

The time is now

Inevitably, any transition away from human labor could result in fewer jobs. The big question is whether AI and automation can produce enough new jobs to ensure that the people being replaced aren’t left unemployed.

According to the World Economic Forum, automated systems are on track to replace more then five million workers by 2020. In the U.S., some have predicted that 7% of jobs will be lost to automation by 2025, and a recent study found that as many as 10 million jobs in Great Britain could be swallowed up by automation over the next 10 years.

While we still have reasons to be optimistic that AI and automation could create jobs rather than just take them away, that’s not likely to happen organically — we need to make some big societal changes to ensure the benefits of AI outweigh the negatives.

These changes might mean some sort of adjustment to academic curriculum that takes into account the types of jobs that students are likely to hold 10 years from now. Universal basic income (UBI)could also be the answer, giving citizens a way to ensure their basic needs are met even after they are no longer needed at their job.

AI and automation are no longer the wave of the future — the technology is already here, and these systems are being implemented more broadly than even before. The world of work is changing, and the way society functions needs to change along with it.

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Nvidia announced it will bring its artificial intelligence prowess to the exciting world of local logistics, and the stock is rising.

Shares of Nvidia are up 4.09% in early trading on Tuesday at $174.32 a piece.

If the phrase "local logistics" puts you to sleep, imagine a drone delivering pizza or your next Amazon order directly to your door. Nvidia is working to make that possible, the company announced at its GTC China conference.

The company announced it will be partnering with JD.com to bring AI smarts to delivery drones using Nvidia's Jetson platform. The Jetson chips bring low-power AI vision to drones developed by JD.com. The two companies said they are working to lower delivery costs to rural areas of China. The drones are currently able to carry about 66 pounds of cargo at about 62 miles per hour, according to the company's announcement.

The partnership has lowered JD.com's delivery costs to rural areas by 70% in early stages of the partnership.

"At no time in the history of computing have such exciting developments been happening, and such incredible forces in computing been affecting our future," Jensen Huang, CEO of Nvidia, said at the conference.

At the conference, Nvidia released its TensorRT 3 software. The software will speed up existing AI systems and could increase the speed of autonomous driving cars, for example. The company also announced an update to its CUDA AI programming platform, among other announcements.

Analysts have told Markets Insider that the company's tech simply is the best among its competition.

Nvidia is up 75.04% this year.

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-Over the next few years, chatbots will become a ubiquitous component of the customer service experience.

-Phone centers may become a thing of the past as customer service switches to digital interactions. Chatbots will enhance chat conversations by helping humans with micro-tasks and automatic replies, though it's unlikely that bots will replace humans entirely.

-New features like natural language processing are improving chatbots everyday, but engineers are still trying to find ways to make artificial intelligence learn quicker with less data.

As more companies come to embrace chat functions to complement or reduce human phone centers, rudimentary human-to-human chat conversations will soon be a thing of the past, according to experts in the field. In the next three to five years alone, chatbots will become nearly ubiquitous, and work seamlessly with human customer support agents to provide customers with efficient, personalized responses. 

Though chatbots have been around since the release of ELIZA in 1966, vast amounts of data and enhanced artificial intelligence capabilities have pushed the technology into the mainstream commercial space in the last few years, creating a hybrid experience between human customer service agents and bots.

Salesforce first launched an SMS chatbot product in 2014, and has since expanded it to include Facebook Messenger. The company also offers a product called Live Agent Chat, which facilitates human-to-human interactions. 

"Salesforce believes fundamentally that bots are going to be complementing your live staff," said Meredith Flynn-Ripley, vice president of mobile messaging at Salesforce. "We really see bots as changing the job description and turning agents into intelligent problem solvers."

Flynn-Ripley described a future in which bots take over in "micro-moment exchanges" to relieve agents from doing tasks that "they don't even like doing." This could be as simple as information gathering, like asking a customer for their name and account number. But it could also look more like a conversational assistant, who gets smarter over time and can provide suggestions based off of data. 

While the majority of customer service interactions are still over the phone, Flynn-Ripley said that call centers could soon undergo big changes as more companies embrace chat as the most natural way to interact. 

"We often see the voice calls go down in a matter of weeks, and customer satisfaction go up," Flynn-Ripley said of new customers. "There's now an expectation that there should be automated bots." 

A 'seamless' experience 

Leveraging its vast amount of user data, Facebook opened up its messenger platform to developers and businesses in April 2016.

It's since added functions like in-chat payment, built-in natural language processing (NLP), and what it calls Handover Protocol. NLP is the code that helps automated bots understand human messages more easily; Handover Protocol is Facebook's system the lets customer service agents and bots work within the same customer conversation.

Though still in beta mode, some companies like the beauty retailer Sephora implemented the protocol this summer.

It's not yet seamless, but that's the goal. 

For messages that come in through Facebook, Sephora uses Assist, a business messaging platform, to evaluate which customer messages can be dealt with by a bot. If a bot can’t respond, the message will be passed along to a human agent using the customer service platform Sprinklr. 

On the customer side, the bot generates a button which prompts the user to request a human customer service agent. 

"We have a lot of potential to make that seamless, either by making the process smooth, or by providing humans powers like quick replies," Kemal El Moujahid, the lead product manager for Messenger Platform and M at Facebook, told Business Insider.

Like Salesforce, Facebook already has a lot of data about its users. Since artificial intelligence and chatbots are only as smart as the data they have access to, chatbots built on top of Facebook's system will likely have more advanced conversation abilities than chatbots built from scratch. 

"The promise of chatbots is personalization at scale," El Moujahid said, describing a world in which every company has a chat function which can use artificial intelligence to quickly address customer concerns tailored to the data available about that customer.

"The most important thing for humans is for their expectations to be managed. As long as it's really clear what the agent is able to do — whether bot or human — then the users are fine with that," El Moujahid said. "You don't need to have a bot that can talk about its holiday with you for you to have resolution for your cable problem."

Outside of the text box 

Many consumers would rather handle customer service issues by chat than over the phone phone — 56% according to a Nielsen study commissioned by Facebook. But this doesn't mean the future of chatbots is limited to words.  

While Flynn-Ripley wouldn't reveal much about Salesforce's developing projects, she did suggest that in the next few years chatbots might find a use for something like Salesforce's Einstein Vision — a set of application programming interfaces (APIs) which allow programmers to integrate pre-trained image classifiers, or to train their own image recognition software.

It's not hard to imagine a function in which chatbots can read barcodes, or analyze photos to better help customers with their needs. Image recognition is already a common feature with content management systems like Box, which partnered with Google Cloud Vision to allow users to search untagged images, or automatically sort images by their content. 

The data and capabilities appear to be there. It just hasn't been widely adopted. 

Elsewhere in the space, companies like PullString are working on creating more interesting forms of audio chatbots. PullString started creating interactive voice features for children's toys, but it's since expanded to work on software and creative services that power the development of audio-based chat functions for skills on Amazon's Alexa platform. 

Now, PullString focuses on developing personality-driven characters on Alexa, whose voice and word choice personify the brand as a whole. 

Michael Fitzpatrick, president of PullString, said that brand identity is key when it comes to digital customer service, and chatbots can provide a level of continuity and brand messaging that live agents can't. 

"One opportunity, I think, is to spend time designing interactions and model them to reflect truly what the brand's persona is," Fitzpatrick said, mentioning as examples that both Progressive and Geico insurance companies have done well with development of Flo and the Gecko, their respective mascots. After years of TV commercials focused on these characters, it would only seem natural to speak to one of them over Alexa to file an insurance claim or sign up for a new offering, Fitzpatrick said. 

Technological barriers 

Though the adoption of customer service chatbots has increased in recent years, there are still some technological barriers that need to be overcome before the technology is as seamless and helpful as its engineers dream it could be.

"The biggest hurdle at the moment is data," Fitzpatrick said. "I think that's true of artificial intelligence more broadly."

Fitzpatrick said that while there is a lot of data out there, it's not always applied in the best manner. Twitter-trained artificial intelligence like Tay, Microsoft's notorious xenophobic chatbot, highlight the need for smarter systems which can tell the different between good and bad inputs. 

El Moujahid agreed that data is at front of mind, saying that the biggest limitation right now is the speed at which artificial intelligence can process data, and how much data it requires to accurately train a bot.

"Right now there's a lot of potential with the existing technology," El Moujahid said. "NLP is still in its early days, so we're seeing really interesting stories from around making it faster with less data. There's a notion that those algorithms are powerful but require a large amount of data to train." 

Once these hurdles are overcome, however, chatbots could have a much bigger role in our day-to-day lives than they do now. El Moujahid said that it's not hard to imagine a world in which individuals have their own personal assistant-style bots to help with mundane tasks, like calling the cable company.

"There's no reason to imagine at some point you won't have your assistant interacting with the brand's bot," El Moujahid said. 

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Artificial intelligence has been around since the 1950s but is exploding in popularity recently, especially in the world of finance.

The idea that an investor can do a bit of programming, and then sit back to watch the profits roll in is an exciting idea, especially when it works. But according to a story by Adam Satariano and Nishant Kumar from Bloomberg, one hedge fund manager was initially scared by how well his AI trading machine worked.

"Were we scared by it? Yes. You wanted to wash your hands every time you looked at it," Luke Ellis, CEO of $96 billion hedge fund Man Group, told Bloomberg.

Ellis told Bloomberg that his firm developed a system that worked well and generated profits, but the firm couldn't really explain why it worked or made the trades it did, which is why they held off from rolling it out broadly. But, after several years a Ph.D. level mathematician at the firm decided to dust it off and give it a small portfolio to play with. Since then, the firm has been made the AI model a regular part of the family at Man Group.

It's worth reading the story behind the firm's trading algorithm from Bloomberg, as it tells the tale of an especially successful implementation of one of the hottest areas of tech right now. 

Artificial intelligence is an umbrella term for a computer program that can teach itself. Its power comes from its ability to "learn" the rules of the whatever it's tasked with without them being provided ahead of time. The best AI systems find rules and patterns that humans would miss by crunching huge amounts of data that would prove unwieldy for humans.

To understand this concept a bit better, think of a computer playing a game of chess. Chess is a finite world with a defined set of rules that a human can list for a computer ahead of time. There are a huge number of possible scenarios in a game of chess, but the number is finite and computer-crunchable.

Artificial intelligence systems are not given the rules ahead of time. Instead of listing the rules of chess, a computer using AI would simply be told to watch a huge number of chess games being played and figure it out. After enough matches, the computer would learn the rules of the game and be able to go head to head with a human player. That's exactly how Elon Musk's AI company beat a human in the incredibly complex game of Dota 2 recently.

In the world of finance, data points like shipping routes, weather and investor sentiment can all affect the markets. A human could never program all the rules that affect the markets because those rules are hard to define and almost infinitely numerous. But, they could feed a computer a huge number of data points and tell the computer to figure it out, which is largely what Ellis and his firm did to program their AI machine. He told Bloomberg that he gets pitched new data sets all the time because of this.

AI systems are coming into vogue now because the technology used to crunch these huge data sets has finally caught up with traders' ambitions. Companies like Nvidia and AMD are developing new computer chips that are fine-tuned to run AI systems, and Nvidia's CUDA software platform is helping researchers run their programs even faster.

AI doesn't mean the end of human traders though. Some over-exuberant trading programs are suspected to have caused a stock market flash crash in 2010, according to the Bloomberg story. Ellis and his team have successfully used artificial intelligence to improve returns in their firm, but it's not run entirely by the robots yet. 

Regardless, AI is taking over the world of finance. There will be winners and losers, but it's probably here to stay.

Click here to read the full Bloomberg story

SEE ALSO: Artificial intelligence is going to change every aspect of your life — here's how to invest in it

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