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A.I. will replace half of all jobs in the next decade

  • Intelligent Assistant

A Different Kind of Self Service

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Super intelligents AI-Life 3.0

Interview: Max Tegmark on Superintelligent AI, Cosmic Apocalypse, and Life 3.0

Image: Penguin Random House

Ask Max Tegmark why people should read his new book and get involved in the discussion about artificial intelligence, and you get a weighty answer. Forget about book sales, this is about cosmic destiny: The fate of the universe may well be determined by the decisions made “here on our little planet during our lifetime,” he says.

In his book, Life 3.0: Being Human in the Age of Artificial Intelligence, Tegmark first explains how today’s AI research will likely lead to the creation of a superintelligent AI, then goes further to explore the possible futures that could result from this creation. It’s not all doom and gloom. But in his worst case scenario, humanity goes extinct and is replaced with AI that has plenty of intelligence, but no consciousness. If all the wonders of the cosmos carry on without a conscious mind to appreciate them, the universe will be rendered a meaningless “waste of space,” Tegmark argues.

Tegmark, an MIT physics professor, has emerged as a leading advocate for research on AI safety. His thoughtful book builds on the work of Nick Bostrom, who famously freaked out Elon Musk with his book Superintelligence, which described in meticulous detail how a supercharged AI could lead to humanity’s destruction.

Max Tegmark on . . .

  1. Why He Disagrees With Yann LeCun
  2. “I Really Don’t Like It When People Ask What Will Happen in the Future”
  3. What Types of AI Safety Research We Should Fund Now
  4. The Question of Consciousness
  5. Cosmic Optimism vs Cosmic Pessimism
  6. AI as the “Child of All Humanity”

Superintelligent AI, Cosmic Apocalypse, and Life 3.0

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aiden.ai, a virtual colleague

 


Why You Should Start an AI Company Today

A new paradigm. A new opportunity.

“I skate to where the puck is going to be, not where it has been.” Wayne Gretzky

Our century’s biggest disruptor

We’re on the precipice of something really big. Bigger than electricity, bigger than the internet, experts say. AI is already omnipresent in our everyday lives: When Netflix recommends you should watch Jane the Virgin and Silicon Valley (Any resemblances to what I really watch on Netflix is a coincidence), that’s a form of AI i.e. an algorithm that learns from your tastes and predicts what you are most likely to enjoy watching next. Your vacuum cleaner is powered by AI. And if you live in China, even your toilet paper dispenser runs on AI!

In the workplace, artificial intelligence is evolving into intelligent assistants to help us work smarter, but also into drones that deliver the things we order on Amazon and of course into self driving vehicles (today, planes are mostly flown by AI already).

AI isn’t a new concept. It’s been around since 1956, when an MIT computer science teacher called John McCarthy coined the term, as well as the hipster beard looks long before it was a thing.

John McCarthy in his artificial intelligence laboratory at Stanford

He believed that

“every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it.”

AI, at its core, is a simple concept. Here’s the definition of Pedro Domingos an AI researcher I really enjoy learning from (check out this brilliant podcast he did on Farnam Street on the topic of AI)

What is AI ?

“AI is the subfield of computer science that deals with getting computers to do those things that require human intelligence to do as opposed to just routine processing.

Things like:
– Reasoning
– Understanding language
– Common sense knowledge
– Vision
– Learning
– Navigating in the world
– Manipulating things

These are all subfields of AI and if you add them all together what you have is an intelligence entity which would be artificial instead of natural.” –Pedro Domingos

When I mentioned to my parents 18th months ago, that I was leaving my job as a marketer with the goal of building an intelligent software that would automate a lot of the annoying work I had to do previously, their immediate reaction was to ask “why now?”. Indeed, AI has been around for some time and after the hype from the 70’s and late 80’s it cooled off quickly.

The “cool-down” periods my parents were referring to are the famous AI winters, early 1970’s and again late 1980’s that led to reduced funding in AI research. A notable moment was the collapse of the Lisp Machine, considered at one point a high form of AI, in 1987. (Here’s a timeline of the major breakthroughs in AI over the years for more information.).

For more history of AI, see Infographic: Rise of the Chatbots

Well, there’s 3 reasons why in 2017, things are different than 20 years ago:

  • Computing power has exploded. The cost of running intelligent algorithms on servers has dramatically decreased. It’s never been so cheap to train mathematical models.
  • Huge amounts of quality data are now available to train models. The advent of the digital economy and the popularization of smartphones generated billions of data points that companies can now turn into learnings.
  • Quantum leaps in tech, and most notably in Deep Learning. The world’s biggest companies including the big 4 Google, Amazon, Facebook, Apple (‘GAFA’), as a consequence, have heavily invested in AI either through acquisitions or hiring of world class AI researchers. And they have published parts of their research, and parts of their codes, for everyone to use.

AI Winter Is No Longer Coming, AI Spring Is.

This is why my cofounder and I decided, a year ago, that the time to start building our own virtual assistant was now (well, in June 2016 really). Aiden is a smart assistant for marketers, which was built as an expert system, and then augmented by machine learning. Here are the subsets of artificial intelligence Aiden deals with, and doesn’t deal with:

Aiden is what is rudely called a chatbot, but we see it as much more than that: the virtual colleague of the future.

Here’s a quote from Phil Libin that captures the essence of how “botentrepreneurs” should see their startup:

“Don’t think of yourself as a bot developer. Don’t pitch the whole yourself like that. Think of yourself as making a great product and a product that was impossible to make even 2 or 3 years ago because the technology stack didn’t exist. So what can you do now, it’s a little bit magic that you couldn’t do before. And now is the best time to go and build those things, because the tools and capabilities exist.”

The time is now.

You can sign up to request early access to Aiden on www.aiden.ai


I’m the CEO and cofounder of Aiden (Built with PJ Camillieri) If you think this article is interesting, please don’t hesitate to recommend it by clicking the button 👏 below. Sharing is caring and more people will see it :) Thanks!

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5-year trends in artificially intelligent marketing

How will artificial intelligence transform marketing over the coming years? Columnist Daniel Faggella dives into the results from a survey exploring the major trends and opportunities in AI for marketers.

Artificial intelligence has been making headlines over the last 12 months in domains like health care, finance, face recognition and more. Marketing, however, doesn’t seem to be getting the same kind of coverage, despite major developments in the application of AI to marketing analytics and business intelligence.

Five or 10 years ago, only the world’s savviest, most heavily funded companies had a serious foothold in artificial intelligence marketing tech. As we enter 2017, there are hundreds of AI marketing companies all over the world (including some that have gone public, like RocketFuel). These companies are making AI and machine learning accessible to large corporations and SMBs (small and medium-sized businesses) alike, opening new opportunities for smarter marketing decisions and approaches.

Over the last three months, we surveyed over 50 machine learning marketing executives (email registration required for the full report data) to get a sense of the important trends and implications of AI over the next five years.

Below, I’ve highlighted three major trends that impact the theme of “Intelligent Content.”

Recommendation and personalization predicted to be greatest profit opportunity

While most of our executives voted “Search” as the AI marketing tool with the highest profit potential today, “Recommendation and Personalization” topped the list for ROI potential in the coming five years.

While search requires users to express their intent in text (or speech), recommendation pulls from myriad points of data and behavior — often bringing a user to a) what they were truly looking for, or b) what the advertiser wanted them to find.

The implications of recommendation in content marketing are numerous. Below I’ll list just a few:

First, recommendation engines help serve the content most likely to engage readers. In the past, this was done with simple text analysis or tools like elastic search. The “recommended” content was better than a random guess, but it was by no means truly optimized for user engagement.

Companies like Boomtrain and Liftigniter are developing technologies to tailor content to individual visitors, displaying material most likely to keep them on the site based on their previous engagements, purchases, clicks and more.

Second, programmatic advertising (like that used on giant platforms like Facebook and Google AdWords) is often used to drive users directly to content before seeing a product page or being asked to book an appointment. Many ad networks (Facebook included) don’t allow for direct lead generation and instead prefer to engage users with the right content first before looking for a conversion.

Ad networks are partial to keeping user experience high in addition to driving engagement on ads, which is a delicate balance. Companies that can leverage these programmatic platforms to target the right prospects with the right content are the most likely to win.

Third, we see entire content marketing platforms at the heart of business models. One such example is Houzz.com, a site that hosts millions of articles and photo albums about home improvement and decoration. This content ecosystem links to and references millions of home goods products (from throw rugs to couches and more), and “recommendation” drives the entire experience.

Houzz is one of the best current examples of “intelligence content” directly tying to sales, and I suspect that in the coming five years, we’ll see elements of their business model become much more prevalent.

Intelligent content might be content that makes itself

Content generation is a complex machine learning problem, and until recently, it’s been relegated to big-budget media firms working in quantitatively oriented domains (namely sports and finance). Yahoo Finance uses natural language generation (NLG) to turn information about stocks and bonds into coherent, human-readable articles, saving time for Yahoo’s writers so that they can complete more important and creative tasks.

NLG is now being used in a vast number of business applications including compliance, insurance and more — and a quick visit to the “solutions” page at Narrative Science shows a plethora of use cases and case studies for machine-written content.

While domains like finance and compliance involve strict, formulaic transformations of cold data into readable text, executives in the field are excited about its profit potential, too. Rather than simply saving costs on human writers, intelligent content generation will alter existing content (and/or create new content) to help driving marketing goals. As Laura Pressman, manager of Automated Insights, explained in our survey:

Content generation has high profit potential in the coming five years. Personalization and segmentation can be achieved through altering the content text to speak to certain groups of people, across different platforms, highlighting unique and targeted features that are most important to each specific segment.

B2C companies may have an advantage in intelligent content

When we polled our batch of executives about the most meaningful applications of artificial intelligence in marketing, we didn’t want to leave out their opinions about which businesses or industries would be most able to take advantage of AI’s advancements in marketing.

“Industry” didn’t seem to have much to do with the predicted success that a company might have with AI marketing tech. Much more important was the way the company did business and sold products. For a business to take advantage of AI, the most important traits (as predicted by our batch of executives) include:

  • Data collection: Ability to quantify customer touch points across all marketing activities.
  • Transaction volume: Reaching the marketing “goal” more often helps to train marketing algorithms and provide better predictions and recommendations.
  • Uniformity: Businesses that pool their marketing and sales data into a single stream are more likely to succeed in applying AI.

The above three qualities repeated themselves again and again in our survey responses, along with strong predictions that “Digital Media” companies and “E-commerce/Consumer Retail” companies would be most poised to take advantage of AI in marketing. As Lisa Burton, chief data officer of AdMass, explained in the survey:

Advertisers and e-commerce businesses have the highest potential gain from machine learning because of the ease of measurement and quick feedback needed to train and improve machine learning algorithms.

While B2C and retail companies seem to have an edge on “quantifiability” and attribution to sale, some of our respondents also hinted at the strong opportunity in B2B. Leveraging the many content and interaction touch points in a B2B sale will aid greatly in “cracking the code” on B2B marketing attribution, which is undoubtedly valuable.

In the coming five years, it may be possible that attribution and recommendation take off quickly in retail, while adoption in services and B2B sectors will provide more of an “ahead of the curve” advantage in industries where tech adoption is slower.

5-year trends in artificially intelligent marketing

 

AI Experts Want to End ‘Black Box’ Algorithms in Government

Researchers at AI Now say algorithms increasingly used by government can be opaque and discriminatory.

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    Artificial emotional intelligence

  • Instamate Premium Monthly Instamate is the worlds first all in 1 web based Instagram tool that finds the most viral content on FB, Instagram and Pinterest then allowing you to post and Schedule directed from the computer.
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Better Than Smart Speakers? Japan Is Making Robot and Hologram Companions

While American internet giants are developing speakers, Japanese companies are working on robots and holograms. They all share a common goal: to create the future platform for the Internet of Things (IoT) and smart homes.

Names like Bocco, EMIEW3, Xperia Assistant, and Gatebox may not ring a bell to most outside of Japan, but Sony, Hitachi, Sharp, and Softbank most certainly do. The companies, along with Japanese start-ups, have developed robots, robot concepts, and even holograms like the ones hiding behind the short list of names.

While there are distinct differences between the various systems, they share the potential to act as a remote control for IoT devices and smart homes. It is a very different direction than that taken by companies like Google, Amazon, and Apple, who have so far focused on building IoT speaker systems.

Bocco robot. Image Credit: Yukai Engineering

“Technology companies are pursuing the platform—or smartphone if you will—for IoT. My impression is that Japanese companies—and Japanese consumers—prefer that such a platform should not just be an object, but a companion,” says Kosuke Tatsumi, designer at Yukai Engineering, a startup that has developed the Bocco robot system.

At Hitachi, a spokesperson said that the company’s human symbiotic service robot, EMIEW3, robot is currently in the field, doing proof-of-value tests at customer sites to investigate needs and potential solutions. This could include working as an interactive control system for the Internet of Things:

“EMIEW3 is able to communicate with humans, thus receive instructions, and as it is connected to a robotics IT platform, it is very much capable of interacting with IoT-based systems,” the spokesperson said.

The power of speech is getting feet

Gartner analysis predicts that there will be 8.4 billion internet-connected devices—collectively making up the Internet of Things—by the end of 2017. 5.2 billion of those devices are in the consumer category. By the end of 2020, the number of IoT devices will rise to 12.8 billion—and that is just in the consumer category.

As a child of the 80s, I can vividly remember how fun it was to have separate remote controls for TV, video, and stereo. I can imagine a situation where my internet-connected refrigerator and ditto thermostat, television, and toaster try to work out who I’m talking to and what I want them to do.

Consensus seems to be that speech will be the way to interact with many/most IoT devices. The same goes for a form of virtual assistant functioning as the IoT platform—or remote control. Almost everything else is still an open ballgame, despite an early surge for speaker-based systems, like those from Amazon, Google, and Apple.

Why robots could rule

Famous android creator and robot scientist Dr. Hiroshi Ishiguro sees the interaction between humans and the AI embedded in speakers or robots as central to both approaches. From there, the approaches differ greatly.

Geminoid-female-human-android-Hiroshi-Ishiguro-Laboratories
Image Credit: Hiroshi Ishiguro Laboratories

“It is about more than the difference of form. Speaking to an Amazon Echo is not a natural kind of interaction for humans. That is part of what we in Japan are creating in many human-like robot systems,” he says. “The human brain is constructed to recognize and interact with humans. This is part of why it makes sense to focus on developing the body for the AI mind as well as the AI mind itself. In a way, you can describe it as the difference between developing an assistant, which could be said to be what many American companies are currently doing, and a companion, which is more the focus here in Japan.”

Another advantage is that robots are more kawaii—a multifaceted Japanese word that can be translated as “cute”—than speakers are. This makes it easy for people to relate to them and forgive them.

“People are more willing to forgive children when they make mistakes, and the same is true with a robot like Bocco, which is designed to look kawaii and childlike,” Kosuke Tatsumi explains.

Japanese robots and holograms with IoT-control capabilities

So, what exactly do these robot and hologram companions look like, what can they do, and who’s making them? Here are seven examples of Japanese companies working to go a step beyond smart speakers with personable robots and holograms.

1. In 2016 Sony’s mobile division demonstrated the Xperia Agent concept robot that recognizes individual users, is voice controlled, and can do things like control your television and receive calls from services like Skype.

2. Sharp launched their Home Assistant at CES 2016. A robot-like, voice-controlled assistant that can to control, among other things, air conditioning units, and televisions. Sharp has also launched a robotic phone called RoBoHon.

3. Gatebox has created a holographic virtual assistant. Evil tongues will say that it is primarily the expression of an otaku (Japanese for nerd) dream of living with a manga heroine. Gatebox is, however, able to control things like lights, TVs, and other systems through API integration. It also provides its owner with weather-related advice like “remember your umbrella, it looks like it will rain later.” Gatebox can be controlled by voice, gesture, or via an app.

4. Hitachi’s EMIEW3 robot is designed to assist people in businesses and public spaces. It is connected to a robot IT-platform via the cloud that acts as a “remote brain.” Hitachi is currently investigating the business use cases for EMIEW3. This could include the role of controlling platform for IoT devices.

5. Softbank’s Pepper robot has been used as a platform to control use of medical IoT devices such as smart thermometers by Avatarion. The company has also developed various in-house systems that enable Pepper to control IoT-devices like a coffee machine. A user simply asks Pepper to brew a cup of coffee, and it starts the coffee machine for you.

6. Yukai Engineering’s Bocco registers when a person (e.g., young child) comes home and acts as a communication center between that person and other members of the household (e.g., parent still at work). The company is working on integrating voice recognition, voice control, and having Bocco control things like the lights and other connected IoT devices.

7. Last year Toyota launched the Kirobo Mini, a companion robot which aims to, among other things, help its owner by suggesting “places to visit, routes for travel, and music to listen to” during the drive.

Today, Japan. Tomorrow…?

One of the key questions is whether this emerging phenomenon is a purely Japanese thing. If the country’s love of robots makes it fundamentally different. Japan is, after all, a country where new units of Softbank’s Pepper robot routinely sell out in minutes and the RoBoHon robot-phone has its own cafe nights in Tokyo.

It is a country where TV introduces you to friendly, helpful robots like Doraemon and Astro Boy. I, on the other hand, first met robots in the shape of Arnold Schwarzenegger’s Terminator and struggled to work out why robots seemed intent on permanently borrowing things like clothes and motorcycles, not to mention why they hated people called Sarah.

However, research suggests that a big part of the reason why Japanese seem to like robots is a combination of exposure and positive experiences that leads to greater acceptance of them. As robots spread to more and more industries—and into our homes—our acceptance of them will grow.

The argument is also backed by a project by Avatarion, which used Softbank’s Nao-robot as a classroom representative for children who were in the hospital.

“What we found was that the other children quickly adapted to interacting with the robot and treating it as the physical representation of the child who was in hospital. They accepted it very quickly,” Thierry Perronnet, General Manager of Avatarion, explains.

His company has also developed solutions where Softbank’s Pepper robot is used as an in-home nurse and controls various medical IoT devices.

If robots end up becoming our preferred method for controlling IoT devices, it is by no means certain that said robots will be coming from Japan.

“I think that the goal for both Japanese and American companies—including the likes of Google, Amazon, Microsoft, and Apple—is to create human-like interaction. For this to happen, technology needs to evolve and adapt to us and how we are used to interacting with others, in other words, have a more human form. Humans’ speed of evolution cannot keep up with technology’s, so it must be the technology that changes,” Dr. Ishiguro says.

Image Credit: Sony Mobile Communications

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This ultra-cute tiny PS4 controller is a great option for children and the small-handed

 If you like playing console games with the younger generation, you may have come across the issue of their tiny hands being unable to perform certain combos, reach certain buttons easily, and so on. While this makes them satisfying opponents, it might be better if they had a controller more suited to their physiology. Well, good thing there is one! Read More

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AlphaGo Zero trains itself to be most powerful Go player in the world

(credit: DeepMind)

Deep Mind has just announced AlphaGo Zero, an evolution of AlphaGo, the first computer program to defeat a world champion at the ancient Chinese game of Go. Zero is even more powerful and is now arguably the strongest Go player in history, according to the company.

While previous versions of AlphaGo initially trained on thousands of human amateur and professional games to learn how to play Go, AlphaGo Zero skips this step. It learns to play from scratch, simply by playing games against itself, starting from completely random play.

(credit: DeepMind)

It surpassed Alpha Lee in 3 days, then surpassed human level of play, defeating the previously published champion-defeating version of AlphaGo by 100 games to 0 in just 40 days.

The achievement is described in the journal Nature today (Oct. 18, 2017)

DeepMind | AlphaGo Zero: Starting from scratch


Abstract of Mastering the game of Go without human knowledge

A long-standing goal of artificial intelligence is an algorithm that learns, tabula rasa, superhuman proficiency in challenging domains. Recently, AlphaGo became the first program to defeat a world champion in the game of Go. The tree search in AlphaGo evaluated positions and selected moves using deep neural networks. These neural networks were trained by supervised learning from human expert moves, and by reinforcement learning from self-play. Here we introduce an algorithm based solely on reinforcement learning, without human data, guidance or domain knowledge beyond game rules. AlphaGo becomes its own teacher: a neural network is trained to predict AlphaGo’s own move selections and also the winner of AlphaGo’s games. This neural network improves the strength of the tree search, resulting in higher quality move selection and stronger self-play in the next iteration. Starting tabula rasa, our new program AlphaGo Zero achieved superhuman performance, winning 100–0 against the previously published, champion-defeating AlphaGo.

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Here Are Twitter’s Latest Rules for Fighting Hate and Abuse

Memo outlines steps Twitter plans to control hate and abuse on the service, including expanded definitions of nudity and more enforcement.

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B2B marketing has undergone a massive transformation.

Over the past decade, B2B marketing has undergone a massive transformation. According to Forrester Research, the entire B2B sector represents more than $1 trillion in digital commerce every year, more than double the size of the B2C economy.  But what’s next? Is artificial intelligence the rocket fuel to take us through the next decade of marketing technology?

AI is not about inventing a new task or a new way of being intelligent, but simply mimicking human intelligence. It’s about doing the same old human tasks at super-human scale. Given that it’s a machine doing the work, AI can be done at infinite scale since it can read and process billions of data points with perfect memory.

The abundance and availability of data around marketing is why marketing processes are such a sweet spot for AI. Marketing is also a process that still has very low yields (0.03 percent, from an initial inquiry to closed business) and thus provides ample opportunities for ROI. We’ve already seen everyone jumping into the fray, including Salesforce with Einstein and Microsoft with its new Dynamics AI platform. In addition, Sundar Pinchai, the CEO of Google, recently announced that AI will be the central component in all of their products.

AI is different from just sorting data or predicting leads based on a limited CRM database. It’s a lot closer to Amazon Echo than to a spreadsheet. The next frontier for AI will be on the frontline of the brand communicating directly with the buyers rather than some back-office process. But to do so, it must be able to understand and communicate in the language of buyers and gauge deep insights about them. Given that most of the world’s knowledge is expressed in natural language, it has to be able to understand and communicate in human language and not in scores or numbers.

Hyper-personalized conversations at scale

There are many areas in marketing where current and future AI can be applied, including lead ranking, buyer identification, data cleansing, dynamic account assignment, opportunity forecasting, and the next sales action. But the most interesting and valuable use for AI is the ability for marketers to have a one-on-one personalized conversation with buyers who know their pain points, goals, and ambitions. The value of hyper-personalization comes from its ability to eliminate one of the scourges of marketing: worthless spam. It allows the brand to scale a personalized conversation to millions of buyers as if there were a personal concierge attending to them.

What exactly do I mean by that? Today, strategic account or field marketing managers act as such a concierge; they have in-depth knowledge of the accounts, business landscape, and industry and know how to align their conversation to the buyer’s business priorities. Until recently, such conversations happened only with an exclusive realm of highly paid people. But now AI can allow each of a company’s 10 million website visitors to have a unique conversation with a brand.

We already know this tactic works when conducted by humans. In fact, according to McKinsey, personalization can deliver five to eight times the ROI on marketing spend.

Types of hyper-personalization

Every industry has slightly different methods and channels in which they communicate to their buyers. To make hyper-personalization work and to avoid sounding disjointed, AI has to be applied consistently to all the ways in which a brand communicates to their existing and new customers. Three ways marketers can apply hyper-personalization across the buyer’s journey are:

  • Dynamic ad copy: Today, we don’t think of advertising as part of a conversation, because it’s stuck on a billboard or a website and doesn’t apply to 99 percent of the people viewing the ad. What if the ad copy could actually change for every buyer and account? We know that would be more effective. What if we knew that the ad impression was going to a female CMO of an auto parts manufacturer in Detroit, with a new partnership with Mercedes, targeting Tesla as an account, with budget for a new digital marketing system? AI could develop personalized ad copy tailored to this CMO — “Marissa, download a case study of how Mercedes is using our marketing engine to transform their digital experience.”
  • 1-to-1 emails: This is the most exciting opportunity for hyper-personalization at scale, since emails still remain the primary communication for deals. While generic messages don’t really work, researching buyer interest to create personalized messaging does. If a human does this, it is inefficient and rarely effective. With AI, you can understand buyers’ interests at scale and craft highly personalized emails to them.
  • Unique website experience:  The same advertising conversation has to continue to a brand’s website. Today, about 50 percent of the people bounce, and 97 percent of the people don’t really find what they’re looking for. Imagine a Netflix-style personalization engine where richer content is weaved from individual pieces and net new web content is generated with suggestions for what a prospect would like based on past viewing experiences. What if the same CMO of the car parts manufacturer clicked through the personalized ad and we knew that she likes her content in video format? Would you want her to be on a generic website or just show her the video case studies you have for the auto industry?

How can marketing organizations make this happen today?

In some not-too-distant future, each hyper-personalized conversation across ads, the web, and email will be automatically generated from scratch. But that’s not possible today. Natural language generation is still a complex developing field. Thankfully we can hack around this problem by weaving in pieces of existing content.

There’s nothing wrong with that, and in reality, that’s what your smart sales and marketing people are doing when they’re asked to do something custom. Companies like Netflix and Amazon have become masters of product and content recommendations over the past decade, and there is absolutely no reason why other businesses can’t apply the same techniques based on data on their own websites or third-party identifiers.

By combining a company’s internal clickstream data and simple machine learning, effective personalized experiences can be delivered today so we are not sending our users down a structured maze of industry or product categories.

 

    Artificial emotional intelligence

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Blockchain Will Be the Foundation of Trust in the Metaverse

“Virtual worlds are going to be one of the first killer apps for blockchains and perhaps the deepest users of them.” – Fred Ehrsam, Co-Founder, Coinbase

Christian Lemmerz, a German-Danish sculptor who normally carves his subjects into marble, currently has his latest work on display in Venice, Italy. “La Apparizione,” a towering golden image of a crucified Jesus Christ, won’t be found sitting on a pedestal, however, because this is a work of virtual reality art.

That means viewers attending the exhibit are first made to stand in an empty room where they are placed inside a VR headset display. Only once the headset is on do they see the floating, pulsing Jesus hovering before them.

Museum curators and art collectors, now slowly embracing virtual reality as a medium of expression, are taking notice of pieces like this. Lemmerz’s statue is currently for sale, and with only five editions of the piece now released, each one costs around $100,000. That may be an expensive price tag for a piece of software, but not out of line for a high-end work of art.

In theory, this work of art could also be hacked, stolen, endlessly copied, and distributed online. Art forgery, a practice that dates back at least 2,000 years, presents a unique set of challenges for the industry when the art itself is made from lines of code. It’s likely that Lemmerz would not appreciate if forgeries of his work soon poured out from file-sharing sites like Pirate Bay.

Since the price of art depends on scarcity and authenticity to preserve it’s value, how might the value of a prized digital work be protected?

One promising solution is blockchain technology.

In fact, blockchain may become the way we verify the legitimacy of almost any virtual asset, including currencies, identity, and the authenticity and ownership of virtual property. Fred Ehrsam, co-founder of the popular cryptocurrency exchange Coinbase, has written that “virtual worlds are going to be one of the first killer apps for blockchains and perhaps the deepest users of them.”

In the case of verifying digital art like “La Apparizione,” using a blockchain is more straightforward. As I wrote in 2016, “blockchains are powerful for one reason: they solve the problem of proving that when someone sends you a digital “something” (like bitcoin, for example), they didn’t keep a copy for themselves, or send it to 20 other people.” Using a blockchain to buy and sell rare VR art is one way to validate that a particular work is indeed the original.

“Blockchains may be the best way to authenticate ownership of virtual property, or even establish and preserve someone’s identity.”

Ehrsam is pointing at an even deeper insight about the use of blockchains in virtual reality. As more companies, including Second Life developer Linden Lab, work to build the large-scale virtual worlds often compared to concepts like the “metaverse” from Neal Stephenson’s Snowcrash or the OASIS in Ready Player One, blockchains may be the best way to authenticate ownership of virtual property, or even establish and preserve someone’s identity.

Philip Rosedale, the founder of Second Life and a new VR world called High Fidelity, posted an essay indicating his own enthusiasm for the way that blockchains may be useful in VR. High Fidelity is now launching a new cryptocurrency, called HFC, on a public blockchain that will be used, among other things, to verify the authenticity and ownership of virtual goods.

“If there was no concept of intellectual property in virtual worlds, there would be little motivation to create things, since your creations would immediately be re-used and re-distributed by others without agreement,” Rosedale tells Singularity Hub.

Rosedale says that content creators won’t be incentivized to create digital property if they cannot protect and profit from their work. And considering that buying and selling virtual property is already profitable for many virtual world users, it does seem like an aspect of virtual life many will want to protect.

In 2016 alone, the buying and selling of virtual goods and services between users in Second Life was $500 million—making its economy larger than the GDP of some small countries. Users exchange fashion accessories for their avatars and virtual furniture to decorate their online spaces, and artists like Lemmerz could reasonably seek out collectors and galleries willing to buy their work.

According to High Fidelity, the HFC blockchain will be used to ensure that virtual goods are the original by allowing creators to assign certificates to their work.

“Users will be able to register their creations on the blockchain so they can prove ownership of their designs. Next, when something is bought, a certificate will be issued on the blockchain proving that the new owner has a legitimate copy,” Rosedale says.

This system will serve a similar function as patents and trademarks in the real world. High Fidelity says they intend to create a process of review, similar to that conducted in many countries, to ensure that the registration of a digital certificate be granted to real original work that doesn’t infringe on earlier creations. Once assigned, the certificate cannot be canceled and will be insured on the HFC blockchain.

“Unverified goods could be dangerous, for example containing malicious scripts. Certified digital assets will be much more safe, just as with the App Store today,” Rosedale adds.

“If your assets are on a blockchain, no single operator of a world can take them from you. If your identity lives on the blockchain, you can’t be deleted,” Ehrsam writes.

Another major benefit blockchains offer, as Ehrsam points out, is that they prevent any single company or centralized intermediary from having the power to manipulate things. As depicted in Ready Player One, where a single oligarchic company owns and operates the servers that host the story’s virtual world, a single company hosting any virtual world could in theory exploit users in a variety of ways.

“If your assets are on a blockchain, no single operator of a world can take them from you. If your identity lives on the blockchain, you can’t be deleted,” Ehrsam writes.

Ehrsam’s key takeaway is insightful. He writes, “When you drill down, blockchains are really a shared version of reality everyone agrees on. So whether it’s a fully immersive VR experience, augmented reality, or even Bitcoin or Ethereum in the physical world as a shared ledger for our ‘real world,’ we’ll increasingly trust blockchains as our basis for reality.”

Since virtual reality is a public space constructed entirely of software, blockchains may prove useful and perhaps essential in providing a foundation for trust.

For more, High Fidelity also posted a followup post detailing the use of the HFC blockchain specifically for protecting intellectual property in virtual reality.

Image Credit: Tithi Luadthong / Shutterstock.com

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