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      "body": "![main image.jpg](https://steemitimages.com/DQmNUGSJmkLMw53P7Xbazwyu7GCmT8feX1ZYtSrG1gqZnWQ/main%20image.jpg)\n\nLooking back, 2017 was a significant year for technology. Consider that at the beginning of 2017, Bitcoin was virtually unknown to most people , and Artificial Intelligence was something that they had perhaps heard of once or twice, but was still a concept confined to science fiction. Cloud computing was still untested to many people, and hardly anyone would realize how prevalent Bots would become a mere 12 months later.\n\nAs you can see, if we have a similarly fruitful “roller coaster” in 2018, we shall certainly be living in a more interesting world at the end of it !\n\nPreviously on my blog, I used to make a few predictions at the beginning of every year, trying to figure out what the tech world would do over the next 12 months. It was more light hearted than anything else , and it’s always funny to go back and see how wrong you were. On occasion though, I did manage to get a few right……So lets try and do the same for 2018. We certainly have an abundance of content to work with.\n\n<b>Personal A.I Gets Really Personal</b>\n\nLast year I wrote an article called “Personal A.I”. It described how machine learning and eventually artificial intelligence will run on devices on your person, in order to dramatically enhance your lifestyle. This also described another use case for “Edge Computing”, away from IOT ( although this technically is still IOT ). Very soon after the article , we saw that phone manufacturers were advertising the “machine learning” capabilities of their devices. The iPhoneX, for example, uses machine learning to recognise your face, in order to unlock the phone.\n\nFor 2018, I predict that while use more cases for phones will be found, Machine Learning will move to other devices like smart watches, and even clothing. Now I have mentioned this before, but the key is sensor technology. As sensors become more powerful, accurate, and most importantly cost effective, the integration into a shirt or under garment will become easier and more useful. The obvious use cases are monitoring of vital functions, with the clothing syncing with your smartphone ( which syncs to the cloud ), however once the basic use cases are implemented we will see more advanced scenarios. For example, if you're a budding athlete, smart socks measure how your feet hit the ground and help you perfect your running stride. One step further - temporary smart tattoos, designed to facilitate a specific use case for a timeframe (ie. imagine a stick-on tattoo on your wrist that identifies you at an event, not very far fetched ).\n\nIn 2018, I predict that smart clothing will become more common.\n\n<b>Personal A.I Gets Mature</b>\n\nWhile the physical medium for A.I extends to things like clothing, I’m also predicting a maturing in 2018 for Personal A.I on traditional devices, like smartphones. Currently we are seeing limited use cases but the hardware is there. In 2018, I think we’ll start seeing advanced use cases start to surface. Health monitoring is an easy use case to predict, since we're all already wearing the sensor device ( the smart watch or fitness band ). The next step, which Personal A.I will enable, is performing diagnosis on the device , not just data collection. This super-early diagnosis will eventually warn you before you have a heart attack, for example.\n\nThe next level would include environmental analysis on device, a smartphone that measures and understands air temperature, air quality and radiation levels. In real-time , you will be able to analyze carbon monoxide levels and methane levels. Your A.I assistant will know your history of exposure to dangerous gasses, and will warn you that you are exceeding the threshold, and you should move to a cleaner area if possible.\n\nIf you think this sounds far fetched, the device in your pocket already has more sensors than you would imagine. Yes, the smartphone is actually an amazing piece of engineering when you think about it.\n\n<b>Internet 2.0 ?</b>\n\nI read an article recently which claimed that Machine Learning will be the Internet 2.0.\n\nI have to disagree with this statement for many reasons. While Machine Learning will definitely provide tremendous advantages to businesses and may even create new industries over the next few years, Machine Learning is something that will still be implemented by humans in the near future. The algorithms used in business cases will be only as good as the statistician building them. The rise of Machine Learning is similar to the rise of Business Intelligence and Big Data a few years ago, except the potential business benefits will be much greater per successful implementation.\n\nBut, as with the other two, many systems integrators will claim to have Machine Learning capabilities but will not, and there will be many failed projects. A prominent tech industry exec recently claimed that A.I ( in its current state ) is more important than electricity or even fire. This is utterly absurd, have you ever seen such hype. Once again remember that Machine Learning currently is mostly human implemented.\n\nI predict that the Internet 2.0 will instead be the rise of the decentralised blockchain, and the applications and innovations that it will bring. This is the big disruptor over the short term, and this has been spoken of previously.\n\nAfter that, the Internet 3.0 will be, in my opinion, the development of sentient AI, or Strong AI. This will bring about the significant leap that we expect from this technology. Once the Singularity occurs, machines will be smart enough to analyze your business problem and design solutions for you, removing the risk of human error in the process.\n\nIn 2018, my view is that the decentralized blockchain, if it can reach its potential, will start to show signs of being Internet 2.0, and some key use cases will be uncovered over the next 12 months.\n\n<b>BOTS Will Be Everywhere</b>\n\nAnother easy prediction, because right now, BOTs are already everywhere, and most people don’t even realize it. A study in early 2017 showed that bots accounted for over 52 percent of internet traffic. That figure may be higher now , and the worrying thing is that most bots are attack bots. DDOD attackers, data-scrapers, spambots, and scavengers , they’re all there and they’re watching you. Trading is being done by bots , and as a human you won’t beat it. There are even theories that comment-bots write comments on sites such as Reddit, in order to further a particular opinion and give the impression that a certain view is more popular amongst the public.\n\nAway from the dystopia, there will simply be more automation in business processes by bots in 2018. I’m predicting that this trend will increase in 2018, and more processes all around us will be controlled by a Machine Learning powered bot.\n\nWhich brings me to ……\n\n<b> Machine to Machine Ecosystems</b>\n\nSo for me, machine-to-machine ecosystems is the first phase of A.I taking a more prominent role in society. The automated Bot driven process will start talking to other automated Bot driven processes, and entire ecosystems will be created. Imagine entire business value chains existing that are automated, controlled by Bots with the majority of decisions being machine learning driven , but with certain critical decisions being made by human beings. The machines will even be given the power in certain cases to perform transactions, especially where the timely nature of the transaction could lead to business advantages.\n\nThe next step from there would be the A.I using cryptocurrency to pay other A.I’s for goods or services. This is called the Machine Economy. Cryptocurrencies like IOTA have been created specifically for this purpose. The entire IOT industry is very important as the endpoint for the Machine Economy. The Machine Economy will both compliment and compete with the traditional economy. The fear mongers will predict doom and gloom ( in terms of jobs ) , the smart businessman will see the opportunity to help build the Machine Economy.\n\nIts not all about business ecosystems though. Things like vehicle to vehicle communications could become commonplace. Your car ( with its own Personal AI onboard ) will communicate with other cars around it to share information which could impact the efficiency and safety of your journey.\n\n<b>VR Doesn’t Take off - Again</b>\n\nVirtual Reality is a frustrating thing to follow. Throughout the 80’s and 90’s, we were promised that this would be the next big thing, a game changer. In the 2010’s, we have the technology to make this real, and in 2016 the first headsets were launched. After a slow start, we were told that 2017 would be the big year for VR ……it didn’t happen.\n\nAfter waiting for this technology for two decades , when I first got to try it about a year ago ……. It was ok. I don’t know why but it just doesn’t excite me anymore. I think that wearing a bulky helmet and being isolated from the outside world is something that humans just don’t want. The only thing that will change this is the emergence of a “killer app” ( remember this phase ? ).\n\nThere are some new headsets being launched in 2018 which may help but its the experience as a whole that needs to improve. Perhaps if they offer me a racing sim or flight sim that really puts me in the action , it will make me want it.\n\nThe current wave isn’t taking off - lets talk about it again in 3 years.\n\n<b>The Alt-coin Wars in Full Swing</b>\n\nThere are two types of people today - those who think that cryptocurrencies are a fad , and those who have seen the future potential of it. The crypto space is more than just Bitcoin, and there are solutions being worked on for all aspects of business. This is what the crypto-skeptics don’t realize. Blockchains enable more than just crypto-currency. There are “alt-coins” (alternative coins) which are actually platforms for solutions to be built on top of them, like Ethereum. In 2018, I predict that the “Alt-coin” wars will heat up.\n\nRemember, its not just about the value of the cryptocurrency, but more importantly, the potantial of the project to change society.\n\nCurrently, the following mini battles are being fought.\n\n<b><i>The Platform War - Ethereum vs NEO vs CARDANO</i></b>\n\nEthereum has so much potential. Some people call Ethereum the internet 2.0. Basically, it is a global scale decentralized platform that can support smart contracts and distributed applications. A smart contract is a piece of software that contains rules and regulations for negotiating the terms of a contract. In this way , automated smart contracts running on the Ethereum network remove the middleman and bring about trust. However, competitors to Ethereum have emerged, one being NEO. What makes NEO a force to be reckoned with is that it is backed by the Chinese government, as well as large Chinese companies such as Alibaba. This could be a boost to the platform in Asia , but could also make it less attractive in the West. This is the first major battle that will play out in 2018. Its still early day for CARDANO, but the price has already shot up.\n\n<b><i>The Money Transfer War - Ripple ( XRP ) vs Stellar Lumens ( XLM )</i></b>\n\nFor decades, banks have used SWIFT to facilitate cross border payments and money transfers. Now, crypto technology is leading to the emergence of alternative platforms, promising faster transaction times and fees that are a fraction of the cost. Currently, international transfers take days. With XRP and XLM , we are talking SECONDS. The Ripple network uses the XRP token to facilitate this transfer , although you don’t have to use XRP. Ripple has announced partnerships with organisations like American Express, and many trials are being conducted at the moment. Ripple isn’t a decentralized platform in the vein of Bitcoin and ETH though , the Ripple company controls everything. Stellar Lumens is a “fork” of Ripple, with some of the people from Ripple starting Stellar. It does have some technological differences as well as some big backers of its own. Currently Ripple is grabbing the headlines but some say that XLM could fight back hard in 2018. And there may well be room for both of these - look at the credit card industry where we have Mastercard, VISA and AMEX.\n\n<b><i>The Privacy War - Monero vs ZCash</i></b>\n\nMonero has been around since 2014 and was designed to be anonymous. Monero pursues user privacy in two ways: by concealing account balances and by mixing transactions. There is no public record of transations or user balances. Now Monero is already being used for illicit activities becuase of this , but so is the Internet itself. The increase in adoption is a reflection of the inherent value of the coin.\n\nZcash builds on blockchain based cryptocurrencies by offering end-to-end encryption. There is a big debate about which is superior ( which I wont get into now ), but with these 2 and other coins like Verge, totally private untraceable financial transactions are now a reality.\n\nThe crypto space is booming. It really does have that “Wild West” feel of the early internet. There will be winners , and of course, some big losers. My prediction for 2018 is that we will start seeing the winners emerge from the various mini battles.\n\n<b>One of the Big Retailers Announces Support for a Cryptocurrency in 2018.</b>\n\nThis, if it happens, is a big one. A retailer, one that is big enough, announcing support for crypto currencies could change the global landscape in one announcement. It will bring legitimacy to the crypto space, and cause real worry amongst established institutions.\n\nThe \"big three\" that I see who could accomplish the above are Amazon.com, UBER and Walmart.\n\nIf one , or all 3 of those announce support for crypto, it will be the tech announcement of the year.\n\nThe stumbling block though, is the current state of the industry. Long transaction times and high fees (for some coins), user unfriendliness, hackable wallets, and most importantly VOLATILITY in value will be the biggest barriers to it happening. Outside chance of an announcement in 2018, perhaps if one the big retailers wants to be seen as technologically advanced.\n\n<b>Massive A.I Powered Marketing Onslaught on Consumers</b>\n\nWhile every industry is hyping A.I, the reality is that marketing is probably the most common and broad use case for A.I today. The marketing industry also seems to be the one embracing A.I and Machine Learning the quickest.\n\nAlready, we see propensity models being created and used to analyse customer behaviour in ways previously unimagined. Retailers want to know everything about you so that they can predict your next move. While this has been happening for awhile, there are further developments which will expand in 2018. We are starting to see A.I generated content , optimised for marketing purposes and targeting you, the consumer. Every customer touchpoint will be optimized by A.I in order to be more relevant to you. An email sent to you will be more personalized than ever , since all your habits, interests and buying history will be collected and analyzed.\n\nA.I Platforms just for marketing will be built, like Albert. These will be able to execute across mutiple channels simultaneously, and much more effectively than before. There are now A.I powered content generation platforms like Wordsmith, which generate the perfect marketing blurb without the need for inefficient humans.\n\nConsumer facing businesses who embrace A.I for marketing, will gain such a big lead over their competitors in a short time, that it might as well be called Marketing 2.0.\n\nAs a consumer, you will not be prepared for this A.I powered onslaught.\n\nMore importantly, you will not be able to resist.\n\nIf your wallet is a lot lighter at the end of 2018, blame HAL.\n\nSo, I’ve stuck my neck out with a few predictions. In addition to the above , I don’t believe that autonomous cars will become common in 2018. Forget about the tech, I don’t think that the legal and insurance issues aren’t sorted out yet. I also think that Tesla is will not take over the car industry, and will have a difficult 2018. It will be funny to come back in a year to see what I got wrong. It will scary to come back and see what I got right. Lets hear your thoughts in the comments section.",
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      "body": "<html>\n<p>Congratulations <a href=\"/@thavash\" target=\"_blank\">@thavash</a>, you have decided to take the next big step with your first post! The Steem Network Team wishes you a great time among this awesome community.</p>\n<hr>\n<div class=\"pull-left\"><img src=\"https://steemitimages.com/DQmaAdLUJ3yaSkmcmWECWyPGPWcjfbCoZ8Tu4RM6H4DbjCi/steem-network-thumbs-up.gif\" alt=\"Thumbs up for Steem Network´s strategy\" title=\"I suggest Steem Network´s strategy\" width=\"320\" height=\"222\"></div>\n<h1>The proven road to boost your personal success in this amazing Steem Network</h1>\n<p>Do you already know that awesome content will get great profits by following these <a href=\"/steem-network/@steem-network/spread-your-posts-through-this-proven-strategy-and-get-great-profits-in-return--for-posts-created-at-2018-01-03\" target=\"_blank\" alt=\"Steem Network\" title=\"Follow Steem Network´s suggestions to boost your success\">simple steps</a>, that have been worked out by experts?</p>\n</html>",
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      "body": "As A.I becomes mainstream , it is still something that is not understood by a broad majority of people. So, I thought that I’d dabble in unpacking some of the key concepts here , for the beginner. \n\nFirstly, Artificial Intelligence isn’t really something brand new. It has been written about for decades, most famously by Alan Turing in 1951. In his article “Computing Machinery and Intelligence” he spoke of the “imitation game”, which later came to be known as the Turing Test. There was a movie in 2014 called “The Imitation Game” which details Turing’s life, and how he cracked the enigma code in WW2 (starring the usually excellent Benedict Cumberbatch). Highly recommended.\n\nIn terms of actually experiencing a simple AI, the easiest way to do this is to play a videogame. Even in the 80’s with “Pac-Man”, as the player you were trying to outwit the 4 enemies on screen – the algorithms behind the enemy players could be considered an early implementation of simple AI. Modern games have more complex implementations of \"AI\" that may surprise you with their intelligence.\n\n![Pacman.jpg.png](https://steemitimages.com/DQmXEk1yCGuPzsjbcjjUVghthnqKmoSMcwap3qkcyCV2Msf/Pacman.jpg.png)\n\n*Was Binky an A.I ?*\n\nSo why is AI becoming more prominent now? Very simply, we have now reached a tipping point where Big Data, software advances and cloud computing can be leveraged together to add value to businesses and society. Even though we are still many years from creating a sentient AI like HAL 9000, we can implement things like Machine Learning today to bring about improvements and efficiencies.\n\n**Machine Learning**\n\nMachine Learning is a subset of A.I, not really A.I in totality. Way back in 1959, Arthur Samuel defined Machine Learning as \"the ability to learn without being explicitly programmed\". Basically, this field entails creating algorithms that can find patterns or anomalies in data, and make predictions based on those learnings. Once \"trained\" on a set of data, these algorithms can very reliably (if chosen correctly), find those patterns and make predictions. Using tools like Azure Machine Learning, you can deploy this as a web service to automate the prediction process, and also do these predictions as a batch.\n\nNow I personally became exposed to similar concepts around 2006 when working with SQL 2005. That product release included a lot of \"data mining\" functionality. Data Mining basically involved using algorithms (many built into SSAS 2005) to find patterns in datasets, a precursor to Machine Learning today.\n\nI was really exciting by the possibilities of Data Mining, and tried to show it to as many customers as possible, however the market was just not ready. Many customers told me that they just want to run their data infrastructure as cheaply as possible and don't need any of this \"fancy stuff\". Of course, the tools today are a lot easier to use and we now include support for R and Python, but I think what was missing back in 2007 was industry hype. Industry hype, coupled with fear of competitors overtaking them, is possibly forcing some of those old I.T managers to take a look at Machine Learning now, while we also have a new breed of more dynamic I.T management (not to mention business users who need intelligent platforms) adopting this technology.\n\nMachine Learning today has evolved a lot from those Data Mining tools, and the cloud actually makes using these tools very feasible. If you feel unsure about the value Machine Learning will bring to your business, you can simply create some test experiments in the cloud to evaluate without making any investment into tools and infrastructure, and I'm seeing customers today embrace this thinking.\n\n**Deep Learning**\n\nDeep Learning can be considered a particular type of Machine Learning. The difference is that Deep Learning relies on the use of Neural Networks, a construct that simulates the human brain. We sometimes refer to Deep Learning as Deep Neural Networks, i.e. Neural Networks with many, many layers. The scale of deep learning is much greater than Machine Learning.\n\n**Neural Networks**\n\nNeural Networks have been around for decades. As mentioned, this is a construct that mirrors the human brain. In the past, we could build neural networks but simply didn't have the processing power to get quick results from them. The rise of GPU computing has given Neural Networks and Deep Learning a boost. There is a fast widening gap in the number of Floating Point Operations per second (FLOPS) that is possible with GPUs compared to traditional CPUs.  In Azure, you can now spin up VMs that are GPU based and build neural networks (where you might not have invested in such resources in the old on-premises world).\n\n![Nvidia.jpg](https://steemitimages.com/DQmPXdDUA2KjUQ59WL1RpzCE3ZvbRQayetNGD7iVznzMofA/Nvidia.jpg)\n\n*Image courtesy NVIDIA corporation\n\n While Machine Learning works well with repetitive tasks (i.e. Finding a pattern in a set of data), a neural network is better for performing tasks that a human is good at ( i.e. Recognizing a face within a picture).\n\n**Narrow AI vs General AI**\n\nAll of the above would typically fall under Narrow AI (or Weak AI). Narrow AI refers to non-sentient AI that is designed for a singular purpose (I.e. A Machine Learning model designed to analyze various factors and predict when customers are likely to default on a payment, or when a mechanical failure will occur). Narrow AI can be utilized today in hundreds of scenarios, and with tools like Azure ML, it's very easy to get up and running.\n\nGeneral AI (or Strong AI) refers to a sentient AI that can mimic a human being (like HAL). This is what most people think of when they hear the words \"Artificial Intelligence\". We are still many years away from this type of AI, although many feel that we could get there by 2030. If I had to predict how we get there, I would say perhaps a very large scale neural network built on quantum computing, with software breakthroughs being made as well. This is the type of AI that many are fearful of, as it will bypass human intelligence very quickly and there's no telling what the machine will do.\n\nWhy would we need a Strong AI? Some obvious use cases would be putting it onboard a ship for a long space journey – it is essentially a crew member that does not require food or oxygen and can work 24/7. On Earth, the AI would augment our capabilities and be the catalyst for rapid technological advancement. Consider this : we may not know where the AI will add the most value , however, once we build it, it will *tell us* where. \n\nThe good news is that you don't need General AI (a HAL 9000) to improve businesses in the world today. We are currently under-utilizing Narrow AI, and there is tremendous opportunity in this space. I encourage you to investigate what's out there today and you will be amazed at the possibilities.",
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