The Fabric Of The Internet Is About To Change - Boldstart Technology
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The Fabric Of The Internet Is About To Change


The Fabric Of The Internet Is About To Change

The 4th industrial revolution is about change the very fabric of the internet forever, enabling every human on the planet to participate for the first time.


That’s a bold statement! Let me explain…..

1. Language – The Ultimate Leveller

2-y-oldLanguage is the foundation of all communication for humanity. Every man, woman and child on the planet holds the skills of language. They may not be able to read or write or use a computer by they can communicate through a given language to understand and be understood. (video)


That makes language a far more powerful fabric than our current internet framework of websites and apps, and it’s AI technologies that are enabling this new framework.


Rudimentary language skills will allow even the poorest citizens to access information to enrich their lives, and undertake tasks that would currently require much higher levels of education. Whilst only 4.5 billion of the world’s population have access to modern sanitation, 6 billion have access to a mobile phone, but only 3.5 billion of those currently access the internet.


Voice & language will initiate this metamorphosis and provide the gateway for the third world. AI technologies like Google Translate will allow an illiterate child in one of the poorest nations to compose a gmail message in English or find an instructional video on how to treat the abscess on his donkey’s hoof.


The fabric of the internet will become less about device compatibility and more about human compatibility, more closely aligned to the human senses of sight, sound, and touch.


2. NLP- The New Internet Markup Language

The Natural Language branch of AI technologies hold the ability to do away with the vast majority of this ageing and costly framework.


IoT devices would use NLP engines as their firmware API, enabling all manner of objects to become instantly interoperable using the simple communication protocol of natural language. This means all the development to add a device to any network can be done at the point of manufacture, so to switch on a smart light bulb you simply pass it a simple command string like ‘turn on’. Your smart TV identifies itself on the home network and any of your Amazon Echoes or Google Home devices simply pass simple instructions to it like “Go To Sky News”. The skill built into your Echo device just became easier to create, as the API call is now merely a string of language commands.


In this 4th industrial revolution websites will quickly grow natural language interfaces, where natural language engines become the beating heart of the site, consuming all the data, and delivering exactly what users come to the site for, allowing them to access it in a number of ways, not just verbally, but in ways that will see traditional websites become redundant.


Deep learning is accelerating the progress of chatbots and enabling the use of end-to-end conversational systems through recurrent neural networks making the creation of chatbots and conversational interfaces much easier to build. Highly competent bots can now be built with as little as 50 lines of code and some training data for, say, a bot that will talk about movies.

hype_cycleGartner recently re-adjusted it’s thinking on language interaction by stating that AI bots will power 85% of customer service interactions by 2020” . That’s just three years away! A shift from the “5-10 years away” in their 2016 Hype Cycle chart.
messaging_appsMessaging apps are already over taking social media in terms of consumer popularity and these provide a natural channel for service and commerce bots to exist. With text messaging being so prevalent as a means of communication nowadays purchasing and customer service through these channels is a sure bet for success. It is also a good indication of how the world wide web will look early on in this new paradigm.


3. ‘Big Data’ Fusion

For the first time in history, technology has advanced to a point where big data is actually useable, it’s always been useful but now, with the progress in AI technologies, it’s also useable for the first time.


Up until the last 24 months or so data lakes have been pretty much silos with minimal integration and interrogation, except those owned by the major tech companies like Google. Machine learning techniques have enabled data fusion and analysis in realtime to such an extent that we can now produce truly accurate predictive modelling for use in everything from the VA in your smartphone that tells you when to leave for meeting based on real-time data, through to diagnosis and triage for cancer treatment.


This fusion of massive amounts of real-time data is helping tech and car companies provide autonomous driving at high speed in constantly changing environments. This is only possible through fusion of point cloud data in real-time. The disruptive side-effect is it has the potential to redefine transport usage and car ownership that itself has a knock on effect to many industries, like insurance. Auto manufacturers have realised this late and are now investing billions through M&A to maintain a stake in the game going forward.


In everything from retail to manufacturing, even baggage handling, AI and data fusion is redefining buy and supply cycle workflows to improve every function across an enterprise.


Data is the key asset here and technology merely the tools. Here’s the kicker; Data can be generated by anyone with proximity to customers. The big tech companies have realised this, and that’s why enterprises need to put their data assets to work. Customers of businesses are customers of big tech too. Google knows more about your customers than you do, and they’re using that data. Amazon has reinvented itself from being a bookseller to one of the largest and fastest growing tech businesses and retailers in the world, through data.

cameraThese tech companies are building highly scalable products and services through customer data to disrupt industries either themselves or by providing startups with enabling technology and services. The app stores, AWS, Amazon Echo, Google Home, Google vision, Raspberry Pi and Tensorflow, are all examples of enabling technologies that are giving startups a level playing field to disrupt traditional businesses. It is now easier than ever to build a business based around technology.


In 5 years, no part of a business will be left undisrupted by the influence of AI to improve efficiency or customer satisfaction. Entire professions based around documented historical experience like legal and accounting face a mounting challenge, as new AI services emerge to address everything from challenging your parking ticket to handling divorce.


The pace of this industrial revolution will be governed by the volume of data available to improve learning. Given that 90% of the world’s data was created in the last two years this is almost certain to be a fast paced revolution. Change will become a fluid constant, driven by data. You will either disrupt through data and the use of AI, or be rapidly disrupted to become obsolete.

4. Cognitive Computing

Applications and data formats will become less important. Large amounts of unstructured data can now be analysed by a variety of AI technologies to generate intelligent understanding, and from that make informed decisions. How we store information will become unimportant, and how we consume information will be refocused to fundamental human senses of sight, sound and touch, enabling even those with the most rudimentary of education to gain intellectual and commercial advantage.


Cognitive computing has enabled accelerated performance in new technologies. For example, back in 2010 Google voice (part of Google translate) was faster but less accurate than Nuance’s equivalent. This rapidly improved from 2012 thanks largely to the work of Google’s Brain Team, and is now as good if not better than Nuance. Try Google voice or translate now and the quality is immeasurably better.


Google Translate has managed to generate self-learning through the creation of an interlingua, a tool it has created by itself to translate any language to another instead of using say English as an intermediary.


These new AI technologies are fuelling accelerated learning and self-learning, and for the first time keeping pace with the volume of data being generated. They can now execute similar, if not better accuracy than the human brain, faster and for sustained periods better than any person.


Within a few short years AI will replace most traditional application technologies. CRM will be obsolete, giving way to more accurate data maps of individual activities with real-time accuracy that can be used to make faster, better, more efficient decisions going forward. Even UX/UI as we currently know it will be driven by AI, delivering highly personalised methods for accessing data and applications.


Product design is even starting to benefit from AI techniques. For example the design for this simple cable support (below) has been optimised through software analysis (the one on the right) using data from the natural world to produce a more efficient product, weighing up to 75% less than a human designed one (the one the left), and it is 3D printable.

connectorsThe opportunities to improve the lives of billions of people has never been more achievable than it is today. We are already seeing AI that can reduce the environmental impact of humanity through things like material waste, or Google’s use of DeepMind to improve datacentres’ power efficiency.
cucumberThe diversity of applications is astonishing, and demonstrates the big tech companies’ ability to quickly democratise access to these new technologies. Earlier this year a cucumber farmer in Japan used Tensorflow’s neural networks to manage a quality control system for sorting cucumbers by using images of cucumbers and analysing colour, shape and imperfections.


In the very near future AI will be able to assist people learn new skills and gain greater understanding. Just as the internet has enabled more nations to trade internationally, AI will enable more people across the socio-economic spectrum to participate.


As we’ve already seen, the scale at which AI enabled services can grow through repeatability, and improve through self-learning, is unprecedented. To date the majority of AI services, like bots, are deployed by enterprise and used by consumers. This could easily change as more consumer based services emerge, eg. a bot that challenges your parking ticket could cause havoc for the ticket issuer.


The big tech giants are gathering enormous amounts of data through these services that will benefit wider society but most importantly benefit the tech companies.


Companies that fail to invest in AI now will become the Blockbuster Entertainment of tomorrow, bankrupted by new economic paradigms enabled through technology. AI technologies are not just an opportunity, they are an imperative to stay ahead and stay relevant, and accelerating progress at such a rate that change is the new constant.


I expect we’ll see more retailers and consumer driven companies investing corporate development dollars in tech companies, through accelerator programs and M&A activity, as much of the AI tech at this point in the revolutionary cycle holds proprietary advantage.


This revolution is a paradigm shift for the internet. Digital transformation initiatives need to be re-evaluated with Artificial Intelligence placed at the heart of projects which involve workflow, customer touch points or data interrogation.


The 4th industrial revolution is upon us, and it’s in a hurry!

A little tale of progress in the 4th industrial revolution

All of this paves the way for 12-year-old Akash from Bangladesh to rise above the poverty line of $2 a day. Using the 3-year-old android phone he was given by a foreign aid organisation, he has quickly understood how to find information and people across the world using voice commands, accessing free wifi in downtown Dhaka.


He’s ambitious, he’s seen Bollywood movies in the market square, and craves a better lifestyle. His parents own a very small garment business supplying own brand clothes to European and US retailers, sold via a series of intermediaries. Akash is smart, from his time in the food markets of Dhaka he knows how supply chains work and people along the chain take a slice of profits. Within weeks of getting his phone he’s used it to find people further up the chain and chip away at the middle men.


Six months later Akash is learning to read and write basic English through his phone and the night classes his family can afford after improving the profit margins of his parent’s garment business. He can’t read a word of Bengali but can confidently compose simple emails in English with the help of some Google tools for translation and grammar.


Within a year Akash has helped his parents more than double the size of their garment business, which is now selling direct to some of the smaller US retail chains thanks to a peer-to-peer lending platform he found on line willing to finance his export credit bills.


His older brother, Mamun, is now learning English and to read and write, thanks to the improved family finances. The two brothers now have an old windows laptop thrown out by one of the European export companies that downsized in Dhaka recently. They begin selling garments from their parents business on eBay & Amazon that didn’t make it past quality control , in addition to the market stall Mamun is now running.


Within two years of receiving his android phone Akash has learnt to access the internet and then read and write a foreign language. He has used this new found knowledge to help his family buy their first house, with a bedroom for each of them, and running water.


By the time Akash turns 18 he and his brother have transformed their family garment business. They are now sub contracting to a co-operative of 35 small garment factories, and his parents are managing quality control across a line of over three hundred clothing items. With the help of computer vision and other AI technologies, their garment business is becoming more efficient in it’s use of material with automated marking for garment patterns.


The two brothers have been on 12 selling trips to Europe and the US, increasing the fortunes of the family business to become a multi-million dollar exporter, and helping countless other families out of poverty.

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