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Tech trends

We hear specific technology terms more frequently, however some individuals may not know what they mean. My goal is to help you understand the topics that are changing our world and will most likely continue to play an integral part in how we interact with technology.

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Prepared by Raoul Gomes
May 26, 2015
Introduction
The world is changing so rapidly, with adoption rates being shorter and
shorter. A lot of this is driving innovation at such speed it’s hard to track.
Presentation Goal
3
We hear specific technology terms
more frequently, however some
individuals may not know what
they mean.
My goal is to help you understand
the topics that are changing our
world and will most likely continue
to play an integral part in how we
interact with technology.
Trends for Discussion
4
There are many technologies starting to enter the corporate world. Some
of these are older (i.e. 3D printing), however, they have once again started
to appear as an ‘innovative’ technology. Trends we’ll cover are as follows:
• Smart Machines
• Artificial Intelligence
• 3D Printing
• Augmented Reality
• Predictive Analytics
• Internet of Things
• Big Data
• Wearables
What is a Trend?
5
What classifies a technology for being a trend? I state two factors:
1. The adoption rates for the technology.
2. The potential of becoming a disrupter.
A disruptive innovation is one
that helps create a new market
and value network, and
eventually disrupts an existing
market and value network,
displacing an earlier technology.
Smart Machines / Machine Helpers
6
Smart machines are systems that
use machine learning to perform
work traditionally conducted by
humans in an effort to boost
efficiency and productivity.
These are smarter multitask
machines that are more robust,
powerful, and flexible.

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Tech trends

  • 1. Prepared by Raoul Gomes May 26, 2015
  • 2. Introduction The world is changing so rapidly, with adoption rates being shorter and shorter. A lot of this is driving innovation at such speed it’s hard to track.
  • 3. Presentation Goal 3 We hear specific technology terms more frequently, however some individuals may not know what they mean. My goal is to help you understand the topics that are changing our world and will most likely continue to play an integral part in how we interact with technology.
  • 4. Trends for Discussion 4 There are many technologies starting to enter the corporate world. Some of these are older (i.e. 3D printing), however, they have once again started to appear as an ‘innovative’ technology. Trends we’ll cover are as follows: • Smart Machines • Artificial Intelligence • 3D Printing • Augmented Reality • Predictive Analytics • Internet of Things • Big Data • Wearables
  • 5. What is a Trend? 5 What classifies a technology for being a trend? I state two factors: 1. The adoption rates for the technology. 2. The potential of becoming a disrupter. A disruptive innovation is one that helps create a new market and value network, and eventually disrupts an existing market and value network, displacing an earlier technology.
  • 6. Smart Machines / Machine Helpers 6 Smart machines are systems that use machine learning to perform work traditionally conducted by humans in an effort to boost efficiency and productivity. These are smarter multitask machines that are more robust, powerful, and flexible.
  • 7. Smart Machines – How they work 7 This technology is possible using deep analytics applied to an understanding of context. It is combined with advanced algorithms allowing systems to understand their environment, learn for themselves, and act autonomously.
  • 8. Smart Machines – Categories 8 Smart machines can be divided into three categories: • Movers: autonomous robots that can move items from points A to B without human intervention. Google’s Prototype autonomous vehicles. • Doers: robots that use sensors, cameras and machine learning to perform complex tasks like scheduling or handling and manipulating small objects. Tesla Factory or Amazon warehouse. • Sages: Information-based helpers that rely on context and a familiarity with their users' environments and patterns to provide options and recommendations. Amy the virtual personal assistants at www.x.ai
  • 9. Internet Everywhere – Mobile & Internet 9 The Cell Phone and Internet, being the most recent two new technologies that have attained mass adoption, are driving most of the conversation when discussing tech trends. The combination of these has driven an increasing adoption rate.
  • 10. Internet Everywhere – Leaders 10 Project Loon is a research and development project developed by Google with the mission of providing Internet access to rural and remote areas. The project uses high-altitude balloons placed in the stratosphere to create an aerial wireless network. Internet.org is a partnership between Facebook and six mobile phone companies to bring affordable access of selected Internet services to less developed countries through network efficiencies and new business models around the provision of Internet access.
  • 11. Internet Everywhere – Business Model 11 The idea is to not charging end-customers on data used by specific applications or internet services through the mobile network. The industry term is know as zero-rating or commonly known as Toll-Free. Facebook, Wikipedia, and Google want to harness the development of new business models around the provision of Internet access using this concept in providing their service more broadly into developing markets.
  • 12. Internet Everywhere – Challenge 12 In plain terms, users would have a subsidised access to services from these service providers. However, there is a cautionary note, in particular around net neutrality. Some believe that this would lead to a closed internet, of which aligns with to the industry’s desire for Internet 2. The Subsecretaria de Telecomunicaciones of Chile ruled that this practice violated net neutrality laws and had to end by June 1, 2014.
  • 13. Artificial Intelligence 13 Artificial intelligence (AI) is the intelligence exhibited by machines or software. These systems have the capability of learning and teaching themselves. This builds on the concept of Machine Learning, however extends more broadly to include other areas such as ability to have natural language processing, knowledge representation, and automated reasoning.
  • 14. Artificial Intelligence - Leaders 14 The most recognizable companies out there working the area of how to create computers and software that are capable of intelligent behaviour are IBM (Watson), Google (Search Engine/Self driving cars), Microsoft (Cortana), and Baidu (Minwa). This industry has progressed at an increasing rate with the advent of cheaper parallel computing, big data, and better algorithms.
  • 15. Artificial Intelligence – IBM Watson 15 Cognitive Cooking with Chef Watson includes 65 recipes. Instead of dealing with dishes at an ingredient level, Watson looks at the actual chemicals that control taste and how one food pairs with another to come up with new ideas that would not logically be combined.
  • 16. Artificial Intelligence – Baidu Minwa 16 Chinese’ Baidu Minwa supercomputer AI trumps Google, Microsoft and humans at image recognition. This supercomputer scanned more than 1 million images and taught itself to sort them into 1,000 categories with a 95.42% accuracy.
  • 17. 3D Printing 17 This technology is already considered older, however with the advent of new alloys, quicker printer technology, more powerful computer processing, reduced costs, and the transfer of printing schematics via internet have driven this technology to the forefront.
  • 18. 3D Printing - Examples 18 There are a few neat examples of where 3D printing is having great impact: • Healthcare, where organs, bones, custom hip joints, are printed • 3D printing guns, bypassing statues that infringe common-law rights. • Food with elaborate designs. • Tools in outer space, rather than taking each tool, a printer is taken. • Mechanical engineering having cheaper, stronger, and lighter parts. All this leads to more precise work, less labour required, quicker turnaround, less waist, higher quality.
  • 19. Augmented Reality 19 Augmented reality is a live direct or indirect view of a physical, real- world environment whose elements are augmented (or supplemented) by computer-generated sensory input such as sound, video, graphics, or GPS data.
  • 20. Augmented vs. Virtual Reality 20
  • 21. Predictive Analytics 21 Large amounts of data continue to be collected within and outside of the enterprise. From such places as social media, IoT, wearables etc. Predictive analytics is the practice of extracting information from these existing data sets and analyzing it in order to determine patterns. Thus, allowing for information to be delivered to the right individuals or systems at the right time.
  • 22. Predictive Analytics – Big Answers 22 It predict future outcomes and trends but does not tell you what will happen in the future. Big data remains an important enabler for this trend, however the value is in the big answers to the big questions and not necessarily the data.
  • 23. Internet of Things 23 The Internet of Things (IoT) is the network of physical objects or "things" embedded with electronics, software, sensors and connectivity. The goal is to provide greater value and service by exchanging data with the manufacturer, operator, and/or other connected devices.
  • 24. Internet of Things – Ecosystem 24 The IoT ecosystem is complex and diverse. The areas of focus that make sum the concept are the consumer play, along with the software and hardware. The applications of this technology span: • Media • Environmental monitoring • Infrastructure management • Manufacturing • Energy management • Medical & healthcare systems • Building & home automation • Transportation • Large scale deployments
  • 25. Big Data 25 Big data is term used to describe a massive volume of both structured and unstructured data that is so large it is difficult to process using traditional database and software techniques. In the next five years, data growth is set to increase by 800 percent and even now, 90 percent of all of the data that exists in the world was created in the last two years.
  • 26. Big Data – Actionable Intelligence 26 Correlations are completed by taking data from various sources and making actionable intelligence. This doesn’t necessarily mean you should always act on it. Example when NOT to use: Sending flyers for baby items to a teen living at home who just bought a pregnancy test, or was searching ‘am I pregnant’ in google search.
  • 27. Wearables 27 Wearable technology, wearables, fashionable technology, wearable devices, tech togs, or fashion electronics are clothing and accessories incorporating computer and advanced electronic technologies. Applications of this technology lie in health, AR, connected products, etc.
  • 28. Other Trends 28 I encourage you to continue exploring other trends not listed in this presentation. They can include, and are not limited to: • Biometrics • Bitcoin • Crowd Sourcing • QR Codes • Drones • Self-driving cars • Robotics • Bio-chips • Nanotechnology • Smart Dust • Batteries

Editor's Notes

  1. hypothesis generation and evaluation
  2. Advanced Analytics
  3. Visualization of daily Wikipedia edits created by IBM. At multiple terabytes in size, the text and images of Wikipedia are an example of big data.
  4. Forbes article: How Target Figured Out A Teen Girl Was Pregnant Before Her Father Did