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Top Artificial Intelligence Trends to Watch in 2018

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In this report, we explore 13 AI trends reshaping industries and economies. China is racing ahead in AI. Deep learning is getting a make over. AI is coming to Cannabis tech. Artificial intelligence is changing the fundamental structure of every industry in areas ranging from agriculture to cybersecurity to commerce to healthcare, and more.

We’re interacting with technology in new ways, from giving voice commands to washer-dryers to playing advanced gesture-controlled video games. Governments are competing to establish superior AI research, seeing AI as a lever for greater economic influence and power. We’re also in the early stages of drastic shifts in the labor market.

Publicado en: Tecnología
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Top Artificial Intelligence Trends to Watch in 2018

  1. 1. 2 @cbinsights @deepalearning #cbi-ai J O I N T H E C O N V E R S A T I O N O N T W I T T E R
  2. 2. 3 W H O W E A R E The technology market intelligence platform. CB Insights software lets you predict, discuss, and communicate emerging technology trends using data in ways that are beyond human cognition. We are a leader in the Expert Automation & Augmentation Software (EAAS) space.
  3. 3. 4 Contents 5 1 1 1 7 2 3 3 2 New blue collar job — robot babysitters White-collar automation accelerates 6-figure salaries in the AI talent wars China vs US competition heats up AI for X is … everywhere 36 4 1 4 5 5 1 The machine learning hype will die Amazon, Google, Microsoft dominate enterprise AI The emergence of ‘capsule networks’ AI diagnostics gets the nod from regulators
  4. 4. 5 J O B S New blue collar job — robot babysitters
  5. 5. 6 Manufacturing jobs are on the rise Source: BLS
  6. 6. 7 Chinese manufacturing giant moves to Arkansas Chinese T-shirt manufacturer Tianyuan Garments Company signed a Memorandum of Understanding (MoU) with the Arkansas government to employ 400 workers at $14/hr at its new garment factory in Arkansas.
  7. 7. 8 SoftWear develops “Sewbots” to automate sewing worklines in the manufacturing of garments and shoes. Select Investors CTW Venture Partners C H I N A ’ S T I A N Y U A N P A R T N E R S W I T H G E O R G I A - B A S E D S T A R T U P Funding $7.5M
  8. 8. 9 “…the system will make one T-shirt every 22 seconds. We will produce 800,000 T-shirts a day for Adidas… even the cheapest labor market can’t compete with us.” A U T O M A T I O N I S C H A N G I N G T H E S U P P L Y C H A I N Tang Xinhong, chairman of Tianyuan Garments, speaking to ChinaDaily
  9. 9. 10 The number and nature of jobs will never be the same as 2008 numbers. L A B O R M A R K E T I S S H I F T I N G
  10. 10. 11 J O B S White-collar automation accelerates
  11. 11. 12 A growing wave of Expert Automation & Augmentation Software (EAAS) platforms will usher in a new era of AI-enhanced productivity. E A A S T H R E A T E N S E N T R Y - L E V E L W H I T E C O L L A R J O B S
  12. 12. 13 The market map highlights some of the EAAS startups across number of professions ranging from lawyers to journalists to wealth managers, and more.
  13. 13. 14 Early-stage AI deals in law (green lines indicate investments) AI may impact fee structure of law firms AI can summarize thousands of pages of legal documents within minutes while reducing the probability of error. This will impact the fee structure of law firms that charge by the hour on the revenue side but also be a potential cost savings as they will be able to hire fewer junior lawyers.
  14. 14. 15 “Most of (the) software we write today at Google, everything, these are hand-coded systems... Over time, these could be lone systems, which automatically writes itself.” A I I N S O F T W A R E D E V E L O P M E N T Sundar Pichai, Google CEO
  15. 15. 16 Machine learning removes safety net for entry- level software developers Early-stage deals are emerging to startups focused on AI-based software testing, debugging, and basic frontend development.
  16. 16. 17 J O B S 6-figure salaries in the AI talent wars
  17. 17. 18 The demand for AI talent is far outpacing the availability of skilled researchers. T A L E N T & S K I L L S S H O R T A G E
  18. 18. 19 Big tech scoops top AI talent Google’s Deepmind Technologies reported that “staff costs and other related costs” accounted for £104.8M. A quick LinkedIn search puts the staff number at 415. Assuming this as team size in 2016, and discounting other expenses, this puts the average employee salary for the team at £252,000 (around $350,000 per annum).
  19. 19. 20 China is on a hiring spree too $567K-$624K $315K-$410K
  20. 20. 21 According to a recent Tencent report, there are around 300,000 qualified AI researchers. But demand is in the millions. T A L E N T & S K I L L S S H O R T A G E
  21. 21. 22 Top AI talent bleeds to startups Ex-Baidu Ex-Google Ex-Baidu T A L E N T W A R S H E A T U P
  22. 22. 23 G E O - P O L I T I C S US vs China competition heats up
  23. 23. 24 The United States is losing its global AI deal share Equity deal share, 2013 - 2017 US global AI deal share falls to all-time low The United States still dominates globally in terms of the number of AI startups and total equity deals. But it is gradually losing its global deal share.
  24. 24. 25 China wants to be a global AI leader Issued by the Chinese government in July 2017
  25. 25. 26 In some areas of AI, China is clearly beating the US. C H I N A R A C E S A H E A D
  26. 26. 27 China dominates global AI funding US vs China total equity funding to startups in 2017 China surpasses US in equity funding Despite a mere 9% global deal share, China accounted for nearly 48% of the total funding. To put this proportion in perspective, in 2016, China accounted for only 11.3% of global funding.
  27. 27. 28 Technologies fueling China’s growth Facial recognition AI chips C H I N A I N A I
  28. 28. 29 China invests heavily in facial recognition tech All deals, including grants, 2013 - 2017 China advances ambitious surveillance plans Three key players here are China-based unicorns Megvii (dba Face++) and SenseTime, and startup CloudWalk (the latter a recipient of a $301M grant from the Guangzhou Municipal Government. $M
  29. 29. 30 AI-related patent publications explode in China Based on keyword searches, 2013 - 2017 Patents reflect China’s AI R&D efforts Based on basic keyword searches of title and abstract, AI-related patent publications in China are surging far ahead of patents being published in these spaces by the US Patent and Trademark Office. (Note: The patent filing process involves a significant time-lag before the publishing of patent applications.)
  30. 30. 31 Cross-border AI investments on the rise Equity deals, 2013 - 2017 Tech swapping between countries increases Despite scrutiny of Chinese companies seeking partnerships or investments in the US, there are more Chinese investments in AI startups in the US than vice-versa.
  31. 31. 32 B U S I N E S S AI for X is… everywhere
  32. 32. 33 There is now AI for weed. DeepGreen uses computer vision to identify the gender and health profile of cannabis plants. Weedguide raised $1.7M to use AI for personalized weed recommendations.
  33. 33. 34 And fish. DeepFish in Russia is using neural networks to identify, well, fish. It merges radar technology with AI to differentiate between fish and noise in radar images.
  34. 34. 35 And horses. Sweden’s Hoofstep raised VC money to bring deep learning-based behavioral analysis to horses.
  35. 35. 36 B U S I N E S S The machine learning hype will die
  36. 36. 37 The ML frenzy in numbers 1,100+ New startups raised 1st equity since 2016 A I I S E V E R Y W H E R E $15.2B Equity funding in 2017 alone, a 141% jump from the previous year 300+ Companies entered incubators in 2017, 3x more than 2016
  37. 37. 38 “I believe that in 2 years, no investor is going to be explicitly looking to fund AI-powered startups.” B U T T H E H Y P E W I L L S O O N D I E Frank Chen, partner at a16z
  38. 38. 39 AI heats up across every industry Equity deals, Q4’12 – Q4’17 Machine learning gets normalized We are already seeing this happen in many industries. Machine learning is inseparable from IIoT. Almost all cybersecurity companies use machine leaning to some extent today. In addition to this, big tech companies are offering a suite of machine learning solutions to enterprises.
  39. 39. 40 Investors will get picky about startup funding Competitive landscape Business model feasibility Robustness of technology M L - B A S E D C O M P A N Y ? S O W H A T ?
  40. 40. 41 B U S I N E S S Amazon, Google, Microsoft dominate enterprise AI
  41. 41. 42 Investors poured $1.8B into enterprise AI startups in 5 years. E N T E R P R I S E A I
  42. 42. 43 Now Amazon, Microsoft, and Google may make smaller companies obsolete. E N T E R P R I S E A I
  43. 43. 44 Big tech doubles down on enterprise services Microsoft is competing neck and neck with AWS with Azure cloud services. Google released Cloud AutoML. Customers can bring their own data to train the algorithms to suit their specific needs. AWS expanded its enterprise AI offerings. Its 4th quarter revenue alone was $5B.
  44. 44. 45 T E C H N O L O G Y The emergence of ‘capsule networks’
  45. 45. 46 Challenges of convolutional neural networks (CNN) The example below shows a very basic illustration. A CNN would identify individual features and mistake the second image to be a face.
  46. 46. 47 Google’s Geoffrey Hinton published a research paper in 2017 that introduces the concept of “capsule networks”. C A P S U L E N E T W O R K S
  47. 47. 48 The promise of capsule networks For example, these networks would more easily identify that when features on a face are rearranged, it is no longer a face.
  48. 48. 49 CapsNets will require less training data With CNNs, for instance, you have to train the algorithm with images of the same object from different angles or viewpoints for it to identify all variations. As a result, it would require a large volume of training data to cover all possible variations. Image source:
  49. 49. 50 CapsNets may be less prone to hacking attempts One of the more popular examples is from a 2015 paper. As seen above, a small change that is not readily noticeable to the human eye results in a neural network identifying a panda as a gibbon, a type of ape, with high confidence.
  50. 50. 51 I N D U S T R Y AI diagnostics gets the nod from regulators
  51. 51. 52 AI heats up across every industry Equity deals, Q4’12 – Q4’17 Healthcare AI deals top the chart Healthcare is the hottest area of AI startup investment as our heatmap shows.
  52. 52. 53 Market map of healthcare AI startups Much of this growth is fueled by medical imaging & diagnostics companies.
  53. 53. 54 The Arterys cloud computing platform was approved for analyzing cardiac images. Select Investors DNA Capital, Emergent Medical Partners, Fosun Capital, GE Ventures, NewYork– Presbyterian Hospital, Northwell Ventures, ORI Capital, Temasek Holdings and Varian Medical Systems F D A A P P R O V A L Funding $42M Valuation $82M
  54. 54. 55 Strong public partnerships in AI diagnostics
  55. 55. 56 Increasingly crowded healthcare AI space 1st equity deals, 2013 - 2017 Smaller health AI startups undeterred by big players Big names Google DeepMind, IBM, GE, and Alibaba make this a tough market for smaller startups to compete in. But this hasn’t stopped new companies from venturing into the space.
  56. 56. 57 The CB Insights platform has the underlying data included in this report W H E R E I S A L L T H I S D A T A F R O M ? CLICK HERE TO SIGN UP FOR FREE
  57. 57. 64 @cbinsights Deepashri Varadharajan @deepalearning