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Machine Learning as a Service: #MLaaS, Open Source and the Future of (Legal) Analytics - By Daniel Martin Katz + Michael J. Bommarito II

Machine Learning as a Service: #MLaaS, Open Source and the Future of (Legal) Analytics - By Daniel Martin Katz + Michael J. Bommarito II

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Machine Learning as a Service: #MLaaS, Open Source and the Future of (Legal) Analytics - By Daniel Martin Katz + Michael J. Bommarito II

  1. 1. #MLaaS, open source and the future of (legal) analytics Machine Learning as a Service (#MLaaS) daniel martin katz blog | ComputationalLegalStudies.com corp | LexPredict.com page | DanielMartinKatz.com michael j bommarito blog | ComputationalLegalStudies.com corp | LexPredict.com page | bommaritollc.com edu | chicago kent college of law edu | university of michigan cscs
  2. 2. Today I would like to look over the #LegalHorizon
  3. 3. We join our story already in progress… Part I< >
  4. 4. #DataScience are already influencing our lives in a variety of meaningful ways #BigData #Analytics #A.I.
  5. 5. To date, the most successful commercial applications have massive returns to scale and aim for cross societal payoffs…
  6. 6. Medicine
  7. 7. Finance
  8. 8. Logistics
  9. 9. Agriculture
  10. 10. Transportation
  11. 11. Retail
  12. 12. Given large fixed costs
  13. 13. Given large fixed costs infrastructure + human capital (data scientists)
  14. 14. harder to successfully deploy high quality enterprise applications for relatively narrow (sub)verticals
  15. 15. The Rise of #LegalAnalytics Part II< >
  16. 16. Law is a relatively small vertical and there is lots of diversity among tasks lawyers undertake …
  17. 17. in addition there is a borderline pathological numerophobia among lawyers
  18. 18. Together with the implicit (explicit) challenge of partnership as the dominant form of the organization within our sector
  19. 19. taken together this has challenged the deployment 
 of analytics in legal
  20. 20. Analytics / Quant Legal Prediction has come to law Notwithstanding these head winds—
  21. 21. #LegalAnalytics Quantitative Legal Prediction
  22. 22. #LegalAnalytics Quantitative Legal Prediction
  23. 23. #LegalAnalytics Quantitative Legal Prediction
  24. 24. #LegalAnalytics Quantitative Legal Prediction
  25. 25. #LegalAnalytics Quantitative Legal Prediction
  26. 26. #LegalAnalytics Quantitative Legal Prediction
  27. 27. Some Commercial Applications
  28. 28. In a real sense, this represents just a narrow set of products
  29. 29. #ContractAnalytics Quantitative Legal Prediction
  30. 30. #JudicialAnalytics Quantitative Legal Prediction
  31. 31. #PredictiveCoding #E-Discovery Quantitative Legal Prediction
  32. 32. General Counsels as Legal Procurement Specialists TyMetrix/ELM - Using $50 billion+ in Legal Spend Data to Help GC’s Look for Arbitrage Opportunities, Value Propositions in Hiring Law Firms #LegalSpendAnalytics Quantitative Legal Prediction
  33. 33. #LegalAnalytics Quantitative Legal Prediction https://lexsemble.com/
  34. 34. #NegotiationAnalytics Quantitative Legal Prediction
  35. 35. Lots of folks ask me what is next in legal analytics …
  36. 36. A big part of the answer comes from one of the most dominant vectors in tech
  37. 37. both those in positions of leadership and those in technical positions need to take stock
  38. 38. #MLaaS and the Enterprise Open Source Movement Part III< >
  39. 39. IBM WATSON First major effort at #MLaaS Machine Learning as a Service
  40. 40. IBM Watson is MLaaS and it would have purported to be among the biggest stories in tech over the past few years
  41. 41. Turns out things would layout in a slightly different fashion …
  42. 42. IBM Watson (per se) IBM Watson (as early #MLaaS) vs.
  43. 43. the democratization of machine learning is underway
  44. 44. Emerging Business Model - Machine Learning as a Service #MLaaS
  45. 45. The Cloud Wars
  46. 46. Commercial Examples
  47. 47. Machine Learning as a Service #MLaaS
  48. 48. Machine Learning as a Service #MLaaS
  49. 49. Machine Learning as a Service #MLaaS
  50. 50. Machine Learning as a Service #MLaaS
  51. 51. But wait there is more …
  52. 52. Machine Learning as a Service #MLaaS
  53. 53. Machine Learning as a Service #MLaaS Enterprise Open Source Movement #OpenSource +
  54. 54. Enterprise Open Source Movement #OpenSource
  55. 55. https://techcrunch.com/2016/06/19/the-next-wave-in-software-is-open-adoption-software/
  56. 56. Part IV< > The Last Mile Problem and the New Dimension of Competition
  57. 57. historically one needed to build the full stack (i.e end to end) for an application
  58. 58. Standing on 
 the Shoulders of Giants
  59. 59. The (Emerging) Last Mile Problem in (Legal) Analytics
  60. 60. Off the Shelf #MLaaS, etc. (perhaps with some configuration and/or customization) Unique Domain Specific Offering
  61. 61. MLaas + Open Source Decreases Cost of Production Lowers the Cost of Protoyping
  62. 62. The New Ball Game
  63. 63. Workflow Across the Machine Learning Landscape
  64. 64. Piece together the combinations of 
 #MLaaS + open source
  65. 65. to build enterprise applications which are unique combinations drawn from across the #MLaaS / open source spectrum
  66. 66. Three Implications for #LegalAnalytics #LegalTech #LegalAI Part V< >
  67. 67. Implication #1< >
  68. 68. every organization in law needs a data strategy
  69. 69. Capture, Clean, Regularize Data to support a range of tasks
  70. 70. Deploy Data for Specific Enterprise Applications Develop a data roadmap
  71. 71. Implication #2< >
  72. 72. every organization in law needs a relevant human captial #LegalAnalytics
  73. 73. Opening the Human Capital Bottleneck
  74. 74. Probably going to need homegrow your own talent
  75. 75. http://www.quantitativemethodsclass.com/Professor Daniel Martin Katz Intro Class
  76. 76. http://www.legalanalyticscourse.com/Professor Daniel Martin Katz Professor Michael J. Bommarito II Advanced Class
  77. 77. Implication #3< >
  78. 78. First Wave vs. Second Wave Legal Tech
  79. 79. Second Movers can catch up faster …
  80. 80. Second Movers need less capital …
  81. 81. Second Movers who start now will have lower fixed costs …
  82. 82. probably will not need to go for a series z round of funding
  83. 83. In Conclusion< >
  84. 84. Our Prediction on the #LegalHorizon
  85. 85. Our Prediction More Legal Tech More Legal Analytics
  86. 86. Leveraging (in part) …
  87. 87. #MLaaS Machine Learning as a Service
  88. 88. Daniel Martin Katz @ computational computationallegalstudies.com lexpredict.com danielmartinkatz.com illinois tech - chicago kent college of law@
  89. 89. Michael J. Bommarito II @ mjbommar computationallegalstudies.com lexpredict.com bommaritollc.com university of michigan center for the study of complex systems@

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