Using Artificial Intelligence to Train Your Chatbot.

Transcription

1 Using Artificial Intelligence to Train Your Chatbot

2 T h e C o n t e x t 1

3 A r e c h a t b o t s a f a d o r a d i s r u p t i o n? M i s c e l l a n e o u s G r o w t h S t a t i s t i c s 2

4 T h e P r o b l e m 3

5 D e e p L e a r n i n g i s n o t t h e b e s t t e c h f o r n a t u r a l i n t e r a c t i o n ( 1 / 2 ) Is meant for structured data Needs a lot of data to train Is not even used by most chatbot implementations 4

6 D e e p L e a r n i n g i s n o t t h e b e s t t e c h f o r n a t u r a l i n t e r a c t i o n ( 2 / 2 ) Keyword Co-occurences Learnt Synonyms Attachments Causal Relationships Hypernyms/ Troponyms Remedial-Causal Relationships Hyponyms Document level associations Mutual Information Indicators 5

7 A c c u r a c y i s t y p i c a l l y l o w w i t h t r a d i t i o n a l c h a t b o t t e c h n o l o g i e s ( 1 / 2 ) 70% failure rate on its messenger platform. Feb % queries in tests of bots on Messenger platform by a 3 rd party were escalated to humans. FB announced changes to M and its chatbot policies 6

8 A c c u r a c y i s t y p i c a l l y l o w w i t h t r a d i t i o n a l c h a t b o t t e c h n o l o g i e s ( 2 / 2 ) $12b B2B Tech Player lets customers look for solutions to their problems on website. Solution powered by Google If no answer is found, customers create a ticket, which costs ~$400 to the company. Case deflection rate ~ 10% (Number of times ticket not created) 7

9 T r a i n i n g n e u r a l n e t w o r k b a s e d m a c h i n e s c a n b e c o m e v e r y e x p e n s i v e MD Anderson ended relationship with IBM after 3 years and $62m Not accurate Needed two more years to model Spent highly expensive SME time to annotate all case histories before Watson could be trained 8

10 B i g c o m p a n i e s w i t h h e f t a n d a c c e s s t o d a t a p r o m o t e n e u r a l n e t w o r k s Google crowd-sourced 2million data points for English to Kazakh translation Kazakh President s office helped recruit volunteers Based on open-source technologies like Tensorflow and Word2Vec 9

11 b u t r e a l b u s i n e s s e s f a c e r e a l p r o b l e m s w i t h c h a t b o t s Not enough data to train neural networks Expensive SMEs to annotate training data Low accuracy in third party point solutions Open Source + Data Scientists doesn t work 10

12 A S o l u t i o n 11

13 R e c o g n i z i n g t h e n u a n c e s o f n a t u r a l l a n g u a g e A g o o d d a y 12

14 C a l i b r a t e d Q u a n t u m M e s h A n A I f o r N a t u r a l L a n g u a g e One articulation can mean a lot of different things Everything is i nterconnected to the answer External evidence helps the mesh to converge 13

15 F i n d i n g t h e m e a n i n g o f r e p o r t The report was loud. All hypotheses Phrase constraint Feature analysis Context 14

16 U s i n g A I t o t r a i n y o u r c h a t b o t C a s e E x a m p l e s Pharma Consulting Finance Technology Chatbot for accelerating the process to assemble FDA meeting packets Chatbot for cognitive knowledge management Chatbot for L1 and limited L2 IT support (white labelled) Chatbot to accelerate supplier problems and notifications through SOPs 15

17 A b o u t U s 16

18 C o s e e r a u t o m a t e s w o r k f l o w s s o t e a m s c a n f o c u s o n g r o w t h a n d i n n o v a t i o n Disruptive Processes Fundamental capabilities that are popular Answer based on concepts like a human Synthesize concepts and data into templates Extract structured info from free text Redact or classify sensitive info 17

19 Best Cognitive Computing Company Best Intelligent R e c o g n i t i o n i n I n d u s t r y Industry Awards Workflow Technology 50 Fastest Growing Company of 2017 A Rising Star

20 C o s e e r s o l v e s f o r k e y f r i c t i o n p o i n t s i n a d o p t i o n o f c o g n i t i v e c o m p u t i n g Problem and context specific training 95-98% Accuracy No need for pretagging data Deployment in 4-12 Weeks Deployed on VPC or private cloud Complete Data Security Scalable, cloud based design Tactical IT for Enterprises

21 E x e c u t i v e S u m m a r y 20

22 E x e c u t i v e S u m m a r y w w w. c o s e e r. c o m Chatbots may be a fad, but can still impact your jobs meaningfully. Current chatbot solutions compromise on accuracy, costs and control. Conflict of interest: Big, data rich companies are playing to their strengths. We have developed a more human AI using Calibrated Quantum Mesh. 95%+ accuracy in live situations. No need for pre-annotated training data. 21