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Artificial Intelligence - A Brief Scan

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Artificial Intelligence - A Brief Scan

  1. 1. AIA BRIEF SCAN - 3 JUN 2016
  2. 2. Artificial Intelligence (AI) is the science and engineering of making intelligent machines. Machine learning (ML) is a subfield of AI that explores the study and construction of algorithms to learn from and make predictions on data without being explicitly programmed. Deep learning (DL), one of the most promising approaches in AI, uses artificial neural networks (ANNs) that consist of one of more hidden layers. DEFINITIONS
  3. 3. 3 SG-Tech Slides Machine Learning Use algorithms such as Single Vector Machines CA Solutioning Statistical approaches that do not improve artificial intelligence over time. Artificial Intelligence Symbolic logic machines (rules engines, expert systems) are non ML AI. Computer Assisted Solutioning AI ML DL Deep Learning ANNs with one or more hidden layers powered by both non DL and DL-specific algorithms COMMON TERMS Specific Deep Learning DL architecture and algorithms set up for specific tasks, e.g. image recognition Specific DL
  4. 4. 4 SG-Tech Slides Exponential increases in computing power has meant that certain algorithms and architecture which were impractical in the past, e.g. DL, have become viable. Computing Power Access to large amounts of data available in the cloud, has made DNNs feasible. Big Data Recent AI innovations have been powered by combining algorithms and architecture together in novel ways to solve specific sets of problems. Algorithms and Architecture 3 Factors Determines AI’s Potential
  5. 5. 5 SG-Tech Slides Artificial Narrow Intelligence Designed to solve highly specialized problems. Computing Power With the slowing down of Moore’s law, quantum computing offers the possibility of brute force advances based on current approaches New Algorithms/Architectures Focused on speed, accuracy as well as reducing the amount of data needed Processing Speed Dedicated AI chips, Parallel processing and in-situ computing solutions can offer increases in processing speed for AI POSSIBLE TRAJECTORIES In AI Research
  6. 6. 6 SG-Tech Slides Genetic Algorithms Using AIs to build AIs more effectively 2040 ? AI as a Discipline Current approaches to AI are largely empirical – i.e. we don’t really understand why algorithms work the way they do. BNN Emulation New areas of research include more closely studying and emulating biological neural networks, including physical or virtual embodiment. Artificial General Intelligence An AGI will be able to generate and merge multimodal datasets, form “situations” based on concepts, and make and test hypotheses across different and new areas. POSSIBLE TRAJECTORIES In AI Research
  7. 7. 7 SG-Tech Slides Rules-based Improve productivity and customer experience Firm specific Change business model Ubiqitous Small AI E.g. Amazon 1-click ML/DL Improve organizational intelligence Problem specific New business model(e.g.MLAAS) 5-10% Big AI E.g. Watson TYPES of AI Applicable to Industry
  8. 8. SG-Tech Slides % Over the next 5 years CAGR In Millions over 15 Major Economies Job Losses In $billions in 2015 VC Funds Market Size The AI industry in $billion by 2020 13.7 IMPACT of AI 33.7 5 1.2
  9. 9. 9 SG-Tech Slides Algorithmic trading, fraud detection, credit risk assessment, identity management Web search, solutioning, prediction, design Image recognition, conversational agents, personalisation Finance Research Business Models High speed threat identification and intervention Medical imaging, patient monitoring, risk assessment, diagnostics and drug discovery Law - Legal research, e-discovery, outcome prediction and contract analytics. Journalism – News writing, news discovery. Education – Artificial teaching assistants Creative Services – Game design, art, music Cybersecurity Healthcare Others IMPACT of AI On Research, Business Models and Industries
  10. 10. 10 SG-Tech Slides 24k+ Publications 11 Of top 12 AI Coys USA $4.2 billion in VC funding (2015). 499 AI companies 40k+ Publications 1 Of top 12 AI Coys CHINA Leader in visual and speech recognition. 2nd In FWCI rankings 6 Local AI startups SINGAPORE Top researcher (by FCWI) is ranked 33rd in the world. Institiutions are ranked between 170s and 1500s. SINGAPORE’S Competitive Advantage
  11. 11. THANK YOU
  12. 12. 12 SG-Tech Slides Single layer ANN Pattern Identification 1 2 layer DNN Building Layers 3 Supervised learning with labelled data Training 4 Testing with new data. Testing 5 Using sparse coding for feature extraction Feature Extraction 2 DEEP LEARNING A Simulation

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