Presentation: Michael May: The next level of intelligence: Artificial Intelligence

Innovation Day USA 2017 | Princeton, March 27, 2017

Michael May, Siemens Corporate Technology

Unrestricted © Siemens Corp. 2017

siemens.com/innovationusa

This document contains statements related to our future business and financial performance and future events or developments involving Siemens that may constitute forward-looking statements. These statements may be identified by words such as "expect," "look forward to," "anticipate" "intend," "plan," "believe," "seek," "estimate," "will," "project" or words of similar meaning. We may also make forward-looking statements in other reports, in presentations, in material delivered to shareholders and in press releases. In addition, our representatives may from time to time make oral forward-looking statements. Such statements are based on the current expectations and certain assumptions of Siemens' management, of which many are beyond Siemens' control. These are subject to a number of risks, uncertainties and factors, including, but not limited to those described in disclosures, in particular in the chapter Risks in the Annual Report. Should one or more of these risks or uncertainties materialize, or should underlying expectations not occur or assumptions prove incorrect, actual results, performance or achievements of Siemens may (negatively or positively) vary materially from those described explicitly or implicitly in the relevant forward-looking statement. Siemens neither intends, nor assumes any obligation, to update or revise these forward-looking statements in light of developments which differ from those anticipated.

This document includes - in IFRS not clearly defined - supplemental financial measures that are or may be non-GAAP financial measures. These supplemental financial measures should not be viewed in isolation or as alternatives to measures of Siemens' net assets and financial positions or results of operations as presented in accordance with IFRS in its Consolidated Financial Statements. Other companies that report or describe similarly titled financial measures may calculate them differently.

Due to rounding, numbers presented throughout this and other documents may not add up precisely to the totals provided and percentages may not precisely reflect the absolute figures.

Unrestricted © Siemens Corp. 2017

Page 2

March 27, 2017

Michael May

Behavior predictions

with large Neural Networks

• Siemens has been working in the field for more than 30 years

• About 50 key patents for learning processes

• We already use the technology for optimizing complex industrial systems

Michael May

Self-optimizing turbines

Reinforcement Learning

NOX [ppm]

Simulation without Autonomous Learning

Actual Value

Simulation with

• Our AI system learns from the behavior of a gas turbine in operation as well as data from the fleet

• The Artificial Intelligence

autonomously lowers the

Autonomous Learning

NOx emissions

Time

0 50 100 150 200

Michael May

Data Store

Agent executes the policy on current turbine data to optimize the operation

Machine learning exploits available data to create control policy

• Siemens has been active in the field of Artificial Intelligence for more than 30 years

• We use our experience in an industrial environment with technologies like (Deep) Reinforcement Learning and neuronal networks combined with domain know-how

• Gas turbines, wind turbines or smart grids and medical imaging

  systems are optimizing themselves through autonomous learning

• Siemens is leading the way on advanced applications

of AI in industrial domains