1. Higher Vision, language and movement

2. Strong AI Is the belief that AI will eventually lead to the development of an autonomous intelligent machine. Some researchers believe that strong AI will be possible because of ever increasing hardware and software advances. Other believe it is philosophically impossible to achieve strong AI.

3. Vision - used to recognise and make sense of images. Computer vision is one of the hardest areas of AI. The aim is to develop systems which can see, make sense of what they see, and react accordingly. Difficulties with Vision Systems –Shadows on Objects –Identifying the Edge of the Image –Glare –Objects hiding other parts of the Image –Viewing from different angles

4. Vision – 5 Stage Process A system breaks down vision into: 1.Image acquisition (digitisation) 2.Signal Processing 3.Edge Detection 4.Object Recognition (pattern matching) 5.Image understanding

5. Applications of Computer Vision The ability of a computer to recognise an image is still limited, but intelligent vision systems have huge potential in many areas: –Security systems – recognise individual faces, and allow or deny access –Identify objects on an assembly line, make changes and respond accordingly Smart weapons

6. Why is computer vision AI? Has the following aspects of human intelligence: –Ability to learn – can improve there recognition capability over time –Have vision –Adapt to new simulations – can cope with unfamiliar scenes

7. Difficulties with Vision Systems (reminder) –Shadows on Objects –Identifying the edge of the Image –Glare –Objects hiding other parts of the Image –Viewing from different angles Problems of interpreting 2D objects as 3D objects

8. Hardware Can be very demanding on computer resources: –Take up vast amounts of memory and backing storage –Processing of digital image requires the manipulating of millions of bits –Many complex algorithms are used (heavy on the processor) –Pattern Matching (processor power) Until recently this was only possible when using large institutional mainframes

9. Natural Language Processing (NLP) Process of a computer system recognising and responding intelligently to written or spoken language. Natural languages such as English are difficult to process. Why? –Have a huge vocabulary ( 1 million words) –Words can have multiple meanings/meanings change –Words may sound the same but have a different meaning –Rules of grammar are not precise and are often broken –Regional variations of word

10. NLP Stages Speech Recognition Natural language understanding (NLU) Natural language generation Speech synthesis

11. Speech Recognition The sounds or text are input into the computer, and letters and words are identified. Text Will be scanned using OCR software and the letters and words identified from a word bank. Audio A microphone is used to capture the sound which is then converted into digital data.

12. Splitting sound into phonemes The software has to be able to break the continuous stream of someone speaking into a series of recognisable sound patterns, called phonemes. What is a phoneme? The smallest sound unit in a language that is capable of conveying a distinct meaning, such as the s of sing and the r of ring. Most western languages have about 50 phonemes

13. Natural language understanding (NLU) The continuous stream of sound data is broken down into phonemes. The pattern of phonemes now has to be recognised as words. The difficult part is now to extract meaning from the list of words. – not easy!

14. Natural language generation Response now has to be made. If it is a response in a language this has to be generated. Problem The difficult part is working out what the words for the response will be. This is the process of generating natural language from information held in a database.

15. Speech synthesis The production of spoken or textual output is digitally formed.

16. Applications of NLP Automatic translation Search engines (database query) Speech driven word processor

17. Robotics Dumb Robots Computer controlled machine with sensors which provide feedback to controlling program Intelligent robots (show some further aspect of human-like behaviour) Vision system with pattern matching Ability learn Can walk/move over uneven ground or up stair

18. problems Hardware Many require large amounts of energy (Asimo 4 hours charging to give 1 hour performance) Multi processing is required Software – navigation, control, vision recognition