Andrzej Zydroń MBCS CITP
CTO @ XTM International, Andrzej Zydroń is one of the leading IT experts on Localization and related Open Standards. Zydroń sits/has sat on, the following Open Standard Technical Committees:
LISA OSCAR GMX
LISA OSCAR xml:tm
LISA OSCAR TBX
OASIS Translation Web Services
OASIS DITA Translation
Andrzej has been responsible for the architecture of the essential word and character count GMX-V (Global Information Management Metrics eXchange) standard, as well as the revolutionary xml:tm (XML based text memory) standard which will change the way in which we view and use translation memory.
Andrzej is also chair of the OASIS OAXAL (Open Architecture for XML Authoring and Localization) reference architecture technical committee which provides an automated environment for authoring and localization based on Open Standards.
He has worked in IT since 1976 and has been responsible for major successful projects at Xerox, SDL, Oxford University Press, Ford of Europe, DocZone and Lingo24 in the fields of document imaging, dictionary systems and localization.
Andrzej is currently working on new advances in localization technology based on XML and linguistic methodology.
Highlights of his career include:
1. The design and architecture of the European Patent Office patent data capture system for Xerox Business Services.
2. Writing a system for the automated optimal typographical formatting of generically encoded tables (1989).
3. The design and architecture of the Xerox Language Services XTM translation memory system.
4. Writing the XML and SGML filters for SDL International's SDLX Translation Suite.
5. Assisting the Oxford University Press, the British Council and Oxford University in work on the New Dictionary of the National Biography.
6. Design and architecture of Ford's revolutionary CMS Localization system and workflow.
7. Technical Architect of XTM International’s revolutionary Cloud based CAT and translation workflow system: XTM.
Specific areas of specialization:
1. Advanced automated localization workflow
2. Author memory
3. Controlled authoring
4. Advanced Translation memory systems
5. Terminology extraction
6. Terminology Management
7. Translation Related Web Services
8. XML based systems
9. Web 2.0 Translation related technology
... will "kick off" the
Discussion Forum on the Future of Translation
by giving a short "Discussion Firework" talk entitled:
Neocortical Computing: Next Generation Machine Translation
The 21st century has ushered in significant advances in the understanding of how human intelligence works at the systems level. What is intelligence and how does it work are subjects that have only recently been addressed. The seminal work by Jeff Hawkins, who has been the primary pioneer in these hitherto uncharted waters, has had a profound effect on our understanding of how the human brain actually functions in the computing sense.
Hawkins’ theories have had a profound effect on the next generation of both computer hardware and software engineers. The single pipe Turing architecture has reached its limits. All attempts at building true artificial intelligence based on current ideas and notions have failed to deliver. Deep rural networks and aligned techniques have failed to provide any advance in our attempt at harnessing the potential of creating true artificial intelligence.
Time to take a different approach. This requires reverse engineering what human and mammal brains do effortlessly and current software engineering attempts have failed spectacularly to deliver. Take the simple matter of a young dog running and catching a ball in mid-flight. A two year old dog does it effortlessly. To program a robot to do this would require around 50 man years of effort and is currently beyond the scope of any organisation apart from possibly the US Department of Defence.
Human and mammalian brains are extremely slow in comparison with today’s processors and yet there capacity to learn and react to their environment is astonishing. Until Jeff Hawkins’ seminal work On Intelligence there were no good or bad theories: there were none. Hawkins has laid out the architectural and computing basis for intelligence and how we can harness this in the next generation of computer architectures which are radically different than the Turing architecture that is used by today’s computers.
The work of Jeff Hawkins has been fundamental in furthering our understanding of intelligence. Its impact on machine translation will be significant. The effects of this new approach will have significant implications over the next 20 years. The current generation of machine translation can be described as an advanced form of Mechanical Turk. No understanding is required of the computer: in fact it cannot have any form of understanding. John Searle’s Chinese Room thought experiment highlighted the limitations of our current approach to automated translation.
Jeff Hawkins’ theories centre on the neocortex, its structure and the way we learn and process the world around us, including language. Cortical computing will have a very profound impact on our daily lives and the way we can use truly sapient machines for translation in the future.
Andrzej Zydroń will also be part of the Discussion Forum panel which follows this presentation.
He also will have presented:
... during Day-1 of TC37. Click the title above for more information on that presentation.
This page last revised by oms: 9 November 2015, 18:300 UTC