2.  Google started to suggest a number of offensive synonyms for the word “gay.” According to All Out organisation: “500 million people use Google Translate every month. That’s a lot of people being taught hateful words and insults…Google already has the technology to filter out hateful language: typing “female” doesn’t throw up sexist words.” Google manually fixed the issue.  Google Translate also got confused geopolitically as the Ukrainian translation for Russia became “Mordor”. Large number of Ukrainians were actually using the word “Mordor” to refer to Russia after it annexed Crimea in 2014. Again, Google manually fixed the problem.  The Food Festival in Galicia became The Clitoris Festival. Local officials in As Pontes had written the announcement for the annual festival in Galician, one of the official languages of the northern Spanish region. They used Google Translate for the Spanish-language version of the text. The translated announcement read: “The clitoris is one of the typical products of Galician cuisine. Since 1981... the festival has made the clitoris one of the star products of its local gastronomy”. The translation error was likely on the town’s official website for months before it was noticed. Source: The Guardian, www.k-international.com 2

3.  60 years ago...  Several mature VR technologies released to public. Already used in online fitting room, travel, real estate and automotive industries.  Internet of Things (IoT) — the network of objects inserted in devices that collect and exchange data online. It is estimated that by 2020 there will be about 50 billion IoT objects. Objects, such as heart implants, biochips, and built-in sensors, transmit vital information; they will control smart grids in smart cities. [Source: Patricia Brenes]  HDR screens available on the market.  Oh, one more thing – gravitational waves have been detected after nearly 100 years of reseach. 3

4.  Google currently translates more words in 1 minute than all human translators in 1 year.  Nearly half the world speaks two or more languages—3.65 billion people. Some translation startups are willing to use that potential.  By 2020 there will be 6.1 billion smartphone users.  If you want to reach 95% of the world’s 3.3 billion Internet users your website needs to support roughly 45 languages. Google Translate now supports more than 100 languages — reaching 99% of all Internet users.  E-commerce boom in India and China; giants like China’s Alibaba and India’s Flipkart are collectively posting double digit growth each year, generating revenue of more than half a trillion dollars annually.  Out of the world’s 6,500 spoken languages, only around 5% are European languages, and in many countries in Africa, Asia, and the Middle East incredible linguistic diversity predominates. [Source: Carl Yao, CSOFT 2016, Web Globalization Report] 4

5.  Travel and leisure (T&L) is one of the world's largest industry sectors. It generated US$7.6 trillion in 2014 and doesn't show any sign of slowing its strong and sustained climb.  Translation proxy – This is a method of on-demand website localization where a proxy server sits between the actual website and any visitor who would request localized content. This proxy serves up the requested translations. This means the business that owns the website needs no additional infrastructure and the language service provider (LSP) handles the lion’s share of the work. „Just keep using your original CMS system for content authoring; and the proxy workflow for translation, and to handle the presentation logic. (e.g hide the blog, etc),”. Some big LSPs in the industry think it’s a bad idea.  Demand for Persian language expected to grow significantly. On January 16th, the Joint Comprehensive Plan of Action (JCPOA) negotiated between Iran and six world powers took effect. Nearly 82 million consumers rejoin the world community. The country has an 86.8% literacy rate, 68.9 million mobile subscribers, and 22.9 million internet users. The online gross domestic product associated with Persian (US$185.40 billion in 2015) could overtake that of Indonesian ($192.86 billion) by 2017.  The Jehovah’s Witnesses website (https://www.jw.org) is still the most translated website on the planed. It is translated into more than 780 languages and dialects, from Abkhazian to Zulu. In comparison the Wikipedia is translated into 287 languages. The first commercial website is Apple’s, which is translated into some 130 languages. [Source: www.pangeanic.com] 5

6.  IBM launched model customization for the IBM Watson Translation Service, further enhancing the company’s flagship machine translation engine.  Li Deng, Partner Research Manager, Microsoft Research NExT, said “state-of-the-art” machine translation and NLP will be the “key deep learning advances” in 2016. Chris Bishop, Managing Director of Microsoft Research: “By 2026 we will have ubiquitous, human-quality translation among all European languages, thereby eliminating the language barrier throughout Europe”. His estimates are just two years off from the EU Patent Office’s. They expect high quality machine translation to nearly take over autonomous patent translations by 2028. Microsoft is also heavily using the Translation Hub and the collaborative translation framework – statistical MT engine, which allows training and post-editing.  Tesla’s Elon Musk and Paypal Co-Founder Peter Thiel are attempting to preempt the takeover of malevolent Artificial Intelligence (AI). Along the way, they inadvertently further the cause of machine translation with the $1 billion fund they invested in their nonprofit AI research institute.  In Japan, the Tokyo 2020 Olympics is expected to trigger a tourism boom for the country, so the government earmarked $500,000 for the development of a paramedic translation app meant to support first responders in translating for patients who do not speak Japanese.  VRI (video remote interpreting) is a fast-growing segment of the interpreting market. Source: Slator.com 6

7.  The military industrial complex meanwhile saw the US’ Defense Advanced Research Projects Agency (DARPA) invest over $26 million (so far) on developing language technology that can help US operations in remote areas of the world. They developed the Low Resource Languages for Emergent Incidents (LORELEI) program, meant to deal with and translate / interpret “rare” or “low resource” languages.  The government of Spain has announced it is investing EUR 90 million into natural language processing (NLP) and other language technologies such as machine translation (MT) starting with EUR 14 million in 2016. The initiative is part of a strategic five-year plan from 2016 to 2020, through which the Spanish administration intends to bolster the Spanish NLP and MT industry.  Netflix Expands in 130 Global Territories and increases the number of supported languages to 20.  BBC News Labs creates a new “virtual voiceover” tool. The new tool uses Google Translate to machine translate the scripts of English-language video and convert it to Japanese for BBC Japan. Source: Slator.com 7

8. Mobile devices becoming a real platform for CAT tools. CSOFT released a chat-based CAT. It allows a linguist to translate one source sentence at a time, which is then delivered to the phone or tablet as a chat message. He or she reads the message and then, using the mobile device's keyboard or voice dictation, sends a translation back to the server. The Stepes' server applies any translation memory or terminology, deals with formatting issues, and assembles the linguist's chat messages into the sentence-by-sentence translated document. The translator can swipe right to see the whole source or left to see the translation to date, thus providing context. Stepes is thinking about using 3.6 billion people who speak two or more languages instead of professional translatators to make translation more available and more affordable. It will offer human translation rather than post-edited MT. Linqapp Live – a service that connects you in real-time to translators who can help you over a voice call on the spot. The makers claim the live translation service is the first of its kind. “We want to become the platform where you can find a native speaker of any language who will help you, we believe we can give much better language assistance than Google Translate.” [Source: TechInAsia.com, CSA, Slator] 8

9. „We live in the disintermediation era, more and more buyers are purchasing translation services like they book hotel rooms: directly from the translators using dedicated on-line services like Say Hello, Unbabel or Gengo. User reviews are becoming major indicators. It's not enough to say we are fast, we are efficient or we provide the best quality. A proof of excellence is what counts. Everything measurable should also be visible. What is your productivity score? What is your efficiency score? What is your quality score?” „The communication process is changing from being unidirectional to multidirectional because consumers are becoming active participants by creating, seeking, and sharing information using a variety of channels and devices. Translation quality is being reshaped by the consumers and it is dynamic. Even productivity becomes dynamic due to this agile approach.” Source: Attila Görög, TAUS 9

10.  Global enterprises rely on social media to promote their services. Yet, most users post in ther native language, which reduces the number of possible viewers. The majority of Americans now cite Facebook and Twitter as major sources for news;  Big Translation concept - large-scale translation efforts by people speaking two or more languages. The goal is to reach a wider, worldwide audience.  Social media has even become a crucial news-gathering tool during natural disasters. Source: Carl Yao, 2016 10

11. Federal Association of Interpreters and Translators [Bundesverband der Dolmetscher und Übersetzer e.V. (BDÜ)] in Germany published its rate survey in January 2016. The survey is based on pricing information collected from almost 1,100 translators and interpreters and covers 35 language pairs. The average fee was €0.15 per word. French association, SFTP, published a very similar results to their survey. 11

12.  CAT/TMS systems joined the “old ones” › ProZ.com, TranslatorsCafe, Aquarius › Across (crossMarket), Lingotek, XTM (Xchange) 12

13.  Google Android › App Translation Services  list of predefined “professional translation vendors”  Adobe Experience Manager › Integrations with Translation Service Providers  about half of the integrations link to LSPs 13

14.  Slate Desktop  personalized solution for professional translators  one time investment 14

15.  Google Translate – 10 years  103 languages*  Covers 99% of online population * February 2016 15

16.  Skype translator now supports spoken(!) English, Spanish, French, German, Chinese (Mandarin), Italian, Portuguese (Brazilian) and Arabic * February 2016 16

17.  “Virtual voiceover” at BBC  US Patent and Trademark Office (USPTO)  IBM Globalization Pipeline  Multilingual App Toolkit (MAT) 4.0 from Microsoft 17

18.  buyers inexperienced in working with the language services market  machine translation with crowdsourced post-editing service  does it scale? 18

19.  SmartCAT (Abbyy LS)  Matecat (translated.net)  Older CATs – fat and lazy? 19

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21.  “Skuuper is a Software-as-a-Service (SaaS) with no learning curve and a modest subscription fee”  “demand from the underserved segment of the market [that] cannot afford to invest money in luxuriously priced mainstream tools and staff training” 21

22.  “first and only production MT system that learns from feedback in real-time”  predictive CAT  productivity increase  English-German, -French, -Spanish, and - Portuguese, with English-Italian and -Dutch in the works 22

23.  use technology to allow users access to direct market- matching without “middlemen agencies”  Uber vision – set the rates and standards, and then shortlist the most suitable, vetted translators for client tasks  translation-quality issues can be avoided by focusing on perfect market-matching upfront 23

24. 24 Source: CSA, 2015  The global market size: ca. 38.16 bln US$  Market keeps growing: 6.46% (2015), 6.23% (2014), 5.13% (2013), 12.17% (2012), 7.41% (2011)  Expected to reach 46.7 bln US$ by 2018  92.2% of industry revenues from language services tasks

25. 25  TechNavio forecasts the Global Language Services market to grow at a CAGR of 5.72% over the period 2013-2018  Global Machine Translation market to grow at a CAGR of 23.53% over the period 2014-2019 (Research and Markets, March 2015)  The analysts estimate the Global STS Translation market (speech recognition, speech translation, and speech synthesis) will grow at a CAGR of 19.11% over the period 2013-2018. (Research and Markets, May 2014)

26. 26 Source: CSA, 2015  Europe - more than half of the revenue  Europe continues to grow (North)  Eastern Europe dropped (ruble decline and sanctions)  North America’s share decreased a bit despite a strong economy

27. 27 Source: CSA, 2015  Europe division: Western E.: 24.95% Northern E.: 24.08% Southern E.: 3.48% Eastern E.: 1.39%

28. 28 Source: CSA, 2015  High fragmentation: most companies (59.71%) has 2 to 5 employees  Only ca. 500 companies have 50+ employees  Biggest: LanguageLine Solutions, ca. 7,600 employees

29. 29 Source: CSA, 2015  Lionbridge stilll #1, but small growth (0.26%)  The largest 100 suppliers developed faster than the total market  9 of the 10 top LSPs got more revenue than a year before. Of them, Moravia (#10) excelled with an increase of 48.45%

30. 30 Source: Slator,Multilingual, Crunchbase  On global scale VC firms still active on language market - Investing in technology companies, marketplaces, online translation firms. - E.g.: Smartling, Cloudwords, Gengo, KantanMT, Lingotek, LinguaNext...  Equity groups invested in several leading LSPs - E.g.: Moravia, SDI Media, Semantix, and Welocalize  Mergers and acquisitions as usual: - Lionbridge (#1) bought CLS Communications (#13) and Clay Tablet (middleware) - Euroscript (#8) purchased Foreign Exchange Translations - RR Donnelley took over MultiCorpora (TMS solutions)  Amazon.com Inc. has acquired Safaba (developer of MT solutions, VC investments). Renamed as Amazon Machine Translation R&D Group.

31. 31 Source: CSA, 2015  Eastern Europe’s share of the market: 1.39% (decreased from 2.44%)  Mostly RU, CZ, PL private companies in Top 20 (RU-9, CZ-5, PL-3)  Moravia – leader by far (revenue increase of 48.45%, the most of global top 10)  Logrus (RU) moved HQ to Czech Republic  Janus (RU) moved HQ to Austria

32. 32  Polish LSP/translation market – very fragmented  About 60,000 entities ”involved” in translations Source: Polish CEIDG (Central Register and Information on Economic Activity)  Of them ca. 1500 are translation companies. Mostly owner is the only employee  About 40-50 companies are members of branch associations and work according to quality standards (e.g. EN 15038 or ISO 9001)  Polish Association of Translation Companies: ca. 30 members  14 Polish companies in GALA (ca. 400 members)  Total size of the Polish translation market estimated as 1 bln PLN

33. 33  The first M&A focused company on Polish market?  Summa Linguae, translation agency founded in 2011  Focused on public procurement market and business sector  Mission: consolidation of the translation market in Poland  From May 2015 Summa Linguae S.A. is publicly-listed at New Connect stock market in Warsaw  Acquisitions so far: busy b translations, Spectraling, CLS Contact, ITG, Transmart, texteo.pl  Revenues in 2015: 4.8 mln PLN (ca. 1.2 mln USD)

34. 34  The EN 15038 quality standard was published in 2006, widely adopted  ISO 17100 Translation Services standard is successor to EN 15038  ISO 17100 published on 1st May 2015, defines aspects of: Commissioning work and translation Proof read and review Contractual requirement and project management Traceability of the translation process Overall quality management of the service  LSPs may opt for declaration of conformity, registration, or standard certification by accredited certifiers  At the initiative of PSBT, the 17100 was translated and published in Polish by the PKN committee in Nov 2015 - as PN-EN ISO 17100:2015

35. 35  Automation – to cope with increasing process complexity or number of smaller and smaller jobs (agile)  Automation – to have immediate access to data and business KPIs  Automation – to allow cooperation of remote resources  But automation often „forgets” about LSPs or translators: - separate invoice generation in each client system - communication splitted between mail, portals and data channels - problems with data access for subcontracting - access to POs details sometimes problematic - annoying QA checks upon data upload to client systems  End result: sometimes PM/translator overhead increases

36. 36  Example of successful implementation of enterprise MT strategy (Dell)  By increasing MT over human translations, and replacing reviews with selective sampling (1-3K/sample) it was possible to reduce cost per word from $0.23 to $0.12  Cost reduction => higher profit  Steady linguistic quality  Turnaround time reduced also by half

37. 37  Already over 50% of translations from English to Spanish and from English to German in Memsource are done combining TM and MT.  After a certain period of adaptation translator can boost from 2000 to 4000-8000 words per day while maintaining a good level of quality. Source: Memsource 15 language combinations with high MT use in Memsource

38. 38  Will PEMT cannibalize the regular translations?  Will automation mean PMs will be obsolete?  Will online translation platforms replace traditional TM tools?  Will rate reductions stop at some point? ...  The answer is...

39. 39  Will PEMT cannibalize the regular translations?  Will automation mean PMs will be obsolete?  Will online translation platforms replace traditional TM tools?  Will rate reductions stop at some point? ...  The answer is... PUTIN Przyszłość Usług Tłumaczeniowych Istnieje Niewątpliwie [może polscy uczestnicy TLC przetłumaczą kolegom z zagranicy...]

40. 40  An international survey of the ergonomics of professional translation.  A total of 1,850 translators from almost 50 countries participated. Survey was made available in 6 languages: German, English, Spanish, French, Italian, and Portuguese.  Respondents: freelancers (77%), institutional (ca. 250), and commercial (over 160) translators. Questions across 5 categories: workspace and environment, computer workstation, tools and resources, workflow and organization, and health and related issues.  „Out of all three groups, freelancers reported the lowest incidence of weakness, fatigue, and low spirits.”  Check your health and well-being! Source: Zurich University of Applied Sciences

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