When it comes to protecting classified data, blackout redaction has been in use for at least a century. While it is not the only acceptable form of data sanitization, it is historically the oldest and most commonly utilized by eDiscovery firms. This is despite the fact there are more modern and easy-to-use alternatives that save time and reduce errors. The two main data sanitization alternatives that meet legal requirements include anonymization and pseudonymization.Continue reading
As noted by Anju Khurana, Head of Privacy of the Americas, Bank of New York Mellon, “There are now over 100+ privacy laws in the world and GDPR is driving other countries to adopt similar regulations.” (corpcounsel.com, Oct. 2019). The California Consumer Protection Act (“CCPA”) which comes into effect on January 1, 2020, is the latest, and very likely not the last. Most data privacy experts anticipate additional states enacting data privacy regulations and think it likely that Congress will eventually do so at the federal level.Continue reading
SYSTRAN has been wholeheartedly involved in open source development over the past few years via the OpenNMT initiative,whose goal is to build a ready-to-use, fully inclusive, industry and research ready development framework for Neural Machine Translation (NMT). OpenNMT guarantees state-of-the-art systems to be integrated into SYSTRAN products and motivates us to continuously innovate.
In 2017, we published OpenNMT-tf, an open source toolkit for neural machine translation. This project is integrated into SYSTRAN’s model training architecture and plays a key role in the production of the 2nd generation of NMT engines.Continue reading
Machine Translation users care about quality and performance. Based on our own observations and the feedback we’ve received; the quality of our Neural MT is impressive. Evaluating performance is a stickier subject, but we’d like to dig our hands in and present our innovations and achievements and how it benefits NMT users.
By performance we mostly mean the manner in which a system performs in terms of speed and efficiency in varying production environments. It is important to note that performance and quality in Neural MT are tightly connected: it is easy to accelerate a given model compromising on the quality. Therefore, when evaluating performance improvement, we always check that quality remains very close to optimal quality.
Since switching to NMT at the end of 2016, we’ve invested our R&D efforts into optimizing our engines to be more efficient, while maintaining and even improving translation accuracy. Our latest, 2nd generation NMT engines, available in our latest release of SYSTRAN Pure Neural® Server, implements several technical optimizations that make the translation faster and more efficient.
New model architecture
The first generation of neural translation engines was based on recurrent neural networks (RNN). This architecture requires the source text to be encoded sequentially, word by word, before generating the translation.Continue reading
Is Your Team Violating Data Compliance Laws?
Data leakage and lack of information are two critical issues that can harm businesses. Nonetheless, due to the ever-growing global marketing and communication needs, the temptation to use the fast and free online translation tools are rising.
Apart from the apparent dangers that these tools pose to businesses such as miscommunication, loss of business, and cultural insults, there is critical important threat that many enterprises often fail to recognize.
Whenever an employee uses a free online translation tool, they may cause massive data privacy breaches by making the consumer data searchable. Data breaches as such mainly happen due to employee negligence looking for quick machine translation, and it can often put millions of customers’ sensitive data at exposed on the internet.
Companies thus struggle to find the right balance between enabling business and securing information. Without the capability of translating software, potentially hundreds, if not thousands, of employees could turn to free translation tools to get their content translated in turn making the content available online.Continue reading
Last week we hosted the 2018 edition of SYSTRAN Community Day! The conference was an exciting day full of energy, from Jean Senellart’s opening speech to our client success stories and celebrating SYSTRAN 50th anniversary! Here is a quick look at the conference highlights:
Jean Senellart announces the launch of a marketplace connecting the expertise of neural model trainers with the needs of industrial MT users
Jean Senellart, CEO of SYSTRAN France and CTO of the group opened the conference with a bold statement: the high quality of Neural Machine Translation has “commoditized” Machine Translation. As a commodity, NMT framework provides raw technology that needs to be refined, adapted and integrated for any industrial usage. After a look at the available NMT open source frameworks, including OpenNMT, cofounded and actively maintained by SYSTRAN, he made clear that streamlined training processes and data quality are the most crucial points to industrialize high quality neural machine translation.
Jean concluded his talk with the announcement of SYSTRAN marketplace, an open online platform where language experts have access to best of breed technology and framework to build, share, and sell language or domain models that can be accessed by industrial users. They will be able to select among hundreds of available models for any language pair and share feedback or evolution requests as per their specific needs.
The latest version of our AI-powered Translation Software designed for Businesses
SYSTRAN Pure Neural® Server is our new generation of enterprise translation software based on Artificial Intelligence and Neural networks. It provides outstanding professional quality with the highest standards in data safety.
Our R&D team, extremely active to provide corporate users with state-of-the-art translation technology tailored for business, just released a new generation of Neural MT engines. SYSTRAN new engines are developed with OpenNMT-tf, our AI framework using latest TensorFlow features, and backed by a proprietary new training process: Infinite Training.
Since 2016, there has been a sharp increase in open source machine translation projects based on neural networks or Neural Machine Translation (NMT) led by companies such as Google, Facebook and SYSTRAN. Why have machine translation and NMT-related innovations become the new Holy Grail for tech companies? And does the future of these companies rely on machine translation?
Never before has a technological field undergone so much disruption in such a short time. Invented in the 1960s, machine translation was first based on grammatical and syntactical rules until 2007. Statistical modelling (known as statistical translation or SMT), which matured particularly due to the abundance of data, then took over. Although statistical translation was introduced by IBM in the 1990s, it took 15 years for the technology to reach mass adoption. Neural Machine Translation on the other hand, only took two years to be widely adopted by the industry after being introduced by academia in 2014, showing the acceleration of innovation in this field. Machine translation is currently experiencing a golden age of technology.
From Big Data to Good Data
Not only have these successive waves of technology differed in their pace of development and adoption, but their key strengths or “core values” have also changed. In rule-based translation, value was brought by code and accumulated linguistic resources. For statistical models, the amount of data was paramount. The more data you had, the better the quality of your translation and your evaluation via the BLEU score (Bilingual Evaluation Understudy, the most widely used algorithm measuring machine translation quality). Now, the move to Machine translation based on neural networks and Deep Learning is well underway and has brought about major changes. The engines are trained to learn language as a child does, progressing step by step. The challenge is not only to process exponential data (Big Data) but more importantly to feed the engines the most qualitative data possible. Hence the interest in “Good data.”
– SYSTRAN celebrates its golden anniversary as a machine translation company by looking back at their most memorable milestones.
In the last 50 years, SYSTRAN has had the great pleasure of delivering machine translation capabilities to the Fortune 500, unicorn start-ups, education institutions, non-profits, government communities and LSPs worldwide. They’ve arrived at a unique vantage point across industries such as banking, finance, manufacturing, legal, internet, security, software, wearable devices and IoT.
“To have experienced decades of SYSTRAN’s impact on technology and culture has been a gift,” says Denis A. Gachot, CEO of SYSTRAN Software Inc. “However, what I find more inspiring is the intention of our founder Peter Toma when starting SYSTRAN.”
“I felt deeply that I had to devote my energy to the elimination of world conflict causing factors. As a first step to overcome the language problem, I felt that I should know as many languages as possible and use technology so others could be understood.” – Peter Toma
From powering the translation that helped the U.S. and Soviet astronauts communicate, bringing on-line translation to the internet and assisting the F500 corporations to collaborate globally, these moments not only commemorate their longevity, but they also show their values.
Commenting on reaching 50, Chairman Mr. Chang-Jin Ji believes that SYSTRAN would not be celebrating today if it was not for the dedication of employees around the globe to customer support and innovation. “I truly thank them and the loyal support we have received from our customers.”
Looking to the future, this month SYSTRAN will launch a new generation of their server solution, SYSTRAN Pure Neural® Server, that pushes the quality and fluency boundary further than ever before explains Jean Senellart, Global CTO of SYSTRAN. “This new release benefits from the state-of-the-art research in neural translation and brings to our customers these technologies for their specialized models in a fully integrated solution. Our commitment to Open Source through the OpenNMT project, now comprising more than 1,600 members, has been pushing our development teams to achieve excellence, and is raising the bar for the whole industry.”
See SYSTRAN’s most memorable moments in this commemorative video.
Contact: | Craig Stern | Director of Marketing | firstname.lastname@example.org
As of January 3rd 2018, companies in the financial industry operating in Europe are required by law to fully comply with the new MiFID II regulation. A good portion of the new rules requires translating various documents for a multilingual audience.
1 – Effortlessly translate detailed information on tons of transactions
2 – Easily provide investors with multilingual research reports and articles
3 – Produce E-Learning and other company material to educate employees across the EU on complying with these new regulations
4 – Translate contracts and other official investment documents
You can find the whole infographic here.