Unbabel eliminates language barriers so that businesses can thrive across cultures and geographies. The company's language operations platform blends advanced artificial intelligence with human editors, for fast, efficient, high-quality translations that get smarter over time. Unbabel integrates seamlessly in any channel so that agents can deliver consistent multilingual support from within their existing workflows. Making it easy for enterprises to grow into new markets and build seamless customer experiences in every corner of the world. Based in San Francisco, California, Unbabel works with leading customer support and marketing teams at brands such as Facebook, Microsoft, Booking.com, and Under Armour to communicate effortlessly with customers around the world, no matter what language they speak.

Unbabel, the AI-powered language operations platform that helps businesses deliver multilingual customer experiences at scale, is announcing that sales leader and marketing expert, Jennifer Bers, has joined the leadership team as Chief Revenue Officer. "She has demonstrated effective leadership and a track record of success as a coach and mentor. Her drive to streamline sales processes and design a strong global sales foundation will ensure that Unbabel continues to see major success as a multilingual customer experience provider." Bers joins Unbabel with 25 years of experience working with technology startups and scaleups in both the US and the UK. During her career, her focus has been on creating high-performance teams, with an emphasis on supporting sales representatives with coaching, feedback, training, and leading by example.

The language industry is having a moment. The ongoing global health crisis has forced organizations to break down borders and support a global remote workforce, requiring more cross-language interactions and coordination than ever before. At the same time, technological innovations in the language translation industry are at an all time high. We've never before had access to such sophisticated technology tools to manage translation processes. I predict it's going to be an exciting year in the industry, with an unprecedented level of innovation.

Thanks to breakthroughs in natural language processing (NLP), machines can generate increasingly sophisticated representations of words. Every year, research groups release more and more powerful language models -- like the recently announced GPT-3, M2M 100, and MT-5 -- that are able to write complex essays or translate text into multiple languages with better accuracy than previous iterations. However, since machine learning algorithms are what they eat (in other words, they function based on the training data they ingest), they inevitably end up picking up on human biases that exist in language data itself. This summer, GPT-3 researchers discovered inherent biases within the model's results related to gender, race, and religion. Gender biases included the relationship between gender and occupation, as well as gendered descriptive words.

New, sophisticated AI models such as OpenAI's GPT-3 are making headlines for their ability to mimic human-like language. Does this mean humans will be replaced with computers? Despite the hype, these algorithms still have major flaws. Not to mention, ethical concerns such as bias in AI still are far from a solution. For these reasons, humans still need to be in the loop in most practical AI applications, especially in nuanced areas such as language.

There's no existing classification for what makes a company an "AI company." Unfortunately for some, AI is just a buzzword that gets tacked onto marketing materials to attract funding. Startups are leveraging AI, and while this has brought some truly innovative solutions to the market, it's also been the spawning ground of a lot of fake AI startups. One of the most telling surveys of 2019 was conducted by London-based MMC Ventures, where it was revealed that 40% of Europe's AI startups are not using any AI at all. This might seem to be a controversial finding, but for many of us who work with AI on a daily basis, it's not particularly surprising.

Artificial intelligence (AI) has infiltrated numerous aspects of our lives in recent years, thanks to improvements in the field of machine learning, where computers ostensibly program themselves. This drive towards digital self-learning has led to major breakthroughs in our day-to-day interactions with machines, most notably the rise of digital home assistants such as Amazon Echo, and the recently launched Google Lens, which identifies objects based on visual cues from your phone's camera. One of the most widely-discussed advances has been the use of AI in translation. Not unlike the Babel Fish from The Hitchhiker's Guide to the Galaxy, with AI translation, "you can instantly understand anything said to you in any form of language." The technology works by recognizing words individually and then, as MIT Technology Review puts it, "takes advantage of the fact that relationships between certain words…are similar across languages" to create its translations. It has already found its way into a number of our most commonly used websites and platforms, with even grander plans in the pipeline – but just how reliable is the technology?

According to Reputation Builder, an angry customer is two or three times more likely to leave a negative review, and 80 percent of customers will steer clear of a business with negative reviews. Getting it wrong may even earn you some really bad press. So how do you keep customers happy? Stop trying to delight your customers. Get their problems solved fast instead. But how do you that?

We are thrilled Wolf is joining our leadership team to head up Unbabel's growth and expansion strategy,