Our Analysts' Insights

As we look back at the annus horribilis that was 2020, what are some things we can learn and take forward to improve 2021 and come back stronger than ever? In this post, I summarize some of the lessons CSA Research has learned from our conversations with professionals working in enterprise localization departments, at LSPs, or as freelance linguists.

Remote simultaneous interpreting has experienced a boom since the start of the COVID-19 pandemic. Organizations of all types turn to RSI platforms to deliver a multilingual experience for virtual or hybrid in-person and online meetings. Likewise, online voting solutions are in high demand for organizations that need a sophisticated virtual voting mechanism when they want to enable remote work for elected officials or other decision-makers.

For the first time since 2005, CSA Research did not release our 2020 Global Market Study sizing and forecasts when we ranked the largest LSPs in the world in June. We just published “Sizing the Language Industry in 2020 and Beyond,” our comprehensive data-based guidance for 2020 through 2025.

In late 2015 most developers still treated Neural Machine Translation (NMT) as a future technology that would come someday, but by the middle of 2016 several developers had released functional neural systems that seemed to outperform even the best statistical MT (SMT) engines. Since that point, momentum has shifted decisively in favor of NMT because it delivered better fluency in its output and seemed to promise the end of incomprehensible MT output. Eventually, this rate of stellar progress slo...

TELUS International announced that it would buy Lionbridge’s artificial intelligence business unit in a deal worth US$935 million that is expected to close by December 31st. Let’s first explain what Lionbridge AI does, review the deal, analyze what it means to the language services and technology sector, and show what it represents to investors.

In 2017, CSA Research introduced the concept of “augmented translation,” a technology-centric approach to amplifying the capabilities of human translators. Although companies such as Lilt, SDL, and Unbabel had already implemented portions of this model – namely the tight integration of human and machine capabilities, we predicted that more technologies would be folded in over time to create an AI-driven platform for linguists that would make them far more efficient and capable by offloading r...

In a recent blog we updated the changing M&A landscape for 2020. We also noted that respondents to CSA Research’s annual Global Market Study (GMS) have shown consistent interest over the years in buying, selling, or merging in response to the question, “How important will the following actions related to merger and acquisitions be in 2020?” Of the 356 respondents from the representative sample of 462, 29% said they wanted to sell, 34% would like to buy, and 30% preferred a merger.

In recent conversations, many enterprises and language service providers have expressed concern about the long-term careers and livelihoods of linguists and of LSP intermediaries. A large high-tech enterprise relayed to us that machine translation (MT) is becoming the dominant source of its global content. Language service providers regularly mention their prices being driven ever lower by fierce competition. Long-time language industry workers worry about the Uberization of a profession that of...

2020 started out with great financial momentum. The MSCI All Country World Index of large-, mid-, and small-cap stocks across 23 developed and 26 developing markets had risen almost 24% over 2018, an ounce of gold was worth 18% more than 12 months prior, and private equity groups had accumulated US$1.5 trillion in funds to invest. Businesses were primed for a stellar 2020, but by March, COVID-19 pushed most of the world to shelter in place. Companies shut down, employees were furloughed, and lif...

A recent examination of how computing power has changed over time calculated how much it would cost today to rent all of the computer capacity that existed at various points in the past. Up until 1968 all the worlds computers’ combined capabilities fell short of what a single server could do in 2018. It was not until 1974 that the then-current capacity (roughly equal to 0.43 teraflops) would exceed £100/month to lease in today’s costs. This exponential drop in the real cost of computing power ...