When it comes to translating software interfaces for users in different languages, machine translation (MT) is a well-established tool for scaling up linguists’ productivity, but what happens when a software product comes equipped with an engine ready to do its own translating? This week, Meta AI is breaking headlines with the claim it has delivered […]
CSOFT is back from Chicago this week following a successful exhibit at the DIA 2022 Annual Meeting, where the team joined some of the most innovative companies in global and decentralized clinical trials, patient recruitment, and patient education to represent CSOFT Health Sciences, leaders in medical translations for the quickly changing drug industry. Exhibiting at […]
In a world of streaming entertainment and serious innovation, where do game localization and experimental language AI cross paths? This week, one common theme appears to be the distant past, as yet another natural language processing (NLP) algorithm tackles an ancient language without modern corollaries to see what AI can reveal about its remnant hieroglyphs […]
As inflation dampens commercial prospects across industries and sectors, it is difficult to think that demand for financial services would remain aloft, but how the current economy is impacting communication areas like investment banking translation may yet be another story. With some facing potentially greater needs for credit line extensions and other means of navigating […]
Those who follow the CSOFT Communications blog are familiar with the myriad and interesting problems born from language AI models trained on the most abundant data resource available: what people say online. What people provide in textual volume, they do not necessarily match in thoughtful consideration, and while the gains for machine learning have been […]
When language AI talks, should it have to explain itself? Those keeping up with the latest applications of natural language processing (NLP) and natural language generation (NLG) may have noticed a subtle shift in the ongoing discussion of ethics surrounding algorithms like GPT-3, which has long dwelt on whether AI will channel our more malevolent […]
Language AI and translation technology are constantly improving, but when are advances in technologies like natural language processing (NLP) truly significant? With a steady stream of news forthcoming, keeping a view of the bigger picture can be a challenge, while the vocabulary of algorithmic concepts that developers are tinkering with is more elaborate at each […]
Last month, CSOFT looked at how language AI is bringing clarity to translations not only of present day content but also relics from the distant past – specifically, by deciphering text artifacts bearing symbols from the earliest known precursor to ancient Greek. Now, in an odd twist of developments from across the AI world, natural […]
As a class of technology centered on automating information, language AI is one of the most widely deployed forms of artificial intelligence across all industries and sectors, led in large part by the globalization potential of machine translation and solidified in the widespread adoption of tools like chatbots, document text recognition, and linguistic data-driven analytics. […]
If you’ve ever copied a string of foreign text into Google Translate, you’re surely familiar with the Detect Language function of neural machine translation, the form of language AI that delivers everything from a quick lookup in another language to the raw MT in any machine translation post-editing (MTPE) localization project. Even if you don’t […]
Amid tales of language AI that can write its own poetry, crack its own jokes, and spin up a plausible, if not realistic, response to prompts that we usually expect people to struggle with, it is easy to wonder what practical good there is in such intensive development of natural language processing (NLP) systems while […]
As we have explored extensively in our recent posts on advancing language AI, the most dynamic developments in areas like NLG and NLP have tended to come via large language models (LLMs) that require massive and high-quality datasets to train, which naturally favors large companies and software groups who alone manage access to these datasets. […]
