{"id":599057,"date":"2023-01-19T06:49:56","date_gmt":"2023-01-19T12:49:56","guid":{"rendered":"https:\/\/news.sellorbuyhomefast.com\/index.php\/2023\/01\/19\/ai-translation-firm-unveils-world-first-timeline-to-singularity\/"},"modified":"2023-01-19T06:49:56","modified_gmt":"2023-01-19T12:49:56","slug":"ai-translation-firm-unveils-world-first-timeline-to-singularity","status":"publish","type":"post","link":"https:\/\/newsycanuse.com\/index.php\/2023\/01\/19\/ai-translation-firm-unveils-world-first-timeline-to-singularity\/","title":{"rendered":"AI translation firm unveils \u2018world-first\u2019 timeline to singularity"},"content":{"rendered":"
\n

An Italian company has unveiled a novel method of measuring AI<\/a> progress: analyzing improvements in machine translation.<\/span><\/p>\n

Translated<\/span><\/a>, a provider of translation services, used the approach to predict when we will achieve singularity, a vague concept often defined as the point where machines become smarter than humans.<\/span><\/p>\n

The Rome-based business<\/a> sets this milestone at the moment when AI provides \u201ca perfect translation.\u201d According to the new research, this arrives when machine translation (MT) is better than top human translations.<\/span><\/p>\n

Translated\u2019s analysis suggests this will happen before the end of the 2020s.<\/p>\n

\u201c[It will be] within this decade, at least for the top 10 languages in a context of average complexity,\u201d Marco Trombetti, the company\u2019s CEO, tells TNW. \u201cThe reality is that in some specific domains and in a few languages this has already happened. For some rare languages and domains it may never come.\u201d<\/span><\/p>\n

\"Marco
Trombetti, a computer scientist and entrepreneur, cofounded Translated in 1999. His customers today include Google, Airbnb, and Uber. Credit: Translated<\/figcaption><\/figure>\n

Translated\u2019s estimates are based on data<\/span> taken from Matecat<\/a>, a<\/span>\u00a0computer-assisted translation (CAT) tool.<\/span><\/p>\n

The platform began life in 2011 as an EU-funded research project. Three years later, the system was released as open-source software<\/a>, which professionals use to<\/span> improve their translations.<\/p>\n

Translated offers Matecat as a freemium product. In return, users provide the company with data that\u2019s used to improve its models.\u00a0<\/span><\/p>\n

To chart the path to singularity, Translated tracked the time users spent checking and correcting 2 billion MT suggestions. Around 136,000 professionals worldwide had made these edits across Matecat\u2019s 12 years of operation. The translations spanned <\/span>diverse domains, from literature to technical subjects. They also included fields in which MT is still struggling, such as speech transcription.<\/p>\n

\n

\u201cSingularity is really close.<\/p>\n<\/blockquote>\n

The data suggests\u00a0that AI is rapidly improving. In 2015, the average time that world-leading translators took to check and correct MT suggestions was around 3.5 seconds per word. Today, that number\u2019s down to 2 seconds per word.<\/span><\/p>\n

At the current rate, the time will hit 1 second in around five years. At that point,\u00a0 MT would provide the epochal \u201cperfect translation.\u201d In practical terms, it will then be more convenient to edit a machine\u2019s translations than a top professional\u2019s.<\/span><\/p>\n

According to Trombetti, any task involving communication, understanding, listening, and sharing knowledge will become multilingual with minimal investment. <\/span><\/p>\n

\u201cThe exact date of when we will reach the singularity point may vary, but the trend is clear: it is really close,\u201d he says.<\/span><\/p>\n

\"When
The \u201cTime to Edit\u201d metric assigns the quality evaluation to professional translators<\/span>. Credit: Translated<\/figcaption><\/figure>\n

Advances in MT require increasing computing power, linguistic data, and algorithmic efficiency. Consequently, the<\/span>\u00a0researchers had presumed progress would slow as singularity approached. To their surprise, the rate of development was highly linear.<\/p>\n

If this momentum continues as predicted, Translated anticipates demand for MT to be at least 100 times higher. <\/span>Workers may worry that their jobs will be automated, but they could also benefit. Translated forecasts at least a tenfold increase in requests for professional translations.<\/span><\/p>\n

\u201cAll our customers who are deploying machine translation on a large scale are also spending more on human translation,\u201d says\u00a0Trombetti.<\/span><\/p>\n

\u201cMachine translation is an enabler in that it creates more interactions between markets and users that were not in contact before. This generates business, and business generates higher-quality content that requires professionals.\u201d<\/span><\/p>\n

Trombetti also expects new roles to emerge for elite translators.<\/p>\n

\u201cTo get the best quality out of machine translation you need it to be trained by the best linguists. <\/span>A significant volume of translations is required to train language models and fix errors in them, so I guess it\u2019s likely that we\u2019ll witness huge competition for the best translators in the upcoming years.\u201d<\/span><\/p>\n

\n

\u201cMT is a good predictor of what\u2019s next in AI.<\/p>\n<\/blockquote>\n

According to Translated, the new research is the first to ever quantify the speed at which<\/span> we\u2019re approaching\u00a0singularity. <\/span>The claim won\u2019t convince every cynic, but MT is a compelling barometer for AI progress.<\/span><\/span><\/p>\n

Human languages are notoriously tricky for machines to master. <\/span>The subjectivity of linguistic meaning, the constantly evolving conventions, and the nuances of cultural references, wordplay, and tone can be elusive for computers<\/a>. <\/span><\/p>\n

In translation, these complexities must be modelled and linked in two languages. <\/span>As a result, <\/span>algorithmic research, data collection, and model sizes are often pioneered in the field. <\/span>The Transformer model<\/a>, for instance, was applied to MT many years before being used in OpenAI\u2019s GPT systems.<\/span><\/p>\n

\u201cMT is simply a good predictor of what is coming next in AI,\u201d says Trombetti.<\/span><\/p>\n

If what comes next is singularity, the Italian entrepreneur anticipates a new era for global communication.<\/p>\n

He envisions universal translators, all content becoming globally available, and everyone able to speak their native language.<\/p>\n

His definition of singularity may be questionable, but its appeal is undeniable.<\/p>\n<\/p><\/div>\n

Read More<\/a>
\n Thomas Macaulay<\/p>\n","protected":false},"excerpt":{"rendered":"

An Italian company has unveiled a novel method of measuring AI progress: analyzing improvements in machine translation. Translated, a provider of translation services, used the approach to predict when we will achieve singularity, a vague concept often defined as the point where machines become smarter than humans. The Rome-based business sets this milestone at the<\/p>\n","protected":false},"author":1,"featured_media":599058,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[46,55273,1009],"tags":[],"class_list":{"0":"post-599057","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-technology","8":"category-translation","9":"category-unveils"},"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/newsycanuse.com\/index.php\/wp-json\/wp\/v2\/posts\/599057","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/newsycanuse.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/newsycanuse.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/newsycanuse.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/newsycanuse.com\/index.php\/wp-json\/wp\/v2\/comments?post=599057"}],"version-history":[{"count":0,"href":"https:\/\/newsycanuse.com\/index.php\/wp-json\/wp\/v2\/posts\/599057\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/newsycanuse.com\/index.php\/wp-json\/wp\/v2\/media\/599058"}],"wp:attachment":[{"href":"https:\/\/newsycanuse.com\/index.php\/wp-json\/wp\/v2\/media?parent=599057"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/newsycanuse.com\/index.php\/wp-json\/wp\/v2\/categories?post=599057"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/newsycanuse.com\/index.php\/wp-json\/wp\/v2\/tags?post=599057"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}