Artificial Intelligence vs. Machine Learning: What Is the Difference

What is artificial intelligence?

Artificial intelligence (AI) is concerned with creating machines that can mimic human intelligence. The aim of AI is for machines to copy humans by performing tasks, learning, and problem-solving.

What is amazing with AI is that it does not require to be pre-programmed. The machine uses complex algorithms that can work completely autonomously with their intelligence. AI enables computers to use math and logic to stimulate human-like reasoning in learning new information and decision-making. 

AI is no longer something futuristic but is today part of most devices we use on daily basis. You can find it in all common smart devices and systems like Siri, Alexa, and more. 

What is machine learning?

Machine learning (ML) is the subfield of AI. It does not enable machines to mimic human intellect, but to learn from past data and experiences. Same as AI, machine learning also doesn't require pre-programming. The system uses massive amounts of data to generate accurate results or give predictions based on this data. The more data the system process, the more it learns and the better it becomes. 

Machine learning works only for specific domains and not for mixed data. For example, if we are creating a machine learning model for speech recognition, it will only work for recognizing someone's talks and nothing else.

Same as AI, we encounter machine learning on a daily basis. Google search algorithms, email spam filters, and many other systems are all powered by ML.

Ml and Ai in translation

Knowing how much fear human translators have towards AI is enough to understand how powerful it is in the translation industry. Many people are curious if AI technology can surpass human translators and make them obsolete. 

For the Forbes article, Ofer Shoshan, CEO of One Hour Translation (now Blend), said that 50% of work carried out by human translators would be replaced by the automated translation.

But how come AI is so powerful when it comes to translation? The technology tracks patterns and trends in data sets, only to compare these patterns to find the perfect solution for a specific situation. Languages are nothing more than large data sets with words and their meanings, governed by precise rules on how to use them. 

Ai uses NMT to learn and improve over time. This system can constantly learn and self-improve by using a large neural network. It improves and learns from every translation task.

But where does machine learning directly come into play in translation? As already explained, ml learns from analyzing large sets of data. The more you translate, the more accurate ML will be. A great example would be autosuggestion. Based on learned patterns, machine learning suggests and fills words along your translation workflow. 

AI applies machine learning to languages. But since AI mimics human intelligence, it doesn't only translate word by word, but also understands:

• Slang
• Tone of voice
• Complex sentence structure
• Jokes.

Pros and cons of using AI and machine learning

As you see, AI brings many benefits to translation. Some of those advantages include:

• Translation speed. AI can deliver multiple translations in many languages in a split of seconds. Translators can thus avoid the slow and rigid translation process, and focus only on content post-editing.
• AI can provide irreplaceable support to human translators. From speeding up their workflow with autosuggestion to giving them instant feedback on the copy.
• Last but not least, AI can greatly cut overhead costs. Especially when it comes to translating large volumes of content into multiple languages. Instead of hiring an army of translators, AI can do the work instantly. What is left to be done is just the quality control and not the full-blown translation from scratch. 

There are not just sunshine and rainbows when it comes to AI. Some of the cons of using AI include:

• Machines can outperform humans when it comes to repetitive work, but they will never surpass human creativity and personal touch. AI can thus produce bland texts, that aren't engaging and fun to read.
• AI will also produce content of lesser quality, than a proficient and experienced translator. Albeit AI is faster, companies will still need a human translator to post and edit the content before showing it to the public.
• Machines will struggle with industry-specific jargon and complex text structures. Using AI for texts like technical manuals won't give you the perfect accuracy. 
• AI doesn't consider cultural differences. Sometimes two nations share the same language, but different cultures. When one translation could be very engaging and fun for one culture, it could be offensive to another.  

Application of AI and machine learning

Using AI and machine learning does not fit every single translation use case. The technology is not an all-in-one translation solution but an assistant to human translators. Harnessing the power of AI and machine learning is thus, the best suited for:

• Internal documentation across global teams. Working in a multinational team means people's language skills will vary, and some may not understand the official language well enough. The technology will eliminate the language barrier with instant translations. 
• External documentation with various stakeholders and customers. AI will enable smoother and more efficient communication without always needing a human translator. For example, AI will translate product reviews to help global customers understand what other buyers are saying.
• Online customer service. Harnessing the power of AI and machine learning will enable brands to interact with customers no matter what language they speak. 
• Localization project management. Companies can automate content creation and monitor workflow with the help of AI.

Conclusion

Artificial intelligence and machine learning are on the rise to change the translation industry forever. Harnessing the power of this technology enables translators to work faster and more efficiently. AI and machine learning technology are becoming more and more powerful, and are part of every aspect of our life. 

Linguana is a multilingual SAAS for Webflow only, powered by the power of AI. Leveraging the power of AI and MT enables every brand to build an online presence beyond the border with ease. Localize your website and content without having to rely on external help. 

Frequently asked questions

Where is machine learning used?

Machine learning is used in cases like Google search engines, spam filters in the mail, autosuggestion on social media, banking software to detect unusual transactions, voice recognition, and more. 

What type of AI is used for translation?

The type of Ai used for translation is called machine translation. It converts text from the source language into a target language. 

Will AI replace human translators?

AI will never replace human translators. Even though AI is powerful, it can't capture the nuance coming from each language's different grammatical rules, semantics, syntax, and cultural influences.