"Machine translation (MT) is the application of computers to the task of translating texts from one natural language to another. One of the very earliest pursuits in computer science, MT has proved to be an elusive goal, but today a number of systems are available which produce output which, if not perfect, is of sufficient quality to be useful in a number of specific domains."
– Definition from the European Association for Machine Translation (EAMT).
GPT3 is the third-generation programming language translation tool from OpenAI. It is based on the previous two versions, GPT2 and GPT1, and offers significant improvements in accuracy and speed. GPT3 has a number of new features that make it more powerful and user-friendly than its predecessors. Perhaps the most significant of these is its ability to automatically generate code from natural language descriptions. This means that, instead of having to write code manually, GPT3 can automatically generate it from a description of what you want it to do.
Languages are the main medium of communication but there are more than 7,100 languages spoken around the world. People who live in different parts of the world speak different languages and it's sometimes hard to communicate with people who don't speak our language. This hinders relationships between people and makes it hard to understand one another or build trust. The ability to translate language, then, makes it easier to communicate across borders, and make information more accessible. With the advances in technology and artificial intelligence, online translators such as Google Translate, DeepL, and Bing Translate have made communication a lot easier among those speaking different languages.
Like every year since 2006, the Conference on Machine Translation (WMT) organized extensive machine translation shared tasks. Numerous participants from all over the world submitted their machine translation (MT) outputs to demonstrate their recent advances in the field. WMT is generally recognized as the event of reference to observe and evaluate the state-of-the-art of MT. The 2022 edition replaced the original news translation task by a "general" translation task covering various domains, including news, social, conversational, and ecommerce, among others. This task alone received 185 submissions for the 21 translation directions prepared by the organizers: Czech English (cs-en), Czech Ukrainian (cs-uk), German English (de-en), French German (fr-de), English Croatian (en-hr), English Japanese (en-ja), English Livonian (en-liv), English Russian (en-ru), Russian Yakut (ru-sah), English Ukrainian (en-uk), and English Chinese (en-zh).
Difficult to do without Google Translate. Whether it is to translate a word, a sentence or an entire text, the tool developed by the American firm and launched in 2006 quickly became essential and one of Google's most used tools. But did you know that it is no longer necessary to type anything in the search bar or in the tool directly? Indeed, thanks to its numerous technological advances, Google now allows us to simply draw the camera of our smartphone. We don't want to offend you by explaining what Google Translate is, its usefulness is directly stated in its name.
Artificial intelligence is a discipline that attempts to simulate human intelligence. The field of AI covers a wide range of technologies, from the relatively simple to the more complex. This wide range of technologies enables AI to solve a wide range of problems, from automated machine translation to high-level reasoning. These technologies include Machine Learning, Natural Language Processing, Knowledge Representation, Probabilistic Reasoning, Logic Programming, Expert Systems, and Genetic Programming. The complexity of AI is often misunderstood by those who have never worked in the field.
Imagine you are in a foreign country where you don't speak the language and your small child unexpectedly starts to have a fever seizure. You take them to the hospital, and the doctors use an online translator to let you know that your kid is going to be OK. But "your child is having a seizure" accidentally comes up in your mother tongue is "your child is dead." This specific example is a very real possibility, according to a 2014 study published in the British Medical Journal about the limited usefulness of AI-powered machine translation in communications between patients and doctors. Sometimes we need American-British translation, too.)
One of the most important jobs in computer vision is image annotation. Computer vision essentially aims to give machine eyes -- the capacity to perceive and comprehend the world -- through various applications. Machine learning initiatives occasionally appear to unleash futuristic technologies that we never imagined conceivable. Augmented reality, automated voice recognition, and neural machine translation are just a few of the AI-powered technologies that have the potential to alter people's lives and enterprises all over the world. Computer vision can also provide incredible technology (autonomous cars, facial recognition, and unmanned drones).
Amazon Alexa AI researchers recently unveiled Alexa Teacher Models (AlexaTM 20B) that beats GPT-3 on NLP benchmarks. The model is yet to be released publicly. Check out the GitHub repository here. Unlike OpenAI's GPT-3 or Google's PaLM, which are decoder-only models, AlexaTM 20B is a seq2seq model that contains an encoder and a decoder allowing better performance on machine translation (MT) and summarization. Sequence-to-sequence model is a special class of recurrent neural network architecture, typically used to solve complex language problems, including machine translation, creating chatbots, question answering, text summarisation, etc.
The dataset has 25000 positive and negative reviews in the training set and 25000 positive and negative reviews in the test set. The image below shows the number of unique reviews and unique sentiment values in the dataset. The movie reviews are classified as having either a positive sentiment or a negative sentiment. The image below takes a peek at four reviews and their target sentiments. As can be seen from the keywords of the first three reviews – hooked, wonderful, unassuming, wonderful – lend the review a positive connotation.