Top 10 AI innovations of 2021 to date


AI is a complex and constantly evolving field in which organizations and individuals are constantly focused on finding new solutions to pressing challenges. The year has been rich in revolutionary innovations that have pushed the boundaries and paved the way for better results. In this article, we list the top ten AI innovations of 2021 to date.

GitHub co-pilot

Microsoft’s OpenAI and GitHub Copilot is an AI-based tool for programmers to write better code. The programmer can describe a function to the co-pilot in plain English as a comment, and the machine will convert it to actual code. OpenAI Codex lays the foundation for Copilot, it provides an AI system trained on a dataset consisting of a large set of public source code. It works on a wide range of frameworks and languages, and is ideal for languages ​​like Python, JavaScript, TypeScript, Go, and Ruby. The team claimed that Copilot was much more advanced than existing code assistants.

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Unified transformer

Researchers from Facebook AI Research have presented a new transformer model, Unified Transformer (UniT). UniT has an encoder-decoder architecture that handles multiple tasks and domains in a single model with fewer parameters; according to the Facebook team, UniT is a step towards general intelligence.

OpenAI DALL.E & CLIP

DALL. E is the 12 billion parameter version of OpenAI. It is a transformer that can generate images from text prompts. The template can work with multiple objects in an image to render an image or modify it based on text prompts.

The OpenAI research team also demonstrated a neural network called Contrastive Language-Image Pre-training or CLIP. This neural network has been trained on 400 million pairs of images and text. CLIP is also similar to the GPT family and can learn to perform tasks like object character recognition (OCR), geolocation, action recognition, etc.

Mixer Bot 2

Facebook’s BlenderBot 2 is the first open-source chatbot of its kind with long-term memory. Facebook has worked to make AI more empathetic, knowledgeable, and capable. The BlenderBot 2.0 can create long term memory for continuous access. It does this while simultaneously searching the internet for information and having conversations on almost any topic.

Google Translatotron 2

In 2019, Google launched Translatotron, an end-to-end speech-to-speech translation model. It was then the first end-to-end framework capable of directly translating speech from one language to another.

The system was used to create synthesized translations of the voices to ensure that the sound of the original speaker is intact. But this feature could be misused to generate speech with a different voice and create deep fake voices.

This year, Google released Translatotron 2, an updated version where the trained model is limited to retain the source speaker’s voice. Unlike the previous version, it cannot generate voices in different voices, which mitigates potential abuse to create audio spoofing artifacts.

Summit AI

Google introduced Vertex AI, a managed machine learning platform for deploying and maintaining AI models, at this year’s Google I / O conference. The new platform unites AutoML and AI Platform into a unified API, client library, and user interface.

Previously, researchers had to run millions of test images for training algorithms, but now they can rely on Vertex’s technology stack to do the heavy lifting.

FLAME

Microsoft’s FLAML is a python package that can tell us which ML model is best suited for low computation. It eliminates the manual process of choosing the best model and setting.

This AutoML system is primarily focused on model selection, hyperparameter tuning, feature engineering, neural architecture research, and model compression.

MusicBERT

MusicBERT is Microsoft’s pre-trained large-scale model for the symbolic understanding of music. It covers applications such as classification of emotions, classification of genres and matching of pieces of music. Microsoft created this model using an OctupleMIDI method, a bar-level masking strategy, as well as a large-scale symbolic music corpus containing over a million pieces of music.

Microsoft’s Neural TTS

Microsoft’s Neural Text-to-Speech (TTS) software enables developers to create custom synthetic voices. AI is structured in three layers: text analyzer, neural acoustic model and neural vocoder.

The text analyzer converts the plain text to pronunciations, the acoustic model converts the pronunciations to acoustic characteristics, and finally, the vocoder generates waveforms.

Tensorflow 3D

Google’s TensorFlow 3D is a highly modular library for bringing 3D deep learning capabilities to TensorFlow. While the previous TensorFlow was not enough to understand the environment, the 3D update provides a set of operations, loss function, data processing tools, metrics and other models to develop, train and deploy advanced 3D scene understanding models.


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Avi gopani

Avi gopani

I am a liberal arts graduate who enjoys researching and writing about new topics. As a budding journalist, I enjoy reading books, driving on a rainy day, and listening to old Bollywood music.

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