If you say… “Hey, computer, play me some music” and then it starts playing you some music, there’s a number of things that have to have happened for that to come true.
So many AI developers are coming up with creative, useful COVID-19 applications during this time of crisis. Among those are Timo from Deepset-AI and Tony from Intel. They are working on a question answering system for pandemic-related questions called COVID-QA. In this episode, they describe the system, related annotation of the CORD-19 data set, and ways that you can contribute!
Catherine Breslin of Cobalt joins Daniel and Chris to do a deep dive on speech recognition. She also discusses how the technology is integrated into virtual assistants (like Alexa) and is used in other non-assistant contexts (like transcription and captioning). Along the way, she teaches us how to assemble a lexicon, acoustic model, and language model to bring speech recognition to life.
Expanding AI technology to the local languages of emerging markets presents huge challenges. Good data is scarce or non-existent. Users often have bandwidth or connectivity issues. Existing platforms target only a small number of high-resource languages.
Our own Daniel Whitenack (data scientist at SIL International) and Dan Jeffries (from Pachyderm) discuss how these and related problems will only be solved when AI technology and resources from industry are combined with linguistic expertise from those on the ground working with local language communities. They have illustrated this approach as they work on pushing voice technology into emerging markets.
Daniel and Chris explore Semantic Scholar with Doug Raymond of the Allen Institute for Artificial Intelligence. Semantic Scholar is an AI-backed search engine that uses machine learning, natural language processing, and machine vision to surface relevant information from scientific papers.
Congrats to Clément and the Hugging Face team on this milestone!
The company first built a mobile app that let you chat with an artificial BFF, a sort of chatbot for bored teenagers. More recently, the startup released an open-source library for natural language processing applications. And that library has been massively successful.
The library mentioned is called Transformers, which is dubbed as ‘state-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch.’
If any of these things ring a bell to you, it may be because Practical AI co-host Daniel Whitenack has been a huge supporter of Hugging Face for a long time and mentions them often on the show. We even had Clément on the show back in March of this year.
SpaCy is awesome for NLP! It’s easy to use, has widespread adoption, is open source, and integrates the latest language models. Ines Montani and Matthew Honnibal (core developers of spaCy and co-founders of Explosion) join us to discuss the history of the project, its capabilities, and the latest trends in NLP. We also dig into the practicalities of taking NLP workflows to production. You don’t want to miss this episode!
The goal of this repository is to build a comprehensive set of tools and examples that leverage recent advances in NLP algorithms, neural architectures, and distributed machine learning systems. The content is based on our past and potential future engagements with customers as well as collaboration with partners, researchers, and the open source community.
A little ingenuity paired with changes to ReCaptcha’s audio challenge allowed this hacker to create a Python ‘robot’ that defeats the ‘not a robot’ test with 90% accuracy. The approach is brilliant:
- Navigate to Google’s ReCaptcha Demo site
- Navigate to audio challenge for ReCaptcha
- Download audio challenge
- Submit audio challenge to Speech To Text
- Parse response and type answer
- Press submit and check if successful
The code is small enough to grok in 5-10 minutes. Love it!
Flair allows you to apply our state-of-the-art natural language processing (NLP) models to your text, such as named entity recognition (NER), part-of-speech tagging (PoS), sense disambiguation and classification.
Multilingual and built on PyTorch.
Tobias Macey, on why this particular episode of Podcast.__init__ is worth a listen:
Tools for natural language processing are often limited in the number of human languages that they support. This was an interesting discussion on some of the work being done to make it easier to analyse text in multiple languages.
CV Compiler is an online resume analysis tool designed exclusively for software engineers.
The review technology scans for keywords from the world of programming and how they are used in the resume, relative to the best practices in the industry.