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NVIDIA's New Speech Rec. Model / NLP in Medicine / Another Lite BERT / NuerIPS 2019 - Issue #17

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Clearly last week's most notable events in the world of AI were the NeurIPS conference held in Vancou
 
December 18 · Issue #19 · View online
AI   Speech   &  Language  Processing  Update
Clearly last week’s most notable events in the world of AI were the NeurIPS conference held in Vancouver (see the segment below) as well as the acquisition of Habana Labs (Israeli Deep Learning hardware company) by Intel for $2B.
As for Natural Language Processing (NLP), more and more industries are finding great use cases that can benefit from NLP. I have included blurbs on a few upstarts that leverage NLP doing great things for the healthcare industry.
The domination of transformer-based language models is expanding and we are seeing smaller and more efficient implementations of the BERT - Bidirectional Encoder Representations from Transformers (Devlin et al., 2018) language model. Additionally two remarkable reports covering the field of AI were published last week. The first report was published by Algorithmia and is titled “2020 state of enterprise machine learning”. The title of the second report is Artificial Intelligence Index Report 2019“ and is published by Human-Centered Artificial Intelligence - Stanford University.

A Lite BERT for Reducing Inference Time
Despite their impressive performance, it is a challenge to work with transformer-based language models such as BERT (Devlin et al., 2018). The extent of computational resources and memory footprint required both for training and inference can be overwhelming. ALBERT: A Lite BERT for Self-supervised Learning of Language Representations (Lan et al., 2019) is a new implementation which has merely 4.7% to 18% of the traditional BERT (Devlin et al., 2018) parameters and its training speed is about 1.7x faster than the traditional BERT. Remarkable accomplishment.
A Lite BERT for Reducing Inference Time - Towards AI - Medium
Google T5 Explores the Limits of Transfer Learning - SyncedReview - Medium
Develop Smaller Speech Recognition Models with NVIDIA’s NeMo Framework
Utilization of Language Processing in Medicine
AI-based Natural Language Processing (NLP) has impacted many industries including voice-assistants, customer service chatbots, finance, and document processing among many others. The field of medicine has also been a big beneficiary of the technology. I came across the following companies that have put NLP to a good use and are doing very neat things making a real impact on patient care. The following are just a few of them:
1. Roam Analytics
The company uses NLP to manage patient’s electronic health records. Their platform enables providers to streamline data analysis and storage.
2. Appto
Appto’s platform solution automates manual tasks like examining X-Rays, tests, CT scans, and data entry which leads to elimination of human errors. Additionally they offer an interactive app intended to respond to patient inquiries.
3. Sense.ly
Sense.ly’s AI-based virtual patient assistant. NLP algorithms are used to efficiently monitor, understand patients queries, and gather feedback. Their platform is able to provide guidance to practitioners aiding them make better treatment suggestions.
NeurIPS 2019
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Hope you have benefited from this issue. Please forward to others if you find value in this content. I always welcome feedback.
Al Gharakhanian
info@cogneefy.com | www | Linkedin | blog | Twitter

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