AWS NLP Newsletter - AWS NLP Summit Recap
Tags: aws, ai, nlp
Published: 2022-10-14 08:34:59

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title: AWS NLP Newsletter - AWS NLP Summit Recap
published: true
description: 
tags: #aws #ai #nlp
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## What is AWS NLP Summit

![AWS NLP Summit - London](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/ivir8j7tsy7j9kqboc6o.png)

The AWS NLP Summit is a two-day, in-person event at the Amazon London Office that took place Oct 5 and Oct 6 2022. It’s a public facing event organised by the AWS Natural Language Processing (NLP) community within AWS. The event covered approaches that you can use to extract insights from text data. For instances, sentiment analysis for financial news, content analysis for educational assets, driving understanding from documents, ..., and more.

Business decision makers learned more about the common use cases and success stories from AWS customers on the first day. Developers and ML practitioners day two, which was packed with workshops and dive deep sessions, was a great opportunity to learn more about the NLP tech stack on AWS.

As you see this post is about “AWS NLP Summit Recap”. We would like to share with you:

* Four highlight sessions of the event
* Session catalog + LinkedIn links for all our speakers and volunteers
* Way to get a copy of the AWS NLP Summit slides :)  


## Highlights

* Keynotes by Craig Saunders
    * ![Keynote from Craig Saunders](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/zckfalsep31ocqfw814x.jpeg)
    * The keynote from Craig included the knowledge of the conversational AI of Alexa. It gave the audience a glance of what is behind the Alexa service. Craig also shared how Alexa understands the conversation without a subject within a sentence and how Alexa response to users look up the sport game status, analysis how many games are left, and the possibilities for each team to win the game in the future. The session opened up the audience’s understanding of what Alexa actually does behind the scenes. 
 
* Start up panel discussion
    * ![Startup Panel Discussion](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/jvy672vvmk0ekmdrk61b.jpeg)
    * Large Language Model (LLM) is super charging AI/ML as an emerging sector. LLM startups have raised over $5bn funding worldwide in the past few years, growing at over 400% YoY. We invited 5 European LLM startup founders, Conjecture, Magic, LightOn, deepset, and Mystic, to share their experience of running LLM startups; How to get started with LLMs - training/fine-tuning/prompting; and the Ethics and the future of AI.
    * Relavant posts on LinkedIn:
        * https://www.linkedin.com/feed/update/urn:li:activity:6978980618894221312/
        * https://www.linkedin.com/posts/mystic-ai_aws-nlp-activity-6983743215875018752-s4uC
        * https://www.linkedin.com/posts/lighton_aws-nlp-summit-activity-6983034698641899520-dACP 
* Customer session [Generating descriptions from structured data with data-to-text models] by NEWTOMS LLC & Antonio Rodriguez
    * ![Customer Speaking - One](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/o08f0cwoyvios3i2x9dc.jpg)
    * ![Customer Speaking - Two](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/gj0ulgqh010nswufoabn.jpg)
    * In this session co-delivered with NEWTOMS, we presented a use case from a Travel & Hospitality customer generating descriptions on hotel properties from structured data using Natural Language Generation (NLG). We saw a demo using SageMaker with a graph database in Neptune, and explored the implementation and its application to other verticals.
* Workshop - Distributed Training and Inference for Large Language Models on Amazon SageMaker 
    * ![Emily in AWS NLP Summit](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/1bmjd0q0jtxgyrdqh2as.jpeg)
    * In this session, Emily shared how to train and deploy distributed state of the art models on Amazon SageMaker. From BERT to GPT to BLOOM and more. One of the skill she shared is leveraging distributed strategies like model and data parallelism to optimize for both throughput and accuracy. The LLM is one of the hottest topic of the event, and the session was full-house, and people joined the session with standing spots.

## Agenda and the LinkedIn Profile of the speakers

Here we share the session title and speaker list of AWS NLP Summit. Feel free to follow them/connect them on Linkedin.

### Keynotes

K01 - AWS NLP Services
[Vasi Philomin](https://www.linkedin.com/in/vasi-philomin/), Vice President & General Manager, Machine Learning & AI at Amazon

K02 - Accelerate business value with AWS AI/ML
[Satish Lakshmanan](https://www.linkedin.com/in/satish-lakshmanan-1a6b3a/), Managing Director: AWS Global Head of AI/ML Sales, Biz Development and Solutions Architecture at Amazon Web Services (AWS)

K03 - NLP in Alexa 
[Craig Saunders](https://www.linkedin.com/in/craigjsaunders/), Director of Machine Learning - Alexa AI. at Amazon


### Start-up Panels

[Yina Ye](https://www.linkedin.com/in/yina-ye/), ML BD, Startups & VC at Amazon Web Services (AWS)
[Connor Leahy](https://www.linkedin.com/in/connor-j-leahy/), CEO and founder of Conjecture
[Eric Steinberger](https://www.linkedin.com/in/ericsteinb/), CEO & Co-Founder at Magic
[Igor Carron](https://www.linkedin.com/in/igorcarron/), Co-Founder and President of LightOn
[Timo Möller](https://www.linkedin.com/in/timo-moeller/), Co-Founder of deepset
[Paul Hetherington](https://www.linkedin.com/in/paul-hetherington/), Co-Founder and CEO of Mystic

### Customer speaking

C01 - NEWTOMS LLC - Generating descriptions from structured data with data-to-text models
[Antonio Rodriguez](https://www.linkedin.com/in/antrodriguez/), Senior AI/ML Specialist Solutions Architect at Amazon Web Services (AWS)

C02 - DKB ticket intelligence - The trials and tribulations of using BERT
[Dr. Thomas Hack](https://www.linkedin.com/in/thomas-hack/), Data Scientist at DKB

C03 - JPMC - Serving BLOOM 176B Model on Amazon SageMaker 
[Suman Addanki](https://www.linkedin.com/in/suman724/), head of the ML Engineering for AI Services in JPMorgan AI Platform

C04 - Quantiphi - Accelerate NLP deployments by building reusable components
[Salman Taherian](https://www.linkedin.com/in/salmant/), AI/ML Partner Solutions Architect at Amazon Web Services (AWS)

C05 - Inawisdom - Driving understanding from Documents and other unstructured data sources
[Ines Jurchevici](https://www.linkedin.com/in/inesjurchevici/), Snr Partner Dev Specialist at Amazon Web Services (AWS)

C06 - Magic.dev - Large Language Model Training: Self-Managed ML on EC2
[Eric Steinberger](https://www.linkedin.com/in/ericsteinb/), CEO & Co-Founder at Magic

### Sessions

S01 - Using AWS AI services for building accessibility features and breaking through language barriers
[Luca Guida](https://www.linkedin.com/in/lucaguida/), Solutions Architect at Amazon Web Services (AWS)

S02 - Sentiment Analysis for Financial News using No Code SageMaker Jumpstart and BERT Models 
[Rahul Sureka](https://www.linkedin.com/in/rahul-sureka-653b616/), Enterprise Specialist Solutions Architect at Amazon Web Services (AWS)

S03 - Combating misinformation using Amazon Comprehend
[Julia Ang](https://www.linkedin.com/in/julia-ang-17786018a/), Associate Solutions Architect at Amazon Web Services (AWS)

S04 - Responsible AI: NLP Bias 
[Hasan Poonawala](https://www.linkedin.com/in/hasanp/), Sr ML Specialist Solutions Architect at Amazon Web Services (AWS)
[Bharathi Srinivasan](https://www.linkedin.com/in/bharathi-srinivasan-1b2312b9/), ProServe Data Scientist at Amazon Web Services (AWS)

S05 - Educational content analysis with AIML workloads on AWS 
[Sebastian Leks](https://www.linkedin.com/in/sebastian-l-40589b230/), Sr. Service Creation Solutions Architect at Amazon Web Services (AWS) 
[Mia Chang](https://www.linkedin.com/in/mia-chang/), AI/ML Specialist Solutions Architect at Amazon Web Services (AWS)

S06 - Visually build conversation flows with Amazon Lex Visual Conversation Builder
[Davide Gallitelli](https://www.linkedin.com/in/dgallitelli/), AI/ML Specialist Solutions Architect at Amazon Web Services (AWS)

S07 - Generating art from text with distributed training on Amazon SageMaker
[Corey Barrett](https://www.linkedin.com/in/coreybarrett/), Sr. Data Scientist at Amazon Web Services (AWS)
[Emily Webber](https://www.linkedin.com/in/emily-webber-921b4969/), Principal AI/ML Specialist Solutions Architect at Amazon Web Services (AWS)

S08 - Deploy large NLP models on SageMaker using DJL DeepSpeed inference
[Dhawal Patel](https://www.linkedin.com/in/dhawalpatel1981/), Principal AI/ML Specialist Solutions Architect at Amazon Web Services (AWS)
[Qingwei Li](https://www.linkedin.com/in/liqingwei/), Sr. AI/ML Specialist Solutions Architect at Amazon Web Services (AWS)

S09 - NLPOps - Operationalise and automate your NLP pipeline using AWS
[Sokratis Kartakis](https://www.linkedin.com/in/sokratis-kartakis/), Sr AI/ML Specialist Solutions Architect at Amazon Web Services (AWS)

S10 - Responsible AI: NLP Explainability
[Hasan Poonawala](https://www.linkedin.com/in/hasanp/), Sr ML Specialist Solutions Architect at Amazon Web Services (AWS)

S11 - Build highly accurate NLP solutions faster with the open-source AutoGluon and Amazon SageMaker
[Anastasia Tzeveleka](https://www.linkedin.com/in/anastasiatzeveleka/), Sr AI/ML Solutions Architect, Public Sector at Amazon Web Services (AWS)

S12 - Deeper Document Understanding with Amazon Textract and Amazon SageMaker
[Alex Thewsey](https://www.linkedin.com/in/athewsey/), Sr AI/ML Solutions Architect at Amazon Web Services (AWS)

S13 - Look Ma, I shrunk BERT (Knowledge Distillation)
[Mariano Kamp](https://www.linkedin.com/in/mariano-kamp/), Principal Solutions Architect at Amazon Web Services (AWS)

S14 - Accelerate your NLP workloads with Trainium & Inferentia
[Matthew McClean](https://www.linkedin.com/in/matthewmcclean/), Sr Manager Solutions Architect at Amazon Web Services (AWS)

S15 - Automated mining of emergent catchphrases for advertising content moderation
[Ajay Vohra](https://www.linkedin.com/in/ajay-vohra-a95495/), Principal Solutions Architect, Prototyping at Amazon Web Services (AWS)
Mayank Gupta, Senior SDE at Amazon Web Services (AWS)

S16 - How to deploy and use HuggingFace in an enterprise environment
[Sergey Ermolin](https://www.linkedin.com/in/sergeyermolin/), Principal Solutions Architect, AI/ML at Amazon Web Services (AWS)

### Workshops

W01 - Build a hotel reservation agent
[Jake Wen](https://www.linkedin.com/in/jakewen/), Solutions Architect at Amazon Web Services (AWS)

W02 - Ask the Architect
[Ioan Catana](https://www.linkedin.com/in/ioancatana/), AI/ML Specialist Solutions Architect at Amazon Web Services (AWS)
[Mia Chang](https://www.linkedin.com/in/mia-chang/), AI/ML Specialist Solutions Architect at Amazon Web Services (AWS)

W03 - Augment your HuggingFace model with Human-in-the-Loop
[Georgios Schinas](https://www.linkedin.com/in/georgios-schinas/), Specialist Solutions Architect ML at Amazon Web Services (AWS)

W04 - Distributed Training and Inference for Large Language Models on Amazon SageMaker
[Emily Webber](https://www.linkedin.com/in/emily-webber-921b4969/), Principal AI/ML Specialist Solutions Architect at Amazon Web Services (AWS)

W05 - Text and Images: Multimodal Learning on SageMaker
[Uri Rosenberg](https://www.linkedin.com/in/uri-rosenberg-ba0758a3/), Senior STAM – AI/ML at Amazon Web Services (AWS)

W06 - Increase the Search relevance using Semantic embeddings
Praveen Mohan Prasad, STAM - Big Data (Sp) at Amazon Web Services (AWS)

W07 - Hugging Face Model Explainability for customer sentiment text analytics
[Tim Wu](https://www.linkedin.com/in/tim-wu-7865a7b0/), Sr. AI Specialist Solutions Architect at Amazon Web Services (AWS)


## Was the event recorded?

No, this was an in-person only event. We focus on the face to face experience in this event.  

*However*, if you did not register the event, and you are interested in to have a copy of our available slides. You can request by this slide request form (https://eventbox.dev/survey/WBTQS3Q)

We will send you the copy of the slides by end of 2022 Oct. Note that not all the sessions are available due to PR reason.

## Stay in touch with NLP on AWS

Our contact: aws-nlp@amazon.com
Email us about (1) your awesome project about NLP on AWS, (2) let us know which post in the newsletter helped your NLP journey, (3) other things that you want us to post on the newsletter. Talk to you soon.


## Final Thanks.

Organizer team: 
[Heiko Hotz](https://www.linkedin.com/in/heikohotz/), Sr. AI/ML Specialist Solutions Architect at Amazon Web Services (AWS)
[Mia Chang](https://www.linkedin.com/in/mia-chang/), AI/ML Specialist Solutions Architect at Amazon Web Services (AWS)
[Andrew Kane](https://www.linkedin.com/in/andrewjkane/), WW Tech Leader and Chief Principal Architect AI Language Services at Amazon Web Services (AWS)
[Anastasia Tzeveleka](https://www.linkedin.com/in/anastasiatzeveleka/), Sr AI/ML Solutions Architect, Public Sector at Amazon Web Services (AWS)
[Anna Gruebler](https://www.linkedin.com/in/annagruebler/), Sr AI/ML Solutions Architect at Amazon Web Services (AWS)
Jon Reade, Sr AI/ML Solutions Architect at Amazon Web Services (AWS)
[Yina Ye](https://www.linkedin.com/in/yina-ye/), ML BD, Startups & VC at Amazon Web Services (AWS)
[Premkumar Rangarajan](https://www.linkedin.com/in/premkr/), Principal Solutions Architect at Amazon Web Services (AWS)

Volunteers from AWS and Amazon:
James Park, Fahad Ahmed, Andrew Ellul, Antonio Rodriguez, Dinesh Mane, Lettie Ndlovu, Max Klass, Srivalsan Mannoor Sudhagar, Cosmin Pascu, Maria Mata, Tyree Glasgow-Alexander, Adam Temple, George Mihaila, Ayman Salama, Mihai Dobri, Hasan Basri AKIRMAK, Burak Gozluklu, Yusraa Djaafer, James Yi, Gabrielle Dompreh, Veeresh Shringari, Naufal Mir, Ahmed Raafat, Jenny Vega, Sam Price, Ajay Vohra, Alex Thewsey, Bharathi Srinivasan, Bilal Zafar, Corey Barrett, Emily Webber, Georgios Schinas, Arnaud Lauer, Jake Wen, Luca Guida, Mariano Kamp, Praveen Mohan Prasad, Rahul Sureka, Sebastian Leks, Sergey Ermolin, Tim WU, Uri Rosenberg, Melanie Li, Subham Kumar, Michelle Gibbs, Elina Lesyk, Roop Bains, Sophia Wilson, Brett Hamilton, Sokratis Kartakis