Difference between revisions of "Amazon"

From
Jump to: navigation, search
m
m (→‎Inferentia)
 
(35 intermediate revisions by the same user not shown)
Line 5: Line 5:
 
|description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools  
 
|description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools  
 
}}
 
}}
−
[http://www.youtube.com/results?search_query=amazon+aws YouTube search...]
+
[https://www.youtube.com/results?search_query=ai+amazon+AWS YouTube]
−
[http://www.google.com/search?q=amazon+aws+deep+machine+learning+ML ...Google search]
+
[https://www.quora.com/search?q=ai%20amazon%20AWS ... Quora]
 +
[https://www.google.com/search?q=ai+amazon+AWS ...Google search]
 +
[https://news.google.com/search?q=ai+amazon+AWS ...Google News]
 +
[https://www.bing.com/news/search?q=ai+amazon+AWS&qft=interval%3d%228%22 ...Bing News]
  
−
* [http://docs.aws.amazon.com/machine-learning/index.html Amazon Machine Learning Documentation]   
+
* [https://docs.aws.amazon.com/machine-learning/index.html Amazon Machine Learning Documentation]   
−
* [[Platforms: Machine Learning as a Service (MLaaS)]]
+
* [[Development]] ... [[Notebooks]] ... [[Development#AI Pair Programming Tools|AI Pair Programming]] ... [[Codeless Options, Code Generators, Drag n' Drop|Codeless]] ... [[Hugging Face]] ... [[Algorithm Administration#AIOps/MLOps|AIOps/MLOps]] ... [[Platforms: AI/Machine Learning as a Service (AIaaS/MLaaS)|AIaaS/MLaaS]]
 +
* [[Bedrock]]
 +
* [[Development#CodeWhisperer|CodeWhisperer]]
 
* [[AWS with TensorFlow]]
 
* [[AWS with TensorFlow]]
 
* [[DeepLens - deep learning enabled video camera]]
 
* [[DeepLens - deep learning enabled video camera]]
 
** [[Getting Started & Project: Object Detection]]
 
** [[Getting Started & Project: Object Detection]]
 
** [[More DeepLens Projects]]
 
** [[More DeepLens Projects]]
 +
** ... [[Image Classification]]  ...[[ResNet-50]]
 
* [[AWS Internet of Things (IoT)]]
 
* [[AWS Internet of Things (IoT)]]
 
** [[AWS IoT Button]]
 
** [[AWS IoT Button]]
 
* [[AmazonML]]
 
* [[AmazonML]]
 
* [[Deep Learning (DL) Amazon Machine Image (AMI) - DLAMI]]
 
* [[Deep Learning (DL) Amazon Machine Image (AMI) - DLAMI]]
−
* [http://developer.amazon.com/alexa-skills-kit Alexa Skills Kit] implementing Amazon’s cloud-based voice service
+
* [https://developer.amazon.com/alexa-skills-kit Alexa Skills Kit] implementing Amazon’s cloud-based voice service
−
* [http://www.floydhub.com/ FloydHub - training and deploying your DL models]
+
* [https://www.floydhub.com/ FloydHub - training and deploying your DL models]
−
* [http://aws.amazon.com/about-aws/events/monthlywebinarseries/on-demand/ On-Demand AWS Tech Talks]
+
* [https://aws.amazon.com/about-aws/events/monthlywebinarseries/on-demand/ On-Demand AWS Tech Talks]
−
* [http://aws.amazon.com/training/ AWS Training and Certification]
+
* [https://aws.amazon.com/training/ AWS Training and Certification]
−
* [[Assistants]]
+
* [[Agents]] ... [[Robotic Process Automation (RPA)|Robotic Process Automation]] ... [[Assistants]] ... [[Personal Companions]] ... [[Personal Productivity|Productivity]] ... [[Email]] ... [[Negotiation]] ... [[LangChain]]
−
** [http://techcrunch.com/2018/02/12/amazon-may-be-developing-ai-chips-for-alexa/ Amazon Is Becoming an AI Chip Maker, Speeding Alexa Responses]
+
** [https://techcrunch.com/2018/02/12/amazon-may-be-developing-ai-chips-for-alexa/ Amazon Is Becoming an AI Chip Maker, Speeding Alexa Responses]
−
** [http://venturebeat.com/2019/09/25/amazon-unveils-echo-buds-alexa-enabled-earbuds-that-track-your-steps/ Amazon unveils Echo Buds, Alexa-enabled earbuds with noise reduction | Kyle Wiggers]
+
** [https://venturebeat.com/2019/09/25/amazon-unveils-echo-buds-alexa-enabled-earbuds-that-track-your-steps/ Amazon unveils Echo Buds, Alexa-enabled earbuds with noise reduction | Kyle Wiggers]
−
** [http://venturebeat.com/2019/09/25/amazons-echo-frames-are-eyeglasses-with-alexa/ Amazon’s Echo Frames are eyeglasses with Alexa | Khari Johnson]
+
** [https://venturebeat.com/2019/09/25/amazons-echo-frames-are-eyeglasses-with-alexa/ Amazon’s Echo Frames are eyeglasses with Alexa | Khari Johnson]
 +
* [https://www.amazon.science/ Amazon Science]
 +
** [https://www.amazon.science/research-areas/automated-reasoning Automated Reasoning]
 +
** [https://www.amazon.science/research-areas/computer-vision  Computer Vision]
 +
** [https://www.amazon.science/research-areas/conversational-ai-natural-language-processing Conversational AI / Natural-language processing]
 +
** [https://www.amazon.science/research-areas/information-and-knowledge-management Information and knowledge management]
 +
** [https://www.amazon.science/research-areas/machine-learning Machine learning]
 +
** [https://www.amazon.science/research-areas/quantum-technologies Quantum Technologies]
 +
** [https://www.amazon.science/research-areas/robotics Robotics]
 +
** [https://www.amazon.science/research-areas/search-and-information-retrieval Search and information retrieval]
 +
* [https://aws.amazon.com/blogs/aws/amazon-q-brings-generative-ai-powered-assistance-to-it-pros-and-developers-preview/ Amazon Q brings generative AI-powered assistance to IT pros and developers (preview) | Amazon]
 +
**[https://techcrunch.com/2023/11/28/amazon-unveils-q-an-ai-powered-chatbot-for-businesses/ Amazon unveils Q, an AI-powered chatbot for businesses | Kyle Wiggers - TechCrunch]
 +
* [https://www.aboutamazon.com/news/company-news/amazon-anthropic-ai-investment Amazon and Anthropic deepen their shared commitment to advancing generative AI | Amazon] ... using [[Anthropic]]'s [[Claude]] on Amazon [[Bedrock]]
 +
 
 
_______________________________________________
 
_______________________________________________
 +
= Inferentia =
 +
* [https://aws.amazon.com/machine-learning/inferentia/ Why Inferentia? | AWS]
 +
* [https://finance.yahoo.com/news/did-amazon-just-checkmate-nvidia-221500449.html Did Amazon Just Say "Checkmate" to Nvidia? | Adam Spatacco - The Motley Fool]
 +
 +
ChatGPT
 +
AWS Inferentia is a custom-designed machine learning inference chip developed by Amazon Web Services (AWS) to accelerate deep learning workloads. The chip is specifically optimized for high performance, low latency, and cost-effective inference, which is the process of running trained machine learning models to make predictions or classifications. By using AWS Inferentia, organizations can achieve faster and more cost-effective deployment of machine learning models for a variety of applications, including image and speech recognition, natural language processing, and recommendation engines. Key features and benefits of AWS Inferentia include:
 +
 +
* <b>High Performance: </b>Inferentia delivers high throughput and low latency, making it ideal for real-time applications. It supports multiple machine learning frameworks such as TensorFlow, PyTorch, and Apache MXNet.
 +
* <b>Cost Efficiency: </b> By providing a dedicated hardware solution for inference, Inferentia can reduce the cost of inference operations compared to using general-purpose CPUs or GPUs.
 +
* <b>Compatibility: </b> AWS Inferentia is integrated with Amazon SageMaker, AWS's fully managed machine learning service, and supports models trained on popular frameworks. This makes it easier for developers to deploy their existing models on Inferentia-based instances.
 +
* <b>Scalability: </b> It can be scaled to handle large-scale machine learning workloads, allowing users to deploy multiple models simultaneously or to serve a high volume of inference requests.
 +
* <b>Availability: </b> Inferentia-powered instances, such as the Inf1 instance type, are available on Amazon EC2. These instances are designed to provide optimal performance for inference applications.
  
−
== Integrated Components/Technologies ==
+
 
 +
<youtube>2XUoDfdBoM8</youtube>
 +
<youtube>pokM1r3rgIg</youtube>
 +
 
 +
= Integrated Components/Technologies =
  
 
* [[Textract]] in the Elastic Stack Architecture
 
* [[Textract]] in the Elastic Stack Architecture
−
* [http://aws.amazon.com/comprehend/ Comprehend] - natural language processing (NLP) service
+
* [https://aws.amazon.com/comprehend/ Comprehend] - natural language processing (NLP) service
−
* [http://aws.amazon.com/kendra/ Kendra] - allow users to ask a question then searches across repositories  
+
* [https://aws.amazon.com/kendra/ Kendra] - natural language search capabilities to your websites and applications; allowing users to ask a question then searches across repositories  
 
* [[Lex]] - conversational interfaces using voice and text
 
* [[Lex]] - conversational interfaces using voice and text
 
* [[SageMaker]] - build, train, and deploy
 
* [[SageMaker]] - build, train, and deploy
 
* [[Polly]] - text to speech
 
* [[Polly]] - text to speech
−
* [[Rekognition]] - video analysis service
+
* [[Rekognition]] - [[Video|video]] analysis service
 
* [[Kinesis]] - collect, process, and analyze real-time, streaming data
 
* [[Kinesis]] - collect, process, and analyze real-time, streaming data
 
* [[Lambda]] - run code without managing servers
 
* [[Lambda]] - run code without managing servers
Line 48: Line 83:
 
* [[DynamoDB]] - NoSQL database  
 
* [[DynamoDB]] - NoSQL database  
 
* [[Simple Storage Service (S3)]] - object storage
 
* [[Simple Storage Service (S3)]] - object storage
−
* [http://aws.amazon.com/athena Athena] interactive query service to analyze data in Amazon S3 using standard SQL
+
* [https://aws.amazon.com/forecast/ Amazon Forecast]  ... looking at a historical series of data, which is called [[Forecasting#Time Series Forecasting|time series]] data
−
* [http://aws.amazon.com/serverless/ Serverless] run applications and services without thinking about servers
+
* [https://aws.amazon.com/athena Athena] interactive query service to analyze data in Amazon S3 using standard SQL
−
* [http://aws.amazon.com/glue/ Glue] a fully managed extract, transform, and load (ETL) service to prepare and load data for analytics
+
* [https://aws.amazon.com/serverless/ run applications and services without thinking about servers]; [[Serverless]]
−
** [http://docs.aws.amazon.com/glue/latest/dg/add-crawler.html Crawlers] to populate the AWS Glue Data Catalog with tables
+
* [https://aws.amazon.com/glue/ Glue] a fully managed extract, transform, and load (ETL) service to prepare and load data for [[analytics]]
 +
** [https://docs.aws.amazon.com/glue/latest/dg/add-crawler.html Crawlers] to populate the AWS Glue Data Catalog with tables
 
* [[Management Console]] - manage web services
 
* [[Management Console]] - manage web services
 
* [[Deep Learning (DL) Amazon Machine Image (AMI) - DLAMI]]
 
* [[Deep Learning (DL) Amazon Machine Image (AMI) - DLAMI]]
−
* [http://en.wikipedia.org/wiki/SoftAP SoftAP] - software enabled access point
+
* [https://en.wikipedia.org/wiki/SoftAP SoftAP] - software enabled access point
−
* [http://www.ubuntu.com/ Ubuntu] - operating system
+
* [https://www.ubuntu.com/ Ubuntu] - operating system
  
 
== Libraries & Frameworks ==
 
== Libraries & Frameworks ==
Line 64: Line 100:
 
* [[gluon]]
 
* [[gluon]]
  
−
<youtube>zkzED9HvMG0</youtube>
+
 
−
<youtube>qCwH94INUFM</youtube>
 
  
 
= Training =
 
= Training =
−
* [http://aws.amazon.com/training/learning-paths/machine-learning/ Learning Paths]
+
<youtube>WoQ3UcEsvTw</youtube>
 +
 
 +
* [https://aws.amazon.com/training/learning-paths/machine-learning/ Learning Paths]
 +
 
 +
 
 +
Business Decision Maker...    ...Data Platform Engineer... ...  Data Scientist.... .....    ....  Developer
 +
 
 +
https://d1.awsstatic.com/training-and-certification/exams_courses_icons/icon_ml-decision-maker.da2f4225ee7b53f91fbc6e1ae08cbf4c13777a0e.png
 +
https://d1.awsstatic.com/training-and-certification/exams_courses_icons/icon_ml-data-platform-engineer.7cf26a6e863a1286e1f94c54a2c6493a68a6bb69.png
 +
https://d1.awsstatic.com/training-and-certification/roles/icon_data-scientist.0ec69c78a7db519f20247c3960f342c1325644dc.png
 +
https://d1.awsstatic.com/training-and-certification/exams_courses_icons/icon_ml-developer.60695054f17ef19224ba3549d901ab640738a6e4.png
 +
 
 +
 
 +
== Business Decision Maker ==
 +
* [https://aws.amazon.com/training/learning-paths/machine-learning/decision-maker/ Business individuals and team leaders]
 +
 
 +
<img src="https://d1.awsstatic.com/Train%20&%20Cert/Learning%20Paths/ml-path_business-decision-maker_v5.fafef41c7ea476dd5d144923e99e0931269dfe20.png" width="800" height="200">
 +
 
 +
== Data Platform Engineer ==
 +
* [https://aws.amazon.com/training/learning-paths/machine-learning/data-platform-engineer/ Data platform engineers]
  
−
Business Decision Maker...   ...Data Platform    ... Engineer Data  .... Scientist Developer
+
<img src="https://d1.awsstatic.com/training-and-certification/Learning_Paths/learning-path-ml-data-platform-engineer_march2020.34a3ad0d968ab9275f09fb9658ad0833971880c1.png" width="800" height="400">
  
−
http://d1.awsstatic.com/training-and-certification/exams_courses_icons/icon_ml-decision-maker.da2f4225ee7b53f91fbc6e1ae08cbf4c13777a0e.png
+
== Data Scientist ==
−
http://d1.awsstatic.com/training-and-certification/exams_courses_icons/icon_ml-data-platform-engineer.7cf26a6e863a1286e1f94c54a2c6493a68a6bb69.png
+
* [https://aws.amazon.com/training/learning-paths/machine-learning/data-scientist/ Learners skilled in math, statistics, and analysis]
−
http://d1.awsstatic.com/training-and-certification/roles/icon_data-scientist.0ec69c78a7db519f20247c3960f342c1325644dc.png
 
−
http://d1.awsstatic.com/training-and-certification/exams_courses_icons/icon_ml-developer.60695054f17ef19224ba3549d901ab640738a6e4.png
 
  
 +
<img src="https://d1.awsstatic.com/training-and-certification/Learning_Paths/learning-paths_ml-data-scientist_march2020.aa1bd23eb8e39e6ed369c2a435e87f171bad9504.png" width="800" height="500">
  
−
== Developers ==
+
== Developer ==
−
* [http://aws.amazon.com/training/learning-paths/machine-learning/developer/ Builders and Software Developers]
+
* [https://aws.amazon.com/training/learning-paths/machine-learning/developer/ Builders and Software Developers]
  
 +
<img src="https://d1.awsstatic.com/training-and-certification/Learning_Paths/learning-paths_ml-developer_march2020.b7bca6ba2cf5ffe563707f849ef636b3f6d5d91f.png" width="800" height="500">
  
−
http://d1.awsstatic.com/training-and-certification/Learning_Paths/learning-paths_ml-developer_march2020.b7bca6ba2cf5ffe563707f849ef636b3f6d5d91f.png
+
= AWS Summit New York City 2023 =
 +
<youtube>1PkABWCJINM</youtube>

Latest revision as of 15:10, 2 June 2024

YouTube ... Quora ...Google search ...Google News ...Bing News

_______________________________________________

Inferentia

ChatGPT AWS Inferentia is a custom-designed machine learning inference chip developed by Amazon Web Services (AWS) to accelerate deep learning workloads. The chip is specifically optimized for high performance, low latency, and cost-effective inference, which is the process of running trained machine learning models to make predictions or classifications. By using AWS Inferentia, organizations can achieve faster and more cost-effective deployment of machine learning models for a variety of applications, including image and speech recognition, natural language processing, and recommendation engines. Key features and benefits of AWS Inferentia include:

  • High Performance: Inferentia delivers high throughput and low latency, making it ideal for real-time applications. It supports multiple machine learning frameworks such as TensorFlow, PyTorch, and Apache MXNet.
  • Cost Efficiency: By providing a dedicated hardware solution for inference, Inferentia can reduce the cost of inference operations compared to using general-purpose CPUs or GPUs.
  • Compatibility: AWS Inferentia is integrated with Amazon SageMaker, AWS's fully managed machine learning service, and supports models trained on popular frameworks. This makes it easier for developers to deploy their existing models on Inferentia-based instances.
  • Scalability: It can be scaled to handle large-scale machine learning workloads, allowing users to deploy multiple models simultaneously or to serve a high volume of inference requests.
  • Availability: Inferentia-powered instances, such as the Inf1 instance type, are available on Amazon EC2. These instances are designed to provide optimal performance for inference applications.


Integrated Components/Technologies

Libraries & Frameworks


Training


Business Decision Maker... ...Data Platform Engineer... ... Data Scientist.... ..... .... Developer

icon_ml-decision-maker.da2f4225ee7b53f91fbc6e1ae08cbf4c13777a0e.png icon_ml-data-platform-engineer.7cf26a6e863a1286e1f94c54a2c6493a68a6bb69.png icon_data-scientist.0ec69c78a7db519f20247c3960f342c1325644dc.png icon_ml-developer.60695054f17ef19224ba3549d901ab640738a6e4.png


Business Decision Maker

Data Platform Engineer

Data Scientist

Developer

AWS Summit New York City 2023

Retrieved from "https://primo.ai/index.php?title=Amazon&oldid=37431"