Ai Services on AWS

Editor's Notes

• #3: אני חושב שהאתגר הכי גדול שלנו בעידן ה – Big Data הוא להבין איך אנחנו כותבים תוכנה שתוציא תובנות מאותו Data. ופה AI בא לעזרתנו....
• #4: ההגדרה הבסיסית של AI היא מערכת או שרות שמאפשרים לי לבצע משימות שעד אז דרשו התערבות אנושית, רצוי אינטליגנטית. And for us, AI is a system or service which can perform tasks that usually require human intelligence, such as visual perception, speech recognition, decision-making or translation
• #5: 1994
• #7: Today Ai is everywhere is Amazon From recommendation pages, to fulfillment centers, Prime Air Drones ***CLICK***
• #8: Amazon Go
• #10: There are lots of other examples. Machine learning is being used to filter spam emails, flag inappropriate content, personalize user experience, targeted marketing campaigns, call routing in support centers, social network monitoring, and many more.
• #11: And the result of this is that we see a ton of machine learning up on AWS today, literally from A through to Z. So everything from Ancestry, who are using machine learning and deep learning to be able to process genomic information and build out family trees, all the way through to Zillow, who use machine learning to do house-price estimation up on the website.
• #12: מצד אחד שליטה מצד שני פשטות
• #14: כל Framework פופולרי בתחום ה - AI
• #18: Amazon Rekognition currently supports the JPEG and PNG image formats. You can submit images either as an S3 object or as a byte array.Amazon Rekognition supports image file sizes up to 15MB when passed as an S3 object, and up to 5MB when submitted as an image byte array.Amazon Rekognition is currently available in US East (Northern Virginia), US West (Oregon) and EU (Ireland) regions. Mxnet convolutional deep neural networks (CNNs),
• #24: Using AWS, C-SPAN can sample a frame every six seconds for recognition against indexed faces in a database of 97,000 people. Previously, this was done manually: Indexers scrolled through screen captures to identify who was speaking at any given point and select an image to represent each individual in each video. C-SPAN expects to save 8,000 to 9,000 hours a year in labor by automating that process using Rekognition, and will be able to index 100% of its incoming footage and archives.
• #27: The basics are pretty simple, but the service has deep functionality. You can send the service a simple string of text, and it will generate the life like voice in your choice of 47 different voices. But it’s not naive of the context of the text. For example, the text here - ‘WA’ and ‘degree F’, that would sound strange if it were spoken out loud. Instead, Polly will automatically expand the text strings ‘WA’ and ‘degree F’, to ‘Washington’ and ‘degrees fahrenheit’, to create more life like speech. The developer doesn’t have to do anything - just send the text, and get life like voice back.
• #31: Speech Synthesis Markup Language (SSML) Version 1.0 The Voice Browser Working Group has sought to develop standards to enable access to the Web using spoken interaction. 
• #33: שינוי של הקולות הקיימים למקרה ומספר הקולות שיש היום לא מספיק לכם
• #42: With Lex, any application running on the web, a mobile app, or a device, can send natural language - as both text or speech - to Lex using an API or SDK. Lex will apply ASR and NLU to the incoming message to understand the intent of the user, so to understand what the question is, and map that to a Lambda function which will process the information, and…
• #43: Then form a response, which will be passed back to the user as either text, or will use Polly automatically to generate a voice response. I wont deep dive on Lex now since we have a full session dedicated to building Bots using Lex later during the day so I encourage you to go and check it out!
• #47: $0.004 per voice request, and $.00075 per text request.  1,000 speech requests would be $4.00 1,000 text requests would cost $0.75. 10,000 text requests and 5,000 speech requests – Free tier