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So no, OpenAI didn’t roll out a search engine competitor to take on Google at its May 13, 2024 Spring Update event. Instead, OpenAI unveiled GPT-4 Omni (or GPT-4o for short) with human-like conversational capabilities, and it's seriously impressive. Beyond making this version of ChatGPT faster and free to more folks, GPT-4o expands how you can interact with it, including having natural conversations via the mobile or desktop app. Considering it's arriving on iPhone, Android, and desktop apps, it might pave the way to be the assistant we've all always wanted (or feared). OpenAI's ChatGPT-4o is more emotional and human-like OpenAI demoing GPT-4o on an iPhone during the Spring Update event. (Image credit: OpenAI) GPT-4o has taken a significant step towards understanding human communication in that you can converse in something approaching a natural manner. It comes complete with all the messiness of real-world tendencies like interrupting, understanding tone, and even realizing it's made a mistake. During the first live demo, the presenter asked for feedback on his breathing technique. He breathed heavily into his phone, and ChatGPT responded with the witty quip, “You’re not a vacuum cleaner.” It advised on a slower technique, demonstrating its ability to understand and respond to human nuances. So yes, ChatGPT has a sense of humor but also changes the tone of responses, complete with different inflections while conveying a "thought." Like human conversations, you can cut the assistant off and correct it, making it react or stop speaking. You can even ask it to speak in a certain tone, style, or robotic voice. Furthermore, it can even provide translations. In a live demonstration suggested by a user on X (formerly Twitter), two presenters on stage, one speaking English and one speaking Italian, had a conversation with Chat GPT-4o handling translation. It could quickly deliver the translation from Italian to English and then seamlessly translate the English response back to Italian. It’s not just voice understanding with GPT-4o, though; it can also understand visuals like a written-out linear equation and then guide you through how to solve it, as well as look at a live selfie and provide a description. That could be what you're wearing or your emotions. In this demo, GPT said the presenter looked happy and cheerful. It’s not without quirks, though. At one point, ChatGPT said it saw the image of the equation before it was even written out, referring back to a previous visual of just a wooden tabletop. Throughout the demo, ChatGPT worked quickly and didn't really struggle to understand the problem or ask about it. GPT-4o is also more natural than typing in a query, as you can speak naturally to your phone and get a desired response – not one that tells you to Google it. A little like "Samantha" in "Her" If you’re thinking about Her or another futuristic-dystopian film with an AI, you’re not the only one. Speaking with ChatGPT in such a natural way is essentially the Her moment for OpenAI. Considering it will be rolling out to the mobile app and as a desktop app for free, many people may soon have their own Her moments. The impressive demos across speech and visuals may only be scratching the surface of what's possible. Overall performance and how well GPT-4o performs day-to-day in various environments remain to be seen, and once available, TechRadar will be putting it through the test. Still, after this peek, it's clear that GPT-4o is preparing to take on the best Google and Apple have to offer in their eagerly-anticipated AI reveals. The outlook on GPT-4o However, announcing this the day before Google I/O kicks off and just a few weeks after we’ve seen new AI gadgets hit the scene – like the Rabbit R1 – OpenAI is giving us a taste of the truly useful AI experiences we want. If this rumored partnership with Apple comes to fruition, Siri could be supercharged, and Google will almost certainly show off its latest AI tricks at I/O on May 14, 2024. But will they be enough? We wish OpenAI showed off a bit more live demos with the latest ChatGPT-4o in what turned out to be a jam-packed, less-than-30-minute keynote. Luckily, it will be rolling out to users in the coming week, and you won’t have to pay to try it out. You Might Also Like Microsoft launches generative AI model designed exclusively for US ...What is AI? Everything you need to know about Artificial Intelligence ...OpenAI will now transcribe notes from your doctor ... View the full article
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Since I’ve been working with Azure OpenAI Service from a developer perspective as well, I’ve decided to build a sample application to help demonstrate not just the IaC deployment of Azure OpenAI Service and GPT models, but also to demonstrate some basic use cases of integrating AI into your own enterprise applications. Here’s a screenshot […] The article Introducing AIChatUI: Open Source AI Chat Sample with Azure OpenAI Service & GPT-3 / GPT-4 appeared first on Build5Nines. View the full article
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Sora fans just learned a hard lesson: filmmakers will be filmmakers and will do what's necessary to make their creations as convincing and eye-popping as possible. But if this made them think less of OpenAI's generative AI video platform, they're wrong. When OpenAI handed an early version of the generative Video AI platform to a bunch of creatives, one team – Shy Kids – created an unforgettable video of a man with a yellow balloon for a head. Many declared Air Head to be a weird and powerful breakthrough, but a behind-the-scenes video has cast a rather different spin on it. And it turns out that as good as Sora is at generating video from test prompts, there were many things that the platform either couldn't do or didn't produce just as the filmmakers wanted. The video's post-production editor Patrick Cederberg offered, in an interview with FxGuide, a lengthy list of changes Cederberg's team made to Sora's output to create the stunning effects we saw in the final, 1-minute, 22-second Air Head video. Sora's developers, for instance, included no understanding of typical film shots like panning, tracking, and zooming, so the team sometimes had to create a pan and tilt shot out of the existing more static clip. Plus, while Sora is capable of outputting lengthy videos based on long text prompts, there is no guarantee that the subjects in each prompt will remain consistent from one output clip to another. It took considerable work and experimentation in prompts to get videos that connected disparate shots into a semi-connected whole. As Cederberg notes in an Air Head Behind the Scenes video "What ultimately you're seeing took work time and human hands to get it looking semi-consistent." The balloon head sounds particularly challenging, as Sora understands the idea of a balloon but doesn't base its output on, say, an individual video or photo of a balloon. In Sora's original idea, every balloon had a sting attached; Cederberg's team had to paint that out of each frame. More frustratingly, Sora often wanted to put the impression (see above), outline, or drawing of a face on the balloons. And while the final video features a yellow balloon in each shot, the Sora output usually had different balloon colors that Shy Kids would adjust in post. Shy Kids told FxGuide that all the video they used is Sora output, it's just that if they had used the video untouched, the film would've lacked the continuity and cohesion of the final, wistful product. This is good news Does this news turn the charming Shy Kids video into Sora's Milkshake Duck? Not necessarily. If you look at some of the unretouched videos and images in the Behind the Scenes video, they're still remarkable and while post-production was necessary, Shy Kids never shot a single bit of real film to produce the initial images and video. Even as AI innovation races forward and we see huge generational leaps as often as every three months, AI of almost any stripe is far from perfect. ChatGPT's responses are usually accurate, but can still miss the context and get basic facts wrong. With text-to-imagery, the results are even more varied because, unlike AI-generated text response – which can use fact-based sources and mostly predicts the right next word – generative imaging base their output on a representation of that idea or concept. That's particularly true of diffusion models that use training information to figure out what something should look like, which means that output can vary wildly from image to image. "It's not as easy as a magic trick: type something in and get exactly what you're hoping for," Shy Kids Producer Syndey Leeder says in the Behind the Scenes video. These models may have a general idea of what a balloon or person looks like. Asking such a system to imagine a man on a bike six times will get you six different results. They may all look good, but it's unlikely the man or bicycle will be the same in every image. Video generation likely compounds the issue, with the odds of maintaining scene and image consistency across thousands of frames and from clip to clip extremely low. With that in mind, Shy Kids' accomplishment is even more noteworthy. Air Heads manages to maintain both the otherworldliness of an AI video and a cinematic essence. This is how AI should work Automation doesn't mean the complete removal of human intervention. This is as true for videos as it is on the factory floor, where the introduction of robots has not meant people-free production. I vividly recall Elon Musk's efforts to automate as much of the Tesla Model 3's production as possible. It was a near disaster and production went more smoothly when he added back the humanity. A creative process such as filmmaking or production will always require the human touch. Shy Kids needed an idea before they could start feeding it to Sora. And when Sora didn't understand their intentions, they had to adjust the output by hand. As most creative endeavors do, it became a partnership, one where the accomplished Sora AI provided a tremendous shortcut, but one that still didn't take the project to completion. Instead of bursting Air Head's bubble, these revelations remind us that the marriage of traditional media and AI still requires a human's guiding hand and that's unlikely to change – at least for the time being. 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Apple is once again talking with OpenAI about using OpenAI technology to power artificial intelligence features in iOS 18, reports Bloomberg's Mark Gurman. Apple held talks with OpenAI earlier in the year, but nothing had come of the discussion. Apple and OpenAI are now said to be speaking about the terms of a possible agreement and how Apple might utilize OpenAI features. Along with OpenAI, Apple is still having discussions with Google about licensing Google's Gemini AI. Apple has not come to a final decision, and Gurman suggests that the company could partner with both Google and OpenAI or pick another provider entirely. Rumors suggest that iOS 18 will have a major focus on AI, with Apple set to introduce AI functionality across the operating system. Apple CEO Tim Cook confirmed in February that Apple plans to "break new ground" in AI. We'll get a first look at the AI features that Apple has planned in just over a month, with iOS 18 set to debut at the Worldwide Developers Conference that kicks off on June 10.Related Roundup: iOS 18Tag: Apple GPT This article, "Apple Reignites Talks With OpenAI About Generative AI for iOS 18" first appeared on MacRumors.com Discuss this article in our forums View the full article
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Introduction APIs are the key to implementing microservices that are the building blocks of modern distributed applications. Launching a new API involves defining the behavior, implementing the business logic, and configuring the infrastructure to enforce the behavior and expose the business logic. Using OpenAPI, the AWS Cloud Development Kit (AWS CDK), and AWS Solutions Constructs to build your API lets you focus on each of these tasks in isolation, using a technology specific to each for efficiency and clarity. The OpenAPI specification is a declarative language that allows you to fully define a REST API in a document completely decoupled from the implementation. The specification defines all resources, methods, query strings, request and response bodies, authorization methods and any data structures passed in and out of the API. Since it is decoupled from the implementation and coded in an easy-to-understand format, this specification can be socialized with stakeholders and developers to generate buy-in before development has started. Even better, since this specification is in a machine-readable syntax (JSON or YAML), it can be used to generate documentation, client code libraries, or mock APIs that mimic an actual API implementation. An OpenAPI specification can be used to fully configure an Amazon API Gateway REST API with custom AWS Lambda integration. Defining the API in this way automates the complex task of configuring the API, and it offloads all enforcement of the API details to API Gateway and out of your business logic. The AWS CDK provides a programming model above the static AWS CloudFormation template, representing all AWS resources with instantiated objects in a high-level programming language. When you instantiate CDK objects in your Typescript (or other language) code, the CDK “compiles” those objects into a JSON template, then deploys that template with CloudFormation. I’m not going to spend a lot of time extolling the many virtues of the AWS CDK here, suffice it to say that the use of programming languages such as Typescript or Python rather than the declarative YAML or JSON allows much more flexibility in defining your infrastructure. AWS Solutions Constructs is a library of common architectural patterns built on top of the AWS CDK. These multi-service patterns allow you to deploy multiple resources with a single CDK Construct. Solutions Constructs follow best practices by default – both for the configuration of the individual resources as well as their interaction. While each Solutions Construct implements a very small architectural pattern, they are designed so that multiple constructs can be combined by sharing a common resource. For instance, a Solutions Construct that implements an Amazon Simple Storage Service (Amazon S3) bucket invoking a Lambda function can be deployed with a second Solutions Construct that deploys a Lambda function that writes to an Amazon Simple Queue Service (Amazon SQS) queue by sharing the same Lambda function between the two constructs. You can compose complex architectures by connecting multiple Solutions Constructs together, as you will see in this example. Infrastructure as Code Abstraction Layers In this article, you will build a robust, functional REST API based on an OpenAPI specification using the AWS CDK and AWS Solutions Constructs. How it Works This example is a microservice that saves and retrieves product orders. The behavior will be fully defined by an OpenAPI specification and will include the following methods: Method Functionality Authorization POST /order Accepts order attributes included in the request body. Returns the orderId assigned to the new order. AWS Identity and Access Management (IAM) GET /order/$(orderId} Accepts an orderId as a path parameter. Returns the fully populated order object. IAM The architecture implementing the service is shown in the diagram below. Each method will integrate with a Lambda function that implements the interactions with an Amazon DynamoDB table. The API will be protected by IAM authorization and all input and output data will be verified by API Gateway. All of this will be fully defined in an OpenAPI specification that is used to configure the REST API. The Two Solutions Constructs Making up the Service Architecture Infrastructure as code will be implemented with the AWS CDK and AWS Solutions Constructs. This example uses 2 Solutions Constructs: aws-lambda-dynamodb – This construct “connects” a Lambda function and a DynamoDB table. This entails giving the Lambda function the minimum IAM privileges to read and write from the table and providing the DynamoDB table name to the Lambda function code with an environment variable. A Solutions Constructs pattern will create its resources based on best practices by default, but a client can also provide construct properties to override the default behaviors. A client can also choose not to have the pattern create a new resource by providing a resource that already exists. aws-openapigateway-lambda – This construct deploys a REST API on API Gateway configured by the OpenAPI specification, integrating each method of the API with a Lambda function. The OpenAPI specification is stored as an asset in S3 and referenced by the CloudFormation template rather than embedded in the template. When the Lambda functions in the stack have been created, a custom resource processes the OpenAPI asset and updates all the method specifications with the arn of the associated Lambda function. An API can point to multiple Lambda functions, or a Lambda function can provide the implementation for multiple methods. In this example you will create the aws-lambda-dynamodb construct first. This construct will create your Lambda function, which you then supply as an existing resource to the aws-openapigateway-lambda constructor. Sharing this function between the constructs will unite the two small patterns into a complete architecture. Prerequisites To deploy this example, you will need the following in your development environment: Node.js 18.0.0 or later Typescript 3.8 or later (npm -g install typescript) AWS CDK 2.82.0 or later (npm install -g aws-cdk && cdk bootstrap) The cdk bootstrap command will launch an S3 bucket and other resources that the CDK requires into your default region. You will need to bootstrap your account using a role with sufficient privileges – you may require an account administrator to complete that command. Tip – While AWS CDK. 2.82.0 is the minimum required to make this example work, AWS recommends regularly updating your apps to use the latest CDK version. To deploy the example stack, you will need to be running under an IAM role with the following privileges: Create API Gateway APIs Create IAM roles/policies Create Lambda Functions Create DynamoDB tables GET/POST methods on API Gateway AWSCloudFormationFullAccess (managed policy) Build the App Somewhere on your workstation, create an empty folder named openapi-blog with these commands: mkdir openapi-blog && cd openapi-blog Now create an empty CDK application using this command: cdk init -l=typescript The application is going to be built using two Solutions Constructs, aws-openapigateway-lambda and aws-lambda-dynamodb. Install them in your application using these commands: npm install @aws-solutions-constructs/aws-openapigateway-lambda npm install @aws-solutions-constructs/aws-lambda-dynamodb Tip – if you get an error along the lines of npm ERR! Could not resolve dependency and npm ERR! peer aws-cdk-lib@"^2.130.0", then you’ve installed a version of Solutions Constructs that depends on a newer version of the CDK. In package.json, update the aws-cdk-lib and aws-cdk dependencies to be the version in the peer error and run npm install. Now try the above npm install commands again. The OpenAPI REST API specification will be in the api/openapi-blog.yml file. It defines the POST and GET methods, the format of incoming and outgoing data and the IAM Authorization for all HTTP calls. Create a folder named api under openapi-blog. Within the api folder, create a file called openapi-blog.yml with the following contents: --- openapi: 3.0.2 info: title: openapi-blog example version: '1.0' description: 'defines an API with POST and GET methods for an order resource' # x-amazon-* values are OpenAPI extensions to define API Gateway specific configurations # This section sets up 2 types of validation and defines params-only validation # as the default. x-amazon-apigateway-request-validators: all: validateRequestBody: true validateRequestParameters: true params-only: validateRequestBody: false validateRequestParameters: true x-amazon-apigateway-request-validator: params-only paths: "/order": post: x-amazon-apigateway-auth: type: AWS_IAM x-amazon-apigateway-request-validator: all summary: Create a new order description: Create a new order x-amazon-apigateway-integration: httpMethod: POST # "OrderHandler" is a placeholder that aws-openapigateway-lambda will # replace with the Lambda function when it is available uri: OrderHandler passthroughBehavior: when_no_match type: aws_proxy requestBody: description: Create a new order content: application/json: schema: "$ref": "#/components/schemas/OrderAttributes" required: true responses: '200': description: Successful operation content: application/json: schema: "$ref": "#/components/schemas/OrderObject" "/order/{orderId}": get: x-amazon-apigateway-auth: type: AWS_IAM summary: Get Order by ID description: Returns order data for the provided ID x-amazon-apigateway-integration: httpMethod: POST # "OrderHandler" is a placeholder that aws-openapigateway-lambda will # replace with the Lambda function when it is available uri: OrderHandler passthroughBehavior: when_no_match type: aws_proxy parameters: - name: orderId in: path required: true schema: type: integer format: int64 responses: '200': description: successful operation content: application/json: schema: "$ref": "#/components/schemas/OrderObject" '400': description: Bad order ID '404': description: Order ID not found components: schemas: OrderAttributes: type: object additionalProperties: false required: - productId - quantity - customerId properties: productId: type: string quantity: type: integer format: int32 example: 7 customerId: type: string OrderObject: allOf: - "$ref": "#/components/schemas/OrderAttributes" - type: object additionalProperties: false required: - id properties: id: type: string Most of the fields in this OpenAPI definition are explained in the OpenAPI specification, but the fields starting with x-amazon- are unique extensions for configuring API Gateway. In this case x-apigateway-auth values stipulate that the methods be protected with IAM authorization; the x-amazon-request-validator values tell the API to validate the request parameters by default and the parameters and request body when appropriate; and the x-amazon-apigateway-integration section defines the custom integration of the method with a Lambda function. When using the Solutions Construct, this field does not identify the specific Lambda function, but instead has a placeholder string (“OrderHandler”) that will be replaced with the correct function name during the launch. While the API will accept and validate requests, you’ll need some business logic to actually implement the functionality. Let’s create a Lambda function with some rudimentary business logic: Create a folder structure lambda/order under openapi-blog. Within the order folder, create a file called index.js . Paste the code from this file into your index.js file. Our Lambda function is very simple, consisting of some relatively generic SDK calls to Dynamodb. Depending upon the HTTP method passed in the event, it either creates a new order or retrieves (and returns) an existing order. Once the stack loads, you can check out the IAM role associated with the Lambda function and see that the construct also created a least privilege policy for accessing the table. When the code is written, the DynamoDB table name is not known, but the aws-lambda-dynamodb construct creates an environment variable with the table name that will do nicely: // Excerpt from index.js // Get the table name from the Environment Variable set by aws-lambda-dynamodb const orderTableName = process.env.DDB_TABLE_NAME; Now that the business logic and API definition are included in the project, it’s time to add the AWS CDK code that will launch the application resources. Since the API definition and your business logic are the differentiated aspects of your application, it would be ideal if the infrastructure to host your application could deployed with a minimal amount of code. This is where Solutions Constructs help – perform the following steps: Open the lib/openapi-blog-stack.ts file. Replace the contents with the following: import * as cdk from 'aws-cdk-lib'; import { Construct } from 'constructs'; import { OpenApiGatewayToLambda } from '@aws-solutions-constructs/aws-openapigateway-lambda'; import { LambdaToDynamoDB } from '@aws-solutions-constructs/aws-lambda-dynamodb'; import { Asset } from 'aws-cdk-lib/aws-s3-assets'; import * as path from 'path'; import * as lambda from 'aws-cdk-lib/aws-lambda'; import * as ddb from 'aws-cdk-lib/aws-dynamodb'; export class OpenapiBlogStack extends cdk.Stack { constructor(scope: Construct, id: string, props?: cdk.StackProps) { super(scope, id, props); // This application is going to use a very simple DynamoDB table const simpleTableProps = { partitionKey: { name: "Id", type: ddb.AttributeType.STRING, }, // Not appropriate for production, this setting is to ensure the demo can be easily removed removalPolicy: cdk.RemovalPolicy.DESTROY }; // This Solutions Construct creates the Orders Lambda function // and configures the IAM policy and environment variables "connecting" // it to a new Dynamodb table const orderApparatus = new LambdaToDynamoDB(this, 'Orders', { lambdaFunctionProps: { runtime: lambda.Runtime.NODEJS_18_X, handler: 'index.handler', code: lambda.Code.fromAsset(`lambda/order`), }, dynamoTableProps: simpleTableProps }); // This Solutions Construct creates and configures the REST API, // integrating it with the new order Lambda function created by the // LambdaToDynamomDB construct above const newApi = new OpenApiGatewayToLambda(this, 'OpenApiGatewayToLambda', { // The OpenAPI is stored as an S3 asset where it can be accessed during the // CloudFormation Create Stack command apiDefinitionAsset: new Asset(this, 'ApiDefinitionAsset', { path: path.join(`api`, 'openapi-blog.yml') }), // The construct uses these records to integrate the methods in the OpenAPI spec // to Lambda functions in the CDK stack apiIntegrations: [ { // These ids correspond to the placeholder values for uri in the OpenAPI spec id: 'OrderHandler', existingLambdaObj: orderApparatus.lambdaFunction } ] }); // We output the URL of the resource for convenience here new cdk.CfnOutput(this, 'OrderUrl', { value: newApi.apiGateway.url + 'order', }); } } Notice that the above code to create the infrastructure is only about two dozen lines. The constructs provide best practice defaults for all the resources they create, you just need to provide information unique to the use case (and any values that must override the defaults). For instance, while the LambdaToDynamoDB construct defines best practice default properties for the table, the client needs to provide at least the partition key. So that the demo cleans up completely when we’re done, there’s a removalPolicy property that instructs CloudFormation to delete the table when the stack is deleted. These minimal table properties and the location of the Lambda function code are all you need to provide to launch the LambdaToDynamoDB construct. The OpenApiGatewayToLambda construct must be told where to find the OpenAPI specification and how to integrate with the Lambda function(s). The apiIntegrations property is a mapping of the placeholder strings used in the OpenAPI spec to the Lambda functions in the CDK stack. This code maps OrderHandler to the Lambda function created by the LambdaToDynamoDB construct. APIs integrating with more than one function can easily do this by creating more placeholder strings. Ensure all files are saved and build the application: npm run build Launch the CDK stack: cdk deploy You may see some AWS_SOLUTIONS_CONSTRUCTS_WARNING:‘s here, you can safely ignore them in this case. The CDK will display any IAM changes before continuing – allowing you to review any IAM policies created in the stack before actually deploying. Enter ‘Y’ [Enter] to continue deploying the stack. When the deployment concludes successfully, you should see something similar to the following output: ... OpenapiBlogStack: deploying... [1/1] OpenapiBlogStack: creating CloudFormation changeset... OpenapiBlogStack Deployment time: 97.78s Outputs: OpenapiBlogStack.OpenApiGatewayToLambdaSpecRestApiEndpointD1FA5E3A = https://b73nx617gl.execute-api.us-east-1.amazonaws.com/prod/ OpenapiBlogStack.OrderUrl = https://b73nx617gl.execute-api.us-east-1.amazonaws.com/prod/order Stack ARN: arn:aws:cloudformation:us-east-1:123456789012:stack/OpenapiBlogStack/01df6970-dc05-11ee-a0eb-0a97cfc33817 Total time: 100.07s Test the App Let’s test the new REST API using the API Gateway management console to confirm it’s working as expected. We’ll create a new order, then retrieve it. Open the API Gateway management console and click on APIs in the left side menu Find the new REST API in the list of APIs, it will begin with OpenApiGatewayToLambda and have a Created date of today. Click on it to open it. On the Resources page that appears, click on POST under /order. In the lower, right-hand panel, select the Test tab (if the Test tab is not shown, click the arrow to shift the displayed tabs). The POST must include order data in the request body that matches the OrderAttributes schema defined by the OpenAPI spec. Enter the following data in the Request body field: { "productId": "prod234232", "customerId": "cust203439", "quantity": 5 } Click the orange Test button at the bottom of the page. The API Gateway console will display the results of the REST API call. Key things to look for are a Status of 200 and a Response Body resembling “{\"id\":\"ord1712062412777\"}" (this is the id of the new order created in the system, your value will differ). You could go to the DynamoDB console to confirm that the new order exists in the table, but it will be more fun to check by querying the API. Use the GET method to confirm the new order was persisted: Copy the id value from the Response body of the POST call – "{\"id\":\"ord1712062412777\"}" Tip – select just the text between the \” patterns (don’t select the backslash or quotation marks). Select the GET method under /{orderId} in the resource list. Paste the orderId you copied earlier into the orderId field under Path. Click Test – this will execute the GET method and return the order you just created. You should see a Status of 200 and a Response body with the full data from the Order you created in the previous step: "{\"id\":\"ord1712062412777\",\"productId\":\"prod234232\",\"quantity\":\"5\",\"customerId\":\"cust203439\"}" Let’s see how API Gateway is enforcing the inputs of the API. Let’s go back to the POST method and intentionally send an incorrect set of Order attributes. Click on POST under /order In the lower, right-hand panel, select the Test tab. Enter the following data in the Request body field: { "productId": "prod234232", "customerId": "cust203439", "quality": 5 } Click the orange Test button at the bottom of the page. Now you should see an HTTP error status of 400, and a Response body of {"message": "Invalid request body"}. Note that API Gateway caught the error, not any code in your Lambda function. In fact, the Lambda function was never invoked (you can take my word for it, or you can check for yourself on the Lambda management console). Because you’re invoking the methods directly from the console, you are circumventing the IAM authorization. If you would like to test the API with an IAM authorized call from a client, this video includes excellent instruction on how to accomplish this from Postman. Cleanup To clean up the resources in the stack, run this command: cdk destroy In response to Are you sure you want to delete: OpenApiBlogStack (y/n)? you can type y (once again you can safely ignore the warnings here). Conclusion Defining your API in a standalone definition file decouples it from your implementation, provides documentation and client benefits, and leads to more clarity for all stakeholders. Using that definition to configure your REST API in API Gateway creates a robust API that offloads enforcement of the API from your business logic to your tooling. Configuring a REST API that fully utilizes the functionality of API Gateway can be a daunting challenge. Defining the API behavior with an OpenAPI specification, then implementing that API using the AWS CDK and AWS Solutions Constructs, accelerates and simplifies that effort. The CloudFormation template that eventually launched this API is over 1200 lines long – yet with AWS CDK and AWS Solutions Constructs you were able generate this template with ~25 lines of Typescript. This is just one example of how Solutions Constructs enable developers to rapidly produce high quality architectures with the AWS CDK. At this writing there are 72 Solutions Constructs covering 29 AWS services – take a moment to browse through what’s available on the Solutions Constructs site. Introducing these in your CDK stacks accelerates your development, jump starts your journey towards being well-architected, and helps keep you well-architected as best practices and technologies evolve in the future. About the Author Biff Gaut has been shipping software since 1983, from small startups to large IT shops. Along the way he has contributed to 2 books, spoken at several conferences and written many blog posts. He’s been with AWS for 10+years and is currently a Principal Engineer working on the AWS Solutions Constructs team, helping customers deploy better architectures more quickly. View the full article
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OpenAI's new Sora text-to-video generation tool won't be publicly available until later this year, but in the meantime it's serving up some tantalizing glimpses of what it can do – including a mind-bending new video (below) showing what TED Talks might look like in 40 years. To create the FPV drone-style video, TED Talks worked with OpenAI and the filmmaker Paul Trillo, who's been using Sora since February. The result is an impressive, if slightly bewildering, fly-through of futuristic conference talks, weird laboratories and underwater tunnels. The video again shows both the incredible potential of OpenAI Sora and its limitations. The FPV drone-style effect has become a popular one for hard-hitting social media videos, but it traditionally requires advanced drone piloting skills and expensive kit that goes way beyond the new DJI Avata 2. Sora's new video shows that these kind of effects could be opened up to new creators, potentially at a vastly lower cost – although that comes with the caveat that we don't yet know how much OpenAI's new tool itself will cost and who it'll be available to. What will TED look like in 40 years? For #TED2024, we worked with artist @PaulTrillo and @OpenAI to create this exclusive video using Sora, their unreleased text-to-video model. Stay tuned for more groundbreaking AI — coming soon to https://t.co/YLcO5Ju923! pic.twitter.com/lTHhcUm4FiApril 19, 2024 See more But the video (above) also shows that Sora is still quite far short of being a reliable tool for full-blown movies. The people in the shots are on-screen for only a couple of seconds and there's plenty of uncanny valley nightmare fuel in the background. The result is an experience that's exhilarating, while also leaving you feeling strangely off-kilter – like touching down again after a sky dive. Still, I'm definitely keen to see more samples as we hurtle towards Sora's public launch later in 2024. How was the video made? (Image credit: OpenAI / TED Talks) OpenAI and TED Talks didn't go into detail about how this specific video was made, but its creator Paul Trillo recently talked more broadly about his experiences of being one of Sora's alpha tester. Trillo told Business Insider about the kinds of prompts he uses, including "a cocktail of words that I use to make sure that it feels less like a video game and something more filmic". Apparently these include prompts like "35 millimeter", "anamorphic lens", and "depth of field lens vignette", which are needed or else Sora will "kind of default to this very digital-looking output". Right now, every prompt has to go through OpenAI so it can be run through its strict safeguards around issues like copyright. One of Trillo's most interesting observations is that Sora is currently "like a slot machine where you ask for something, and it jumbles ideas together, and it doesn't have a real physics engine to it". This means that it's still a long way way off from being truly consistent with people and object states, something that OpenAI admitted in an earlier blog post. OpenAI said that Sora "currently exhibits numerous limitations as a simulator", including the fact that "it does not accurately model the physics of many basic interactions, like glass shattering". These incoherencies will likely limit Sora to being a short-form video tool for some time, but it's still one I can't wait to try out. You might also like OpenAI just gave artists access to Sora and proved the AI video tool is weirder and more powerful than we thoughtOpenAI's new voice synthesizer can copy your voice from just 15 seconds of audioElon Musk might be right about OpenAI — but that doesn't mean he should win View the full article
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Let’s learn all the useful services from the OpenAI.View the full article
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OpenAI CEO Sam Altman and former Apple design chief Jony Ive have officially teamed up to design an AI-powered personal device and are seeking funding, reports The Information. Little is known about the AI device at this time, but it won't look like a smartphone. Altman is a major investor in the Humane AI pin, a wearable AI device that does not have a screen, so it's possible he will create a similar product with Ive. News of a possible partnership between Ive and Altman first surfaced last fall, but talks were in the early stages and nothing was official then. Ive and Altman's unnamed startup is now sourcing funds from major venture capitalists, with Ive aiming to raise up to $1 billion in funding. OpenAI could own a piece of the business, and the duo has also been in talks with SoftBank CEO Masayoshi Son. Potential investors include Thrive Capital, an OpenAI investor, and Emerson Collective, a venture capital firm and philanthropic organization founded by Laurene Powell Jobs. Ive left his role as Apple design chief in 2019, and while he still worked with the Cupertino company as a consultant for several years after through his firm LoveFrom, Ive and Apple stopped working together entirely in 2022.Tags: Artificial Intelligence, Jony Ive, OpenAI This article, "Jony Ive and OpenAI's Sam Altman Seeking Funding for Personal AI Device" first appeared on MacRumors.com Discuss this article in our forums View the full article
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OpenAI recently published a music video for the song Worldweight by August Kamp made entirely by their text-to-video engine, Sora. You can check out the whole thing on the company’s official YouTube channel and it’s pretty trippy, to say the least. Worldweight consists of a series of short clips in a wide 8:3 aspect ratio featuring fuzzy shots of various environments. You see a cloudy day at the beach, a shrine in the middle of a forest, and what looks like pieces of alien technology. The ambient track coupled with the footage results in a uniquely ethereal experience. It’s half pleasant and half unsettling. It’s unknown what text prompts were used on Sora; Kamp didn’t share that information. But she did explain the inspiration behind them in the description. She states that whenever she created the track, she imagined what a video representing Worldweight would look like. However, she lacked a way to share her thoughts. Thanks to Sora, this is no longer an issue as the footage displays what she had always envisioned. It's "how the song has always ‘looked’” from her perspective. Embracing Sora If you pay attention throughout the entire runtime, you’ll notice hallucinations. Leaves turn into fish, bushes materialize out of nowhere, and flowers have cameras instead of petals. But because of the music’s ethereal nature, it all fits together. Nothing feels out of place or nightmare-inducing. If anything, the video embraces the nightmares. We should mention August Kamp isn’t the only person harnessing Sora for content creation. Media production company Shy Kids recently published a short film on YouTube called “Air Head” which was also made on the AI engine. It plays like a movie trailer about a man who has a balloon for a head. Analysis: Lofty goals It's hard to say if Sora will see widespread adoption judging by this content. Granted, things are in the early stages, but ready or not, that hasn't stopped OpenAI from pitching its tech to major Hollywood studios. Studio executives are apparently excited at the prospects of AI saving time and money on production. August Kamp herself is a proponent of the technology stating, “Being able to build and iterate on cinematic visuals intuitively has opened up categorically new lanes of artistry for me”. She looks forward to seeing “what other forms of storytelling” will appear as artificial intelligence continues to grow. In our opinion, tools such Sora will most likely enjoy a niche adoption among independent creators. Both Kamp and Shy Kids appear to understand what the generative AI can and cannot do. They embrace the weirdness, using it to great effect in their storytelling. Sora may be great at bringing strange visuals to life, but in terms of making “normal-looking content”, that remains to be seen. People still talk about how weird or nightmare-inducing content made by generative AI is. Unless OpenAI can surmount this hurdle, Sora may not amount to much beyond niche usage. It’s still unknown when Sora will be made publicly available. OpenAI is holding off on a launch, citing potential interference in global elections as one of its reasons. Although, there are plans to release the AI by the end of 2024. If you're looking for other platforms, check out TechRadar's list of the best AI video makers for 2024. You might also like OpenAI's new voice synthesizer can copy your voice from just 15 seconds of audioElon Musk might be right about OpenAI — but that doesn't mean he should winGoogle isn’t done trying to demonstrate Gemini’s genius and is working on integrating it directly into Android devices View the full article
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Picus Security today added an artificial intelligence (AI) capability to enable cybersecurity teams to automate tasks via a natural language interface. The capability, enabled by OpenAI, leverages the existing knowledge graph technologies from Picus Security. Dubbed Picus Numi AI, the company is making use of a large language model (LLM) developed by Open AI to.. The post Picus Security Melds Security Knowledge Graph with Open AI LLM appeared first on Security Boulevard. View the full article
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OpenAI has been rapidly developing its ChatGPT generative AI chatbot and Sora AI video creator over the last year, and it's now got a new artificial intelligence tool to show off: Voice Generation, which can create synthetic voices from just 15 seconds of audio. In a blog post (via The Verge), OpenAI says it's been running "a small-scale preview" of Voice Engine, which has been in development since late 2022. It's actually already being used in the Read Aloud feature in the ChatGPT app, which (as the name suggests) reads out answers to you. Once you've trained the voice from a 15-second sample, you can then get it to read out any text you like, in an "emotive and realistic" way. OpenAI says it could be used for educational purposes, for translating podcasts into new languages, for reaching remote communities, and for supporting people who are non-verbal. This isn't something everyone can use right now, but you can go and listen to the samples created by Voice Engine. The clips OpenAI has published sound pretty impressive, though there is a slight robotic and stilted edge to them. Safety first Voice Engine is already used in ChatGPT's Read Aloud feature (Image credit: OpenAI) Worries about misuse are the main reason Voice Engine is only in a limited preview for now: OpenAI says it wants to do more research into how it can protect tools like this from being used to spread misinformation and copy voices without consent. "We hope to start a dialogue on the responsible deployment of synthetic voices, and how society can adapt to these new capabilities," says OpenAI. "Based on these conversations and the results of these small scale tests, we will make a more informed decision about whether and how to deploy this technology at scale." With major elections due in both the US and UK this year, and generative AI tools getting more advanced all the time, it's a concern across every type of AI content – audio, text, and video – and it's getting increasingly difficult to know what to trust. As OpenAI itself points out, this has the potential to cause problems with voice authentication measures, and scams where you might not know who you're talking to over the phone, or who's left you a voicemail. These aren't easy issues to solve – but we're going to have to find ways to deal with them. You might also like OpenAI's rumored Google rival could soon change how we search Sora is weirder and more powerful than we thought OpenAI is looking to build a giant AI chip empire to power its tools View the full article
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A man with a balloon for a head is somehow not the weirdest thing you'll see today thanks to a series of experimental video clips made by seven artists using OpenAI's Sora generative video creation platform. Unlike OpenAI's ChatGPT AI chatbot and the DALL-E image generation platform, the company's text-to-video tool still isn't publicly available. However, on Monday, OpenAI revealed it had given Sora access to "visual artists, designers, creative directors, and filmmakers" and revealed their efforts in a "first impressions" blog post. While all of the films ranging in length from 20 seconds to a minute-and-a-half are visually stunning, most are what you might describe as abstract. OpenAI's Artist In Residence Alex Reben's 20-second film is an exploration of what could very well be some of his sculptures (or at least concepts for them), and creative director Josephine Miller's video depicts models melded with what looks like translucent stained glass. Not all the videos are so esoteric. OpenAI Sora AI-generated video image by Don Allen Stevenson III (Image credit: OpenAI sora / Don Allen Stevenson III) If we had to give out an award for most entertaining, it might be multimedia production company shy kids' "Air Head". It's an on-the-nose short film about a man whose head is a hot-air-filled yellow balloon. It might remind you of an AI-twisted version of the classic film, The Red Balloon, although only if you expected the boy to grow up and marry the red balloon and...never mind. Sora's ability to convincingly merge the fantastical balloon head with what looks like a human body and a realistic environment is stunning. As shy kids' Walter Woodman noted, “As great as Sora is at generating things that appear real, what excites us is its ability to make things that are totally surreal." And yes, it's a funny and extremely surreal little movie. But wait, it gets stranger. The other video that will have you waking up in the middle of the night is digital artist Don Allen Stevenson III's "Beyond Our Reality," which is like a twisted National Geographic nature film depicting never-before-seen animal mergings like the Girafflamingo, flying pigs, and the Eel Cat. Each one looks as if a mad scientist grabbed disparate animals, carved them up, and then perfectly melded them to create these new chimeras. OpenAI and the artists never detail the prompts used to generate the videos, nor the effort it took to get from the idea to the final video. Did they all simply type in a paragraph describing the scene, style, and level of reality and hit enter, or was this an iterative process that somehow got them to the point where the man's balloon head somehow perfectly met his shoulders or the Bunny Armadillo transformed from grotesque to the final, cute product? That OpenAI has invited creatives to take Sora for a test run is not surprising. It's their livelihoods in art, film, and animation that are most at risk from Sora's already impressive capabilities. Most seem convinced it's a tool that can help them more quickly develop finished commercial products. "The ability to rapidly conceptualize at such a high level of quality is not only challenging my creative process but also helping me evolve in storytelling. It's enabling me to translate my imagination with fewer technical constraints," said Josephine Miller in the blog post. Go watch the clips but don't blame us if you wake up in the middle of the night screaming. You might also like Best AI toolsWhat is AI? Everything you need to know about Artificial Intelligence ...The first batch of Rabbit R1 AI devices will be shipping next week ...What is Suno? The viral AI song generator explained – and how to ...The iPhone 16 Pro's chipset could be designed with AI in mind ... View the full article
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A recent study has revealed that AI language models, specifically OpenAI's GPT-4, are outperforming humans in tasks that require divergent thinking - which involves the generation of unique solutions to open-ended questions, a key facet of creativity. The study, conducted by Kent F. Hubert and Kim N. Awa, Ph.D. students at the University of Arkansas, and Darya L. Zabelina, an assistant professor at the same institution, involved 151 human participants. They were tested against the AI model on the Alternative Uses Task, Consequences Task, and Divergent Associations Task. And in bad news for the humans, the AI model demonstrated greater originality and detail in its responses, thus indicating higher creative potential. Of course, these findings are not definitive proof of AI's superior creativity. The study's authors caution that while the AI models were more original, they were not necessarily more appropriate or practical in their ideas. The AI’s creative potential is also dependent on human input, which limits its autonomy. More research needed The study additionally found that AI used a higher frequency of repeated words compared to human respondents. While humans generated a wider range of responses, this did not necessarily result in increased originality. The findings challenge the assumption that creativity is a uniquely human trait. However, the question remains whether AI's superior performance in creative tasks poses a threat to humans, now or in the future. While the results were undoubtedly impressive, the authors stress that the study only assesses one aspect of divergent thinking. It does not necessarily indicate that AI is more creative across the board. The authors conclude that future research will need to consider the usefulness and appropriateness of the ideas, as well as the real-world applications of AI creativity. The study, titled "The current state of artificial intelligence generative language models is more creative than humans on divergent thinking tasks," was published in Scientific Reports. More from TechRadar Pro These are the best AI tools around todayLearn from shadow IT's mistakes: don’t let Generative AI go undergroundMany companies still aren't offering proper AI guidance View the full article
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Lawyers acting on behalf of Tesla boss Elon Musk have filed a lawsuit against OpenAI. Naming the CEO and the president of OpenAI, Sam Altman and Greg Brockman, respectively, the crux of the Superior Court of California suit (PDF) is the allegation that OpenAI’s founding agreement has been breached. View the full article
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OpenAI has announced that it will do something very special to protect its users from copyright issues. The introduction of a new scheme, entitled Copyright Shield, will see the company foot any bills relating to GPT copyright cases. There’s a catch, though, because Copyright Shield only applies to customers using generally available products, which could leave many regular consumers in limbo. Using ChatGPT won’t cost you in any legal battles In an announcement, the company stated: “OpenAI is committed to protecting our customers with built-in copyright safeguards in our systems.” OpenAI added: “we will now step in and defend our customers, and pay the costs incurred, if you face legal claims around copyright infringement.” Copyright Shield only protects users running generally available OpenAI products, including ChatGPT Enterprise and the developer platform. The news comes after months of pressure – Microsoft announced that it would protect its own customers against legal battles by footing the bill earlier in September, two months before OpenAI’s move. Copyright in the world of generative AI has become an increasingly important topic, because models like the firm’s latest GPT-4 use publicly available information for training purposes. This means that, on occasion, AI-generated responses could include content that belongs to somebody else. Copyright protection is even more important in the case of OpenAI, which, at the same event, announced that it would make its sources much more current. The GPT-4 Turbo model now has knowledge of real-world events up to April 2023. It’s worth noting that, at least for a few more weeks, GPT-4 turbo is in preview, so Copyright Shield won’t actually step in in the event of an infringement allegation. Clearly, protection against copyright cases for products that are still in development would be a foolish move on OpenAI’s part, but its offer for generally available products demonstrates a clear commitment to responsible AI, just days after a British-organized summit saw representatives from various countries and enterprises discuss the future of AI. More from TechRadar Pro 28 countries agree to develop AI safely and responsibly at Bletchley Park summitWant to help boost productivity at work? Here are the best AI toolsCraft your best work every with the best AI writers View the full article
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Both Microsoft and OpenAI have announced they are extending on the 3 year partnership they already have to keep making advancements together around Artificial Intelligence (AI). This partnerships includes AI products like ChatGPT, DALL-E, GitHub Copilot, and the Azure OpenAI Service. Both companies are stating that they’re missions both support the idea of ensuring that […] The article Microsoft and OpenAI: Extended Partnership Announcement for ChatGPT, Azure, and more appeared first on Build5Nines. View the full article
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