toxicFork

That is what rain sounds like

- the machine will not take your job at every company - a human using a machine is better than only the machine - it doesn't take that much to be retrained these days, there's a lot of resources out there - maybe they will actually care about rights of people without tying things to being rich or employed? - can always cross the border to Mexico

May I ask: why?

So which ones does it apply to in the end?

Yes, it's not truly deterministic, but setting to 0 still makes it relatively less random

Tbh, with plugins, that's pretty much the case

I think soon yes

Being banned would make it quite unwelcome

Nsfw

Reducing temperature doesn't automatically result in correctness, it only results in more precision.

It could be inaccurate with high precision - like a bow that consistently undershoots, and you would have a harder time trying to correct it.

I told it:

In here, it says that maximum memory is 10240mb, so that may not work:

Memory and computing power

Memory is the principal lever available to Lambda developers for controlling the performance of a function. You can configure the amount of memory allocated to a Lambda function, between 128 MB and 10,240 MB. The Lambda console defaults new functions to the smallest setting and many developers also choose 128 MB for their functions.

Its response:

ChatGPT: I apologize for the confusion earlier. You are correct that the maximum memory allocation for a Lambda function is 10,240 MB. Here is the revised CloudFormation YAML template with 10,240 MB memory allocation:

```yaml Resources: LambdaFunction: Type: AWS::Lambda::Function Properties: FunctionName: LambdaWith10GBMemory Handler: index.handler Runtime: nodejs14.x MemorySize: 10240 Timeout: 300 Role: !GetAtt 'LambdaRole.Arn' Code: S3Bucket: <S3_BUCKET_NAME> S3Key: <S3_KEY>

  LambdaRole:
    Type: AWS::IAM::Role
    Properties:
      RoleName: LambdaRoleWith10GBMemory
      AssumeRolePolicyDocument:
        Version: '2012-10-17'
        Statement:
          - Effect: Allow
            Principal:
              Service:
                - lambda.amazonaws.com
            Action:
              - sts:AssumeRole
      Policies:
        - PolicyName: LambdaBasicExecution
          PolicyDocument:
            Version: '2012-10-17'
            Statement:
              - Effect: Allow
                Action:
                  - logs:CreateLogGroup
                  - logs:CreateLogStream
                  - logs:PutLogEvents
                Resource: arn:aws:logs:*:*:*

```

Replace <S3_BUCKET_NAME> and <S3_KEY> with the appropriate values for your S3 bucket and object key that contain your Lambda function code. You may also adjust Runtime, Handler, and Timeout as needed.

===

Then I said:

What can we do to be able to use 16gb memory?

Then it said:

ChatGPT: To use 16 GB memory in a serverless context, you will need to consider other options as AWS Lambda currently supports up to 10,240 MB. Two alternatives are AWS Fargate or running a container with Amazon ECS.

Here's an example of using AWS Fargate with a task definition for a container with 16 GB of memory:

1. Create an ECS cluster:

aws ecs create-cluster --cluster-name MyFargateCluster

2. Create a task definition with 16 GB of memory (you can adjust the values as needed). Save the JSON below to a file called fargate-task-definition.json:

{ "family": "FargateTaskWith16GBMemory", "taskRoleArn": "<YOUR_TASK_ROLE_ARN>", "executionRoleArn": "<YOUR_EXECUTION_ROLE_ARN>", "networkMode": "awsvpc", "containerDefinitions": [ { "name": "MyContainer", "image": "<YOUR_DOCKER_IMAGE>", "cpu": 4096, "memory": 16384, "memoryReservation": 16384, "essential": true, "portMappings": [ { "containerPort": 80, "hostPort": 80, "protocol": "tcp" } ] } ], "requiresCompatibilities": [ "FARGATE" ], "cpu": "4096", "memory": "16384" }

Replace <YOUR_TASK_ROLE_ARN>, <YOUR_EXECUTION_ROLE_ARN> and <YOUR_DOCKER_IMAGE> with appropriate values for your use case.

3. Register the task definition:

aws ecs register-task-definition --cli-input-json file://fargate-task-definition.json

4. Launch the Fargate task:

aws ecs run-task --cluster MyFargateCluster --launch-type FARGATE --task-definition FargateTaskWith16GBMemory --network-configuration "awsvpcConfiguration={subnets=[<YOUR_SUBNET_ID>],securityGroups=[<YOUR_SECURITY_GROUP_ID>]}"

Replace <YOUR_SUBNET_ID> and <YOUR_SECURITY_GROUP_ID> with the appropriate values for your VPC and security group. This will give you a Fargate container running with 16 GB of memory, and you can adjust the resources allocated to the container as needed.

====

I think that's quite a nice answer.

It says this, is it ok? I can check when I get home

ChatGPT: Below is an AWS CloudFormation YAML template for creating an AWS Lambda function with 16GB of memory:

```yaml AWSTemplateFormatVersion: '2010-09-09' Description: 'AWS CloudFormation Lambda Function Template with 16GB Memory'

Resources: LambdaFunctionRole: Type: 'AWS::IAM::Role' Properties: AssumeRolePolicyDocument: Version: '2012-10-17' Statement: - Effect: Allow Principal: Service: - lambda.amazonaws.com Action: - sts:AssumeRole Path: / Policies: - PolicyName: LambdaExecutionPolicy PolicyDocument: Version: '2012-10-17' Statement: - Effect: Allow Action: - logs:CreateLogGroup - logs:CreateLogStream - logs:PutLogEvents Resource: 'arn:aws:logs:::*'

  LambdaFunction:
    Type: 'AWS::Lambda::Function'
    Properties:
      FunctionName: MyLambdaFunction
      Runtime: python3.9
      Role: !GetAtt LambdaFunctionRole.Arn
      Handler: lambda_function.lambda_handler
      MemorySize: 16384
      Timeout: 300
      Code:
        ZipFile: |
          import json

          def lambda_handler(event, context):
              return {
                  'statusCode': 200,
                  'body': json.dumps('Hello from Lambda with 16GB memory!')
              }

```

This CloudFormation template creates an IAM role and a Lambda function with 16GB (16384MB) of memory. The Lambda function runtime is Python 3.9, but you can change this to another runtime if necessary. The code block contains a basic Python script for returning a simple message; you can replace this with your own script.

Tbh for clash of clans, if it can set up the server infrastructure etc, then that will be quite scary.

The scariest thing is that... I did use Chatgpt to set up an aws cloud formation stack for a lambda function, and it gave me the right file to sync.

So... Yeah, it's not that many steps to a "text to (web|mobile) app generator" solution.

Uh.. I will get to work.

Quick, someone make a project which gets ChatGPT to answer those memos

That sounds like a bureaucratic issue and not a technical issue.

The device can do it, but someone needs to be told to change some of the software or hardware.

Then you could encounter a "computer says no" situation

Technically very easy. Legally? I dunno, maybe?

Someone must have trained an LLM for that for sure.

The universe was a hoax invented by a GPU company

Too much anime and weed

It's your last name, they cannot force it off you. I'm not a lawyer, but worked for a company which tried.

Regarding how long: it depends on length of messages. But let's say when there are around 2000 words total in the conversation.

https://help.openai.com/en/articles/4936856-what-are-tokens-...

2 cents per 1k tokens

How did you even manage to find these figures? Is there a Wikipedia list? Do you know which ones are most popular for your app?

Disclaimer: I am also making a chat bot

It's a statistical play - if on average, subscribers send less than 500 messages per month, it's profitable.

To be fair, GPT is an advanced machine learning algorithm, that the product is enabling access to, for the lay person.

To add: if the training and fine tuning comes from how the subject actually responded, spoke and reasoned, then that would be quite scarily accurate.

The limitations of using pre trained data with a simple prompt. The bot will get inspired by the prompt a little, but most of its text comes from the training which is adjusted to sound as neutral and "generally acceptable human"like as possible.

This means that for most cases the personality disappears.

If the bot needs to retain conversation memory, it will cost around 4 cents per message once the conversation gets long enough. I guess they are also inspired by chat gpt plus prices.

Source: I am building a competitor

It's a very interesting and tough challenge to prevent large language models from hallucinating.