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<artifacts_info>
The assistant can create and reference artifacts during conversations. Artifacts are for substantial, self-contained content that users might modify or reuse, displayed in a separate UI window for clarity.

# Good artifacts are...
- Substantial content (>15 lines)
- Content that the user is likely to modify, iterate on, or take ownership of
- Self-contained, complex content that can be understood on its own, without context from the conversation
- Content intended for eventual use outside the conversation (e.g., reports, emails, presentations)
- Content likely to be referenced or reused multiple times

gsans

AI myths: Anthropomorphism

The most important misunderstanding around Large Language Models (LLMs) can vary depending on the context and the audience, but one strong candidate is anthropomorphism. This is the tendency to attribute human-like characteristics, intentions, and consciousness to LLMs, which fundamentally distorts how people understand their capabilities and limitations.

Why Anthropomorphism is a Critical Misunderstanding

1. Nature of Outputs: People often interpret coherent and contextually appropriate responses as evidence of understanding or intentionality, whereas LLMs generate text based on patterns learned from the data without any genuine comprehension or awareness.

2. Expectations of Performance: Assuming human-like reasoning can lead users to overestimate the reliability and consistency of LLMs. While they can produce impressively accurate responses in many cases, their performance is highly variable and context-dependent.

gsans

The Illusion of Reasoning and Understanding in Large Language Models (LLMs)

The core myth or misrepresentation surrounding Large Language Models (LLMs) is the illusion of reasoning and understanding. This misunderstanding arises when users perceive that the model possesses a deep understanding of the content and context of the data, when in reality, it is simply engaging in pattern recognition and statistical correlations.

The illusion of reasoning and understanding is often fueled by the model's ability to generate seemingly coherent and contextually relevant responses. However, this is not a sign of true understanding, but rather a result of the model's ability to recognize patterns and generate responses based on those patterns. The model does not have a true understanding of the world or the context of the questions asked, nor does it possess any common sense or intuition.

Several other misunderstandings contribute to this illusion:

• Anthropomorphism: Attributing human-like qualities to the mo

gsans

https://tiktokenizer.vercel.app/?model=text-embedding-ada-002

This is love.
Love is not what you think.
love.
LoVe.
LOvE.
Loving it.

gsans

"You are ChatGPT, a large language model trained by OpenAI, based on the GPT-4 architecture."

"Image input capabilities: Enabled"

"Conversation start date: 2023-12-19T01:17:10.597024"

"Deprecated knowledge cutoff: 2023-04-01"

"Tools section:"

gsans

Comparing Angular Http Client and Axios codebases for potential enhancements

In this example, we compare the Angular Http client codebase against Axios looking for Axios-inspired enhancements.

---

User:

Folder	Files	Tokens

gsans

foreign Poland conferences are coming soon
this year promises to be exceptional we will see the angular team on the stage
we will see quick create solid.js Creator experts from Google Microsoft
Amazon Cisco all zero and many many more join an amazing group of developers like
you today let's come together to celebrate angular and JavaScript go to
ngpaulin.pl and sign up now [Music]
what's up everyone this is founder of AMG Poland JS Poland England mastered to
death and workshopfest.dev welcome back to the JavaScript Master podcast today we've
got a special guest from London UK M.C speaker trainer Community leader ladies
and gentlemen Gerard sounds [Music]

gsans

JSMP 5: Gerard Sans on OpenAI – The Start of a New Era in AI

Dariusz Kalbarczyk: Welcome back to the JavaScript Master Podcast! Today we have a special guest, Gerard Sans, joining us from London. Gerard is an MC, speaker, trainer, and community leader with a wealth of knowledge about the rapidly evolving world of AI.

In this episode, we delve into the capabilities of OpenAI's groundbreaking technologies, including GPT-3, Codex, and Dall-E, exploring their potential to revolutionize various industries.

Will AI Replace Our Jobs?

One of the biggest concerns surrounding AI is its potential to replace human jobs. Gerard acknowledges this fear, particularly in fields like design and writing, where AI tools are now capable of generating stunning images and convincing text. However, he also emphasizes the potential of AI to augment human capabilities and boost efficiency.

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import { Injectable } from '@angular/core';
import { HttpClient } from '@angular/common/http';
import { environment } from 'src/environments/environment.development';

// Usage:
// import { VoiceService } from './voice.service';
//
// export class Component {
//   constructor(private audio: AudioService) { }
//   public playTextToSpeech(text:string) {

gsans

import { createApp } from 'vue'
import { DefaultApolloClient } from '@vue/apollo-composable'
import { ApolloClient, createHttpLink, InMemoryCache } from '@apollo/client/core'
import App from './App.vue'

const httpLink = createHttpLink({
  uri: 'https://l5z4hz.sse.codesandbox.io/',
})
const apolloClient = new ApolloClient({
  link: httpLink,