Tesla FSD: Driving Towards the Future

Also: $100 Billion AI Models are Coming, Youtube's Audio Eraser Tool ...

July 07, 2024 • Estimated Reading Time: 9 minutes

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Hey There, Human Marvel!

Tesla's Full Self-Driving (FSD) technology has seen significant improvements, with users reporting enhanced experiences and increased confidence in the system's capabilities. Recent updates, particularly version 12.4.3, have been praised for their effectiveness, with some users noting zero interventions and human-like driving experiences.

Today’s AI Marvels

  • Tesla FSD: Driving Towards the Future

  • $100 Billion AI Models are Coming

  • AI Learning - BEAUTIFUL.ai

  • Prompts for Text and Image Generation, AI Term - RNN

  • Top Trending AI Tools

  • More essential AI & Tech updates today

TOP AI INSIGHTS

TESLA FSD

Driving Towards the Future

Source: Not a Tesla App

Overview:

Tesla's Full Self-Driving (FSD) technology has taken a significant step forward with its latest updates, particularly version 12.4.3. Users are reporting enhanced experiences and increased confidence in the system's capabilities, marking a potential turning point in autonomous driving.

Highlights:

  • Some users report zero interventions and human-like driving experiences

  • Improved performance on long road trips

  • Potential to reduce accidents and reshape transportation

  • Still requires supervision and has limitations (e.g., pothole avoidance)

Importance: While FSD technology is not yet perfect, these improvements represent a major advancement in autonomous driving. As the system continues to evolve, it could revolutionize transportation, making roads safer and changing how we think about travel. However, it's crucial to remember that driver supervision is still necessary as the technology matures.

$100 Billion AI Models are Coming

Source: Forbes

Overview: Anthropic CEO Dario Amodei reveals that AI models currently in development may cost up to $1 billion to train. This marks a significant increase from the $100 million price tag of existing models like ChatGPT-4. Amodei predicts even more expensive models costing $10 to $100 billion could emerge by 2025-2027.

Highlights:

  • AI model training costs are rising exponentially

  • Current models cost around $100 million to train

  • $1 billion models are already in development

  • $100 billion models predicted within 3-5 years

  • Hardware is the primary cost driver for AI training

  • Increased costs may lead to more powerful AI capabilities

Importance: This rapid escalation in AI training costs reflects the growing complexity and potential of artificial intelligence. As models become more sophisticated they require more powerful hardware and resources. The industry faces challenges in scaling up infrastructure and managing energy consumption to support these advanced AI systems.

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AI LEARNING

BEAUTIFUL.ai - GENERATIVE AI PRESENTATION SOFTWARE

To Use:

  1. Log in to Beautiful.ai or create a free account.

  2. Enter your requirements and generate a slide with AI.

  3. You can also set your Custom Branding, Theme if you are premium user or through Free Trial.

  4. Generate Stunning Presentation Slides using AI.

PROMPTS OF THE DAY!

PROMPT FRAMEWORK: PEEP(Point Example Explanation Point)
DOMAIN: Data Science
ROLE: Data Analyst
TASK: Describe the process of data preprocessing in machine learning.

PROMPT:

Point: "Describe the process of data preprocessing in machine learning."
Example: "Provide an example of how missing values are handled during data preprocessing."
Explanation: "Explain the importance of feature scaling in data preprocessing and its impact on model performance."
Point: "Conclude by discussing the significance of data preprocessing for machine learning models."

*Note: Combine and Modify this Prompt Framework According to Your Tasks or Requirements.

PICTURE PERFECT PROMPT for Image Generation:

PROMPT:

a realistic scene, an old home from the 1930's. The background is a planet that is on the edge of collapse. The skies are grey, the trees are barren. it is very depressing. a rocket ship is launching and leaving the earth

IMAGE:

AI TERM TIME

Recurrent Neural Network (RNN):

A recurrent neural network (RNN) is a type of artificial neural network which uses sequential data or time series data. These deep learning algorithms are commonly used for ordinal or temporal problems, such as language translation, natural language processing (nlp), speech recognition, and image captioning; they are incorporated into popular applications such as Siri, voice search, and Google Translate. Like feedforward and convolutional neural networks (CNNs), recurrent neural networks utilize training data to learn. They are distinguished by their “memory” as they take information from prior inputs to influence the current input and output. While traditional deep neural networks assume that inputs and outputs are independent of each other, the output of recurrent neural networks depend on the prior elements within the sequence. While future events would also be helpful in determining the output of a given sequence, unidirectional recurrent neural networks cannot account for these events in their predictions.

TOOLS, JOBS , FUNDING & MEMES

Top AI Tools

  • 🧑‍🎨 Excatly.ai - Ethical ai for Creators - Train a personal ai on your artwork.

  • 🧠 ChatGPT - Chatbot and Virtual assistant developed by OpenAI

  • ✍️ WriteHuman - Bypass AI detection with the world's most powerful AI Humanizer.

  • 🏎️ Zapier - Automate faster by using Natural Language to create Workflows that connect thousands of apps.

  • 🏃 Asana - The #1 AI work management platform

MORE AI UPDATES

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The AI MARVEL Team

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