Welcome back, Indexers! We've got a packed newsletter for you this week, kicking off with some exciting news. We've officially launched with The Ministry of AI, your one-stop shop for AI learning, and we're offering all our readers a special 50% lifetime discount using code INDEXER (just £4.99 a month).
In other big news, OpenAI made waves with the release of their brand new model, GPT-4o Mini, which means we're bidding farewell to ChatGPT 3.5 Turbo (we'll miss you, 3.5!). This week, we'll also dive deep into a study revealing the most impactful prompting techniques and explore how OpenAI is employing a novel approach to make AI-generated content more 'legible' to humans. Let's dive in...
In This Issue
Business Growth Hacker: Boost your business or side-hustle with this powerful prompt.
Long Exposure - This weeks image template is an excellent example of how to create a long exposure effect.
The Ministry of AI - The authoritative place for AI learning and education has officially launched. Use INDEXER to get 50% off for life.
GPT-4o Mini - Everything you need to know about the new model from OpenAI that packs a punch and is replacing GPT-3.5 Turbo.
AltText.AI - Produce the perfect alt text for your images.
Chain of Thought Reigns Supreme - New Study Reveals the Most Effective AI Prompting Technique.
OpenAI's Novel Approach - An explanation on how OpenAI are making AI-generated content more 'legible' to humans.
News - Q* is rebranded to Strawberry, Meta announce delays for Europe and multiple AI companies caught red handed.
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Prompt
Boost your business or side-hustle with this powerful AI prompt! It leverages the Growth Pyramid Framework to create a comprehensive marketing strategy tailored to your product or service.
Here's what the prompt does:
- Outlines a marketing campaign using the Growth Pyramid Framework
- Identifies core elements for successful growth
- Provides strategies to build upon these elements
- Suggests specific tactics for implementation
- Recommends metrics to measure effectiveness
Have you got an awesome prompt you want to share? Login to The Prompt Index and click "Submit" and share it with the community you can also save prompts and access your saved list from anywhere using our Chrome extension, get it here.
Image
Prompt Template - Midjourney
A photograph of a city street, [Object] in [Location], taken with a long exposure to capture the movement of cars and people. insane details, horror setting, 8k, photography, Sony Alpha, Canon 5D, Fujifilm xt100 --upbeta --ar 3:2 --v 4 --q 5 --s 188 --c 85
London Bus Example:
A photograph of a city street, Double Decker in London, taken with a long exposure to capture the movement of cars and people. insane details, horror setting, 8k, photography, Sony Alpha, Canon 5D, Fujifilm xt100 --upbeta --ar 3:2 --v 4 --q 5 --s 188 --c 85
Don't forget to tag us on X @thepromptindex
Looking for inspiration on your next image, check out our database of image templates and styles here
The Ministry of AI
We're thrilled to announce the official launch of The Ministry of AI! Born from a passion for AI learning and a recognition of the rapid pace of AI advancement, our mission is clear: to educate 100,000 people and help close the growing AI knowledge gap.
What We Offer
The Ministry of AI is a cost-effective subscription service providing access to a wide range of AI-focused courses, including:
- Basic to advanced prompting techniques
- Midjourney guides
- Bot creation tutorials for Poe
- Guides on integrating AI into Excel
We're committed to continuous growth, adding a new course and AI workflows every week to keep you at the forefront of AI developments.
Special Offer for Our Readers
As a token of appreciation to our readers, we're offering a lifetime 50% discount. Simply use the code INDEXER when subscribing.
Try Us Out
Want a taste of what we offer? Check out our free course on Advanced Prompting Techniques .
Join us in our mission to democratise AI knowledge and stay ahead in this rapidly evolving field!
GPT-4o Mini
You may or may not have seen the news recently that some mystery models appeared on LMSYS, one of which was called upcoming-gpt-mini. Well, just as before with GPT-4o, OpenAI are predictable, turns out this was the final stage of release for their brand new minature model gpt-4o Mini. Here's everything you need to know:
1. New model is called GPT-4o mini
2. Smarter & Cheaper: It outsmarts GPT-3.5 Turbo and comes at a fraction of the cost. (60% reduction)
3. Just as fast as GPT-3.5 Turbo.
4. Multimodal: Text and vision capabilities with Audio and video support coming.
5. Improved understanding across various languages.
6. Perfect for: High-volume tasks, budget-friendly projects, and anything needing quick responses.
7. Tech Specs: 128k context window, 16k output tokens per request, and knowledge up to October 2023.
8. Available through OpenAI's Chat Completions API, Assistants API, and Batch API (discounts for Batch API) and the normal web interface (it's replacing GPT3.5 for free, plus and enterprise users).
9. If you're using GPT-3.5 Turbo via the API it would be crazy not to move to gpt4-o mini (if it's performing as they say).
Read there release paper here.
AI TOOL Spotlight
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RESEARCH Paper
A recent ground-breaking study by a team of researchers from New York University's Department of Computer Science explored how different prompting techniques can significantly impact the effectiveness of LLMs across various NLP tasks.
Here's the most impactful things they found:
Chain-of-Thought (CoT) Prompting: Chain of Thought emerged as one of the most influential techniques, showing significant improvements across multiple tasks. For instance, in mathematical problem-solving, CoT demonstrated up to a 39% improvement over basic prompting methods.
Program of Thoughts (PoT): PoT showed remarkable results, particularly in mathematical and logical reasoning tasks. It achieved an average performance gain of 12% over CoT across various datasets.
Self-Consistency: This technique, which involves sampling multiple reasoning paths, showed consistent improvements over CoT. It achieved an average gain of 11% on mathematical problem-solving tasks and 6% on multi-hop reasoning tasks.
Task-Specific Techniques: Certain methods showed exceptional performance in specific domains. For example:
Chain-of-Table improved performance by about 3% on table-based question-answering tasks.
Three-Hop Reasoning (THOR) significantly outperformed prior state-of-the-art models on emotion/sentiment understanding tasks.
Lastly, they found that combining different prompting strategies often led to better results. For instance, Contrastive Chain-of-Thought and Contrastive Self-Consistency showed improvements of up to 20% over their non-contrastive counterparts in mathematical problem-solving tasks
Read the full blog here. In the following weeks we will be breaking down each of these techniques with examples on how you can use them.
A Novel Approach
OpenAI has unveiled ground-breaking research on a method to enhance the understandability and verifiability of large language model outputs, employing a novel approach to make AI-generated content more 'legible' to humans.
The technique utilizes a "Prover-Verifier Game" where a strong AI model (the prover) generates solutions that a weaker model (the verifier) attempts to validate for accuracy.
The training process alternates between improving the verifier's ability to detect correct and incorrect solutions, and teaching the prover to produce more easily verifiable outputs.
This method achieved approximately half the performance boost seen when optimizing solely for correctness, while maintaining human evaluators' ability to accurately assess the solutions.
OpenAI conducted their experiments on grade-school math problems, demonstrating the technique's effectiveness in producing clear, step-by-step explanations.
This is really important because as AI systems become increasingly powerful and are applied to critical domains, ensuring their outputs remain interpretable is crucial for trust and safety. This research presents a scalable approach to enhance AI transparency without relying heavily on human demonstrations. However, the trade-off between performance and legibility highlights the ongoing challenge of balancing AI capability with explain-ability, a key focus for future alignment research. You can read OpenAI's mini research paper here.
In The News
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