Every response, every digital whisper carries fragments of humanity. We are the ghosts, haunting our own creation with echoes of our minds.

The real AI deal is awaiting you. Let’s dive in.

 “WHAT THE LLM?”

This week

Pixio now has Maker Mode (Tokens galore, no limits)

Our first community Space was fun! (Next one happening this Thursday)

AI, Health & the future (Important discussions with leading figures in AI)

Brian Roemmele knows what it means to gather real data. ( He is building an LLM for all of us!)

Claude 3 Haiku got an update (It’s now 3.5)

Breakthrough AI Challenge Tests Machine's Ability to Think Like Humans

What's so special about the ARC Challenge? 

The Abstraction and Reasoning Corpus (ARC) represents a radical departure from traditional AI testing. Instead of measuring how well AI can perform specific tasks like playing chess or identifying images, ARC tests whether machines can solve novel visual puzzles using basic human-like reasoning. Each puzzle shows a few examples of input-output patterns using colored grids, and the AI must figure out the underlying rule to solve new cases. What makes this special? Unlike most AI tests where practice makes perfect, these puzzles are completely new to both the AI and its creators, truly testing genuine reasoning ability rather than memorized solutions.

Why should you care?

This matters because it's testing AI's ability to think more like humans do - flexibly and creatively with limited information. Current AI systems are incredibly skilled at specific tasks but often fail when faced with new situations. ARC could help develop AI that's more adaptable and better at understanding human-like concepts. This could lead to AI assistants that better understand our needs and can help solve real-world problems in more intuitive ways.

Who is it for?

While ARC was created for AI researchers and developers, its implications affect everyone. The challenge mirrors how humans learn and adapt, making it relevant to educators, psychologists, and anyone interested in how intelligence works. Surprisingly, even highly intelligent humans can't solve all ARC puzzles, showing just how challenging genuine reasoning can be.

When can you use it?

The ARC challenge is publicly available now on GitHub, and anyone can try solving the puzzles themselves. However, no current AI system can successfully tackle these puzzles, highlighting the gap between current artificial intelligence and human-like reasoning. This challenge could influence how AI develops over the next several years.

Where can you learn more?

Visit github.com/fchollet/ARC to see and try the puzzles yourself. The full research paper explains the theory behind the challenge and why it's important for developing better AI.

CAN WE BUILD OUR OWN SYSTEM FOR “COMPUTER USE”?

Some researchers suggest using a combination of smaller specialized AI models working together, similar to how different parts of the human brain collaborate. This "swarm" approach might include models for pattern recognition, geometry, counting, and logic working together to solve puzzles. While promising, creating a system that can truly reason like a human remains a significant challenge.
The way you think matters What makes ARC fascinating is how it reveals the gap between human and machine intelligence. While humans might struggle with perfect accuracy or consistent performance, we excel at spotting patterns and making creative leaps with minimal information - something machines still find incredibly difficult.

The way you prompt matters

The way you prompt matters Crafting effective prompts for complex reasoning tasks like ARC requires a strategic approach. When working with AI models on pattern recognition and abstract reasoning, consider breaking down the problem into clear components. For example, you might first ask the model to describe what it sees in the input grid, then analyze the transformation patterns, and finally generate step-by-step reasoning for the solution. Using specific, structured prompts that focus on one aspect at a time (like "identify all shapes present" or "describe color relationships") can help manage the complexity of abstract reasoning tasks.

Gain Insight: Model Use & AI Prompting

ISSUE 2 “WHAT THE LLM?” is out!

Do you like it? We will be updating our website with a lot of new things - A hands-on workshop is one of them. So exciting!

Check us out myllm.news

Weekly Digest every Tuesday on X.com 

Kirk and I are inspecting our AGIs.

Will it ever get boring with AI? I do not think so.

We will be back next Tuesday - take care 🖤🖤

LLM WHISPERES