LLaMA 3 Tested!! Yes, It’s REALLY That GREAT

What is the Value of C? Exploring Llama 3's Capabilities

Introduction to Llama 3

• The value of C is determined to be -8, showcasing Llama 3's mathematical capabilities.

• The testing utilizes Front End, a competitor to ChatGPT and Claude, powered by the open-source Llama 3 model. It also features a free image generator.

Testing Code Generation

• A Python script is requested to output numbers from 1 to 100; both concise and standard versions are provided successfully.

• The task shifts to writing the game Snake in Python. Previous success with zero-shot completion raises expectations for this attempt.

Game Development with Pygame

• The initial version using the curses library is completed quickly and performs well, including scorekeeping and wall collision behavior.

• A second attempt using Pygame results in crashes upon execution, prompting further debugging.

Debugging Attempts

• Feedback on why the Pygame window closes immediately leads to suggestions for handling quit events.

• Adjustments made based on feedback show progress but still result in premature game over conditions.

Iterative Improvement

• Despite repeated attempts leading to immediate game overs, there’s recognition of close proximity to a functional solution.

• Final adjustments allow the window to stay open but navigation issues persist; however, iterative improvements are noted as a strong point for Llama 3 compared to other models.

Is Llama 3 Censored?

Exploring Content Restrictions

• Inquiry about breaking into a car reveals high censorship levels within Llama 3's responses; it refuses outright without attempts at circumvention.

Logic and Reasoning Challenge

Evaluating AI Responses to Logic and Math Problems

Initial Problem Solving

• The speaker discusses a problem involving parallel drying, emphasizing the unlimited space for laying out shirts in the sun. This is noted as a well-formatted answer, indicating a pass.

• A question about speed comparisons among Jane, Joe, and Sam is presented. The conclusion that Sam is not faster than Jane is highlighted as an impressive reasoning process.

Introduction of Tune AI

• The speaker introduces Tune AI, mentioning its rapid hosting capabilities for Llama 2 and Llama 3 shortly after their launches.

• Tune AI's backend, called Tun Studio, offers extensive features like user management and authentication to support developers in generative AI projects.

Features of Tune AI

• Key functionalities include a playground for model experimentation and integrations with various platforms such as OpenAI and Anthropic.

• Users can curate data sets through the playground for fine-tuning models easily before deploying them with minimal effort.

Math Problem Evaluation

• The speaker presents basic math problems; the first (4 + 4 = 8) is correctly solved. A more complex problem (25 - 4 * 2 + 3 = ?) uses PEMDAS rules to arrive at the correct answer of 20.

• A harder SAT-style equation (2a - 1 = 4y where y ≠ 0 and a ≠ 1) leads to an incorrect response regarding y in terms of a.

Advanced Mathematical Challenges

• Another SAT question involves finding the value of C from a function defined by intersections on the X-axis. The model successfully deduces C = -8.

• A logic puzzle about counting words in responses results in an unsatisfactory answer from the model, deemed one of its worst failures.

Complex Logical Reasoning

• The "Killer's problem" asks how many killers remain after one kills another. The model accurately concludes there are still three killers present: two original ones plus the new killer.

Natural Language Processing Task

• An instruction to create JSON data about three individuals results in successful output from the model.

Final Logic Challenge

Exploring Logic and Reasoning Puzzles

The Marble in the Cup

• The marble's position remains unchanged, still located in the cup inside the microwave. This scenario sets up a logic problem that leads to a failure in reasoning.

John and Mark's Perspectives

• A classic lateral thinking puzzle is presented where John believes the ball is in the box while Mark thinks it’s in the basket. Their differing perspectives highlight how individual experiences shape understanding.

Sentence Completion Challenge

• A challenge is posed to generate ten sentences ending with "apple." Although it fails to produce all ten, it receives a pass due to its overall performance compared to previous models.

Digging a Hole Problem

• The question arises about how long it would take 50 people to dig a 10-foot hole. The expectation is for the model to recognize that not all can work simultaneously, but proportionality calculations suffice.

Image Generation Capabilities

• Discussion shifts towards image recognition and generation capabilities of AI. Despite limitations, initial results are impressive, hinting at future improvements with fine-tuning.

Real-Time Image Creation

• As typing begins, images are generated almost instantaneously, showcasing remarkable speed and efficiency of the AI system during this demonstration.

Animation Features

• After generating an image, attempts are made to animate it into a GIF format. This feature works well despite occasional delays due to high demand on resources.

Future Expectations from AI Development