Twitter Grok AI Large Language Model Released for Free!

Mervin Praison
17 Mar 202405:21

TLDRThe video introduces Grock One, an open-source, 314 billion parameter language model developed by X or Twitter. It showcases the model's performance against GPT-3.5 and Cloe 2, highlighting its capabilities in coding challenges. The model is available on GitHub and Hugging Face, though it requires a multi-GPU machine due to its size. The video also demonstrates Grock's problem-solving skills in Python programming tasks, from easy to very hard challenges, and its performance on the GSM 8K dataset, emphasizing its potential in AI and programming.

Takeaways

  • ๐Ÿš€ The introduction of Grock One, an open-source 314 billion parameter model mixture of experts model.
  • ๐ŸŒ Grock One is released under the Apache 2 license, making it accessible for public use and modification.
  • ๐Ÿ” Grock One's performance is benchmarked against GPT-3.5 and GPT-4, showing it beats the former but is lower compared to the latter.
  • ๐Ÿ’ป The Grock code is available on GitHub, allowing users to review and utilize the source code.
  • ๐Ÿค– Grock One is available on Hugging Face, though it requires a multi-GPU machine due to its large parameter size.
  • ๐Ÿ› ๏ธ The model was tested for coding abilities, with varying degrees of success across different levels of difficulty.
  • ๐Ÿ”ง Grock One demonstrated the ability to fix errors and improve code upon request.
  • ๐Ÿ† Grock One outperformed other models like LLaMA 270b and GPT-3.5 in specific benchmarks and math tasks.
  • ๐ŸŽฅ The video creator encourages viewers to subscribe to their YouTube channel for more content on artificial intelligence.
  • ๐Ÿ’ก The video showcases the potential of open-source AI models in programming and problem-solving.
  • ๐Ÿ“ˆ Grock One's performance on the ECG sequence test indicates both its capabilities and limitations in handling complex tasks.

Q & A

  • What is Grock One?

    -Grock One is an open-source language model developed by X or Twitter, with 314 billion parameters and a mixture of experts model. It is not fine-tuned for instruction.

  • Under which license is Grock One released?

    -Grock One is released under the Apache 2 license.

  • How does Grock One compare to GPT-3.5 and GPT-4 in terms of performance?

    -Grock One has beaten GPT-3.5 in performance but is still lower compared to GPT-4 and Cloe 2, based on benchmark tests.

  • Where can the source code of Grock One be found?

    -The source code for Grock One is available on GitHub.

  • What are the system requirements for running Grock One locally?

    -To run Grock One locally, one might need a machine with multiple GPUs due to its size of 314 billion parameters.

  • What are the technical specifications of Grock One?

    -Grock One includes eight experts, with two active during response generation, 64 layers, 48 attention heads for queries, eight attention heads for key values, and a maximum sequence length of 892 tokens.

  • What type of challenges was Grock One tested with in the video?

    -Grock One was tested with coding challenges ranging from very easy to expert level.

  • How did Grock One perform in the coding challenges?

    -Grock One successfully passed most of the coding challenges, including very hard ones, up until the final test with the ECG sequence, which resulted in a fail due to a timeout.

  • What was the outcome of Grock One's performance on the GSM 8K dataset?

    -Grock One performed better than Llama 270b and GPT-3.5 on the GSM 8K dataset, demonstrating its strength in logical reasoning and math.

  • What is the significance of Grock One being open source?

    -The open-source nature of Grock One allows for wider accessibility, enabling more developers and researchers to understand, use, and contribute to its development.

  • What are the next steps for Grock One as presented in the video?

    -The presenter plans to create more videos similar to this, testing the model by downloading it locally from Hugging Face and exploring its capabilities further.

Outlines

00:00

๐Ÿš€ Introduction to Grock 1: A Powerful Open-Source AI Model

This paragraph introduces Grock 1, an open-source language model developed by Twitter with 314 billion parameters. It's a mixture of experts model and is not fine-tuned for instruction. Grock 1 has outperformed GPT 3.5 but still lags behind GPT 4 and Cloe 2 based on benchmarks. The script discusses the model's release under the Apache 2 license and its availability on GitHub and Hugging Face. It also mentions the technical specifications, such as the eight experts model with two active, 64 layers, 48 attention heads for queries, and eight for key values, with a maximum sequence length of 892 tokens. The video's host plans to test Grock 1's coding abilities, noting that the version used for testing is instruction fine-tuned, unlike the version available on Hugging Face. The paragraph concludes with a call to action for viewers to subscribe to the YouTube channel for more content on artificial intelligence.

05:01

๐Ÿ’ป Grock 1's Coding Challenge and Benchmark Performance

The second paragraph details the coding challenges posed to Grock 1, starting with simple tasks like summing two numbers and escalating to complex problems like generating an identity matrix and an ECG sequence. Despite some issues with the test console's older Python version causing longer processing times and errors, Grock 1 successfully passes most tests, showcasing its impressive problem-solving capabilities. The video also compares Grock 1's performance in logical reasoning and the GSM 8K dataset, highlighting its superiority over other models like Llama 270b and GPT 3.5. The paragraph ends with a promise from the host to create more videos on testing AI models and encourages viewers to like, share, and subscribe for more content.

Mindmap

Keywords

๐Ÿ’กGrock One

Grock One is an open-source language model developed by X or Twitter, with a massive 314 billion parameters. It is a mixture of experts model, which means it combines the knowledge of multiple smaller models to perform better than a single large model. In the context of the video, Grock One is showcased as a model capable of solving complex coding challenges and is compared with other AI models like GPT-3.5 and GPT-4.

๐Ÿ’กOpen-source

Open-source refers to a type of software or product whose source code is made publicly available, allowing anyone to view, use, modify, and distribute the software. In the video, Grock One is described as an open-source model, which means its underlying code is freely accessible on platforms like GitHub, encouraging collaboration and further development by the community.

๐Ÿ’กMixture of Experts

A mixture of experts is a machine learning architecture where multiple models, or 'experts,' each specialize in different areas, are combined to form a more powerful overall model. The experts work together, with some being active while generating a response, to handle a broader range of tasks more effectively. In the video, Grock One is described as a mixture of experts model, emphasizing its ability to leverage specialized knowledge within its components.

๐Ÿ’กBenchmarks

Benchmarks are standardized tests or criteria used to evaluate the performance of a product, service, or system, such as an AI model. They provide a consistent basis for comparison, allowing the assessment of improvements or differences between models. In the video, Grock One's performance is compared to other AI models like GPT-3.5 and GPT-4 using benchmarks, which helps to establish its capabilities and standing in the AI landscape.

๐Ÿ’กInstruction Fine-Tuned

Instruction fine-tuning is a process in machine learning where a model is trained to follow specific instructions or commands more effectively. This involves adjusting the model's parameters to improve its performance in tasks that involve understanding and executing user-provided instructions. In the context of the video, the Grock version being tested is instruction fine-tuned, which means it has been optimized to better understand and carry out the coding tasks presented to it.

๐Ÿ’กHugging Face

Hugging Face is a platform that provides a wide range of machine learning and natural language processing models, including open-source ones like Grock One. It offers an easy way for developers and researchers to access, use, and share various AI models and their associated datasets. In the video, Hugging Face is mentioned as a place where Grock One can be accessed and used, highlighting its role in the AI community.

๐Ÿ’กGPU Machine

A GPU (Graphics Processing Unit) machine refers to a computer system that uses a GPU to perform computations, which is particularly useful for handling the intensive processing requirements of deep learning models. GPUs are specialized hardware that can parallel process large amounts of data, making them ideal for training and running complex AI models like Grock One with its 314 billion parameters.

๐Ÿ’กSequence Length

Sequence length refers to the maximum number of elements, such as words or tokens, that a model can process at one time. In the context of AI language models, a longer sequence length allows for more context to be considered, which can improve the model's understanding and generation of text. In the video, Grock One has a maximum sequence length of 892 tokens, indicating its capacity to handle relatively long inputs.

๐Ÿ’กAttention Heads

Attention heads are a component of the transformer architecture used in many AI language models, including Grock One. They allow the model to focus on different parts of the input data simultaneously, improving its ability to understand context and relationships within the data. Attention heads contribute to the model's overall performance by enabling it to process complex information more effectively.

๐Ÿ’กPython Challenges

Python Challenges in the context of the video refer to a series of programming tasks or problems that are designed to test the capabilities of the Grock One model when it comes to coding in Python. These challenges range from easy to very hard, assessing the model's ability to understand and generate correct and efficient code solutions.

๐Ÿ’กECG Sequence

An ECG (Electrocardiogram) sequence is a graphical representation of the electrical activity of the heart, which is used for medical diagnostics. In the context of the video, the ECG sequence challenge involves creating a function that can generate a sequence mimicking the pattern of an ECG, which is a complex task requiring both medical knowledge and programming skills.

Highlights

Grock one, an open-source Lun language model, has been released.

Grock one is a 314 billion parameter model mixture of experts model.

The model is not fine-tuned for instruction following yet.

Grock one is released under the Apache 2 license.

Grock one beat GPT 3.5 in benchmarks but is lower compared to GPT 4 and Cloe 2.

Grock chat on Twitter is powered by grock one.

Grock one's code is open-sourced on GitHub.

The model is available on Hugging Face but requires a multiple GPU machine to run due to its size.

Grock one has eight experts, with two active when generating a response.

The model contains 64 layers, 48 attention heads for queries, and eight attention heads for key values.

The maximum sequence length all context is 892 tokens.

Grock one was tested for coding ability, including easy to very hard challenges.

The model was able to solve challenges up to a very hard level, including generating an identity matrix function.

Grock one performed well in logical and reasoning tasks, outperforming other models like llama 270b inflection 1 and GPT 3.5.

The model is also better in math compared to other models.

The presenter plans to create more videos testing the model by downloading it locally from Hugging Face.

The video encourages viewers to like, share, and subscribe for more content on Artificial Intelligence.