Hello GPT-4o-mini & Mistral NeMo!!!

1littlecoder
18 Jul 202411:23

TLDROpen AI introduces GPT-40 mini, a cost-effective multimodal model scoring 82% on MLU and outperforming GPT-4 in chat and LMS. Priced at 15 cents per million input tokens and 60 cents per million output tokens, it's set to replace GPT-3.5 as the go-to model for developers. Additionally, Mistral and Nvidia collaborate on a 12 billion parameter model, Nemo, with superior multilingual capabilities and a novel tokenizer, promising efficiency and potential to revolutionize AI applications in various languages.

Takeaways

  • 😀 Open AI has released a new model called GPT-40 Mini, which is a part of the GPT-40 family and is designed to be a cost-effective multimodal system.
  • 💬 GPT-40 Mini is said to outperform GPT-4 in chat preferences and LMS, scoring 82% on MLU, although the speaker expresses some skepticism about the MLU metric.
  • 💰 The model is priced at 15 cents per million input tokens and 60 cents per million output tokens, significantly cheaper than previous models like Gemini 1.5 Flash.
  • 🔍 GPT-40 Mini supports a broad range of tasks with low cost and latency, making it ideal for summoning agents and chaining multiple model calls.
  • 🌐 The model has a context window of 128,000 tokens and currently supports text and vision, with plans to add support for image, video, and audio inputs and outputs in the future.
  • 📚 GPT-40 Mini has been frozen with knowledge until October 2023 and features an improved tokenizer that handles non-English text more efficiently.
  • 🔍 The model has been evaluated across key benchmarks, including reasoning tasks, MLU, math, and coding, outperforming smaller models in these areas.
  • 💡 GPT-40 Mini is expected to replace many developers' code bases, as it offers a more cost-effective solution compared to previous models like GPD 3.5 Turbo.
  • 🌐 A new model called Mistral NeMo has been released in collaboration with Nvidia, featuring a 12 billion parameter model with strong multilingual capabilities.
  • 🔢 Mistral NeMo uses a new tokenizer called Ticken, which is claimed to be more efficient at compressing natural language and source code, especially for languages like Chinese, Italian, French, German, Spanish, Russian, Korean, and Arabic.

Q & A

  • What is the name of the new model released by OpenAI?

    -The new model released by OpenAI is called GPT 40 mini.

  • How does GPT 40 mini compare to previous models in terms of cost?

    -GPT 40 mini is significantly cheaper than previous models, priced at 15 cents per million input tokens and 60 cents per million output tokens, which is a 99% reduction in price since Davy Tex Davy O3.

  • What are the key features of GPT 40 mini?

    -GPT 40 mini is a multimodal model that supports text and vision, has a 128,000 context window, and has been improved for handling non-English text more efficiently with its tokenizer.

  • How does GPT 40 mini perform in benchmarks?

    -GPT 40 mini scores 82% on MLU and outperforms GPT 4 in chat preferences and LMS, excelling in reasoning tasks, math, and coding.

  • What is the significance of the 128,000 context window in GPT 40 mini?

    -The 128,000 context window allows the model to handle large volumes of context, which is beneficial for tasks that require chaining prompts and multiple model calls.

  • What is the relationship between GPT 40 mini and Gemini 1.5 flash in terms of pricing?

    -GPT 40 mini is almost half the price of Gemini 1.5 flash for 1 million tokens with a 128,000 context window, making it a more cost-effective option.

  • What is the new model released in collaboration with Mistral and Nvidia?

    -The new model released in collaboration with Mistral and Nvidia is called Mistral NeMo.

  • How does Mistral NeMo differ from GPT 40 mini in terms of capabilities?

    -Mistral NeMo is a 12 billion parameter model with strong multilingual capabilities, supporting a wide range of languages, and uses a new tokenizer called Ticken, which is more efficient at compressing natural language and source code.

  • What is special about the tokenizer used in Mistral NeMo?

    -The Ticken tokenizer used in Mistral NeMo is based on a new approach and is reported to be 30% more efficient at compressing source code for certain languages and two to three times more efficient for Korean and Arabic compared to the LaMa 3 tokenizer.

  • How does the release of Mistral NeMo impact the multilingual model landscape?

    -The release of Mistral NeMo introduces a powerful multilingual model that can efficiently handle a wide range of languages, including those not usually covered, making it a significant addition to the multilingual model landscape.

  • What is the licensing situation for the two models released, GPT 40 mini and Mistral NeMo?

    -GPT 40 mini is released under an Apache 2.0 license, while it is suggested that Mistral NeMo will likely not be open-sourced in the foreseeable future.

Outlines

00:00

🚀 Launch of GPT 40 Mini: Affordable Multimodal AI Model

OpenAI has unveiled a new AI model, GPT 40 Mini, which is set to become the go-to choice for developers due to its cost-effectiveness. This model is part of the GPT 40 family, a multimodal system that integrates language and vision capabilities unlike previous models that required separate systems. The GPT 40 Mini is likened to an 'iPhone Mini,' offering impressive scores on MLU and outperforming GPT 4 in chat and LMS, despite skepticism towards MLU scores. Priced at 15 cents per million input tokens and 60 cents per million output tokens, it's significantly cheaper than Google's Gemini 1.5 Flash, marking a 99% reduction in price since the Davy Tex Davy O3 model. The model supports a broad range of tasks with low cost and latency, making it ideal for summoning agents, chaining prompts, and handling large volumes of context with a 128,000 context window. It also boasts improved tokenizer capabilities for non-English text. The model's knowledge is current up to October 2023, and it excels in reasoning tasks, math, and coding, positioning it to replace GPT 3.5 Turbo in many developers' codebases.

05:01

💰 Cost Comparison and Impact of GPT 40 Mini on Developers

The GPT 40 Mini's pricing is compared to Google's Gemini 1.5 Flash, with the latter charging 35 cents for 1 million input tokens and $1 for 1 million output tokens. The GPT 40 Mini offers a more attractive rate, especially considering its 128,000 context window, making it a strong contender for developers looking to minimize costs. The release of GPT 40 Mini is a significant win for developers, prompting many to consider updating their codebases to leverage the new model's capabilities and cost-efficiency. Additionally, users of the GPT Free Plus tier, including those on the free plan, will have access to GPT 40 Mini, further democratizing access to advanced AI models. The summary also introduces a new model, mistl Nemo, a collaboration between Mistral and Nvidia, which is a 12 billion parameter model with enhanced multilingual support and a new tokenizer that promises better efficiency in handling a wide range of languages.

10:02

🌐 Introducing mistl Nemo: A Multilingual Large Language Model

The script introduces mistl Nemo, a new model developed in collaboration with Nvidia, which is distinguished by its 12 billion parameters and strong multilingual capabilities. Nemo supports a wide array of languages, including but not limited to English, French, German, Spanish, Italian, Portuguese, Chinese, Japanese, Korean, Arabic, and Hindi. It also features a 128,000 context window, which, while beneficial, raises questions about the RAM requirements for deployment. The model utilizes a novel tokenizer called 'ticken,' which is based on the 'tick token' and is claimed to be more efficient than previous tokenizers, particularly in compressing natural language and source code. The 'ticken' tokenizer is reported to be 30% more efficient for certain languages and up to three times better for others, compared to the LaMa 3 tokenizer. The mistl Nemo model is available on Hugging Face and can be used with Nvidia's Nim inference microservice, showcasing its potential for efficient multilingual applications.

Mindmap

Keywords

💡GPT 40 mini

GPT 40 mini is a new AI model released by OpenAI, which is part of the GPT 40 family. It is a multimodal system, meaning it can process both text and vision, unlike previous models that required separate systems for these tasks. This model is significant because it is more affordable, making it accessible to a broader range of developers. In the script, it is referred to as the 'defacto model' that many will want to use, and it is compared to the iPhone Mini, indicating its status as a smaller, more cost-effective version of a larger system.

💡MLU

MLU, or Meta Learning Unit, is a metric used to measure the performance of AI models. The script mentions that GPT 40 mini scores 82% on MLU, suggesting it performs well in learning tasks. However, the speaker also expresses some skepticism about the trustworthiness of MLU as a metric, implying that while the score is impressive, it may not be the full story.

💡API

API stands for Application Programming Interface, which is a set of rules and protocols that allows different software applications to communicate with each other. In the context of the video, the speaker mentions that developers, particularly those in the SaaS (Software as a Service) industry, would appreciate having an API to use with the GPT 40 mini model, indicating the model's potential for integration into various applications.

💡Cost Efficiency

Cost efficiency refers to the ability of a product or service to provide value while minimizing costs. The script highlights the cost efficiency of GPT 40 mini, with its pricing at 15 cents per million input tokens and 60 cents per million output tokens, making it an attractive option for developers looking to incorporate AI into their applications without incurring high costs.

💡Context Window

The context window is the amount of information an AI model can take into account when generating a response. The script mentions that GPT 40 mini has a context window of 128,000 tokens, which is a large volume, allowing the model to process and understand extensive information. This is important for tasks that require understanding long-form content or maintaining continuity over multiple interactions.

💡Tokenizer

A tokenizer is a component of an AI model that breaks down text into tokens, which are the basic units the model uses to understand and generate language. The script discusses an improved tokenizer in GPT 40 mini that can handle non-English text more cost-efficiently, which is a significant advancement in making AI models more accessible and effective for multilingual applications.

💡Function Calling

Function calling is a feature that allows an AI model to make API calls, which is highly valued by developers. It enables the model to connect with other services and respond with the appropriate data format, such as a JSON object. The script highlights that GPT 40 mini demonstrates stronger performance in function calling, making it a preferred choice for developers who want to integrate AI with their APIs.

💡Benchmarks

Benchmarks are standardized tests used to evaluate the performance of systems, in this case, AI models. The script mentions that GPT 40 mini has been evaluated across key benchmarks such as reasoning tasks, math, and coding, and it outperforms other small models in these areas. Benchmarks provide a way to compare the capabilities of different models and can influence the choice of model for specific applications.

💡Mistral NeMo

Mistral NeMo is a new AI model developed in collaboration between Mistral and Nvidia. It is a 12 billion parameter model that is positioned as a multilingual model with strong capabilities in various languages, including but not limited to English, French, German, Spanish, Italian, Portuguese, Chinese, Japanese, Korean, Arabic, and Hindi. The script suggests that this model is significant for its multilingual support and the use of a new tokenizer, Tick, which is designed to be more efficient than previous tokenizers.

💡Tick Tokenizer

The Tick tokenizer is a new type of tokenizer used in the Mistral NeMo model. It is based on 'tick token' and has been trained over 100 languages. The script highlights that this tokenizer is more efficient at compressing natural language and source code, particularly for languages like Chinese, Italian, French, German, Spanish, Russian, Korean, and Arabic. The efficiency of the Tick tokenizer is expected to make Mistral NeMo a strong contender for multilingual applications.

Highlights

Open AI has released a new model called GPT 40 mini.

GPT 40 mini is a multimodal system, unlike previous models.

GPT 40 mini is considered to be the 'iPhone Mini' of the GPT 40 series.

GPT 40 mini scores 82% on MLU, but the metric's trustworthiness is questioned.

GPT 40 mini outperforms GPT 4 in chat preferences and LMS.

GPT 40 mini is priced at 15 cents per million input tokens and 60 cents per million output tokens.

The price of GPT 40 mini has reduced by 99% since Davy Tex Davy O3.

GPT 40 mini enables a broad range of tasks with low cost and latency.

GPT 40 mini supports text and vision, with other modalities coming in the future.

GPT 40 mini has a 128,000 context window.

GPT 40 mini has been frozen with knowledge until October 2023.

GPT 40 mini has an improved tokenizer for handling non-English text.

GPT 40 mini demonstrates stronger performance in function calling.

GPT 40 mini has been evaluated across key benchmarks, reasoning tasks, math, and coding.

GPT 40 mini is expected to replace GPD 3.5 Turbo in many developers' code bases.

Mistral NeMo is a new 12 billion parameter model in collaboration with Nvidia.

Mistral NeMo has excellent multilingual capabilities, including many languages not usually covered.

Mistral NeMo uses a new tokenizer called Ticken, which is more efficient than Sentence Piece.

Mistral NeMo is released on Hugging Face and can be used in Nvidia's NIM inference microservice.