“ (ObsGdGnAI)
top 10 LLM (Large Language Model) products in the world:
LLaMA 2 (used by Brave Leo AI)
Claude (used by Brave Leo AI)
ChatGPT (by OpenAI)
Google Gemini (by Google)
Microsoft Copilot (by Microsoft)
GitHub Copilot (by GitHub)
Meta LLaMA (by Meta Platforms)
Bing AI (by Microsoft)
IBM Watson Assistant (by IBM)
Amazon Polly (by Amazon)
notable LLMs and related tools mentioned include:
OpenAI GPT models (e.g., GPT-3, GPT-3.5, GPT-4)
Anthropic’s Claude
Meta’s LLaMA
Together Computer’s RedPajama
OpenAI Codex
Whisper by OpenAI
DALL-E by OpenAI
Hugging Face platform
Azure OpenAI Service
Google Cloud AI Platform
It's tricky to give a definitive “top 10” list of LLMs, as “best” can depend on your specific needs and how you measure performance. However, here are some of the most popular and powerful LLMs currently available, with a focus on those that have accessible products or APIs:
**1. OpenAI's GPT-4**
**2. Google's PaLM 2**
**Product:** Bard (chatbot), Vertex AI (platform for developers)
**Strengths:** Excellent at language understanding and generation, translation, and code-related tasks. Available through Google Cloud Platform for developers.
**Why it's notable:** Backed by Google's massive resources and research, integrated with other Google services.
**3. Anthropic's Claude 2**
**Product:** Claude.ai (chatbot),
API access
**Strengths:** Focus on helpfulness and harmlessness, long context windows (up to 100K tokens).
**Why it's notable:** A strong competitor to GPT-4, emphasizing ethical considerations and safety.
**4. Meta's Llama 2**
**Product:** Open-source model, available through various providers (e.g., Amazon SageMaker, Hugging Face)
**Strengths:** High performance, customizable, and accessible for research and commercial use.
**Why it's notable:** A major open-source LLM, enabling wider access and innovation.
**5. Cohere's Command**
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**Strengths:** Designed for developers, with a focus on tasks like summarization, copywriting, and dialogue generation.
**Why it's notable:** A strong option for businesses looking to integrate LLMs into their applications.
**6. AI21 Labs' Jurassic-2**
**Product:** AI21 Studio (platform for developers)
**Strengths:** Powerful language model with good performance on tasks like question answering and text generation.
**Why it's notable:** Offers a user-friendly platform for experimenting with and deploying LLMs.
**7. NVIDIA's NeMo**
**Product:** Framework and pretrained models (e.g., Megatron-Turing)
**Strengths:** Focus on large-scale language models and high-performance computing.
**Why it's notable:** Pushing the boundaries of LLM size and capabilities, often used for cutting-edge research.
**8. Hugging Face's Transformers**
**Product:** Open-source library and model hub
**Strengths:** Provides access to a vast collection of pretrained LLMs and tools for fine-tuning and deployment.
**Why it's notable:** A central hub for the open-source LLM community, facilitating collaboration and sharing.
**9. Stability AI's StableLM**
**Product:** Open-source models
**Strengths:** Transparency, community-driven development, and a focus on ethical considerations.
**Why it's notable:** Contributes to the open-source LLM ecosystem, making powerful models more accessible.
**10. EleutherAI's GPT-NeoX**
**Product:** Open-source models
**Strengths:** Large-scale language models trained on massive datasets.
**Why it's notable:** Pioneering open-source LLMs, pushing the boundaries of what's possible with publicly available models.
**Important Notes:**
This list is not exhaustive, and new LLMs are constantly emerging.
The “best” LLM for you will depend on your specific needs and priorities.
Consider factors like performance, cost, ease of use, and ethical considerations when choosing an LLM.
It's essential to stay informed about the latest developments in the LLM space.
I recommend exploring the websites and documentation of these LLMs to learn more about their capabilities and how they can be used.
DALL-E - For generating images from text prompts
Whisper - The multilingual speech recognition model
Moderation model - Designed specifically to optimize measuring compliance with OpenAI usage policies to help ensure an LLM isn’t misused
Embeddings - A classification tool for measuring the relatedness between two pieces of text, a key element in the work LLMs do
Codex - The engine driving the programming assistant used by Copilot, GitHub’s AI tool for generating contextually-aware programming code
usage tokens - “It can be helpful to think of a token as a unit of language characters. Within the GPT universe at least, one token is more or less equal to four characters of English text. Sometimes we’re interested in how many tokens a task will consume and, other times, on what kinds of tokens will do the best job completing a task. The most obvious differences between various model flavors are their maximum token limits and the cutoff date for their training data. You’re generally billed according the number of such units a prompt consumes.” (
ObsGdGnAI)
The Borg Disclosure and Disclaimer: “you must disclose to your customers or end users that you are using Borg (SkyNet - aka ”The Borg“ and their Central Intelligence Agency (CIA) Venture Capital - In-Q-Tel - CIAborg) AI-ML-DL-LLM-RAG-Chatbots-GPT, OpenAI ChatGPT (CBorg), Google Gemini (GBorg), Cursor AI, Anthropic Claude, JetBrains AI, Manning AI, O'Reilly AI, Amazon Q Developer, Amazon CodeWisperer, GitHub Copilot (GHBorg), Microsoft Copilot and Bing AI (MBorg), LINQPad AI, Meta LLaMA - Meta AI (FBorg), Brave Leo AI, DuckDuckGo AI, Wikipedia AI, Yahoo AI (Key Takaways), Stackoverflow AI (OverflowAI), Local LLMs, Alexa, Siri, Apple Intelligence services to help inform your decisions or recommendations.” Key Takeaway: “Don't Trust The Borg” (borg_usage_disclaimer - see also navbar_chatgpt, navbar_ai)