A quick introduction to the world of existing large language models (LLMs) for beginners
Originally intended for a select group of researchers and organizations, it as a result of the leak, it quickly ended up on the Internet by early March 2023making it available to a wider audience. In response to the widespread distribution of its code, the company has decided to support the open distribution of LLaMA, consistent with its commitment to open science and expanding the impact of this cutting-edge AI technology.
In July 2023, LLaMA-2 was launched in collaboration with Microsoft.which was an evolutionary development of the original model, increasing the training data size by 40% and refining it to improve data handling and security, focusing on reducing errors and model security.
LLaMA 2, still open source and free for research and commercial use, builds on the legacy of LLaMA by offering 7B, 13B, and 70B models, including the LLaMA 2 chat with dialog support.
The developer has increased accessibility by publishing model weights and accepting more flexible licensing for commercial applications, demonstrating its continued commitment to responsible AI development amid concerns about bias, toxicity and misinformation.
The main goals of LLaMA and LLaMA 2 are to democratize AI research by providing more compact and efficient models that open new avenues for research and enable the creation of specialized applications for users with limited computing resources.
Additionally, releasing these models publicly encourages collaborative research, helping to address important issues such as bias and toxicity in AI. This approach also allows for private instances of models, reducing reliance on external APIs and increasing data privacy.
Examples of using
General purpose chatbots: LLaMA models are capable of running specialized applications, offering an alternative to chatbots such as ChatGPT, especially in the areas of customer service and educational opportunities.
Research tool: The models provide an invaluable aid to AI researchers, facilitating the exploration of new methodologies and understanding of LLM behavior.
Code generation and analysis: LLaMA models are also excellent at code generation and analysis, which provides significant benefits in the field of programming and software development.
By providing open access to LLaMA and LLaMA 2, the company is advancing AI research and setting a precedent for responsible LLM development and use.
Prospects
The developer is pushing Llama 3 by targeting improved code generation and advanced dialog, aiming to match the capabilities of Google's Gemini model.
CEO of the development company stated that while Llama 2 was the leading open source model, the goal of Llama 3 is to achieve status as the leading LLM in the industry with the most advanced features. He also spoke about the company's commitment to open-source AI models and detailed organizational changes to expand its AI efforts. It also announced plans to purchase more than 340,000 Nvidia H100 GPUs by the end of the year, with total computing power approaching 600,000 H100 GPUs.
This significant investment underscores Llama's commitment to becoming a leader in AI research and development.
Resources
Anthropic
Claude
Anthropic Companya security and AI research company, has made a significant leap forward in AI development with Claude, focusing on building trustworthy, interpretable, and controllable AI systems.
Claude was released in March 2023 and marked Anthropic's entry into the open-source AI marketplace, aimed at making AI safer and more ethical. Claude was born as a response to the unpredictable, unreliable, and opaque challenges of large AI systems.
Claude 2 arrived in July 2023, building on the foundation of its predecessor, with improved performance and broader application capabilities, with an emphasis on ethical AI development.
Claude is distinguished by having an autoregressive model with 52 billion parameters, trained on a large unsupervised text corpus, similar to the GPT-3 training methodology, but with an emphasis on ethics and safety.
Architecture and Innovation
Claude's architecture reflects a commitment to innovation, using solutions similar to those described in Anthropic's research, but with a unique twist.
Unlike models trained using reinforcement learning from human feedback (RLHF), Claude uses a model-generated ranking system in accordance with the “constitutional” approach to AI. .
This method begins with a set of ethical principles that form a “constitution” that guides the development of the model and the alignment of its results, demonstrating Anthropic's commitment to ethically correct and autonomous AI systems.
Basic goals
Anthropic's primary goals in working with Claude include democratizing AI research and creating an open research environment to collaboratively address AI-specific issues such as bias and toxicity.
By offering Claude, Anthropic enables more secure and private use of models, reducing dependency on external APIs and ensuring data privacy.
Examples of using
Claude's versatility is evident in a variety of applications:
Creative content writing and summarizing: Makes content creation easier for writers and content creators.
Coding Help: Improves developer workflows, as seen in Sourcegraph's AI-powered coding assistant, Cody, who uses Claude 2 to improve query responses.
Collaboration platforms: Powers AI-powered writing assistants like the one integrated into Notion, revolutionizing content creation and management across its ecosystem.
Search and questions and answers: Implementing Claude in Quora and DuckDuckGo improves answer accuracy and user engagement.
Individual interaction with users: Ideal for personalized customer service, Claude tailors its tone and responses to suit users' specific needs.
The Future of Claude: Strategic Vision for Claude 3
Anthropic plans to launch Claude 3 in mid-2025. (However, it has already been released – https://habr.com/ru/news/798081/ – translator's note). This is a major milestone in the development of artificial intelligence, which promises to push the boundaries of technology through improved language processing, reasoning, and generality.
This model, incorporating AI's constitutional framework, targets an unprecedented 100 trillion parameters to improve human interaction, analytical capabilities, and creative output based on trust and safety.
The strategic deployment of Claude 3 highlights Anthropic's commitment to balanced AI development, prioritizing both innovation and ethical considerations:
Responsible Scaling: Designed for 100 trillion parameters, Claude 3 is being developed at a pace that ensures stability and efficiency, and is scheduled to be rolled out over 18 months.
Strategic partnership: Anthropic is collaborating with sectors such as healthcare and education to refine Claude 3's applications, ensuring it runs on practical and impactful use cases.
Consistency with the needs of society: By monitoring public attitudes towards AI, Anthropic aims to align the implementation of Claude 3 with public expectations, fostering trust and acceptance.
Preparing for commercialization: Anthropic is developing a comprehensive commercial strategy for Claude 3, focusing on licensing, go-to-market and partner support to ensure the model is widely and usefully adopted.
The creation of Claude 3 includes refining the constitutional body to encourage healthy and safe conversations.
By conducting external audits and safety assessments, Anthropic aims to minimize the risks associated with AI development and ensure that Claude 3's capabilities are used without unintended consequences.
With the upcoming launch of Claude 3, Anthropic will focus on improving integration capabilities, expanding application areas, and customizing AI assistants to meet the different needs of organizations.
The company expects regular updates to the Claude series, and Claude 3 will be a critical step towards creating general-purpose artificial intelligence, reflecting a conscious approach to the responsible use of the potential of AI.
Resources
Hugging Face
Hugging Face, often referred to as the GitHub for Large Language Models (LLMs), promotes an open ecosystem for LLMs.
The company initially specialized in natural language processing, but in 2020 it refocused on LLM, creating Transformers library.
This library, using various LLM architectures, has become one of the fastest growing open source projects in the field.
The Hugging Face platform, known as “Hub“, is a huge storage facility models, tokenizers, data sets And demo applications (spaces)available as open source resources.
This combination of open source and traditional SaaS offerings has allowed Hugging Face to become a key player in democratizing AI development.
BLOOM
In 2022, Hugging Face released BLOOMan autoregressive transformer-based LLM with 176 billion parameters, openly licensed.
Trained on 366 billion tokens, BLOOM is the result of collaborative AI research, the main product of the BigScience initiative, a year-long research workshop led by Hugging Face.
This workshop brought together hundreds of researchers and engineers from around the world, drawing on significant computing resources French supercomputer Jean Zay.
Additionally, Hugging Face recently introduced a competitor to ChatGPT called HuggingChatexpanding its suite of innovative artificial intelligence tools.
The company also conducts Open LLM ratingwhich is a platform for tracking, ranking and evaluating open LLMs and chatbots, including popular models such as Falcon LLM And Mistral L.L.M.as well as new projects.
This initiative underscores Hugging Face's commitment to transparency and progress in AI, fostering a collaborative environment for AI innovation and evaluation.
Hugging Face is on track to solidify its status as a leading hub for large language models (LLMs), outpacing traditional AI communities in terms of growth and engagement.
More and more developers and companies are implementing Transformers and Tokenizers libraries into their processes and products.
Hugging Face is lowering the barriers to innovation in LLM, much like how GitHub revolutionized software development. This platform does more than just facilitate access to LLM technologies. It has the potential to open up new markets and strengthen human-AI collaboration, marking a significant leap in technological progress.
Resources
conclusions
In conclusion, the evolution of LLM is changing the AI landscape, offering unprecedented opportunities for innovation across multiple sectors.
As the industry evolves, navigating the many available models to find the right one for your specific needs becomes increasingly important.
With the rise of multilingual capabilities and the push for more open and inclusive development, AI platforms are becoming key enablers of technological progress. Currently the key models are:
GPT-3
GPT-4
Gemini
LLAMA
Claude
BLOOM
These platforms provide democratic access to cutting-edge AI tools and foster a collaborative ecosystem that accelerates innovation.
We are now on the cusp of a new frontier in AI, and the future promises a more connected, inclusive and intelligent world, powered by AI systems that are more adaptive, reliable and consistent with human values.
