We are living in exciting times in the world of artificial intelligence. (AI) where new models can generate realistic text. Create beautiful images You can write new code and compose songs. These are capabilities born from foundational models, which are AI systems trained on big data from the internet, including text, images, videos, and more.
Foundation Models คืออะไร?
Imagine that: Foundation Models is a large "AI brain" trained with huge amounts of data from all over the world.
Whether it's text, images, videos, or even program code.
This "AI brain" has a variety of abilities, just like people with knowledge around them. It can be applied to many types of work.
such as
- Document Summary: Shorten long reports in a concise and easy-to-understand format.
- Create a story: make up a story. Plays or even video scripts.
- Answer questions: Find answers to questions you are wondering about.
- Code: Help with computer programming.
- Solve math problems: help solve complex math problems.
- Create synthetic voices: Create natural speech voices (for example, virtual assistant voice generation).
An obvious example is GPT (Generative Pre-trained Transformer) OR DALL-E THAT CAN CREATE IMAGES FROM SIMPLE EXPLANATORY TEXT.
Benefits of Foundation Models
Foundation Models unlock new possibilities for AI applications without having to create new models for each task.
For example:
- Business: Use AI to analyze vast amounts of customer data and offer products or services that are relevant to each customer in real-time.
- Education: Create personalized lessons that adapt content and teaching methods to each student's abilities and interests.
- Art and Music: Create new forms of art, paintings, or music that are difficult to separate from the work of real humans.
Examples of well-known Foundation Models
Foundation Models or basic models that are well-known in each area, such as:
Text Model
- GPT (Generative Pre-trained Transformer) From OpenAI: It is the basis of ChatGPT and GPT-4 that can write articles, answer questions, code, and compose verses realistically.
- Claude From Anthropic: GPT's competitors focus on security, providing logical answers, and answering long questions in detail.
- Flame From Meta: It is an open source model that developers can build on. They come in a variety of sizes, from small to large.
- Gemini From Google: Models that work with both text and images Active in Bard (now Gemini)
Image
- DALL-E From OpenAI: Create an image from a description, such as "A cat sitting on a roof on a full moon night".
- Midjourney : The model creates a beautiful artistic image from the description.
- Stable Diffusion : An open-source model that can be downloaded for free. There is a large community that develops and increases capacity.
Audio/Video Models
- Whisper From OpenAI: Accurate speech-to-text models in multiple languages
- Sora From OpenAI: Create multi-second videos from descriptions with very high realism.
- Dream Machine from Luma Labs : A text-to-video Video Generative Foundation Model for creating beautiful, virtual videos from text prompts.
- I see 2 จาก Google DeepMind : It is a text-to-video used to create high-quality 4K virtual reality videos.
- LLark From Spotify: It is a Multimodal Foundation Model for music, which can be used to describe various songs such as rhythm, instrumentation, etc.
- Bark From Suno: Text-to-audio and text-to-music models for creating music and composing music from text prompts developed by Suno.
- Share : is a text-to-audio and text-to-music model Suno created by former researchers from Google Deepmind
Risks and precautions
Despite the high potential of Foundation Models, there are risks to consider:
- Data Bias
- This is because the model is trained with data from the internet, which may contain bias or inappropriate content. As a result, the model may unconsciously reflect those biases. For example, if the data used for the training is mostly of men in the role of scientists, the model may automatically associate "scientists" with "men" and may not be able to create a good image of women scientists, or it may instead create images of women in other stereotypical roles.
- Disinformation
- Bad actors can use Foundation Models to create fake news. Misleading articles, distorted articles, or other deceptive content that looks so realistic that it's hard to distinguish them as false information.
- Concentration of power
- This is due to the very high cost of developing these models (tens to hundreds of millions of dollars). As a result, only a few large technology companies have been able to develop it. This results in centralization of power and inequality in access to technology.
The Future of Foundation Models and How to Respond
Foundation Models will continue to play an important role in the future. Transforming the way we work However, for this technology to truly benefit society, we need to:
- Establish clear standards and guidelines: Establish standards and practices for the development and implementation of Foundation Models that are transparent, verifiable, and take into account social impacts.
- Encourage collaboration: Establish partnerships between the government, the private sector, and civil society to establish an appropriate ethical and regulatory framework for the use of AI.
- Invest in research: Support research and development to address bias, increase data diversity, and create fair and reliable AI.
- Educate the public: Promote understanding of AI and Foundation Models to the general public so that everyone can use this technology in an informed and equitable manner.
conclusion
Foundation Models is a major milestone in the AI industry, opening the door to many new opportunities, but it also comes with challenges that must be carefully addressed.
The development and use of this technology must be responsible, transparent, and socially impactful to be the key to creating a future where AI truly benefits everyone.