Artificial intelligence (AI) is one of the most exciting and impactful fields of technology today. It has the potential to transform various domains such as healthcare, education, entertainment, and more. Balancing AI power with ethics and safety is crucial. AI systems must align with human values and benefit society.
In this article, we will compare and contrast two prominent AI research companies that are working towards this goal: Anthropic AI and OpenAI. We will explore their mission, vision, organization, structure, research, products, safety, responsibility, funding, and partnerships.
What is Anthropic AI?
Anthropic AI is a relatively new AI safety and research company based in San Francisco. It was founded in 2021 by former members of OpenAI, including Dario Amodei and Daniela Amodei. Anthropic AI specializes in developing large-scale AI systems that are not only powerful but also steerable, interpretable, and safe.
Anthropic AI’s vision is to create AI systems that can be aligned with human preferences and values, and that can be controlled and understood by humans. Anthropic AI believes that this is essential for ensuring that AI benefits all of humanity and does not cause harm or unintended consequences.
Anthropic AI’s approach is to combine cutting-edge machine learning research with rigorous safety engineering and testing. Anthropic AI also collaborates with other researchers and stakeholders in the AI community to share insights and best practices.
What is OpenAI?
OpenAI is a well-known artificial intelligence research laboratory consisting of the non-profit OpenAI Inc. and its for-profit subsidiary corporation OpenAI LP. It was founded in 2015 by a group of prominent tech entrepreneurs and researchers, including Elon Musk, Peter Thiel, Sam Altman, Ilya Sutskever, Greg Brockman, and others.
OpenAI’s mission is to ensure that artificial general intelligence, which is defined as AI that can perform any intellectual task that humans can, is aligned with humanity’s values and can be used for good. It also aims to create a path to artificial superintelligence, which is defined as AI that surpasses human intelligence in all domains.
OpenAI’s approach is to conduct pioneering research on the path to AGI and ASI, as well as to create products and platforms that enable developers and users to access and benefit from their models. OpenAI also advocates for ethical and responsible use of AI, as well as for openness and collaboration in the AI field.
Key Differences Between Anthropic AI and OpenAI
Anthropic AI and OpenAI are two prominent organizations in the field of artificial intelligence, both with a shared commitment to developing advanced AI systems that are safe and beneficial to humanity. However, they differ in several key aspects. Exploring differences in AI organizations for insights into their unique roles.
Difference 1: Mission and Vision
One of the main differences between anthropopic AI and open AI is their mission and vision. While both companies share a common goal of creating safe and beneficial AI systems, they have different perspectives on what that means and how to achieve it. Anthropic AI aims for steerable, interpretable, and value-aligned AI.
Anthropic AI does not explicitly aim for AGI or ASI, but rather for reliable and trustworthy AI systems that can be used for various tasks. OpenAI focuses on creating AGI and ASI that are aligned with humanity’s values and can be used for good. OpenAI aims for democratized access, openness, and AI collaboration.
Difference 2: Organization and Structure
Another difference between Anthropic AI and OpenAI is their organization and structure. While both companies are based in San Francisco, they have different legal forms and governance models. Anthropic AI, a PBC, combines profit with social purpose, free from shareholder constraints, enabling its unique vision.
OpenAI consists of two entities: a non-profit corporation (OpenAI Inc.) and a for-profit corporation (OpenAI LP). The non-profit corporation oversees the research agenda and the vision of the organization, while the for-profit corporation handles the commercialization of the products and platforms. Dual-entity governance: board includes both sides.
Difference 3: Research and Products
A third difference between Anthropic AI and OpenAI is their research and products. While both companies conduct cutting-edge machine learning research, they have different areas of focus and outputs. Anthropic AI’s research is mainly focused on generative models and how to align them with human values.
Generative models are a type of AI models that can generate new data or content, such as text, images, audio, or video. Anthropic AI’s research topics include natural language processing, computer vision, reinforcement learning, meta-learning, and safety engineering.
Anthropic AI’s main product is Claude, a large-scale language model that can be instructed in natural language to help users with various tasks, such as writing, coding, math, and reasoning. Claude is available via API as well as a public-facing beta website. Claude: API and public website access, conversational, safe, with enhanced memory.
OpenAI’s research is mainly focused on creating powerful and scalable AI systems that can achieve human-level or superhuman performance on various tasks. OpenAI’s research topics include natural language processing, computer vision, reinforcement learning, robotics, meta-learning, and safety engineering.
OpenAI’s main product is the OpenAI API, a platform that offers access to their latest models and guides for safety best practices. The OpenAI API can be applied to virtually any task that requires understanding or generating natural language and code. The OpenAI API offers image editing, and features GPT-4 for diverse text generation.
Difference 4: Safety and Responsibility
Anthropic AI and OpenAI diverge in their safety and responsibility approaches. Anthropic AI prioritizes creating AI systems that are steerable, interpretable, and aligned with human values. Anthropic AI enhances safety via red-teaming, adversarial training, and more. They collaborate with AI experts to share insights.
OpenAI, on the other hand, concentrates on building powerful and scalable AI systems aligned with humanity’s values for positive applications. Their safety measures encompass red-teaming, adversarial training, specification gaming, reward hacking, alignment testing, and confidence-building measures.
Beyond these technical safeguards, OpenAI emphasizes ethical and responsible AI use, advocating for openness and collaboration in the AI community. These distinct approaches reflect their commitment to ensuring AI’s safe and beneficial integration into society.
Difference 5: Funding and Partnerships
A fifth difference between Anthropic AI and OpenAI is their funding and partnerships. While both companies have received significant funding from various sources, they have different strategies and goals for their financial sustainability and growth.
Anthropic AI and OpenAI differ in their funding and growth strategies. Anthropic AI secured $124 million in seed funding, backed by prominent investors including Reid Hoffman, Dustin Moskovitz, and Elon Musk. They aim to utilize this funding to expand their team, scale research, and develop products.
In contrast, OpenAI has amassed over $1 billion from various sources, including its founders and tech giants like Microsoft and SpaceX’s Elon Musk. OpenAI utilizes its significant resources to advance research, realize its vision, and develop revenue-generating products, setting a distinct path for financial sustainability.
You can also check out our blog, Anthropic Claude 2: A New ChatGPT Competitor for more tips and tutorials on Anthropic Claude 2. Claude 2 can process larger blocks of text and code, solve math problems, and explain its thinking and actions better than ChatGPT. It follows a set of principles based on human rights and values.
Frequently Asked Questions
In conclusion, Anthropic AI and OpenAI are two prominent AI research companies that are working towards creating safe and beneficial AI systems. However, they have different perspectives on what that means and how to achieve it. Their distinctions illuminate AI’s current and future landscape.