{"id":662801,"date":"2026-10-23T04:52:18","date_gmt":"2026-10-23T04:52:18","guid":{"rendered":"https:\/\/www.newsbeep.com\/ie\/662801\/"},"modified":"2026-10-23T04:52:18","modified_gmt":"2026-10-23T04:52:18","slug":"hugging-face-announces-ai-model-to-chat-with-dna","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/ie\/662801\/","title":{"rendered":"Hugging Face Announces AI Model to \u2018Chat\u2019 With DNA"},"content":{"rendered":"

A new AI model can connect DNA to human language, enabling scientists to interact with genetic code in new ways. Hugging Face announced the Carbon-X model<\/a> on Thursday as the latest and most powerful in the company\u2019s Carbon family, a group of AI models built to analyze DNA.\u00a0<\/p>\n

\u201cCarbon-X allows researchers to \u2018chat with DNA\u2019 for the first time: They can provide a sequence and ask questions about it in natural language,\u201d Hugging Face research scientist Lewis Tunstall told CNET via email. <\/p>\n

The word \u201cchat\u201d doesn\u2019t mean talking to your genome but rather using an AI as a conversational interface, allowing users to paste in a DNA sequence, ask a question in plain English and receive back an interpretation, prediction or explanation \u2014 like a chatbot for DNA analysis. <\/p>\n

The most popular chatbots, such as ChatGPT, Gemini and Claude, are cloud-based models that don\u2019t run on your computer. The processing happens remotely, and you get the results back.\u00a0But if you\u2019re working on confidential or proprietary research that you haven\u2019t yet published, you might not want to share it with an AI company. \u201cResearchers need models they can study, adapt and run with sensitive or unpublished sequences on their own hardware,\u201d said Tunstall. <\/p>\n

One of the nice things about smaller, specialized AI models like Carbon-X is that it can run without using someone else\u2019s computer. Hugging Face says the model can also work in tandem with other AI agents.<\/p>\n

DNAgents<\/p>\n

To be clear, Carbon-X is not a lab machine, so it can\u2019t physically sequence DNA. It can look at DNA, such as a DNA sequence in a text file, and you can ask questions about it.\u00a0Tunstall said Carbon-X\u2019s strongest area is the model\u2019s ability to predict mutation effects and complete DNA sequences.<\/p>\n

\u201cCarbon-X is particularly strong at helping researchers investigate genetic variation, for example, predicting whether a change in a DNA sequence is likely to be harmful,\u201d Tunstall said.<\/p>\n

He also said that it can give another AI model access to a DNA specialist when it needs to extract information. <\/p>\n

However, the model does have limitations, according to the company\u2019s blog post<\/a>. Carbon-X can mess up sequencing operations through miscounts, and it can also hallucinate, which means the model just makes up information. Hugging Face noted that the model may invent the identity or function of a sequence when a user does not provide sufficient information in the prompt.\u00a0<\/p>\n

The quality of Carbon-X\u2019s output also tends to degrade when users ask the model to produce particularly long DNA sequences, according to the company.\u00a0<\/p>\n

Lightning fast\u00a0<\/p>\n

In September, Nvidia announced<\/a> it would buy Hugging Face for a little under $13 billion. At the time, Nvidia CEO Jensen Huang called the company a \u201cvibrant home for the open model developer community.\u201d Open models are AI models in which some aspects of how they were trained are publicly available.\u00a0<\/p>\n

The release of Carbon-X comes just weeks after OpenAI models began solving<\/a> longstanding mathematics problems. The AI lab drew widespread backlash from academic researchers after its proprietary models solved several long-standing problems without consulting scientists or showing what work went into solving them.<\/p>\n

But Carbon-X is an open model, so AI-savvy biologists can at least peek under the model\u2019s proverbial hood and glimpse how it runs.<\/p>\n

\u201cWe think researchers also need open alternatives whose capabilities, limitations and risks they can examine independently,\u201d Tunstall said. \u201cBy releasing Carbon-X and its training recipe openly, we enable the wider scientific community to test where it works, identify where it fails and help improve it.\u201d<\/p>\n

\t\t\t\t\t\t\t\"Julian\t\t\t\t\t\t<\/p>\n

\t\t\t\t\t\t\t\t\t\t\tJulian is a contributor and former staff writer at CNET.
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