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    Home Latest News

      Meet Evo: The DNA-Trained AI That Creates Genomes Out of Thin Air

      Written by

      Sunny Yadav
      Published November 28, 2024
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        DNA - the bodys instruction manual.

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        A cutting-edge artificial intelligence model developed by Stanford University researchers is set to transform genetic research by decoding and designing DNA sequences with remarkable precision. Evo works like a large language model (LLM), but instead of analyzing words, it processes DNA sequences, offering unprecedented insights into genome functionality.

        Developed by Stanford University and the Arc Institute, the genomic foundation model was designed with 7 billion parameters, enabling it to process and analyze extensive genetic data. It uses single-nucleotide, byte-level tokenization to operate with a context length of up to 131,072 tokens, which allows it to examine long DNA sequences with precision and depth.

        Evo AI’s Breakthrough Capabilities

        Unlike earlier models constrained by short sequences or specific tasks, this DNA-trained AI uses advanced machine learning to process entire genomes with high resolution. This capability allows Evo to uncover patterns and large-scale interactions within genetic material, offering insights that would be challenging with traditional methods.

        This enables it to predict the effects of genetic mutations on proteins and generate synthetic DNA—a major breakthrough of AI in healthcare. Evo excelled in tests, matching or surpassing the accuracy of specialized models in mutation impact prediction. It also successfully designed protein and RNA components capable of protecting cells from viruses, proving its ability to create functional genetic materials.

        In a more ambitious test, Evo generated genome-length DNA sequences. While these synthetic genomes are not yet viable for life, they resemble natural DNA, though often with incomplete or nonsensical features—similar to AI-generated images with subtle flaws. Despite these limitations, Evo demonstrates the potential for AI to create complex genetic blueprints in ways traditional methods cannot.

        Ethical and Safety Considerations

        Evo’s training excluded sequences from viruses harmful to humans or animals to address concerns over misuse. The researchers emphasized the importance of ethical safeguards, calling for proactive collaboration between scientists, security experts, and policymakers to mitigate risks as the AI technology evolves. They also stress that Evo AI, while powerful, remains a research tool rather than a commercial product.

        Evo represents a significant step forward in AI-driven genomics, unlocking new possibilities for understanding DNA and combating disease. However, its development underscores the need for caution as AI expands into sensitive science areas.

        Sunny Yadav
        Sunny Yadav
        Sunny is a content writer for eSecurity Planet (eSP) with a bachelor’s degree in technology and experience writing for leading cybersecurity brands like Panda Security, Upwind, and Vanta. At eSP, he covers the latest news on cyberattacks, cryptography, data protection, and emerging threats and vulnerabilities. He also explores security policies, governance, and endpoint and mobile security. Sunny enjoys hands-on testing, rigorously evaluating tools to assess their capabilities and real-world performance. He also has extensive experience working with AI tools like ChatGPT and Gemini, experimenting with their applications in cybersecurity, content creation, and research.

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