LLMs

Claude Science is Anthropic’s newest flagship product

Publicado porRedacao AIDaily
4 min de leitura
Autor na fonte original: Grace Huckins

At an event for pharmaceutical executives, biotech founders, and researchers on Tuesday, Anthropic announced Claude Science, a major new product intended to support scientific research in the same way that Claude Code supports software engineering. Like Claude Code, Claude Science can autonomously carry out meaningful work when given concise, high-level instructions, and it has access…

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At an event for pharmaceutical executives, biotech founders, and researchers on Tuesday, Anthropic announced Claude Science, a major new product intended to support scientific research in the same way that Claude Code supports software engineering. Like Claude Code, Claude Science can autonomously carry out meaningful work when given concise, high-level instructions, and it has access to tools that make it particularly useful for research in computational biology and drug development. Along with launching and previewing Claude Science, which is now available to all paid Claude subscribers, Anthropic also announced that it will be using the product to pursue some of its own research into drugs for rare, neglected diseases. This is not Anthropic’s first foray into AI for science. In October, the company released plug-ins that help Claude make use of scientific software and databases under the heading “Claude for Life Sciences.” But unlike this earlier release, Claude Science is a full-featured, standalone product. Anthropic’s decision to elevate Claude Science to the same rank as Claude Code and Claude Cowork indicates that the company is taking AI’s scientific applications very seriously—or at least wants to give the impression that it is. “It represents how important this is to our mission that this is right up there with Claude Code and Claude Cowork as the next really significant product that we’re releasing,” says Eric Kauderer-Abrams, Anthropic’s head of life sciences. “Our mission is to develop AI that serves humanity’s long-term well-being, and we believe that by far the greatest opportunity to do that is in the life sciences.” For the past decade, one company—Google DeepMind—has been at the vanguard of AI for science. CEO Demis Hassabis and researcher John Jumper won the Nobel Prize in chemistry for their work on the company’s AlphaFold model, and DeepMind has also made major contributions to meteorology, materials science, and a variety of other disciplines. But in the past several months, the fast-advancing frontier of AI progress seems to have left DeepMind in the dust. When it comes to coding, which has become the most lucrative use case for LLMs, DeepMind is stuck playing catch-up . Anthropic is well positioned to take up DeepMind’s scientific mantle. Like Hassabis, Anthropic CEO Dario Amodei is a PhD scientist—unlike OpenAI CEO Sam Altman, who’s a businessman through and through. Many scientists are already avid users of tools such as Claude Code. These days, a lot of scientific research involves some amount of coding, but not all scientists are expert software engineers, and so tools like Claude Code can make a huge difference for their productivity. And the company has recently earned a major scientific vote of confidence: Earlier this month, Jumper announced that he is leaving DeepMind for Anthropic. Since agents powered by LLMs, including Anthropic’s Opus model series, became capable of useful, independent work in late 2025, scientists have been seeing just how much they can do. In a blog post published on Anthropic’s website, the Harvard physicist Matthew Schwartz estimated, on the basis of his work with Claude Code and other Anthropic tools, that the company’s Opus 4.5 model is about as capable of executing scientific projects as a second-year graduate student. According to Kauderer-Abrams, Claude Science isn’t intended to displace Claude Code and Claude Cowork in scientists’ workflows. Instead, it’s designed to build on what scientists already find useful about Anthropic’s products. For instance, it not only writes code but also helps scientists run their code on powerful computer clusters, which many many scientists need for their work but can be difficult to manage. And it prioritizes reproducibility, so that scientists can trace back the source of any figure or result and check it for accuracy and validity. Though Claude Science could in principle assist with any area of scientific research, it seems designed and marketed as a tool for molecular and cellular biology, and for drug development in particular. It can interface with various tools used in genetics, chemistry, and protein biology, all of which could come in handy for researchers on the hunt for new drugs. During the Tuesday event, Alexander Tarashansky, who led the development of Claude Science, demonstrated how the system could autonomously identify new drug candidates for phenylketonuria, a rare genetic disease. And Anthropic isn’t leaving all that work to the pharma companies and university labs that were represented at the event. Armed with Claude Science, it will be pursuing its own research into drug candidates for neglected diseases—both to help move science forward and to gain a clearer sense of how Claude Science works in the real world. There are obvious humanitarian reasons to prioritize drug development when creating a general-purpose scientific research tool, and AI industry leaders often cite curing disease as a major potential upside of the technology. But it’s also notable that pharmaceutical companies have far deeper pockets than academic researchers. Anthropic says it’s set to see its first profitable quarter, and if major new contracts with pharmaceutical companies are forthcoming, they could help ensure it stays profitable as the tokenmaxxing craze dies down—something that’s ever more important as an IPO approaches later this year.

Pontos-chave

  • Claude Science pode revolucionar a pesquisa científica no Brasil, especialmente em biotecnologia.
  • A competição entre Anthropic e DeepMind pode beneficiar o ecossistema de IA no Brasil.
  • A implementação de Claude Science em pesquisas sobre doenças raras pode servir como modelo para o país.

Análise editorial

A introdução do Claude Science pela Anthropic representa um avanço significativo no uso de inteligência artificial para a pesquisa científica, especialmente em áreas críticas como biotecnologia e desenvolvimento de medicamentos. Para o setor tecnológico brasileiro, isso pode abrir novas oportunidades de colaboração e inovação, especialmente em um momento em que o país busca fortalecer sua posição em pesquisa e desenvolvimento. A capacidade do Claude Science de executar tarefas complexas com instruções de alto nível pode ser um divisor de águas para startups e instituições de pesquisa no Brasil, que frequentemente enfrentam limitações de recursos e expertise em IA.

Além disso, a decisão da Anthropic de posicionar Claude Science ao lado de produtos já estabelecidos como Claude Code sugere uma intenção clara de competir diretamente com líderes de mercado, como a Google DeepMind. Isso pode incentivar um ambiente de competição saudável, levando a um aumento na qualidade e na diversidade das soluções de IA disponíveis. Para o Brasil, isso significa que empresas locais podem se beneficiar de uma maior acessibilidade a ferramentas avançadas, potencializando a pesquisa em áreas como saúde pública e farmacologia.

É importante observar como a Anthropic irá implementar Claude Science em suas próprias pesquisas sobre doenças raras e negligenciadas. Isso pode não apenas demonstrar a eficácia da ferramenta, mas também servir como um modelo para outras empresas e instituições no Brasil, que podem se inspirar a adotar soluções de IA em suas pesquisas. O impacto dessa tecnologia pode ser profundo, especialmente em um país que enfrenta desafios significativos na área da saúde.

Por fim, a evolução do Claude Science e sua recepção no mercado serão cruciais para determinar se a Anthropic conseguirá realmente desafiar o domínio da DeepMind. O Brasil, com seu ecossistema de startups em crescimento e um corpo acadêmico robusto, pode ser um campo fértil para a adoção e adaptação dessas tecnologias emergentes, desde que haja um suporte adequado em termos de infraestrutura e formação de profissionais qualificados.

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  • Enquadramento editorial sobre relevancia, impacto e proximos desdobramentos.
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Sobre este artigo

Este artigo foi curado e publicado pelo AIDaily como parte da nossa cobertura editorial sobre desenvolvimentos em inteligência artificial. O conteúdo é baseado na fonte original citada abaixo, enriquecido com contexto e análise editorial. Ferramentas automatizadas podem auxiliar tradução e estruturação inicial, mas a decisão de publicar, a revisão factual e o enquadramento de contexto seguem responsabilidade editorial.

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