Contrary Research Rundown #126
The Language of Life: ChatGPT for DNA, plus new memos on Attentive, Discord, and more
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Research Rundown
Last May, we published a deep dive on how AI is breathing new life into biological research. And today, the field of biology is standing on the precipice of that transformation. In February 2025, Arc Institute unveiled Evo 2, an AI model trained on over 100K species' DNA, capable of identifying disease-causing mutations and generating entirely new genomes. This breakthrough represents a fundamental shift from merely deciphering life's code to actively rewriting it from scratch.
Evo 2 was trained on 9.3 trillion nucleotides extracted from more than 128K complete genomes across bacteria, archaea, phages, humans, plants, and various eukaryotes. In tests with the BRCA1 gene, it achieved over 90% accuracy in predicting which variants might cause breast cancer.
"Our development of Evo 1 and Evo 2 represents a key moment in the emerging field of generative biology, as the models have enabled machines to read, write, and think in the language of nucleotides," explains Patrick Hsu, Arc Institute Co-Founder and Core Investigator.
The journey to decode DNA began in 1869 when Friedrich Miescher first isolated what he called "nuclein" from cells. By 1953, Watson and Crick had revealed DNA's double helix structure, and by the 1970s, scientists were sequencing complete genes. These discoveries laid the foundation for genetic engineering and eventually the Human Genome Project, which fully mapped our genetic blueprint by 2003.
DNA analysis and computing has a rich history dating to the 1960s when Margaret Oakley Dayhoff pioneered using computers for biology research. This computational approach accelerated dramatically with next-generation sequencing technologies, allowing scientists to generate massive genomic datasets.
Each breakthrough in understanding genetics sparked new questions about function, regulation, and manipulation. The tension between unraveling nature's complexity and developing tools to modify it has driven progress, influenced by ethical considerations, computing advances, and funding priorities.
Evo 2 represents a quantum leap in technical capability. The model can process genetic sequences of up to 1 million nucleotides at once, enabling it to understand relationships between distant parts of a genome. This eight-fold increase over its predecessor was enabled by an architecture called StripedHyena 2, developed with assistance from OpenAI's Greg Brockman.
Evo2 offers immediate and tangible benefits for researchers and clinicians. The model excels at identifying disease-causing mutations in human genes with over 90% accuracy, potentially eliminating countless hours of expensive lab work while accelerating both diagnosis and drug development.
Researchers can use Evo2 to design gene therapies with cell-specific targeting, reducing side effects. As co-author Hani Goodarzi explains: "If you have a gene therapy that you want to turn on only in neurons to avoid side effects, or only in liver cells, you could design a genetic element that is only accessible in those specific cells."
The Arc Institute has prioritized accessibility by providing three user interfaces: a developer-friendly GitHub repository, integration with NVIDIA's BioNeMo framework to accelerate scientific research, and Evo Designer—a user-friendly interface requiring minimal technical expertise.
"We think of this as enabling an app store for biology," says Patrick Hsu, emphasizing that Evo2 functions as a foundation layer upon which specialized applications can be built. The fully open-source approach allows researchers to fine-tune the model for specific genes or organisms.
The significance extends beyond current capabilities. As Chief Technology Officer Dave Burke notes, researchers will likely discover "beneficial uses for Evo2 we haven't even imagined yet," from predicting how mutations affect protein function to designing genetic elements with novel properties. These innovations could revolutionize everything from disease treatment to sustainable bio-manufacturing.
As Evo models continue to scale, they may soon analyze a person's entire genome to predict disease risks, design targeted therapies, and perhaps craft biological structures never before seen in nature. The path from reading life's code to writing it has only just begun.
Attentive is an AI-powered SMS and marketing platform that enables brands to connect with customers through personalized messages. To learn more, read our full memo here and check out some open roles below:
Engineering Manager, Machine Learning - San Francisco, CA
Senior Software Engineer, Frontend - San Francisco, CA
Discord aims to build the “community” layer of the internet where users can find, join, and interact in servers personalized for custom user experiences. To learn more, read our full memo here and check out some open roles below:
Senior Security Engineer, Enterprise Security - San Francisco, CA or Remote (US)
Head of Data Platform - San Francisco, CA or Remote (US)
The rise of earned wage access (EWA) companies like EarnIn signals a broader shift toward modern pay practices. By providing employees access to the wages they’ve already earned when they need them most, EarnIn bridges the gap between work and pay. To learn more, read our full memo here and check out some open roles below:
Senior Product Manager (Card) - Mountain View, CA
Senior AI Solutions Engineer - Mountain View, CA
Check out some standout roles from this week.
LaunchDarkly | Remote (US) - Backend Engineer (AI), Frontend Engineer (Experimentation), Fullstack Engineer (Error Monitoring), Senior Platform Engineer
Verkada | San Mateo, CA - Head of Product (Computer Vision and Artificial Intelligence), Senior Product Designer, Lead Frontend Engineer (Growth), Sr. Digital Designer
Alloy | New York, NY - Machine Learning Engineer (Predict), Full Stack Engineer II (Client Insights), Lead Product Manager (Data Partner Integrations), Founding Engineer (Data Platform Team)
ClickUp | Remote (US or Poland) - Senior Product Designer, GTM Enablement Specialist, Senior Backend Engineer (Data Platform)
Azeem Azhar writes about how today many people see AI as a tool primarily for automation, assuming it works best with structured, defined tasks. But the reality is quite different: AI is reshaping how we turn fuzzy intuitions into tangible, powerful ideas.
Ramp released their monthly SaaS report where they share the new vendors that customers are purchasing for the first time. By new customer count, OpenAI topped the list while Anthropic was 5th on the list.
Alef Aeronautics' Model Zero electric flying car achieved it’s first-ever city drive and vertical takeoff. The vehicle took flight for 40 seconds and the company claims it has a 320km driving range and a 160km flight range.
Companies like OpenAI and Perplexity have made claims that their AI search engines will help publishers drive traffic to their sites. But new data shows AI search engines send 96% less referral traffic to news sites and blogs than traditional Google search.
Klarna is seeking to raise at least $1 billion in its IPO and is set to file publicly as soon as next week. The company is targeting a valuation of more than $15 billion in the NYSE listing.
This article sketches out the history of the future from 2030-2040, focusing on the dramatic impact of AI and robotics automation on the economy, job market (e.g. the end of white-collar work), geopolitics, and society.
OpenAI plans to charge up to $20K per month for specialized AI “agents” tailored for different applications like sorting sales leads and software engineering.
Epirus has raised a $250 million Series D round, putting its valuation over $1 billion and making it one of the “unicorn” defense tech companies, alongside others like Anduril and Shield AI.
CoreWeave, a cloud computing company, is in talks to acquire Weights & Biases, an AI startup, for around $1.7 billion.
Microsoft has created a new consumer AI arm focused on Mustafa Suleyman's vision of an "AI companion" that is emotionally aware, in a race to build this before competitors.
The U.S. Energy Secretary declared that the AI race with China is a “Manhattan Project 2” — a critical, worldwide technology competition that the U.S. must win, just like the original Manhattan Project to develop nuclear weapons.
The tests by Nvidia and Broadcom on Intel's 18A manufacturing process indicate that major chip designers are moving closer to potentially committing hundreds of millions of dollars in manufacturing contracts to Intel, which could provide a much-needed revenue boost and endorsement for Intel's struggling contract manufacturing business.
Anthropic has raised $3.5 billion at a $61.5 billion post-money valuation.
TSMC plans to invest $100 billion to build 3 new chip plants, 2 packaging plants, and an R&D center in the U.S.
Ramp has finalized a $150 million secondary deal, where employees and some early investors can cash out. The financing values the company at $13 billion. Khosla Ventures, Thrive Capital and General Catalyst all bought shares in the deal.
The International Energy Agency (IEA) expects global energy demand to increase in 2023 for the first time in years.
After years of speculation, there’s genuine growth of GenAI hiring — from virtually zero in mid-2023 to 1 in 300 of all US job postings today.
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