No one should be able to order a bioweapon through the mail. @IFP & @JoinFAI are proud to co-lead an open letter calling for mandatory DNA synthesis screening & recordkeeping. Signatories include: - Sam Altman, CEO & Co-Founder, OpenAI - Dario Amodei, CEO & Co-Founder, Anthropic - David Baker, Director, Institute for Protein Design; 2024 Nobel Prize in Chemistry recipient - Patrick Collison, CEO & Co-Founder, Stripe - Paul Graham, Founder, Y Combinator - Demis Hassabis, CEO, Google DeepMind; 2024 Nobel Prize in Chemistry recipient - Emily Leproust, CEO & Co-Founder, Twist Bioscience - Lawrence Lessig, Roy L. Furman Professor of Law and Leadership, Harvard Law School - Gerald W. Parker, former Special Assistant to the President for Biosecurity and Pandemic Response - Mustafa Suleyman, CEO, Microsoft AI - Alex Tabarrok, Professor of Economics, George Mason University - Alexandr Wang, Chief AI Officer, Meta; Founder, Scale AI - Christine E. Wormuth, President & CEO, Nuclear Threat Initiative; 25th Secretary of the Army Read the letter and see the full list of signatories: screendna.org Many DNA synthesis companies voluntarily screen orders to mitigate biosecurity risks, but no law requires them to do so. Leaders in AI, biotech, life sciences, national security, and the nucleic acid synthesis industry agree that Congress should act to strengthen safeguards against biological threats. @deanwball put it well in the WSJ: “If you’re synthesizing the stuff that yields biological life and viruses, we’re asking you to screen to see whether it is dangerous in some way. That seems like a reasonable thing for society to insist upon.”

At @IFP, we’ve spent the past 3 years thinking about all the different ways the US government & philanthropy fund R&D. Until now, R&D funders haven’t had a systematic way to match the innovation problem to the right funding tool. We built THE ATLAS OF INNOVATION to fill that gap. atlasofinnovation.org Alongside @UChi_MSA, we’ve boiled down thousands of hours of research into a handful of questions covering how much the R&D funder knows about: - the problem they want to solve - the solution it should have - the team that should build the solution Why the Atlas matters: The US government spends close to $200 billion every year on R&D. And after the Anthropic and OpenAI IPOs, there will be hundreds of billions of dollars in new philanthropic giving. Choosing the correct funding approach to the social problems they’re trying to solve will mean the difference between success and failure. For example, NSF research grants have helped seed breakthroughs from MRI machines to search engines, but grants aren’t built to deliver the kind of industrial speed and scale that a project like Operation Warp Speed required. Picking the wrong funding approach can leave programs behind schedule, over budget, or without anything to show for all the money they spent. How we built the Atlas: 1. We began by creating a matrix of dozens of considerations that a thoughtful policymaker or funder would ideally weigh before deciding how to fund a project. 2. We looked at every major funding approach, from grants to R&D tax credits to advance market commitments, analyzing when they work well and when they fail to meet the mission. 3. We spent months deep in the weeds of contract theory and incentive design, looking at historical examples and the state-of-the-art research in innovation economics. 4. We then worked to turn that research into a tool that time-strapped policymakers and philanthropic funders could rely on at the start of an innovation funding cycle. 5. Three years later, we are launching just that: a new (and visually stunning) website to help funders decide how to best incentivize innovation. And all they have to know… is what they currently know about their innovation goal! The Atlas takes care of the rest. How to navigate the Atlas: Answer questions about your goal to find the funding approach aligned with the information you have. Each funding mechanism has its purpose for particular technologies and specific moments in development. There shouldn’t be an ARPA for every field, just like we don’t need a prize or AMC for every innovation. The Atlas helps you navigate those tradeoffs.

Everything happens at the right time, in the right way...

I’m hiring a Member of Technical Staff at IFP. Your job will be to build software that allows us to operate with the effective capacity of a think tank 10 times our size. If you care about reforming US policy, I think this is one of the highest leverage roles available: you’ll be directly amplifying the work of our extremely cracked and growing team of 35. Given how important this job is, we will pay a $5,000 reward for any referral that results in a hire. More on the role: I expect this will be a hard role to fill, for a few reasons: 1. You have to believe US policy is the most important lever for impact There are plenty of opportunities in the private sector for engineers to have a significant impact. But technical talent in public policy is far more neglected, and often much higher leverage. IFP’s mission is to reform US policy to drive breakthrough discoveries, attract top talent, and expand our nation’s capacity to build. We measure our efficacy by our counterfactual policy impact: whether we create good policy outcomes that would not have otherwise happened. The software you build will directly affect the rate at which we can do this. The work you help us do faster and better will be read in the Oval Office, will shape the direction of billions in federal $, and will directly influence geopolitical strategy. We need someone in this role who internalizes how important this is. 2. You have to want to deeply understand what effective policy work looks like Many tasks in policy research and advocacy are time-consuming but basic text-to-text translation tasks, like simplifying results from academic papers, summarizing public comments on new regulations, and recording information about contacts from meeting notes. This work is necessary to produce good policy outcomes, but laborious. One way to understand this role is by looking at the way progress in AI capabilities has shifted the job of a programmer away from writing code and more towards specifying requirements and verifying the work of AI agents. In this role, you’ll do the same for policy work, moving the focus of our team away from basic natural language manipulation tasks and towards strategy, deep research, and policy engagement. A crucial part of this work is identifying which parts of policy research and advocacy can be effectively automated with frontier models without compromising quality, and continually retooling to adapt to the latest state of the art. The ideal candidate is someone who cares about building tools that people love to use and who can work effectively with our policy teams to understand their goals, processes, and constraints. 3. You have to be able to build a wide variety of great software Your projects will vary widely, from building agent scaffolds to custom CRM tooling to deployment pipelines for maintainable, performant microsites (check out the full job description for more). The right person will have led the design and delivery of complex user-facing products across the full stack, know how to ship quickly while building maintainable tech, and understand the trade-offs inherent in your design choices. – This role is open to both remote work and people able to work out of our office in Washington, DC, with the latter being preferred. The salary range for this role is $165,000 to $245,000. Here’s the full JD and link to apply: ifp.org/opportunity/member-o… Applications close May 31st.

🚨 We're hiring at @IFP! We need an Operations Coordinator with a can-do mindset who's excited to support our innovation policy mission. Minimum salary: $75,000 generous benefits Reward: $3,000 for any referral that results in a hire More details: ifp.org/opportunity/operatio…

REQUEST FOR PROPOSALS What do we need to build to prepare the world for advanced AI? >$25 billion is about to flow into AI resilience and AI-for-science from the OpenAI Foundation, the Chan Zuckerberg Initiative, and other major funders. But there's no shovel-ready list of the essential projects to build, and no critical mass of builders ready to execute. We're trying to fix that with The Launch Sequence, a collection of concrete projects to accelerate science, strengthen security, and adapt institutions to future advanced AI. We're opening up The Launch Sequence for new pitches. We'll help you develop your idea, connect you with funders, and get it built. $10,000 honorarium for published proposals. 🔗 Read the RFP and submit a short pitch (200–400 words): ifp.org/rfp-launch We’re looking for short pitches in three areas: 1. Accelerating science: What do researchers need to make breakthroughs with AI that markets and conventional grants won’t fund fast enough? 2. Strengthening security: What tools, technologies, or orgs can help ensure rapid AI advances don't undermine national security and public safety? 3. Adapting institutions: How do our institutions need to evolve to help society adapt to AI-driven change while preserving human agency? Our advisory panel: – @woj_zaremba, OpenAI co-founder – @tkalil2050, CEO of Renaissance Philanthropy – @matthewclifford, Co-founder & Chair of Entrepreneurs First, founding Chair of ARIA On top of the $10,000 honorarium, we offer a $1,000 bounty for pitching an idea we hadn’t heard before (if we publish it), and for every successful referral. Submissions are rolling, but we'll prioritize early pitches (within the next few weeks) and start reviewing immediately.

REQUEST FOR PROPOSALS What do we need to build to prepare the world for advanced AI? >$25 billion is about to flow into AI resilience and AI-for-science from the OpenAI Foundation, the Chan Zuckerberg Initiative, and other major funders. But there's no shovel-ready list of the essential projects to build, and no critical mass of builders ready to execute. We're trying to fix that with The Launch Sequence, a collection of concrete projects to accelerate science, strengthen security, and adapt institutions to future advanced AI. We're opening up The Launch Sequence for new pitches. We'll help you develop your idea, connect you with funders, and get it built. $10,000 honorarium for published proposals. 🔗 Read the RFP and submit a short pitch (200–400 words): ifp.org/rfp-launch We’re looking for short pitches in three areas: 1. Accelerating science: What do researchers need to make breakthroughs with AI that markets and conventional grants won’t fund fast enough? 2. Strengthening security: What tools, technologies, or orgs can help ensure rapid AI advances don't undermine national security and public safety? 3. Adapting institutions: How do our institutions need to evolve to help society adapt to AI-driven change while preserving human agency? Our advisory panel: – @woj_zaremba, OpenAI co-founder – @tkalil2050, CEO of Renaissance Philanthropy – @matthewclifford, Co-founder & Chair of Entrepreneurs First, founding Chair of ARIA On top of the $10,000 honorarium, we offer a $1,000 bounty for pitching an idea we hadn’t heard before (if we publish it), and for every successful referral. Submissions are rolling, but we'll prioritize early pitches (within the next few weeks) and start reviewing immediately.

NSF is launching one of the most ambitious experiments in federal science funding in 75 years. The program is called Tech Labs, and the goal is to invest ~$1 billion to seed new institutions of science and technology for the 21st century. Instead of funding projects, the NSF will fund teams. I’m in the @WSJ today with a piece on why this matters (gift link): wsj.com/opinion/science-fund… Here’s the basic case: 1) Most federal science funding takes the form of small, incremental, project-based grants to individual scientists at universities. 2) The typical NSF grant is ~$250k/year to a professor with a couple of grad students and modest equipment over a few years. This is a perfectly reasonable way to fund some science, but it's not the only way. 3) A healthy portfolio needs more than one instrument. Project-based grants are like bonds: low-risk, steady, safe. But no one trying to maximize long-run returns would put 70% of their portfolio in bonds. 4) Yet that's basically what our civilian science funding portfolio looks like. Around 3/4ths of NSF and NIH grant funding is project-based. 5) Tech Labs is NSF's attempt to diversify that portfolio. The Tech Labs program is aiming for: - $10-50 million/year awards per team - 5 year commitments - Measuring impact through advancement up the Tech Readiness Level scale rather than papers published - Up to ~$1 billion for the program - Supporting research orgs outside traditional university structures 6) Scientific production looks very different than it did when the NSF launched 75 years ago. The lone genius at the chalkboard can only do so much. Frontier science tech today is increasingly team-based, interdisciplinary, and infrastructure-intensive. 7) The team behind AlphaFold just won the Nobel Prize in Chemistry. It came from DeepMind, an AI lab with sustained institutional funding and full-time research teams. It would be near-impossible to fund this kind of work on a 3-year academic grant. 8) Same pattern at the @arcinstitute (8-year appointments, cross-cutting technical support teams) and @HHMIJanelia (massive infrastructure investments to map the complete fly brain). Ambitious science increasingly needs core institutional support, not a series of project grants stapled together. 9) Similarly, Focused Research Organizations (@Convergent_FROs) have showcased a new model supporting teams with concrete missions and predefined milestones to unlock new funding. 10) There’s a whole ecosystem of philanthropically-supported centers doing amazing research, like the Institute for Protein Design, the Allen Institute, the Flatiron Institute, the Whitehead Institute, the Wyss Institute, the Broad — the list goes on. 11) But philanthropy can’t reshape American science alone. The federal government spends close to $200 billion each year on research and development, an order of magnitude more than even the largest foundations. 12) If we want to change how science gets done at scale, federal funding has to evolve. And the NSF and NIH don’t have dedicated funding mechanisms to support or seed these sorts of organizations. 13) Earlier this year, I started working on a related framework called “X-Labs” that built on all this exciting institutional experimentation that’s been happening within the private and philanthropic sectors. It’s time for the federal government to step into the arena: rebuilding.tech/posts/launch… 14) Traditional university grants are still important for training the next generation of scientists and for certain kinds of curiosity-driven work. But after 75 years of putting nearly everything into one model, we should try something different. 15) And key program details are still being developed! You can reply to the Request for Information with suggestions or feedback on how to design this program here: nsf.gov/news/nsf-announces-n… 16) Science is supposed to be about experimentation. Science funding should be too.

The US has reportedly decided to approve exports of NVIDIA’s H200 chip to China. This gives Chinese AI labs chips that outperform anything China can make until ~2028. How big a deal this is depends on how many we export. Thread with key charts from our new report...

I know this is politically a loser issue, neither the right or the left really care about amrtican technical dominance, probably want to see us suffer, but this is utterly insane