Olly Perris

Terrible at doing the floss dance. All views mine.

[Trung Phan @TrungTPhan]

the key for maximizing horror is to watch Margin Call and The Big Short at the exact same time

[Olly Perris @ollyperris]

@JamesBlunt @AccidentalP

[OpenAI @OpenAI]

We’re releasing a broad range of new mathematical results produced by an internal frontier model.

We’ve been consulting with the independent Advisory Group on Mathematics and Artificial Intelligence at the Institute for Advanced Study, and we have drawn on their advice and public recommendations to inform how we release these results.

https://t.co/7N6TPlft1P

[Dario Amodei @DarioAmodei]

Today we announced the Claude-led discovery of a molecular machine that we suspect could represent a new gene editing mechanism. Its precise function, biotechnological utility (if any), or level of significance is not yet clear, but at minimum it is work I would have been proud to do as a PhD student. The work was done mostly, though not entirely, by Claude: our life sciences team suggested a broad area of research, Claude read through the literature and a bunch of genome data and discovered something interesting, then Claude proposed experiments to verify the discovery and our team carried them out.

It’s easy to dismiss this as a one-off or curiosity, but we’ve repeatedly seen a pattern where AI performance in new intellectual domains goes from weak to superhuman in a matter of a few years. In 2023 models struggled to do math at the level of an average high-school student. In 2024 they started to do well on math competitions for the best high-schoolers in the country, in 2025 they started to solve minor open problems, in early 2026 more significant open problems, and in late 2026 they are beginning to solve the top few open problems in all of mathematics. We believe AI for biology is on a similar exponential trend.

The main difference between biology and mathematics, of course, is that math can be done purely theoretically, while biology requires experimentation. Some have used this to draw the conclusion that AI’s utility in biology will be limited. We think this is wrong. As we’ve demonstrated today, humans can collaborate with AI to perform the experiments, validate key results in a few weeks and, if necessary, work with the AI to iterate on what they find. Eventually it may even be possible for Claude itself to safely perform the experiments by autonomously controlling lab equipment, with appropriate safeguards in place, but we aren’t doing that today (our lab is also a BSL1/BSL2 facility that doesn't handle materials dangerous to humans).

More broadly, biomedical advancement has many stages — from fundamental biology discoveries, to translational research, to drug discovery, clinical trials, and finally the actual delivery of medicines and health care to patients. We are also interested in these later stages, but even simply accelerating the first stage of fundamental biological discoveries has the potential to speed up and broaden the entire pipeline. Improving our understanding of biology and sharpening biologists’ tools can drive forward all of the later stages, for example by identifying new drug targets, finding new therapeutic modalities, allowing for more precise measurement, and speeding up the experimental loop which itself further accelerates our understanding of biology. This will not in itself speed up clinical trial times, but if it succeeds it could greatly increase the number of promising candidates that go into the pipeline — an increase in throughput even though latency remains.

In Machines of Loving Grace, I wrote about AI’s potential to “cure most diseases in 5-10 years” — a goal that sounds impossible, but one I believe is just barely possible if AI is applied to every stage of the pipeline. The first step is showing that AI can first help with, and then drive, biological discoveries.

Claude’s discovery is the latest in a line of related prior work that goes back decades, beginning with systems like CRISPR, and continuing with discoveries like the bridge recombinase and VIPR in the past few years. Recently, there has been heightened interest in systems based on reverse transcriptase (RT) enzymes, the enzyme underlying the system Claude identified. And most recently, a Stanford team working independently described a novel RT system with an associated non-coding array that is in some ways similar to the one Claude found, though they are distinct systems that evolved independently from each other. I believe that we’re at the very beginning of finding such systems and developing them into powerful tools for biotechnology.

I’m proud of the resources Anthropic has invested in accelerating the public benefits of AI through the life sciences, and we’re aiming both to grow our life sciences team and to work with other scientists to extend this approach to a broad range of problems. If you have a proposal for a research collaboration or are interested in joining our life sciences team, please reach out.

[Sholto Douglas @_sholtodouglas]

put it in a museum

[Ejaaz @cryptopunk7213]

the model that solved this was 11 days old. it solved it in 5.

we’re talking about a math problem that’s been stumping humans for 100+ years.

AI didn’t do this alone btw, this is the result of 200+ years of study and shared research. what tristan and levent released september 1st undoubtedly contributed to the solution but the craziest part is AI took us over the finish line

quite beautiful really - this was very much a human-AI effort

[Olly Perris @ollyperris]

@AndreasSteno Hmm.

[Andreas Steno Larsen @AndreasSteno]

https://t.co/aPcuRpjaSf

[Cameron Bradbury 카메론 @CamJBradbury]

My phone for no reason whatsoever:

[Mukhtar @I_amMukhtar]

The Internet is undefeated.

[Olly Perris @ollyperris]

I see Wordle chose violence this morning.

[Olly Perris @ollyperris]

#PANENG

[Olly Perris @ollyperris]

@Medivhus I've had exactly the same issue. Something is wrong. @bcherny

[Olly Perris @ollyperris]

Info: ~600k/1m tokens context project. First prompt used ~35% of my usage as expected (to load the context in). Second follow-up prompt then used a further 50% when I'd expect c. 3-5%.

It's like it's forgetting the context and having to reload it? It's happened twice now.

[Olly Perris @ollyperris]

Something has happened to Claude's limits since the Fable introduction yesterday. In Claude Code (Opus 4.7, Max, Pro plan) I sent one prompt which used a typical amount. Fine. But the second (short) prompt then ate 50% of my 5 hr limit.

@bcherny Is there a "second prompt" bug?

[Olly Perris @ollyperris]

@OSWreview Dusty/Sapphire's entrance at WM6!

[Olly Perris @ollyperris]

🤯🤯🤯

[Ejaaz @cryptopunk7213]

yeah so this is insane

24 year old turned $225M into $5.5B in <12 months. dug into his recent investments and… holy fuck

- MASSIVE $885M position in Bloom Energy (specialises in portable energy turbines for… you guessed it - ai data centers) - this 1 position is 20% of the entire fund lol

- massive SHORT position on Infosys. he’s betting claude code, codex are going to replace outsourced IT work (he’s right)

- added $300M to his corweave position totalling $700M (someones gotta run those gpus)

- aggressively pivoted investments into electrical and energy infra (aka AI’s biggest constraint right now)

- dumped $100Ms of NVIDIA and Intel positions.

- aggressively buying bitcoin mining companies and re-purposing them for ai data centers. (cipher, bitdeer)

- fund up $1.5B in the last 3 months (+35% last quarter)

- now owns 10% of core scientific (levered bet on coreweave 😂)

He outperformed the S&P500 8X in the funds first 6 months. fucking goated.

[Olly Perris @ollyperris]

Been playing with Claude for some coding stuff and oh my holy hell.

[steve hsu @hsu_steve]

OpenClaw mass install in Shenzhen.

[Olly Perris @ollyperris]

@jonaswillett1 @cornerapp @grok are any of the companies mentioned in this post publicly listed anywhere?

[Olly Perris @ollyperris]

@julianHjessop And possibly because additional defence spending may have to come from borrowing.