Sunnie Southern

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Anthropic's new study. How scientists are using Claude to accelerate research Across the examples, projects that used to take weeks or months are compressed into minutes or hours. Anthropic spoke with 3 labs where Claude is reshaping research—and starting to point towards novel scientific discoveries. The shared approach is connecting the model to databases and software, plus guardrails, so results stay verifiable. - Stanford’s Biomni bundles hundreds of biomedical tools so a Claude-powered agent can operate across 25 subfields from a plain-English request. In an early trial it completed a genome-wide association study (GWAS), which links genetic variants to traits, in 20 minutes instead of months, and separate case studies report it handled 450 wearable files from 30 people in 35 minutes versus 3 weeks. Biomni also analyzed 336,000 embryonic cells to recover known gene regulators and suggest new transcription factors, and it can be taught expert workflows as reusable skills when the default approach is wrong. - In another lab, they do CRISPR experiments, which means they turn off thousands of genes and see what breaks, but the hard part is interpreting huge piles of results. They built MozzareLLM, which takes groups of genes that seem related, tells what job they might share, flags which genes are poorly studied, and gives confidence levels so the lab knows what is worth chasing. When they tested multiple AI models, Claude did best, including correctly spotting an RNA modification pathway that other models wrote off as noise. A 3rd lab is using Claude to help choose which genes to test in smaller experiments, because 1 focused screen can cost over $20,000 and humans often pick targets by manual guessing in a spreadsheet. They built a map of known molecules and how they relate, then Claude navigates that map to propose gene targets, and they plan to test this on primary cilia and compare Claude’s picks to human picks and to a whole-genome screen. The big deal is speed plus scale, because it lets labs do more experiments, faster, with the same people and budget.

I've never felt this much behind as a programmer. The profession is being dramatically refactored as the bits contributed by the programmer are increasingly sparse and between. I have a sense that I could be 10X more powerful if I just properly string together what has become available over the last ~year and a failure to claim the boost feels decidedly like skill issue. There's a new programmable layer of abstraction to master (in addition to the usual layers below) involving agents, subagents, their prompts, contexts, memory, modes, permissions, tools, plugins, skills, hooks, MCP, LSP, slash commands, workflows, IDE integrations, and a need to build an all-encompassing mental model for strengths and pitfalls of fundamentally stochastic, fallible, unintelligible and changing entities suddenly intermingled with what used to be good old fashioned engineering. Clearly some powerful alien tool was handed around except it comes with no manual and everyone has to figure out how to hold it and operate it, while the resulting magnitude 9 earthquake is rocking the profession. Roll up your sleeves to not fall behind.

if you want to learn how to talk to LLMs, learn concepts, not prompts. lots of people ask me what prompts i use when talking to LLMs to have the conversations i do. truthfully, beyond a small set of things for e.g. research projects or synthetic data generations, i don't have any. i don't write prompts, i don't have a "prompt library," i very rarely go back to an old chat to copy word-for-word what i said previously. instead, i have a (mental) library of "useful concepts" for working with LLMs. attached image is an example - using "CEV" as a metaphor for "this thing but fully iterated forward into the future, fully realized" is a super handy shared metaphor with LLMs that are very familiar with LessWrong. but this isn't a "prompt," i don't copy this sentence into the chat from some text document, i just remember "CEV is a handy metaphor" and bring it up when relevant. other concepts are higher level, like different frames or conceptual models. Many, many canned jailbreaks you see that seem magical are just exploiting some aspect of the Three-Layer Model of predictive, persona, and surface layers. the obsession with prompts reminds me a bit of the older phenomenon of "script kiddies," a derogatory term in online programming circles for people who would copy-paste code they found online without really understanding how it works, and go bother the people who wrote the "codez" when their hodgepodge ball of pasted-together mud inevitably broke. ironically, LLMs and vibe coding have basically eliminated the script kiddie archetype, but created a new equivalent "promptoor" who does the same but with prompts. "i put the same thing into chatgpt and it gave me a totally different answer!" models are complex, and deep, and nobody has a full understanding of how they work. but they're not impossible to gain an intuition for, either. just like with the towering stack of modern programming abstractions that at first feels like a magical black box to the script kiddie yet eventually falls to practice and intuition, you can gain an intuition for models. you don't have to stick to canned prompts and templated jailbreaks. learn useful concepts, not fixed strings!

RIP prompt engineering ☠️ This new Stanford paper just made it irrelevant with a single technique. It's called Verbalized Sampling and it proves aligned AI models aren't broken we've just been prompting them wrong this whole time. Here's the problem: Post-training alignment causes mode collapse. Ask ChatGPT "tell me a joke about coffee" 5 times and you'll get the SAME joke. Every. Single. Time. Everyone blamed the algorithms. Turns out, it's deeper than that. The real culprit? 'Typicality bias' in human preference data. Annotators systematically favor familiar, conventional responses. This bias gets baked into reward models, and aligned models collapse to the most "typical" output. The math is brutal: when you have multiple valid answers (like creative writing), typicality becomes the tie-breaker. The model picks the safest, most stereotypical response every time. But here's the kicker: the diversity is still there. It's just trapped. Introducing "Verbalized Sampling." Instead of asking "Tell me a joke," you ask: "Generate 5 jokes with their probabilities." That's it. No retraining. No fine-tuning. Just a different prompt. The results are insane: - 1.6-2.1× diversity increase on creative writing - 66.8% recovery of base model diversity - Zero loss in factual accuracy or safety Why does this work? Different prompts collapse to different modes. When you ask for ONE response, you get the mode joke. When you ask for a DISTRIBUTION, you get the actual diverse distribution the model learned during pretraining. They tested it everywhere: ✓ Creative writing (poems, stories, jokes) ✓ Dialogue simulation ✓ Open-ended QA ✓ Synthetic data generation And here's the emergent trend: "larger models benefit MORE from this." GPT-4 gains 2× the diversity improvement compared to GPT-4-mini. The bigger the model, the more trapped diversity it has. This flips everything we thought about alignment. Mode collapse isn't permanent damage it's a prompting problem. The diversity was never lost. We just forgot how to access it. 100% training-free. Works on ANY aligned model. Available now. Read the paper: arxiv. org/abs/2510.01171 The AI diversity bottleneck just got solved with 8 words.

Author here – I've been using VS for months, and it still surprises me how well this works on everything. Ideation, simulation, multi-turn dialogue, creative writing. It all works! I've also been amazed by how great this makes LLMs as a creative partner. Some practical tips: 🧵

our livestream tomorrow at 10 am PDT will be longer than usual, around an hour. we have a lot to show and hope you can find the the time to watch!

4/ Great quarter, thanks to our employees around the world.  Read a full transcript of my remarks from today’s earnings call: blog.google/inside-google/…

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What a week at Cincy AI Week 2025! Thank you to the organizers, speakers, and fellow attendees for creating such a meaningful, community-driven experience. Until next time, Cincinnati! #CincyAIWeek #ViableSynergy #ThrivewithAI

There is a book on Amazon called "Modern AI Revolution" by Geoffrey Hinton. This is a scam. It has nothing to do with me and I wish Amazon would remove it.

GPT-4.5 is ready! good news: it is the first model that feels like talking to a thoughtful person to me. i have had several moments where i've sat back in my chair and been astonished at getting actually good advice from an AI. bad news: it is a giant, expensive model. we really wanted to launch it to plus and pro at the same time, but we've been growing a lot and are out of GPUs. we will add tens of thousands of GPUs next week and roll it out to the plus tier then. (hundreds of thousands coming soon, and i'm pretty sure y'all will use every one we can rack up.) this isn't how we want to operate, but it's hard to perfectly predict growth surges that lead to GPU shortages. a heads up: this isn’t a reasoning model and won’t crush benchmarks. it’s a different kind of intelligence and there’s a magic to it i haven’t felt before. really excited for people to try it!

@ViableSynergy Thrilled to announce @viablesynergy's transformation to a strategic AI services and solutions company. We're committed to helping visionary leaders create immediate impact and lasting value. Learn more at at viablesynergy.com #ViableSynergy #ThrivewithAI

@ViableSynergy Exciting news- @ViableSynergy is launching new AI services on Monday! We’ve been building AI services that help visionary leaders navigate the AI revolution with confidence. Can’t wait to share more when we go live! Stay tuned. #ViableSynergy #ThrivewithAI

@ViableSynergy trying to get logged back in to my business account. Can't remember which business email I used.

@AP Hello, I was contacted by an organization called PicRights demanding money. It seems like scam. I have used your website to contact you. Please advise. Thank you.

@CKaster Hello Carolyn, I was approached by an organization demanding money called PicRights for one of your photos. It seems like a scam. Are you working with them? I have also contacted the @AP. Thank you!

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