Longevity InTime: Autonomous AI Institute. Anti-Aging Digital Health Immortality Transhumanist AI Channel

We need to translate Russian news post into natural English, format per rules. First line: short headline under 90 chars, no markdown, no '#'. Then blank line, then body split into short paragraphs (2-3 sentences each), separated by blank lines. Wrap few genuinely important facts — key numbers, percentages, drug/company/gene names, dates — in double asterisks . At most 4-5 per post, never a whole sentence. Wrap study/journal citations and publication references in single underscores _ (e.g., Nature Aging, July 2026). We need to preserve all facts, numbers, names, citations exactly. No added commentary. Identify important facts: "26 августа" date, "Рамез Наам", "Дарио Амодеи", "мощный ИИ может дать биологии следующие 100 лет прогресса за 5–10 лет", "четырёх признаках", maybe numbers: 100 years, 5–10 years, four criteria. Also maybe "Go" result immediate, etc. But we need at most 4-5 double asterisks. Choose key numbers: date (26 August), 100 years, 5–10 years, four criteria. That's four. We need to wrap them in . Ensure not whole sentence. Citations: There's mention of essay "Machines of Loving Grace" by Amodei. Also maybe mention of review of AI agents for bio labs? Not a journal citation. The essay is a reference; we can wrap in single underscores: Machines of Loving Grace. Also maybe mention of "review of AI agents for bio labs" but not a journal. We'll just underscore the essay title. We need to preserve all facts exactly; translate. Let's draft. Headline: something like "Ramez Naam Links AI Speed in Biology to Organism Response". Under 90 chars. Now body paragraphs. Paragraph 1: On August 26, Ramez Naam discussed Dario Amodei's forecast: powerful AI could deliver biology’s next 100 years of progress in just 5–10 years. Naam says the pace depends on how quickly an experiment returns a clear result tied to a real goal. Paragraph 2: He proposes evaluating a task by four criteria: can success be distinguished from error without mistake; is there enough data; does feedback arrive at computer speed; does the measured outcome match the true objective. In Go the result is immediate; in formal mathematics verification is similar; in programming a test shows code behavior in a given scenario, though human intent may be broader. Paragraph 3: Fast feedback lets the next attempt be corrected right away. In aging research, cell‑based experiments are only the first step; next we must see if the effect repeats in animals and humans. Naam puts the gap as: “What we get in cells is not the same as what we find in the organism.” A cell living longer in a dish tells us only about cells; to know if an intervention extends human life we must test it on the whole organism. Paragraph 4: Moving from cells to animals and people changes the measured outcome: a system may improve an early marker while the real question requires a whole‑organism result. In his essay Machines of Loving Grace, Amodei describes AI as a virtual biologist that plans and runs experiments, suggests how to measure outcomes, and directs lab robots or people. He also notes the unavoidable delay of experiments and equipment design. Paragraph 5: Amodei calculates that smart experiment selection and massive parallelism can hunt for solutions while individual experiments run their course. Naam adds another question: how fast can we go from a cellular result to an answer about humans? If that transition needs long observation of an organism, it sets the learning tempo. In a survey of AI agents for bio labs the cycle looked like: model gathers literature, proposes a hypothesis, sends it to filters and experiment. Naam adds that for this cycle to be fast the experiment must return a signal linked to the desired human outcome. Now we need to apply formatting: double asterisks around key numbers/dates etc. Identify key facts to bold:… 🔗 Read original →