Bayesian data scientist and early machine learning researcher, later drifting into NLP. Worked in various universities and labs. Into healthy living.

Melbourne, Australia
Joined December 2009
Prof. Wray Buntine retweeted
Massive. New Harvard study finds that AI-written paper reviews now beat the best human peer reviews on every measure the authors tested. Peer review is slow and often misses errors. Earlier studies concluded AI should only assist human reviewers, not replace them. They used 134 reviews from rapidPeer, a Harvard service that pays expert reviewers well. Claude Opus 4.8 reviewed the same 1124 papers, and GPT-5.5 plus 3 former journal editors judged the pairs blind. GPT-5.5 picked the AI review in all 132 decided pairs, and the editors picked it 87% of the time. Only 5.5% of the AI's claims about the paper were wrong, versus 15.9% for the human reviews. Teams that depend on expert critique can now let AI do the first full review pass, and keep a human for the final decision.
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Prof. Wray Buntine retweeted
Jay Bhattacharya, director of the National Institutes of Health, has not been shy about his grand ambitions. He is seeking a second scientific revolution rooted in replicability, independent thinking, open inquiry, and an end to the abuse of science by interest groups. It’s a grand and inspiring vision but what hope is there of success? Scientific Change Is the Product of Truth Telling theepochtimes.com/opinion/sc… via @epochtimes
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Prof. Wray Buntine retweeted
BREAKING NEWS: Google Gemini launched a new feature called Guided Learning. Now you can use it to learn literally anything, step by step, like a personal tutor. Below we show you how to access it 👇
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「3年後にAGIが誕生すると分かっていながら,博士号を取り,ポスドクになり,大学教授になる計画を立てているんですか?」 Anthropicの研究者が,博士課程の学生たちに「あなたたちのキャリアプランはもう存在しない」と告げた講演が話題です。 拡散モデルの発明者でもあるJascha Sohl-Dickstein氏(Anthropic)の講演『Advice for a young investigator in the first and last days of the Anthropocene(人新世の最初と最後の日々における若手研究者へのアドバイス)』を紹介します。 youtube.com/watch?v=3LZN2UUx… 人類が主役だった地質年代(人新世)が,AIの台頭によって極めて短い期間で幕を閉じるかもしれない ——そんな前提のもと,提示されたデータは強烈です。 ■ 突きつけられた冷徹なファクト モデル訓練の計算量は過去10年で約1000万倍に増加し,人間の脳が生涯で行う総計算量に迫っている。AIが単独で完遂できるタスクの時間スケールは,数ヶ月ごとに倍増している。ここ7ヶ月ほど,モデルは数学者が長年解けなかった未解決の「Erdős(エルデシュ)問題」を解き始めている。サンフランシスコでは「長いタイムライン(懐疑派)」とは「AGIは10年以内に来る」を意味している。2030年の計算量は2025年の約1万倍に達する見込み。 線形グラフで見れば,現在の劇的な進歩すら「まだゼロと区別がつかない平坦な初期段階にいる」というのが彼の主張です。 ■ 学生たちへのシンプルで容赦ないアドバイス 毎日AIを使え。指数関数の上にいれば,遅れを取ることはない。彼自身はClaudeを「実行力は天才だが、研究のセンスはかなり悪い大学院生」のように毎日使い,自分ではもうコードを一切書いていない。 計算量がスケールするほど良くなるプロジェクトを選べ。それ以外は,完成する前に解かれてしまう サットンの『苦い教訓』の通り,スケールに味方されるテーマを選ばなければ,2年かけた研究も完成する頃には次世代モデルのプロンプト一発で追い抜かれる。 キャリアを「安定したもの」として計画するのをやめろ。安全な選択肢は,もはや安全を買ってくれない 社会全体で大規模な破壊が起きるなら,ベースラインのリスク自体が高い。従来の「手堅い選択肢」は,もはや安全を担保してくれず,ただ潜在的なリターンを犠牲にするだけになる。 そして,最も印象的な一言がこれ。 「書くことは考えることだ(Writing is thinking)。書くことを外注すれば,考えることも外注することになる。」 コーディングや実行は徹底的にAIへ委譲しつつ,問題設定(センス)と思考の核(書くこと)だけは決して手放すな。 AGIのタイムラインを本気で信じているなら,キャリアの計画も本気でそれに合わせろという,極めてストレートなメッセージの講演を紹介しました。
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Prof. Wray Buntine retweeted
Burkina Faso has put beauty pageants on pause for now and instead held a science competition involving 84 young girls, who went up against each other in mathematics, physics and chemistry. The idea is to push STEM education and challenge the view that those subjects are only for men. The top five in each subject got prizes, with first-place winners receiving 2 million CFA francs, a motorcycle, a laptop and other rewards. Every finalist also received a scholarship and university support to help them build the skills the country will need going forward.
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Prof. Wray Buntine retweeted
In the future, "AI for Science" will be a meaningless expression. Every domain scientist will also be an AI scientist. It won't need a special title. A chemist who uses AI will just be a normal chemist.
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Prof. Wray Buntine retweeted
All faculty advertisements must include the line “A proven ability and willingness to be micromanaged is especially preferred in successful candidates.”
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Mostly common sense and current thinking, but a great reminder! Thanks.
Here is the full talk:
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What is TMLR doing under a 300% increase in submissions? - Suspensions of >150 authors - Publicly naming major violations - Submission quotas distinguishing slop patterns - Desk rejections 6% → 53%; focus on clarity - AI reviews evaluating soundness blog.tmlr.org/2026/adapting-…
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🤣😂😢😭 – at Melbourne, Victoria
学生がAIで生成した文章を教員が時間をかけて添削し、その助言を学生がまたAIに投げて改良された文章が納品される
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Prof. Wray Buntine retweeted
Abstract vs Full Paper
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Yeah ... what are we going to do. Something has to change in academic publishing – at Melbourne, Victoria
As an Editor, in past ~6mo, we are receiving an avalanche of unsolicited review articles (“scoping” “systematic”, narrative, NOS) on topics and ?s NO ONE EVER has asked and clearly with heavy AI lift. Even the cover letters all read the same…alarming and sad. #publishing
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Interesting because it's not STEM. – at Melbourne, Victoria
Political scientists and economists: we're looking for researchers with deep expertise to come work with us for a unique 4-month fellowship at @AnthropicAI. You'll work closely with us to evaluate, improve, and apply Claude's capabilities in your field. It's going to be extremely fun and interesting work, and definitely worth taking a short leave from your university for if you need to! More info here: job-boards.greenhouse.io/ant…
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Prof. Wray Buntine retweeted
How professors spend their time
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Prof. Wray Buntine retweeted
Your doctor cuts you off about 11 seconds after you start talking. Researchers literally timed it in a 2018 study. That number is why Google's new Lancet result is bigger than it looks. In the study, 98 real urgent care patients texted with Google's AI days before their appointment. No scans, no exam, no bloodwork, just an unhurried conversation about what was wrong. That alone put the correct final diagnosis on the AI's list 90% of the time. Sounds like magic until you learn what medicine has known for 50 years. Back in 1975, a British team published a study in the BMJ tracking which part of a visit actually produced the right diagnosis. The physical exam? The labs? Nope. In 82% of cases, the patient's story alone got the doctor there. Everything else mostly confirmed what listening had already found. So the playbook for accurate diagnosis has existed since 1975. Let the patient talk. Medicine just built a system where nobody has time to run it, and an 18-minute appointment with 11 seconds of uninterrupted patient talk was the result. Google didn't build a superhuman doctor. It built the first clinician in 50 years with enough time to use the method we already proved works. And my favorite detail buried in the study... physicians who read the AI's pre-visit summary said it changed how they treated the patient in over half of cases. Hand a doctor the full story before you walk in the room and you get different medicine. Turns out the most advanced medical instrument Google ever shipped is a conversation that doesn't get interrupted.
Today @TheLancet published our AMIE study with @BIDMC_Medicine, the first prospective study of patient-facing conversational diagnostics in a real clinic. AMIE is a research system people can chat with before doctors appointments. Testing AMIE outside the lab with real urgent care patients showed how technology can help gather medical histories safely. Clinicians reported that the summaries helped them prepare for visits in 75% of cases and influenced their approach to care in more than half. AMIE’s differential diagnoses also matched the doctors’ final diagnoses 90% of the time giving clinicians more time to focus on patient care. It’s Google’s first-ever paper in The Lancet’s main journal!
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Prof. Wray Buntine retweeted
Such an irony in the current times -- In the wake of AI's progress in fields with "verifiable" outputs, maths, arguably one of humanity’s most rigorous intellectual pursuits, faces an existential crisis. At the same time, many other "academic" areas in humanities continue to thrive on vague and abstract claims that I don't think AI (or humans) can ever define how to verify. :) Ironically, intellectual rigor becomes a liability, while intellectual fuzziness remains a survival strategy
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Prof. Wray Buntine retweeted
Replying to @BachFrancis
(1/7) I'd like to provide some additional context for the remarks that can be found in this interview. (2/7) My discomfort with the attention being paid to existential risk---and with the ongoing dominance of the public discussion of such risks by a few so-called thought leaders---is that there's an elephant in the room that is being missed. That elephant is the effect of all of this discussion on young people, and indeed the effect---beginning with social media a decade ago---of information technology on young lives broadly speaking. (3/7) I recently read an interview by Jill Lepore in which she reports on discussions that she had recently with a group of college students: "They had just three things to say. One, social media completely destroyed their childhoods. Two, AI is destroying their college education and their likely prospects for employment. And three, what the hell are we all doing?" To add a fourth bullet that I've heard in similar discussions: "I'm not going to have children, because the existential risk is just too high." (4/7) Please contemplate such a statement, those of you who think that it's OK that the public, widely diffused, discussion coming from seemingly authoritative figures is so adamant about existential risk. (5/7) Let me add that I have little interest in a debate about what "superintelligence" might mean, or whether we're currently seeing the emergence of superintelligence. For what it's worth, I would certainly agree that the solution of extremely challenging math problems (for example) exhibits a very impressive form of intelligence, although I would want to argue that such intelligence is impossible to dissociate from the collective of humans that provided data to the machine learning system (which itself has become a kind of collective). (6/7) Such philosophical debates are entertaining and even important, but when they then head in the direction of "when such superintelligence emerges, there's a good chance that it will want to kill all humans", I say "science fiction". Again, I don't think that it's bad to consider such thoughts, but I strongly believe that it's bad for society, and especially young people, for such thoughts, unaccompanied by any serious real-world analysis, to become a dominant form of discourse of the era. (7/7) We are damaging human lives, and the consequences of that damage will no doubt be a major theme of the next several decades.
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An article in @insidehighered argues that universities may be helping to create the research integrity problems they are trying to solve. The argument is simple: if we judge academic success largely by publication counts, journal prestige and citations, we should not be surprised when people find ways to maximise those numbers. That can mean salami-slicing research, citation gaming, purchased authorship, paper mills and, increasingly, AI-assisted fraud. The authors suggest a different approach: assess fewer papers, but assess them properly; broaden our definition of impact; and pay much closer attention to suspicious citation practices. Perhaps the bigger question is this: Are research integrity problems really just problems with individual researchers, or are they also a predictable consequence of the systems universities have created to measure academic success? Read the full articlle here: buff.ly/e3qvuzG
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Prof. Wray Buntine retweeted
This could be a game changer. Researchers just published a paper on a smart ring that can continuously monitor glucose, ketones, vitamin C, uric acid, lactate, and alcohol through sweat.
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Prof. Wray Buntine retweeted
GPT-6 Pro finds supposed errors in academic papers all the time, just as part of other work. Confirming the errors & learning their importance would still take a lot of time today, but it will get faster. We don't have the right mechanisms in place to deal a flood of corrections.
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