我们大多数人都曾想过离开一份做了多年的工作。现在，一位诺贝尔奖得主科学家宣布他正是这样做的。CNBC于6月19日报道称，AI科学家约翰·贾珀在X上宣布，他将加入AI初创公司Anthropic。他因共同创建AlphaFold——一种能预测蛋白质结构的AI系统——与谷歌的德米斯·哈萨比斯共同获得了2024年诺贝尔化学奖。哈萨比斯在回复该帖子时给予了赞扬。
Most of us have often wondered about leaving a job we have had for years. Now a Nobel Prize-winning scientist has announced he is doing just that. CNBC reported on June 19 that AI scientist John Jumper announced on X that he is joining AI startup Anthropic. He shared the 2024 Nobel Prize in Chemistry with Google's Demis Hassabis for co-creating AlphaFold, an AI system that predicts protein structures. Hassabis responded to the post with praise.
CNBC称，这是这家大科技巨头AI研究部门最新的一次高调人才流失。这一决定是在争夺顶尖AI人才的竞争中做出的。约翰·贾珀是谁，他创造了什么贾珀曾在谷歌DeepMind担任高级研究科学家，CNBC认为他离开公司令人惊讶。据CNBC报道，贾珀因成为AlphaFold的共同发明者而广为人知，该系统已对超过2亿种蛋白质结构进行了预测。
This is the latest high-profile exit from the AI research unit of the Big Tech giant, CNBC says. The decision comes amid competition for top AI talent. Who John Jumper is and what he createdJumper worked at Google DeepMind as a senior research scientist, and his departure from the company was considered surprising by CNBC. Jumper became well-known for being a co-inventor of AlphaFold, a system that has already made predictions about more than 200 million protein structures, according to CNBC.
同一报道称，它已将生物和医学研究的时间缩短了数年。这些说法很有力，因此有必要看看其背后的研究。有一项发表于2021年的《自然》研究，贾珀被列为第一作者。AlphaFold研究发现了什么该研究指出，蛋白质对生命至关重要，了解其结构有助于揭示其工作原理。作者称，解析单个蛋白质的结构可能需要数月甚至数年的工作。
The same report says it has cut years off biological and medical research. Those are strong claims, so it is worth looking at the research behind them. There is a Nature study published in 2021, and Jumper is listed as the first author. What the AlphaFold study foundThe study notes that proteins are essential for life and that knowledge of their structure can shed light on how they work. According to the authors, solving the structure of a single protein can take months or even years of work.
从氨基酸序列预测蛋白质三维结构一直是困扰科学界50多年的长期挑战。作者将AlphaFold描述为第一种能常规以原子级精度预测蛋白质结构的计算方法，即使在没有已知相似结构的情况下也能做到。作者表示，他们开发了一个完全重新设计的神经网络模型版本。该设计借鉴了关于蛋白质形状的物理和生物学知识。
Predicting protein 3D structure from amino acid sequence has been a long-standing scientific challenge for more than 50 years. The authors describe AlphaFold as the first computational method that can regularly predict protein structures with atomic accuracy, even when no similar structure is known. The authors say they developed a completely redesigned version of their neural network model. The design draws on physical and biological knowledge about protein shape.
该研究补充指出，需要准确的计算方法来填补已知蛋白质结构的空白。在极具挑战性的CASP14测试中，其预测结果在大多数情况下与实验确定的结构具有可比性。该测试名称代表第14届蛋白质结构预测关键评估。该研究本身测试的是预测准确性，而非医疗结果。《财富》杂志报道指出，AlphaFold对药物发现的影响尚待证实，Jumper后来表示，后续模型更有可能在那里发挥直接作用。
The study adds that accurate computational methods are required to fill the gap in known protein structures. In the highly challenging CASP14 test, its predictions were competitive with experimentally determined structures in most cases. The test name stands for the 14th Critical Assessment of Protein Structure Prediction. The study itself tests prediction accuracy, not medical results. A Fortune report notes that AlphaFold's impact on drug discovery is yet to be proven, and Jumper said later models are more likely to play a direct role there.
Hassabis的表态与我们仍不了解的情况Hassabis直接回复了Jumper的帖子，因此这次交流是公开的。CNBC报道称，他说AlphaFold改变了世界，并向该领域展示了AI能为科学和医学做什么。Jumper在帖子中称Google DeepMind是一个“特别的地方”，并表示他仍然好奇它接下来会发现什么。然而，离职原因尚未明确。AI人才争夺战愈演愈烈CNBC描述了一场激烈的人才争夺战。
What Hassabis said and what we still don't knowHassabis responded directly to Jumper’s post, so the exchange was public. CNBC reported that he said that AlphaFold changed the world and showed the field what AI could do for science and medicine. Jumper called Google DeepMind a “special place” in his post and said he was still curious to see what it finds next. However, the reason for leaving hasn’t yet been made clear.A fierce race for AI talentCNBC describes a fierce talent war.
Meta、Alphabet、Anthropic和OpenAI都在争夺顶尖研究人员，以构建下一代人工智能系统。Jumper的离职发生在Noam Shazeer宣布将离开Google加入OpenAI几天之后。CNBC称Shazeer是Google工程副总裁及其Gemini AI模型的联合负责人。
Meta, Alphabet, Anthropic and OpenAI are all fighting for top-level researchers in their race to build next-generation artificial intelligence systems. Jumper’s exit comes days after Noam Shazeer said he would leave Google for OpenAI. CNBC calls Shazeer a vice president of engineering at Google and co-lead of its Gemini AI models.
长话短说，最优秀的AI研究人员供不应求。对读者而言，最稳妥的结论是已确认的事实：一位诺贝尔奖得主在任职近九年后换工作。Jumper的AlphaFold研究于2021年发表在《自然》杂志上，该出版物仍是科学记录的一部分。
Long story short, the best AI researchers are in high demand. For readers, the safest takeaway is the confirmed facts: a Nobel winner is changing jobs after nearly nine years. Jumper's AlphaFold research was published in Nature in 2021, and that publication remains part of the scientific record.