Podcasts about genius makers

Eric Topol (00:00):Hello, this is Eric Topol, and I'm thrilled to have a chance to have a conversation with Magdalena Skipper, who is the Editor-in-Chief of Nature. And a historic note. Back in 2018, she became the first woman editor of Nature in its 149 years, and only the eighth editor of all times. Having taken over for Philip Campbell, who had been previously the editor for 22 years, we're going to ask her if she's going to do 22 or more years, but we're going to have a fun conversation because there's so much going on in medical publishing, and I think, you know, that Nature is the number one cited science journal in the world. So, welcome, Magdalena.Magdalena Skipper (00:41):Thank you very much. Real pleasure to be here and chatting with you today, Eric. Thank you.How COVID-19 Affected NatureEric Topol (00:47):Well, you know, we're still, of course, in the pandemic world. It's obviously not as bad as it had been, but there's still things going on with new variants and Long Covid, and it's not, the virus isn't going away. But first thing I wanted to get into was how did Nature handle this frenetic craziness? I mean, it was putting out accelerated publications on almost a daily or weekly basis and putting out like a speed, velocity of the likes that we've not seen. This must have been really trying for the whole crew. What, what do you think?Magdalena Skipper (01:29):It was! And, you know, the first thing I, I think I will recognize two things at the same time. So the first one, as you say, at a time, such as the pandemic, but actually at any point when there is a, a new health emergency that is spreading, especially something as unknown, as new as, as it was the case with SARS-CoV-2. And of course, in the beginning, we really knew nothing about what we were facing if speed is of the essence, but equally what's truly important is of course, the rigor itself. So that combination of needing to publish as quickly as possible, but at the same time as rigorously evaluating the papers as possible, that was actually quite a challenge. And of course, you know, what we sometimes forget when we talk about, well, researchers themselves, but also editors and publishers is of course, as individuals, as human beings.(02:33):They are going through all the trauma, all the constraints associated with various lockdowns concerns about the loved ones, perhaps those ones who are in the care. You know, in many cases of course there would've been the elderly who are individuals would've been concerned by or indeed children, because of course, schools in so many places were. And all the while, while we were dealing with these very human, very ordinary daily preoccupations, we were very focused on the fact that we had a responsibility and a duty to publish papers and evaluate them as quickly as possible. It really was an extraordinary time. And, and you know, one other thing I should emphasize is, of course, it's not just the manuscript editors who evaluate the research, it's the reporters on my team as well who are going out of their the way to find out as much information to report as robustly, find as many sources to, to interview as possible.(03:44):And, and, you know, I also have to mention colleagues who work on production side of nature actually make Naturehappen, be published online on a daily and then of course weekly basis. And literally from one week to the next all our operations had to be performed from home. And it's really remarkable that the issue was not late. We published the issue, just as you know, from as lockdowns came in. And as it happens, the production side of Nature is mainly based in, in London. So most of that team effectively found themselves not being able to go to the office effectively from one day to the next. So it really was an extraordinary time and, and a time that as I said was, was a time of great responsibility. But looking back on it, I'm actually incredibly proud of, of my team, what, what they achievedEric Topol (04:47):Did they hold up? I mean, they hadn't, they didn't get burnout from lack of sleep and lack of everything. Are they still hanging in there?Magdalena Skipper (04:55):So they are hanging in there. You'll be glad to hear. But I think, very importantly, we were there for one another insofar that we could be, of course, we were all at home remotely. We were not meeting, but we had virtual meetings, which were regular of course in as a whole team, but also in, in subgroups as we sub-teams, as we worked together, that human contact in addition to of course, loved ones and families and friends, that human contact in a professional setting was, was really, really necessary. And clearly what I'm describing was affected all of us one way or another. Sometimes there is a tendency not to remember. That also applies to editors, publishers, and of course researchers themselves. I mean, very clearly they were at the forefront of the issue facing the same problems.Nature and Challenge of Generative A.I.Eric Topol (05:57):Well, a new challenge has arisen, not that the pandemic of course has gone away, but now we have this large language models of AI, Generative AI, which you've written editorials at Nature, which, of course, is it human or is it the machine? What do you think about that challenge?Magdalena Skipper (06:19):Well of course, you know, the way I like to think about it is AI, of course, broadly is, has been around for a very long time, a number of decades, right? And steadily over the last several years, we have seen AI emerge as a really powerful and important tool in research right across a number of disciplines. The reason why we are all talking about AI right now, and I really think all of us are talking about AI all the time, is, of course, specifically the emergence of generative AI, the large language models that, that you just mentioned. And they sort of burst onto the scene for all of us really last year in the autumn with chat GPT and GPT-4 and so on. But it's important to remember that, of course, when we talk about AI, there are other models, other approaches, and machine learning in general has been creating quite some revolution in research already.(07:36): You know, probably the best example that will be familiar to many of the  listeners was of course Alpha Fold which, you know, Nature published a couple of years ago and, and has been really revolutionized structural biology. But, of course, there are many other examples which are now becoming developing much more rapidly, becoming much more, I would say, commonplace in, in research practice. You know, not just predicting structure from sequencing from sequence. And I say just so flippantly now, of course, it was such and it continues to be such an incredible tool. But of course now we have AI approaches, which actually suggest new protein design, new, new small molecule design. We've had in the last couple of years, we've had identification of new potential antibiotics that are effective against bacterial strains that have otherwise been resistant to any known antibiotics.(08:48):And, and of course, it's not just in biomedicine. Material science--I think it's very helpful, hopeful when it comes to, to AI tools as well. And then, and of course, generative AI indeed helps us in some of these contexts already. But I think your question perhaps was more focused on the publishing, the communication, the sort of output of, of research, which of course is also very important. In some way. The reason why I answered, I began to answer the question the way I did, is because I'm actually very excited about harnessing the power of AI in augmenting research itself. Helping navigate enormous data sets generate hypotheses to be tested finding new ways to advance projects. I think that's a very exciting opportunity. And we're just beginning to see the first applications of it.(10:04):Now, in terms of publishing you referred to some editorials that we wrote about this. And right at the beginning of the year, there was a flurry of excitement associated with the ability of generative AI to indeed generate text. There were some manuscripts which were published in journals that were co-authored by Chat GPT. I I even believe there was an editorial which was co-authored by Chat GPT. So in response to that, we felt very strongly that, that clearly there was a need to, to come out with a, a clear position, just as in doing research, we see AI tools as tools to support writing, but clearly they don't have the ability to fulfill authorship criteria. Clearly, they cannot be authors. Clearly, they must only remain as tools supporting researchers and individuals writing and communicating their research.(11:23):And so we, we wrote a very clear editorial about this, essentially summarizing what I just explained and asking the community to be transparent about how AI tool has been used, just as you would be transparent about your methodology, how you have arrived at the results that you're reporting and, and results that support your conclusions. So for us, it's a relatively simple set of recommendations. As I say, we ask for transparency. We understand it can be a tool that can be used to help write a paper. What we also ask at this stage that generative AI tools are not used to generate figures or images in papers, simply because there are a number of outstanding copyright issues, a number of outstanding privacy issues, they remain unresolved. And for as long as they remain unresolved, we feel it's not an appropriate application of these tools. So that's our editorial position.Eric Topol (12:42):Yeah, no, that's very helpful. I mean, where do you think, if you write a manuscript and then you put it into let's say GPT-4 and say, please edit this, is that okay? Or is that something that, and it's acknowledged that the paper was written by us researchers, but then we had it tweaked by chatbot or is that something that it wouldn't go over too well?Magdalena Skipper (13:10):Well, my preference, and actually what I would hope is that if you were writing this paper and then you felt the need to put it through a chatbot as you just put it, although I find it hard to imagine that you would find no need for that,Eric Topol (13:29):I wouldn't do it. But I know there's people out there that are working on it.Magdalena Skipper (13:32):Yeah, absolutely. But then I would hope that the last pass, the final word, would rest with you as the author. Because, of course, if you are using a tool for whatever it is that you do, you want, at the end of the day to make sure that what that tool has returned is aligned with what you intended that you perform some kind of a sense check. We, of course, all know that although GPT-4 has less of a tendency to hallucinate, so to essentially come up with fabricated sort of statements and, and reality, if you like, it remains an issue. It can remain an issue. And very clearly any, any scientific communication has to be rooted in facts. So, in the scenario that you propose, I would hope that if a researcher felt compelled to run the manuscript through a chatbot, and for example, one consideration may for an individual whose English is not their first language, who feel may feel more comfortable with a sort of support of this kind. But in the end, the final check, the final sign off, if you like, on that manuscript before submission would need to come from the researcher, from the corresponding author, from the writing group. and indeed assistance from a chatbot would need to be disclosed.Eric Topol (15:14):For us. Yeah, I mean, it's really interesting because you can almost foresee the shortcut of having to go get all the references and all the links, you could say, you know, please insert these, but you better check them because they may be fabricated Absolutely. It's going to be really interesting to see how this plays out and the difficulty of detecting what is written by a large language model versus a person.Nature and PreprintsNow another topic that I think is really in play is the preprint world and publishing via preprints. And as you know there's been Michael Eisen and the whole idea of how things would move with his journal eLife. And you will remember when you and I were together at a conference. I organized Future of Genomic Medicine many years ago at the kind of dawn of life science preprints. And some people in the audience sai, “what's a preprint?” Right? Nobody else asks about that now. It's come a long way over this decade. And where do we go with this? Should journals like the top journals in the world like Nature require a paper to be vetted through the pre-print mechanism? Where is this headed, do you think?Magdalena Skipper (16:40):Yeah, it's an excellent question. And, and you know, by the way, I have such wonderful memories from, of that conference. I think this must have been like 11 years ago or something like that. It was a long time ago. And I actually remember presenting this, this vision of a rather radical vision of, of the future of publishing. And here we are in the future as compared to then, and we have moved relatively little by comparison to where we were then. But back to your question. So, you know, the first thing to say is that, of course, just as a reminder, preprints have been around for more than two decades now. And, and of course they initially were really spearheaded and advanced by the physical sciences community. archive itself is, as I say, more than two decades old. So, you know, for us at Nature as a multidisciplinary journal where of course, we've been publishing in the physical sciences since the very beginning of our existence as soon as preprints first emerged in those communities, we realized that we could coexist very harmoniously as a journal peer-review based journal with preprints.(17:59):So when initially biological sciences community embraced them and bioRxiv was established, and then of course, many other archives and then subsequently actually really spearheaded by Covid, the medical and clinical community began to embrace preprints. in many ways, for us, that was nothing new. It was just an extension of something that we worked with before. Although our own our own policies have evolved. So, for example, during the pandemic we actually mandated deposition of papers that were submitted to us that were Covid related. We mandated the deposition in a preprint server. The authors had the choice which server they deposited, but we wanted those manuscripts to be available to the community for the scrutiny as soon as they were finalized, as soon as they were actually written. So while we were reviewing them again as quickly as rigorously, but as quickly as possible, the preprint was already available for the community just before the pandemic.(19:17):As it happens, we also took a step forward with our policy. So previously, let's just say we were completely fine with preprints. We saw preprints as compatible with submission to, to Nature, and for that matter to the other journals in the Nature Portfolio. But actually just in the year before COVID started, we decided to actively encourage our authors to deposit preprints. We could see that preprint sharing had great advantage. You know, the, the usuals of advantages, which are often listed first are of course ability to make that primacy claim, make a stake that, that you have been working on something and, and this is your project. You have a set of results that you are ready to communicate to, to the community at large. And of course, another very important one is that sort of community and, and almost public form of peer review and, and ability to comment.(20:30):And incidentally, I remember as you know, my, my history as an editor very well. We've known each other for a long time. I remember when the genomics community, which is sort of my, my background is sort of my old hat, if you like, that, that I used to wear when the genomics community began to embrace preprints especially the population and evolutionary genomicists really embraced this idea that this was like a group peer review. And the authors of those preprints were very grateful to the community for improving the papers before they were submitted to journals, or sometimes that sort of community review was going on while a paper was being considered at a journal. And we, as editors actually encouraged sort of formal submission of these reviews, if you like, I mean, formal maybe is the wrong word, but we were saying that we would take those comments into account when evaluating papers.(21:38):So there has been an interesting evolution that more and more disciplines, more and more fields have embraced preprints as a way of disseminating information. Preprints service themselves have also grown and matured in the sense that there is now realization that, for example, clinical preprints need a higher degree of scrutiny they're posted on a preprint server than maybe let's say theoretical physics or theoretical biology preprints. So overall all communities collectively have grown and matured. Where are we going with this? I mean, who knows? I was predicting 12 years ago you know, a bit of a different, more advanced future today. It's very difficult to predict the future. I do think, however, that what we are seeing today, that sort of hand in glove coexistence of preprints with journals, with peer reviewed papers is going to continue into the future. And I think actually that's a really valuable and interesting combination. So it's a great development to see and great to see that communities right across disciplines have really embraced this.Eric Topol (23:11):Yeah, I think it does complement, obviously the traditional peer review of a few expert reviewers with, you know, could be hundreds if not thousands of people that weigh in on, on a pre-print. So yeah, it's fascinating to see. And it's, I still remember the vision that you portrayed for it, and how we we're not quite there yet, but I'm sure there'll be further evolution.Women in Science: Where Do We Stand?Now, another area that I think is particularly good to get your input, because you're a woman in science, as you mentioned, you know, grounded obviously in genetics and genomics, and here you are, one of the most influential women in science at a time when there's been a reckoning that women in science have been shortchanged historically, I mean, for hundreds of years. Do you see that this is starting to get better? Are there palpable signs that we're finally getting kind of equal rights here? Or are we, is it, is it just still a long fight ahead?Magdalena Skipper (24:20):So the, the optimist in me and, and I should say, you know, my, my glass, my glass is always half full. The optimist in me says that it is getting better, but the realist in me has to add immediately that the changes too slow. It really is too slow. We do see many more women prominently able to make the contributions that they should, they can, and they should make to whatever discipline whatever aspect of the research community and beyond they wish to, to make. I still think it costs them too much. I still think we don't appreciate and support women sufficiently.(25:23):Maybe we have moved on the bottleneck in the, in the pipeline a little bit further, towards more seniority. But we still, we still don't sufficiently support women. As I say, we, I think we still default to an expectation that successful women in science in research more broadly will somehow emulate how success has looked in the past. And that's a shame, that's a shame not just for those women who are trying to come in and make a difference, but it's a shame for all of us because it means that we are denying diversity in that picture of success. Yes. So yes, I think, I think that we have seen many changes, but I think the change is not happening fast enough.Eric Topol (26:23):Yeah. One of the things that I've noticed since of particular interest in AI is that the very profound imbalance of researchers, the gender imbalance there is just, you know, I'm not even sure if it's 10% women researchers in AI, so that has to be changed. And so this, there's so many things that are holding us back, but, but that's certainly one of, of many.Magdalena Skipper (26:49):Absolutely. And, and, and if I can just add, there are some outstandingly influential female researchers in the AI field, as you say, they are just outnumbered. Yes. , I think not given the opportunity to, to fully blossom, if you like, considering their capabilities and, and their contributions already.Eric Topol (27:11):You know, it's so true. I just interviewed Melanie Mitchell from the Santa Fe Institute, and I work with Fei- Fei Li. And when I, when Fei-Fei Li and I spoke some months ago about a book (Genius Makers) that Cade Metz, the New York Times journalist had written, and I say, why didn't he bring up or emphasize the role of any women in the whole book . Yes--who work in A--I mean, she, she obviously was, was did not take that particularly well, and as did I.Too Many Nature Portfolio Journals?So one of the other areas that I think you already touched on, which is separating Nature, the flagship journal from the Nature Portfolio of, I don't know what it's up to now, 200, 300, I'm not sure how many journals are. So do you, do you have to over oversee that? Do you have input on that? Because what I worry about is, you know, people quote a Nature journal and it may not be, you know, at that level that you would be proud of. What, what are your thoughts about this endless proliferation of the nature portfolio?Magdalena Skipper (28:17):Well, I, I'm, first of all, I'm not sure if it's endless, butEric Topol (28:20):Oh, that's good. .Magdalena Skipper (28:22):So, so  let me, I think in your question, you touched on a number of things. So first of all, a clarification. So my role is as Editor-in-Chief of Nature, and of course, that is my main focus. there is another aspect to my role, which is Chief Editorial Advisor for the Nature Portfolio. So in that sense each of the journals within the Nature portfolio has its own chief editor. but by virtue, I guess, of my seniority, and also by virtue of multi-disciplinarity of Nature I have this advisory role to my colleagues in the other journals. I like to think about the Nature Portfolio as an ecosystem, actually. And it's an ecosystem, like any ecosystem. It has different niches, each of which fulfills a different role. Some of them are bigger, some of them are smaller, some of them are very specialized, others are more general.(29:22):And I think you know, working with researchers for many years as an editor now, I can see benefits to having that sort of almost an ecosystem type approach to publishing. You know, for example, we mentioned already earlier that in my previous sort of incarnation as an editor, my focus was on genomics especially in the context of human genomics. of course starting from the Human Genome Project, these were very large or have, where, why, why am I using past tense? They are, to this day, very large collaborative projects involving many different labs, many different approaches these days that they're not just focused on genomics, but of course other omics go hand in hand with them. So when a project comes to fruition, when, when it comes to be published, there are many different pieces that need to be communicated, many different papers of different sizes of different value.(30:32):And for example what value maybe is the wrong word of different utility? So, for example, there may be a flagship paper that is published in the pages of my journal of Nature, but there may be papers that specifically described development of methodology that was part of the same stage of the project. And those papers may be published in Nature Methods, which is part of the Nature Portfolio. There are other journals that are part of Nature Portfolio, which have different editorial bar. And so, you know, one example is Scientific Reports, which is a journal which does not require conceptual novelty in the papers that it publishes. Of course, it requires rigor and, and robustness in the papers that it publishes, like every journal should. But there is utility in publishing papers in a journal like this.(31:36):There may be replications that are published there that further add further evidence to support conclusions that are already well known, but nevertheless, they're useful. I should however, add that in Nature itself, we also publish replications, right? There are different degrees of influence and impact that, of course, different studies be there, replications or not that can carry. So, that will be my way of conceptualizing the Nature Portfolio. and, you know, coming back to your, to your comment that it seems like it's endless. I think well, nothing, nothing is endless. Of course. Nothing, nothing, right, grows forever. I do think that we have in the launches within the portfolio, we have been able to capture and at the same time serve an interesting evolution in the research ecosystem itself. So the final comment I will make on this is, if you look at some of the more recent launches in the portfolio, they've been what we like to call thematic journals, such as, for example, Nature Food or Nature Water.Eric Topol (33:10):Right?Magdalena Skipper (33:10):And here we are really capitalizing on that multi-disciplinarity of these emerging themes that, especially in the context of sustainable development goals, have acquired their own identity. They don't belong to one discipline or another discipline. And, and so these journals, they're new journals, relatively new journals, some of them very new Nature Waters is, is quite new, but they provide a focal point for researchers who come together to solve a particular set of problems from different disciplines. And I think that's an interesting function in, as I say, for the community.What About the Paywalls?Eric Topol (33:53):Yeah, there's no question some of the newer journals and their transdisciplinary mission --they're needed and they become extremely popular and well -cited very quickly to prove that. So along that line obviously the public is all fired up about paywalls and you know, and obviously for Covid, there was no paywalls, which is pretty extraordinary. Do you see someday that journals will have a hard time of maintaining this? I mean, you have what I consider an extraordinary solution, which is the ReadCube postings anyone can access, you just can't download the PDF, and I wish authors would always routinely put that out there because that would solve part of the problem. But do you think we're going to go to a free access that's much more wide, perhaps even routine, in the years ahead?Magdalena Skipper (34:52):So certainly open access as in ability to access a manuscript, published manuscript without any payment or barrier associated with a Creative Commons license is something that is advanced as a, as a preferred future by many researchers, by many funders. and for that matter, actually many publishers as well. You know, let me make one thing very clear. As an editor, I would love as many people as possible to read the papers that I publish in my journal.Magdalena Skipper (35:30):That should go without saying. Sure. at the same time, publishing papers, of course, is associated with a cost, and, and that cost has to be somehow covered. In the old days it was exclusively covered by library subscriptions or site licenses or personal subscriptions. Now the focus is shifting. And of course, Nature itself as well as the other research journals such as, for example, Nature Medicine or indeed Nature Water, as I mentioned before are what we call transformative journals. So effectively we are hybrid journals that advocate for open access. So today, when you submit a paper to Nature, you can publish under the traditional publishing model, or you can choose to publish open access, which is associated with an article processing charge. That should, in my view, be part of your costs of doing research, because after all, I'm a firm believer in the fact that publishing your research should be seen as part of doing research, not sort of an add-on.(36:47):Now, I'm glad you mentioned read Read Cube and this functionality that we call shared it. We developed it actually quite some years ago. I would say at least a decade ago. it remains curiously underappreciated. Yeah. I just don't understand it. Yeah, exactly. And, and we, we inform the authors that they are free to use that link. And, and just to clarify, it's a linked as you exactly as you explained to an online version of the paper. It's the final version, the record version of the paper. You can't download it, but you can share that link. Anyone can share that link once they have it Infinite number of times. So it's not like the link expires, or it's a, a finite number of, of that it has a number of finite number of uses in addition to that nature.(37:49):And for that matter, the whole of Springer Nature is part of Research4Life. Now, that's an organization that provides free access to all content from publishers. And Springer Nature is not the only publisher that's part of Research for Life that provides full access to all of our content in the countries which are designated as low and middle income countries by the World Bank. So that we've been part of that. And, and previously for many, many years, in fact, decades, again, that is curiously underappreciated, including in the low and middle income countries. So, you know, recently had an opportunity to do some visits in Africa. And my, my take home message there was, if there is one thing that you remember from our conversation or from my presentation, please remember about Research4Life.Magdalena Skipper (38:52):Because that content is freely available if you follow, if you go to our content through Research4Life. And incidentally, there's also training, which is available there. So part of Nature portfolio in addition to journals, we have Nature Master classes, which is training for researchers. And that is also completely freely available in those countries. So there are a number of approaches to, to getting content open access is definitely growing, but there are those other ways to gain access to content which is not open access at the moment.Eric Topol (39:33):I'm really glad you reviewed that because a lot of people who are going to be listening are going to really cue into that. Now the last question for you is, you know, it's not just every Wednesday, 51 or whatever, 50 weeks a year, that you're getting the journal ready, but it's every day now that you're putting out stuff and on the Nature website. Features that are by the way, free or full access and many other things to keep Nature out there on a daily, if not minute to minute basis. So this is really a big charge to, you know, do this all so well. So what keeps you up at night about Nature is this, this must be a very tough position.Magdalena Skipper (40:28):So the first thing I would say that is that of course it's, it's not me. I'm just the person here talking to you representing Nature. I have an outstanding team.Eric Topol (40:44):I've met them, and they're amazing.Magdalena Skipper (40:46):And it's really them who are making it possible on a minute by minute, certainly day by day basis. And so the reason why I sleep relatively well is thanks to them actually, okay,Eric Topol (41:00):. Okay.What Keeps You Up At Night?Magdalena Skipper (41:01):But more, but more broadly. and this is a thought which is bigger than Nature itself. What actually keeps me up at night these days is the rather difficult light in which science and research is portrayed these days increasingly.Magdalena Skipper (41:27):And I think it's very unfortunately being to support other goals and other ends forgetting about the fact that science is an ongoing process that science takes steps back when it needs to revise its position, that it still continues to be true, that s science progresses through self-correction. Even if that self-correction doesn't happen overnight, it takes time to realize that a correction is required, takes time to evaluate judiciously that correction is required and what kind of correction is required, right? These are the things that of course, you and I know very well. But the, sometimes if for individuals who are not close to the process of how science research fact-based discovery is conducted, if you just look at information on social media or in general media, you may walk away with an impression that science is not worth paying attention to that science is in some deep crisis.Magdalena Skipper (43:04):And I think that's, that's a shame that that's a picture that we have other things that need other things in science, in research that need correcting, that need sorting out. Of course, we mustn't forget that research is done by humans and, and after all it is human to air. But overall, that's actually something that keeps me up at night. That overall, I really hope that those of us who are engaged in one way or another within the research enterprise, we can continue to advance the right kind of image that it's not perfect in some artificial way, but actually, at the same time, it's the only way that we can move forward. We can understand the world around us, and we can wake, make the world around us better, actually.Eric Topol (44:11):Yeah. I'm so glad you've emphasized this because just like we talked earlier about distinguishing between human and AI content generated here, we have science and anti-science blurring facts, blurring truths, and basically taking down science as a search for truth and making it trying to, you know, obscure its mission and, in many ways, we, we saw it with not just anti-vax, but it's much bigger. The political motives are obvious extraordinary, particularly as we see here in the U.S. but other countries as well. So I almost didn't hit you for that question, just because it's so profound. We don't have the answers, but the fact that you're thinking about it tells, tells us all a lot. So Magdalena, this has been a joy. I really appreciate all your candid and very thoughtful responses to some of these questions.(45:09):Some of them pretty tough questions I have to say. And I look forward to our conversations and chances to visit with you again in the future. And congratulations again on taking on the leadership of Nature for five years now-- I believe just past your five-year anniversary now. You could say that's small out of 155 years, but I think it's a lot. particularly since the last few years have been, you really challenging. But to you and your team ultimately –-major kudos. I'm on the Nature website every single day. I mean, even, I when I'm on vacation, I'll be checking out the Nature site. So you can tell that I think so highly of the its content and we'll look forward to future conversations going forward.Magdalena Skipper (45:52):Thank you very much. Thank you very much, Eric. It's always a pleasure to talk to you. Thank you. Get full access to Ground Truths at erictopol.substack.com/subscribe

Czy jesteście gotowi na podróż w głąb świata sztucznej inteligencji? W tym odcinku recenzuję "Genius Makers" - fascynującą książkę Cade'a Metza, która zabierze Cię na emocjonującą podróż przez ewolucję AI. Genius Makers to intrygująca opowieść o historycznych momentach i ważnych osobowościach, które wpłynęły na rozwój sztucznej inteligencji. Z książką odkryjesz sekrety AI - nie tylko jako technologii, ale także jako efektu ludzkiego geniuszu i determinacji. Cade Metz odmienia nasze spojrzenie na technologię AI, stawiając na pierwszym planie ludzi, którzy za nią stoją. Od naukowców po korporacje sponsorujące badania, aż do samych systemów AI, autor zręcznie splata te trzy elementy w jedną, wielowątkową historię. Opanuj AI z Przeprogramowanymi: https://opanuj.ai Genius Makers: https://www.goodreads.com/en/book/show/55051662 Future Kraków, 22 czerwca: https://www.meetup.com/future-meetup/events/293781543/

Artificial intelligence. It’s a phrase that gets thrown around a lot. But what are we really talking about? “Artificial intelligence is not one thing. It’s not a single technology. It’s a term that is applied to all sorts of technologies that vaguely behave like the human brain, and in some cases, aren’t even close to behaving like the human brain,” said Cade Metz, a technology correspondent covering artificial intelligence at The New York Times and author of the book “Genius Makers: the Mavericks Who Brought AI to Google, Facebook and the World.” When the artificial intelligence field was created in the 1950s, the aim was to mimic human intelligence. Today, some researchers believe we’re already there or really close. But the thing is, there’s still lots about human intelligence we don’t understand. On the show today, we’re going to get smart about the state of AI as Metz walks us through how far AI has come, where it’s at, where it’s headed and what it has to do with cat photos! In the News Fix, Russia is saying the quiet part out loud, and an important marker in the ongoing aftermath of Jan. 6 insurrection. Then, we’ll hear from a new mom about quiet quitting, and what happened after one listener switched Siri’s voice to the one that sounds like Kimberly. Plus, a TikTok finance wiz answers the Make Me Smart question. Here’s everything we talked about today: “A.I. Is Not Sentient. Why Do People Say It Is?” from The New York Times “The ABCs of AI, algorithms and machine learning” from “Marketplace Tech” “More Than 1 In 2 Americans Will Have An Election Denier On The Ballot This Fall” from FiveThirtyEight “Russia has cut off gas supplies to Europe indefinitely. Here’s what you need to know” from CNBC “Couy Griffin: New Mexico county commissioner removed from elected office for role in US Capitol riot” from CNN Join us tomorrow for Whaddya Wanna Know Wednesday. If you’ve got a question you’d like us to answer, email us at makemesmart@marketplace.org or leave a voice message at 508-U-B-SMART. 

Artificial intelligence. It’s a phrase that gets thrown around a lot. But what are we really talking about? “Artificial intelligence is not one thing. It’s not a single technology. It’s a term that is applied to all sorts of technologies that vaguely behave like the human brain, and in some cases, aren’t even close to behaving like the human brain,” said Cade Metz, a technology correspondent covering artificial intelligence at The New York Times and author of the book “Genius Makers: the Mavericks Who Brought AI to Google, Facebook and the World.” When the artificial intelligence field was created in the 1950s, the aim was to mimic human intelligence. Today, some researchers believe we’re already there or really close. But the thing is, there’s still lots about human intelligence we don’t understand. On the show today, we’re going to get smart about the state of AI as Metz walks us through how far AI has come, where it’s at, where it’s headed and what it has to do with cat photos! In the News Fix, Russia is saying the quiet part out loud, and an important marker in the ongoing aftermath of Jan. 6 insurrection. Then, we’ll hear from a new mom about quiet quitting, and what happened after one listener switched Siri’s voice to the one that sounds like Kimberly. Plus, a TikTok finance wiz answers the Make Me Smart question. Here’s everything we talked about today: “A.I. Is Not Sentient. Why Do People Say It Is?” from The New York Times “The ABCs of AI, algorithms and machine learning” from “Marketplace Tech” “More Than 1 In 2 Americans Will Have An Election Denier On The Ballot This Fall” from FiveThirtyEight “Russia has cut off gas supplies to Europe indefinitely. Here’s what you need to know” from CNBC “Couy Griffin: New Mexico county commissioner removed from elected office for role in US Capitol riot” from CNN Join us tomorrow for Whaddya Wanna Know Wednesday. If you’ve got a question you’d like us to answer, email us at makemesmart@marketplace.org or leave a voice message at 508-U-B-SMART. 

In this week's episode, show host Paul Roetzer sits down with Cade Metz, technology correspondent for The New York Times, and author of the book Genius Makers: The Mavericks Who Brought AI to Google, Facebook and the World. This special episode took place during MAICON 2021 when Paul and Cade sat down for a fireside chat to discuss the story of AI throughout the past few decades. Cade's book, published in 2021, gives readers an insider's look at the mavericks leading the race for AI supremacy. Genius Makers dramatically presents the fierce conflict between national interests, shareholder value, the pursuit of scientific knowledge, and the very human concerns about privacy, security, bias, and prejudice. Like a great Victorian novel, this world of eccentric, brilliant, often unimaginably yet suddenly wealthy characters draws you into the most profound moral questions we can ask. And like a great mystery, it presents the story and facts that lead to a core, vital question: How far will we let it go?  As one of Paul's opening lines of the interview, "[Genius Makers] literally just changed my perspective on the significance of what's happening," this episode dives into greater detail into some important moments in the book.

Today, we are privileged to have Cade Metz join us. Cade is a reporter at the New York Times, and covers artificial intelligence and machine learning, driverless cars, robotics, virtual reality, and other emerging areas. Before the New York Times, he was a reporter at Wired. Cade has written what we think is one of the seminal books in AI called The Genius Makers, which is the story of the emergence of AI, from the 1950s to today. In the process of writing this book, he had conversations with some of the brightest and most capable people in the world of AI. He's joining us to share some of the narrative and what he's learned through the process of writing.

The same technology that lets your daughter call up her favorite songs in Alexa is also used for government surveillance, racial profiling, and the creation of deep fake YouTube videos from troll farms. While neural networks make our lives easier, they also create ethical tangles and questions. New York Times Silicon Valley reporter, Cade Metz tackles these moral disparities through hundreds of exclusive interviews in his book, Genius Makers.In this episode, Cade talks about factors that shaped the A.I. technology fueling the biggest tech companies: Google, Microsoft, Facebook, and OpenAI, a new lab founded by Elon Musk. Listen as Greg and Cade discuss the fierce conflict between national interests, shareholder value, the pursuit of scientific knowledge, and the very human concerns about privacy, security, and prejudice. Episode Quotes:Why are open-source companies like Geoffrey Hinton's DNN research considered valuable when people already have access to their information?It's an idea that dated back to the fifties, but by 2012, when Geoff is essentially auctioning himself off, there are few people on Earth who know how that idea works. Because most of the world thought it would never work. And that's the dynamic there. To this day, it's the talent that is valuable. We needed a lot of stuff for this to work. You need the data, and you need the computer processing power needed to analyze that data. But you need the people to make that work. Getting a neural network to work, some people described it as a dark art or black magic. It's about sort of coaxing something out of this data. These systems literally learn by analyzing the data, and it's more data than you and I could ever wrap our heads around. So, it's about coaxing those machines to learn on their own. They do take off in ways that are beyond us, but you need these people to guide them. And that's really what happenedThoughts on institutional frictions that shaped game-changing ideas and progress on neural networksYou have these battles between academics and people like Marvin Minsky ended up having the upper hand, right? Sometimes, it's about who has the loudest voice and who can convince the Department of Defense to give them the money for their particular project.And you see the whole industry shift to what you call good old-fashioned AI, that symbolic AI. Where you're basically putting engineers in a room, and they define how the technology's going to work— rule by rule, line of code by line of code. That became what people had the most hope for. That would be the future and not these systems that could learn on their own from data.Thoughts on pursuing ideas and harnessing curiosity to overcome dead endsI love that you mentioned this theme of his own lab at the University of Toronto. It was old ideas are new. What that meant was, it didn't matter how old the idea was, what mattered was, had you proven that it wouldn't work? If you had not proven that, then you should keep working on it. No matter how much time went by. If you got to that point where you proved it was wrong, then you could put it aside. But until then, you keep working.How did persistence help Geoffrey succeed in finding the missing piece in the neural network?Most of the world at that point had discarded the idea of a neural network. Even his own thesis adviser had abandoned this idea and had recently moved on to that symbolic method you talked about. Yet, Geoff still grabbed hold of that idea and did not let go for decades. So, he had this fundamental belief and that is what drove him.Time Code Guide:00:01:32 What drew you to the stories of these intellectual heroes00:05:02 Stories of people who believe in an idea even though those around them do not and the will to continue to work on it00:07:16 How technologies work for the good and how it's a cause for concern in other areas 00:15:12 The kind of personality needed when you keep on meeting dead ends00:16:53 Success and being removed from mainstream00:24:26 Nonlinear regression and curve-fitting00:27:32 Choosing between writing grants or doing pitches00:29:28 Inevitable discussion about ethics, difficult choices, and large corporations trying to decide how technology will be used00:33:11 Triumph over experts and the champions in the worldShow Links:Guest ProfileCade Metz Author ProfileCade Metz on TwitterCade Metz on LinkedInHis WorkNew York Times ArticlesArticles on WiredMuck Rack ArticlesGenius Makers: The Mavericks Who Brought AI to Google, Facebook, and the World

Welcome to episode #799 of Six Pixels of Separation. Here it is: Six Pixels of Separation - Episode #799 - Host: Mitch Joel. Best known for his reporting on artificial intelligence, driverless cars, robotics, virtual reality, and other emerging areas, Cade Metz is a reporter with The New York Times. Previously, he was a senior staff writer with Wired magazine, the U.S. editor of The Register, PC Magazine, and other outlets. His first book is called Genius Makers - The Mavericks Who Brought AI to Google, Facebook, and the World. Genius Makers looks are deep questions like: What does it mean to be smart? To be human? What do we really want from life and the intelligence we have, or might create? From the back cover: "The book presents the fierce conflict among national interests, shareholder value, the pursuit of scientific knowledge, and the very human concerns about privacy, security, bias, and prejudice. Like a great Victorian novel, this world of eccentric, brilliant, often unimaginably yet suddenly wealthy characters draws you into the most profound moral questions we can ask. And like a great mystery, it presents the story and facts that lead to a core, vital question: How far will we let it go?" Enjoy the conversation... Running time: 55:01. Hello from beautiful Montreal. Subscribe over at Apple Podcasts. Please visit and leave comments on the blog - Six Pixels of Separation. Feel free to connect to me directly on Facebook here: Mitch Joel on Facebook. or you can connect on LinkedIn. ...or on Twitter. Here is my conversation with Cade Metz. Genius Makers - The Mavericks Who Brought AI to Google, Facebook, and the World. Follow Cade on LinkedIn. Follow Cade on Twitter. This week's music: David Usher 'St. Lawrence River'.    

Intro.(1:22) - Start of interview.(1:51) - Jeff's "origin story". He grew up in Dayton, Ohio. He went to Carnegie Mellon University for undergrad "to study engineering and play football." He graduated with electrical and computer engineering degrees, and took off to Silicon Valley. He first worked in the semiconductor industry with Altera. He later got into financial services, first with Gehrson Lehrman Group, then with SecondMarket (early player in the secondary markets for private shares, later acquired by Nasdaq) and Owler (crowdsourcing data on private companies). He joined Nasdaq in 2014 to help launch the Nasdaq Private Market. In 2016 he got promoted to run the listings team for Nasdaq in the west coast.(4:39) - Jeff's take on Nasdaq's role and vision: "In the last 5-6 years our approach has been to create a lifecycle approach to supporting our corporate clients: 1) Nasdaq Entrepreneurial Center (early stage), 2) Nasdaq Private Market (as companies scale and need to provide liquidity to their shareholders), 3) Listings Business (for companies going public), 4) Once companies are public, we offer a number of products and services to empower their IR, corporate governance and ESG disclosure practices." Beyond this work with corporate clients, Nasdaq also operates exchanges in the US and EU, it has an investment intelligence business (indexes, sell market data) and it's a technology provider to capital markets (including market surveillance technology, AML/KYC solutions, and others).(7:38) - Jeff's take on growth of IPOs during the pandemic (~250 operating companies have gone public in Nasdaq this year) and SPACs (there have been 495 IPOs in 2021 raising ~$138bn). "As a private company you've never had more options and better access to capital and liquidity." Private companies can raise: 1) Late stage venture capital rounds ("there seems to be $100m rounds everyday"), 2) IPOs, 3) SPACs and 4) Direct listings.(10:13) - His take on the impact of government actions on the economy (and how they impact markets). The acceleration of digital transformation during COVID-19.(12:39) - His take on the Nasdaq Private Market (facilitated ~$36 billion in transaction volume for ~500+ private companies) and why they decided to spin-off NPM as s stand-alone company, receiving investments from a group of banks including Citigroup, Goldman Sachs, Morgan Stanley, and SVB Financial Group.(16:05) - The "stay private or go public" decision per Jeff: "It all boils down to the company's goals and objectives in different phases of its lifecycle." Companies go public for a variety of reasons, but some of the primary ones are: 1) to raise capital, 2) to provide liquidity, 3) brand enhancement (prestige) of being a  public company, and 4) to leverage its equity as an acquisition currency.(18:53) - His take on regulatory pressures on private markets (particularly from the SEC, as explained by Commissioner Lee's speech on "Going Dark" and problematic aspects of private markets).(23:24) - On the rise of retail investing and "meme stocks". Zero commissions took down the cost of trading, it made trading more accessible to people. The advent and impact of social media (from social message boards to Reddit). The dissemination of information has changed the nature of trading. The SEC report on equity and options market structure conditions (October 2021).(26:08) - On growth of ESG. "It all starts with the generational shift that is going on, from Baby Boomers to Millennials." "The new generation thinks beyond the bottom line." "People and investors are focusing on non-financial metrics for public companies (more and better disclosures)."(29:52) - History and nature of Nasdaq's Boardroom Diversity Rule (approved by the SEC on August 6, 2021). Standard disclosure matrix and minimum diversity standards (gender and minorities) with long phaseout periods. "We received 200+ comment letters to the rule, 80% was positive. From the 20% that was negative comments, 10% said that we shouldn't implement the rule, and the other 10% said we didn't go far enough."(34:10) - His take on crypto and blockchain technology. "We were thrilled to welcome Coinbase to Nasdaq via their direct listing." "It's really an interesting and dynamic time for the crypto markets." "It's still early innings in terms of the regulatory framework (from SEC and CFTC)." (36:16) - His favorite books:How to Win Friends and Influence People by Dale Carnegie (1936)Genius Makers by Cade Metz (2021)(37:05) - His mentor Bruce Aust (retired Vice Chairman of Nasdaq)(38:29) - On Nasdaq's approach to technology in the boardroom: their board portal Nasdaq Boardvantage, critical for security. The Nasdaq Center for Board Excellence "offers the latest governance insights and actionable intelligence for board members and executives (board evaluations and questionnaires". The topic of ESG is very relevant for boards, and they have an advisory team that consults with boards on ESG, Nasdaq OneReport (to simplify the process of ESG data capture, engagement, oversight, and disclosure).(40:05) - An unusual or absurd habit that he loves: From the book Extreme Ownership (Jocko Willing and Leif Babin): "The first thing I do in the morning is to make my bed." This way everyday you start by accomplishing something.Jeff Thomas is a Senior Vice President of Nasdaq's Corporate Services business unit. Based in San Francisco, Jeff oversees Nasdaq's new Listings and Capital Markets businesses. He also oversees business development and relationship management for Nasdaq's listed companies and Investor Relations Solutions' clients in the Western United States. Previously, he served as President of Liquidity Solutions at Nasdaq Private Market, where he worked closely with private companies to help them provide shareholder liquidity prior to an IPO. If you like this show, please consider subscribing, leaving a review or sharing this podcast on social media. __ You can follow Evan on social media at:Twitter @evanepsteinLinkedIn https://www.linkedin.com/in/epsteinevan/ Substack https://evanepstein.substack.com/Music/Soundtrack (found via Free Music Archive): Seeing The Future by Dexter Britain is licensed under a Attribution-Noncommercial-Share Alike 3.0 United States License

Cade Metz is a New York Time Journalist and author of Genius Makers, which details the modern history of AI. This conversation covers a number of interesting topics; The ethical ideology of AI leaders including Google, Microsoft and Facebook. How they acquired AI, what they've done with it, what they might do with it. Why did everyone choose to sell their AI to Google? Ethics? Facebook - Ethical AI or not? The difference between the US Government access to AI and China. It's a fascinating chat for anyone that is interesting in AI, social media, privacy, ethics and the rise of big tech.

John interviews Cade Metz, a technology correspondent at The New York Times and the author of “Genius Makers,” a book on artificial intelligence. The book focuses on neural networks, an approach whereby, given enough data, A.I. can get better at specific tasks — like recognizing speech or images — all on its own. The idea behind neural networks dates to the ‘40s and ‘50s, but it was largely abandoned for decades. Today, a few dogged researchers, along with the tech giants that act as the field's biggest players, have made it ubiquitous. “This is the technology we now use today when we speak commands into our cell phones,” Cade says. “This is what allows self-driving cars.”John asks Cade about the earliest days of artificial intelligence; how the international nature of A.I.'s brightest teams complicates the technology's geopolitical stakes; and why we should all start paying attention to proteomics. See acast.com/privacy for privacy and opt-out information.

In 1958, a psychologist named Frank Rosenblatt took a five-ton computer, fed it a steady diet of punch cards, and taught it how to recognize the letter “A.” He called his creation the Perceptron, and his belief in its potential was like that of a deliriously proud parent. One day, he thought, the artificial intelligence he'd built would learn to recognize faces, speak like a human, translate languages, reproduce itself on an assembly line, and even fly to space — at which point, it would no longer be a computational marvel but a fully conscious being.The fact that you've never heard of the Perceptron tells you that none of Rosenblatt's predictions came to pass — not in his lifetime, anyway. But a small band of brainy rebels never lost faith in the potential of AI to change the world. Thanks to their perseverance — along with dramatic improvements in computing power — they managed to make Rosenblatt's prophecies a reality.The AI they built is what enables Facebook to recognize faces in the photos you upload. It's the reason Siri and Alexa can (sometimes) understand what you're saying, and Google can translate anything you write into 109 languages. Cade Metz has spent years chronicling the rise and rise of AI, first as a reporter at the New York Times and now in his new book, “Genius Makers.” In this forward-looking conversation, he tells Rufus what AI can do, where it's headed, and whether we should be worried that supercomputers will wage war against humanity.Join The Next Big Idea Club today at nextbigideaclub.com/podcast and get a free copy of Adam Grant's new book!Listen ad-free with Wondery+. Join Wondery+ for exclusives, binges, early access, and ad-free listening. Available in the Wondery App https://wondery.app.link/thenextbigidea.Support us by supporting our sponsors:Talkspace — Go to talkspace.com and use the code BIGIDEA to get $100 off of your first monthFiverr Business — Get one free year and save 10% on your purchase by using code BIGIDEA at fiverr.com/businessSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In 1958, a psychologist named Frank Rosenblatt took a five-ton computer, fed it a steady diet of punch cards, and taught it how to recognize the letter “A.” He called his creation the Perceptron, and his belief in its potential was like that of a deliriously proud parent. One day, he thought, the artificial intelligence he'd built would learn to recognize faces, speak like a human, translate languages, reproduce itself on an assembly line, and even fly to space — at which point, it would no longer be a computational marvel but a fully conscious being. The fact that you've never heard of the Perceptron tells you that none of Rosenblatt's predictions came to pass — not in his lifetime, anyway. But a small band of brainy rebels never lost faith in the potential of AI to change the world. Thanks to their perseverance — along with dramatic improvements in computing power — they managed to make Rosenblatt's prophecies a reality. The AI they built is what enables Facebook to recognize faces in the photos you upload. It's the reason Siri and Alexa can (sometimes) understand what you're saying, and Google can translate anything you write into 109 languages. Cade Metz has spent years chronicling the rise and rise of AI, first as a reporter at the New York Times and now in his new book, “Genius Makers.” In this forward-looking conversation, he tells Rufus what AI can do, where it's headed, and whether we should be worried that supercomputers will wage war against humanity.

Information about the AI Event Series mentioned in this episode: https://twitter.com/CNA_org/status/1400808135544213505?s=20 To RSVP contact Larry Lewis at LewisL@cna.org. Andy and Dave discuss the latest in AI news, including the first flight of a drone equipped with the Air Force’s Skyborg autonomy core system. The UK Office for AI publishes a new set of guidance on automated decision-making in government, with Ethics, Transparency and Accountability Framework for Automated Decision-Making. The International Red Cross calls for new international rules on how governments use autonomous weapons. Senators introduce two AI bills to improve the US’s AI readiness, with the AI Capabilities and Transparency Act and the AI for the Military Act. Defense Secretary Lloyd Austin lays out his vision for the Department of Defense in his first major speech, stressing the importance of emerging technology and rapid increases in computing power. A report from the Allen Institute for AI shows that China is closing in on the US in AI research, expecting to become the leader in the top 1% of most-cited papers in 2023. In research, Ziming Liu and Max Tegmark introduce AI Poincaré, an algorithm that auto-discovers conserved quantities using trajectory data from unknown dynamics systems. Researchers enable a paralyzed man to “text with his thoughts,” reaching 16 words per minute. The Stimson Center publishes A New Agenda for US Drone Policy and the Use of Lethal Force. The Onlife Manifesto: Being Human in a Hyperconnected Era, first published in 2015, is available for open access. And Cade Metz publishes Genius Makers, with stories of the pioneers behind AI. Click here to visit our website and explore the links mentioned in the episode.

In de 30ste aflevering van de Business Books Podcast duiken Thijs Peters en Remy Gieling in de geschiedenis van deep learning met het boek Genius Makers, leren we hoe je bedrijf op de rit houdt in tijden van crisis met de lessen van dé groeiprofessor van Nederland Justin Jansen, delen we inzichten uit het oersaaie nieuwe werk van Walter Isaacson over genmanipulatie en spreken we met Martin Pikaart over zijn boek Het polderkartel - hoe een handvol bonden en werkgevers de toekomst van alle Nederlandse werknemers bepaalt. 

In 2020, there were six companies that made up 25% of the S&P 500 and you know which ones they are: Facebook, Amazon, Apple, Netflix, Google, and Microsoft. The common denominator driving the growth for all of these companies is Artificial Intelligence. Google’s CEO, Sundar Pichai has described the development of AI as “more profound than fire or electricity,” but it is still very misunderstood. Everyone has a sci-fi image that appears in their head when they hear about AI, but what actually is it? Where did it come from? How fast is it growing? To answer these questions, Trey Lockerbie sits down with New York Times writer and author Cade Metz, to discuss his new book, Genius Makers, which lays out the story of how AI came to be.IN THIS EPISODE, YOU'LL LEARN:The history of AIHow it works and why it is usedThe challenges for AI aheadSome ethical dilemmas surrounding it and most importantly;Which companies will benefit from it the mostBOOKS AND RESOURCES:Cade’s new book Genius MakersNew York Times articles by Cade MetzPreston, Trey & Stig’s tool for picking stock winners and managing our portfolios: TIP Finance Tool Browse through all our episodes (complete with transcripts) hereGet into a topic quickly, find new topics, and figure out which books you want to spend more time listening to more deeply with Blinkist. Get 25% off and a 7-day free trial todayPush your team to do their best work with Monday.com Work OS. Start your free two-week trial todayBring your WiFi up to speed with Orbi WiFi 6 from NETGEAR. Save 10% with promo code BILLION10Get three months free when you protect yourself with ExpressVPN, the VPN we trust to keep us private onlineJoin OurCrowd and get to invest in medical technology, breakthroughs in ag tech and food production, solutions in the multi-billion dollar robotic industry, and so much more. Find opportunities to help diversify your portfolio with investments in alternative asset classes with minimums starting at $1,000 with YieldstreetCheck out Kraken's industry-leading staking service, where you can put your crypto to work for you and earn up to 20% in additional rewards annuallyElevate your writing with 20% off Grammarly PremiumSimplify working with multiple freelancers, set budgets, and manage projects with ease with Fiverr Business. Get 1 free year and save 10% on your purchase on with promo code INVESTORSSupport our free podcast by supporting our sponsorsHELP US OUT!Help us reach new listeners by leaving us a rating and review on Apple Podcasts! It takes less than 30 seconds, and really helps our show grow, which allows us to bring on even better guests for you all! Thank you – we really appreciate it!

This week, I talk to Cade Metz, the New York Times' lead reporter on artificial intelligence, about his new book, “Genius Makers, the Mavericks Who Brought AI to Google Facebook  and the World."  The book focuses on some of the personalities and companies responsible for the current wave of AI innovation and touches on some of the controversies swirling around the new technology today.

Cade Metz: Genius Makers... with TRE´s Bill Padley

The Sunday Times’ tech correspondent brings on Cade Metz, New York Times tech journalist and author of Genius Makers, to talk about the rise of artificial intelligence (3:00), the most important auction in tech (4:35), Europe’s AI crackdown (7:40), Geoff Hinton and neural networks (10:00), how AI starts to spread (13:00), Deepmind’s Demis Hassabis (18:20), why he turned down Facebook’s takeover bid (21:00), Project Maven (23:20), the AI “arms race” with China (25:25), whether artificial general intelligence is possible (29:20), the AlphaGo moment (33:00), Move 37 (38:10), what AI disrupts next (42:00), bias (45:05), the robot arm room (51:30), and the Rubik’s cube solution (56:15) Support this show http://supporter.acast.com/dannyinthevalley. See acast.com/privacy for privacy and opt-out information.

https://www.alainguillot.com/Cade-Metz/ Cade Metz is a reporter with The New York Times, covering artificial intelligence, driverless cars, robotics, virtual reality, and other emerging areas. Genius Makers is his first book. Get your book here: https://amzn.to/32nCOCo

The human story behind the creation of artificial intelligence. Can artificial intelligence be creative?

An interview with Cade Metz, a New York Times reporter covering artificial intelligence, driverless cars, robotics, virtual reality, and other emerging areas. Previously, he was a senior staff writer with Wired magazine and the U.S. editor of The Register, one of Britain’s leading science and technology news sites. His first book, "Genius Makers", tells the stories of the The Mavericks Who Brought AI to Google, Facebook, and the World. Get the book: http://bit.ly/GeniusMakers​ Follow Cade on Twitter: https://twitter.com/CadeMetz/​ And on Linkedin: https://www.linkedin.com/in/cademetz/ Subscribe: RSS | iTunes | Spotify | YouTube Check out coverage of similar topics at www.skynettoday.com Theme: Deliberate Thought Kevin MacLeod (incompetech.com)

Interesting and informative conversation with Cade Metz, who recently published Genius Makers, documenting the story of the evolution and development of Artificial Intelligence. Cade Metz is a reporter with The New York Times, covering artificial intelligence, driverless cars, robotics, virtual reality, and other emerging areas. Genius Makers is his first book. Previously, he was a senior staff writer with Wired magazine and the U.S. editor of The Register, one of Britain's leading science and technology news sites. A native of North Carolina and a graduate of Duke University, Metz, 48, works in The New York Times' San Francisco bureau and lives across the bay with his wife Taylor and two daughters. You can order the book here https://cademetzauthor.com/order/

Cade Metz is an expert on Artificial Intelligence, writer for the New York Times and author of a new book on the rise of Artificial Intelligence called Genius Makers. In this episode, you're going to hear how AI impacts you both wittingly and unwittingly, where we currently are in the AI journey and what the future holds for big tech, data and the impacts of AI on our daily lives. See acast.com/privacy for privacy and opt-out information.

Let's talk AI history, sci-fi, and AGI. New York Times AI reporter Cade Metz joins #MachineMeetsWorld to discuss his new book, “Genius Makers: The Mavericks Who Brought A.I. to Google, Facebook, and the World.” --- Email the show: mmw@infiniaml.com --- Video + transcript: https://bit.ly/3tdbeU3