The Swyx Mixtape

Listen to Build for Tomorrow: https://www.jasonfeifer.com/episode/the-best-ways-to-use-a-crisis/ (40ish mins in)Today's twitter discussion: https://twitter.com/swyx/status/1599890745200377857TranscriptSo turn to the century, the phonograph, brandnew innovation, the very first record player, consider how completely insanelyrevolutionary this was, for all of human history, before the phonograph. If you wantedto listen to music, there was only one way to do it. And that was to be in front of ahuman being who was playing an instrument. There's no other way. How are you goingto listen to music? And then this machine comes along and can do it for you, can playmusic. Unbelievable. Consumers didn't believe it at first. Like they literally, they had tobe shown like, no, there is not a person behind the wall playing music. Like they had tobe shown. And then once they believed it, they loved it. They brought it home. You know who hated this?[00:43:45] Jordan Harbinger: Yeah. I don't know. Musicians?[00:43:46] Jason Feifer: Yeah. Musicians hated it.[00:43:48] Jordan Harbinger: Yeah.[00:43:49] Jason Feifer: Hated it because they saw themselves being replaced here.That, you know, they see this new technology doing the thing that they do and they seechange and they equate change with loss and they say, "We got to stop this," right?They pull a margarine. And the leader of the resistance was this guy named John PhilipSousa. John Philip Sousa, you may not know his name, but you know his music becauseit's still around today. All the military marches, [Dah-dah-dah-dah] John Philip Sousa.[00:44:12] Jordan Harbinger: You know why we know who he is? Because we haverecordings of the music.[00:44:15] Jason Feifer: Bingo! That's exactly right. So John Philip Sousa, he at thetime was the leader of the resistance against recorded music. He wrote this amazingpiece, like Google it because it is hilarious. It's called The Menace of Mechanical Music.It ran in Appleton's Magazine in 1906 and it contains all of these wonderful argumentsagainst recorded music. And my favorite goes like this. He says, "When you bringrecorded music into the home, it will be the end of all forms of live performance in thehome because why would anybody perform music in the home when now there's amachine that can do it for them." So now, because we're going to extrapolate loss,remember I talked about that earlier, right? Like you see changes loss and youextrapolate the loss. So what's next? Well, he says, "Because people are no longerperforming music at home, mothers will no longer sing to their children."[00:45:00] Jordan Harbinger: It's quite the jump.[00:45:01] Jason Feifer: Yeah. Quite the jump. Why would they do that? When amachine could do it. Here's another jump, "Because children grow up imitating theirmothers, the children will grow up to imitate the machines, and thus, we'll raise ageneration of machine babies." That was his argument, like a real thing that—[00:45:16] Jordan Harbinger: Okay.[00:45:16] Jason Feifer: —people took it seriously. I feel like it's fun to like laugh atJohn Philip Sousa for this, but also—[00:45:20] Jordan Harbinger: Sure.[00:45:20] Jason Feifer: —I feel like what he's doing is pretty relatable.[00:45:23] Jordan Harbinger: It is relatable. It's very human.[00:45:24] Jason Feifer: It's very human. You have something and it works for you.And then you see some change come along and you feel like this change is existential.It is going to outmode you. So he tried to stop it.[00:45:36] And it's worth asking ourselves in this moment, three simple questions. Number one, what is this new thing that's happening? Number two, what new habit orskill are we learning as a result? And then number three, how can that be put to gooduse? Because if you do that, it just helps you reframe any moment of change as let'sfocus on the gain. Is there some kind of gain that we can extrapolate? Maybe it's not aseasy to see as the loss, but is it there and what would it look like?[00:46:06] Because if you ran that scenario with John Philip Sousa, what you would seeis, well, okay, what new thing are people doing? Well, what they're doing is they're nowlistening to music on these machines whenever they want. What new habit or skill arewe learning as a result? We're learning that we have control or consumers have a lotmore control over the music that they listen to. And therefore, also have access to a lotmore music because before the only music that they could get was whoever happenedto be able to travel to their town and perform for them. How could that be put to gooduse? Well, come on guys. Come on, John Philip Sousa. Like this means that you couldrecord something yourself. And you could sell it and now people can listen to and enjoyyour music. And you can monetize that in ways that are much more scalable than whatyou're doing now. Because you're coming from a world in which the only thing that youdo is perform for people that you can get in front of. And that means that you have alimited number of people that you can get in front of. But if you can change thatdynamic, then man, oh man, suddenly your economic ability skyrockets.[00:47:02] As it turns out, John Philip Sousa was protecting a system that limited hisown economic ability. And the reason he was doing that was because he was panickingbecause of change. And once he figured it out, he changed his tune. That is not meantto be a pun, but there it is.[00:47:15] Jordan Harbinger: Yeah. I see what you did there. You are a dad, indeed.[00:47:17] Jason Feifer: There it is. I'm nailing it. I got all the dad jokes. And he startedto record himself and he started to perform on radio and he changed. And this issomething that we all need to be mindful of. There is gain in change and we need to runourselves through these things that can just help us focus on it.

Listen to the InfoQ podcast: https://soundcloud.com/infoq-channel/interview-shawn-swyx-wangBlogpost: https://dx.tips/the-end-of-localhostIn this episode, Shawn Wang (swyx), head of developer experience at Airbyte, sat down with InfoQ podcast co-host Daniel Bryant and discussed the rise of remote development environments. Topics covered included, whether remote development experiences are good enough to see the death of local(host) development, what a wishlist might look like for the ultimate developer experience, and how cloud native organizations are currently developing software.Read a transcript of this interview: bit.ly/3R3OEcDSubscribe to our newsletters:- The InfoQ weekly newsletter: bit.ly/24x3IVq- The Software Architects’ Newsletter [monthly]: www.infoq.com/software-architects-newsletter/Upcoming Events:QCon San Francisco:qconsf.com/- Oct 24-28, 2022- Oct 2-6, 2023QCon Plus online:plus.qconferences.com/- Nov 29 - Dec 9, 2022QCon Londonqconlondon.com/- March 26-31, 2023Follow InfoQ:- Twitter: twitter.com/InfoQ- LinkedIn: www.linkedin.com/company/infoq- Facebook: bit.ly/2jmlyG8- Instagram: www.instagram.com/infoqdotcom/- Youtube: www.youtube.com/infoqDXSWYXLocalHostRemotedevelopment

Make you feel my love: https://www.youtube.com/watch?v=Qxsd7rhhFYwAin't No Mountain: https://www.youtube.com/watch?v=yB5ITxz9CK0Easy on me: https://www.youtube.com/watch?v=lb4f5IPvwXU

Watch: https://www.youtube.com/watch?v=UQkeRxeh34ITranscripteric schmidt is a business leader andsoftware engineer that served asgoogle's chief executive officer from2001 to 2011.under his leadership google grew from anearly silicon valley startup to arguablythe most important technology company onthe planetschmidt is currently co-founder ofschmidt futures and sits on the board ofmany public and private institutionshe is still involved with technologyconsults with the us department ofdefensealso talks about ai in his latest bookthe age of ai and our human futurewritten alongside former u.s secretaryof state henry kissinger and computerscientist daniel huddenlockerschmidt was a guest at the milken globalconference and here he anticipates someof the ai innovations that we willcertainly see in five yearshe also predicts what we might see in 20yearshere are the detailsrecently in the last couple of yearsthere have beenextraordinary gains so for example ateam at google and at the baker labseparatelyfigured out a way to actually understandif you take dna what proteins aregenerated and what their structure isthat's an extraordinary achievement inmy opinion worth a nobel prizethere are drugs being designed now thatcould not be possiblydesigned by humansin any way because of their complexitythere's evidence that ai can be used inbiology ai is mapped to biology the waymath is to physics in other wordsbiology is so complicated that ai willbe used to interpret biology and predictits outcomeover and over again ai will arrive inyour lifeanother example is the hottest area inmy industry right now are large languagemodels uh recently a set of startupshave been funded between 100 and abillion 100 million and a billiondollarsthey have no current product or revenueplans umthe the belief of the power of thistechnology these large language modelsare interesting because you suck all theinformation inlike you read all the web whichcomputers can do but we can't and thenthey discover things they appear todiscover a structure of language and anexample of recent google product lastweek can actually translate from onecomputer language to another and wedidn't give it any examples of one totranslate to the other it discovered astructure and it can predict itthese are the beginning of generalintelligencethe the current um excitement stems froma technology called transformers thatwas invented three or four years ago andwhat transformers do is it can predictthe next word after a set of words so ifyou give it a sentence it can predictwhat the word will be and it's doneusing a complicated mathematicaltechnique it turns out predicting thenext word is mathematically the samething as predicting the next sound thenext video the next imageall of that and so you have aunification a multi multi-modalunification of video text and speech sothese systems sound and look likethey're intelligenta good example is gpt3 which came outlast yearwhich kicked the current revolution offyou asked itdo you think like a human and it says noi do notbecause i am a large language model andyou are a i think a human who has beentaught to think in this waynow is thatit thinking about you or is it patternmatching we can't tell and the truth isand i'm as part of philanthropic worki'm funding projects to try tounderstand this we don't actuallyunderstand why this works we don'tmathematically understand why it worksand we also don't understand its failuremodesso you wouldn't want to use this as areplacement for something that's livecritical because we can't say when itfails when does it just crashthe current large language models forexample have trouble with the notion ofgravity so if you say to them i moved iti moved the object from here to here andthen i put it up here and i put it downthere and so forth now everyone justfollowed what i did the large languagemodel gets confused because it doesn'tunderstand gravity so the computerscientists say we're going to now addconceptsrightso with concepts and then with planningmaybe you get to the point where itlooks like a human-like intelligencewhich has all sorts of issuesif i were 24 today this is exactly whati'd be working on this is where thehardest and most challenging computerscience systems problems are with thegreatest payoffnow remember that the system can predictpatternsand if you can predict a pattern you canalso generate an artifact there's aduality in these systems where they cangenerate thingsso part of the issues that we face nowis that these systems can generatespeech i'll give you an examplewithin five yearsthe following will be trueyou'll be able to take a systemum take one of these language modelswhich would be infinitely expensive tomake but you didn't pay for itit shows up in your doorstep and it finetunes the technical term is literallyfine-tuning it you fine-tune it to youwho are you what do you care about itsort of watches you and learns from youit learns your voiceright all of a sudden it can generatevideos with you in itnow you could think of this as a secondai rightnow the interesting thing is imaginefive years from now i install this thingand i use it for a few years andeventually we all die unfortunately wellit lives onrightas a pretty good impersonation of meand what happens when i'm dead and it'sstill learning is that meis that an artifact of me or is it justa stupid artifact of history that you'llkeep in a box and some future will sayoh eric was so stupid back then but it'sentertaining to watch him right becausehe didn't keep learning we don't know wehave no way of discussing these thingsthis stuff is incredibly powerful itwill be the basis of enormous gains inhuman healthlanguage translation communicationsummary and educationall the things that milken representswill be affected in an almost alwayspositive way having said that there'sterrifying consequences as well so thefirst question has to do with jobsdoes this fundamentally mean there aremore jobs or less jobs i spent my wholelife people saying computers willreplace humans humans won't haveanything to do so far that narrative hasbeen false notice that there's a hugesurplus of jobs and not people to fillit certainly in the united states thesecond one has to do with nationalsecurity something i've worked on foralmost a decade nowand in our in the kissinger book we talka lot about thiswhat happens when the...

Listen to Cautionary Tales: https://www.listennotes.com/podcasts/cautionary-tales/cautionary-conversation-the-FW0bxClD_ij/

Listen to Ted Talks Daily: https://www.listennotes.com/podcasts/ted-talks-daily/the-marvels-and-mysteries-JkbNAa9DMYl/ (or video: https://www.ted.com/talks/heidi_hammel_and_nadia_drake_the_marvels_and_mysteries_revealed_by_the_james_webb_space_telescope?language=en)more with Heidi: https://www.youtube.com/watch?v=oMbeCKh-9v4

Listen to Revisionist History and Inside Voice: https://www.listennotes.com/podcasts/revisionist-history/from-inside-voice-lake-bell-8XVyoz7eT5A/

LIsten on YouTube: https://www.youtube.com/watch?v=O1puRnV6gwE

Listen to the Chopping Block:Nov 9 https://www.listennotes.com/podcasts/unchained/the-chopping-block-ftx-the-3ki-p42chnb/Nov 16 https://www.listennotes.com/podcasts/unchained/the-chopping-block-why-rlhFySZAtMB/

- Listen to Data Eng Podcast: https://www.dataengineeringpodcast.com/data-ecosystem-year-in-review-2021-episode-251/- How dbt Fails: https://benn.substack.com/p/how-dbt-fails