Podcasts about kth

Kärnkraften är på tapeten igen. Många politiker vill satsa på ny kärnkraft. Andra menar att det tar för lång tid och blir för dyrt. Men hur ser egentligen kärnkraftens svenska historia ut? Och hur har attityderna till kärnkraft förändrats? Per Högselius är forskare på KTH och har ägnat sig åt det här ämnet i många år. Här berättar han om kärnkraftens historia.Detta är det sista avsnittet av fyra som vi gör i samarbete med Riksbankens jubileumsfond. Vill du läsa mer om deras årsbok med temat "misslyckanden", går du in på www.rj.se.Programledare: Fritte FritzsonProducent: Ida WahlströmKlippning: Silverdrake förlagSignaturmelodi: Vacaciones - av Svantana i arrangemang av Daniel AldermarkGrafik: Jonas PikeFacebook: https://www.facebook.com/alltduvelatveta/Instagram: @alltduvelatveta / @frittefritzsonHar du förslag på avsnitt eller experter: Gå in på www.fritte.se och leta dig fram till kontakt!Podden produceras av Blandade Budskap AB och presenteras i samarbete med Acast Become a member at https://plus.acast.com/s/alltduvelatveta. Hosted on Acast. See acast.com/privacy for more information.

Hitta billig mat eller bli rik på bitcoins - många influencers vill ge sina följare ekonomiska råd. Men vem kan man lita på? Lyssna på alla avsnitt i Sveriges Radio Play. Hör Moa Langemark, Finansinspektionen, om varningstecknen att hålla utkik efter när det gäller ekonomiska tips i sociala medier. Dessutom, så sparar du pengar på den nya effektavgiften som elnätsbolagen inför. Hans Nordstrand, Energi- och klimatrådgivningen i Stockholms stad, förklarar. Och är vi beredda att minska vår bostadsyta för att minska vår klimatpåverkan? Så litet behöver vi bo för att leva hållbart. Samtal med Pernilla Hagbert, forskare på KTH. Programledare: Anna BergProducent: Linda Aktén

Kärnkraftsdebatten har kört in i en återvändsgränd av ensidig argumentation som i för stor utsträckning fokuserar på kostnad och kilowattimmar. Geografisk placering av reaktorer, svängmassa och andra faktorer som kan gynna stabilitet i elsystemet är minst lika viktiga, skriver Lars Nordström, professor i elkraftteknik på KTH, som skissar på hur en utbyggnad kan se ut. Inläsare: Jörgen Huitfeldt

1800-talet har kallats arsenikens århundrade. Då användes Arsenik till allt möjligt; färgglada tapeter, kläder och karameller, som läkemedel och bekämpningsmedel. Det var lättillgängligt, luktlöst och starkt giftigt - ett ämne som orsakade stor debatt. Vi fördjupar oss i arseniken : dödens färg. Medverkande: Emelie Höglund från Hallwylska museet, Göran Ståhlbom från KTH och Olle Matsson från Uppsala universitet.    Bild: The Arsenic Waltz The new dance of death. (Dedicated to the green wreath and dress-mongers), John Leech (1817-1864), Punch Magazine, 1862. Färgad samt beskuren.

Det här avsnittet med Thom Thavenius, biträdande säkerhetschef på KTH och f d underrättelseofficer, är inspelat innan händelserna i Vita Huset med Trump och Zelensky. Och det har inte direkt blivit lugnare sen dess.Enligt Thom Thavenius ägnar sig Trump åt, ”strategiskt självskadebeteende”, han behöver inte ens genomföra det han säger för att det skall skada oss som bor i Europa. Men det är vad det är och vi diskuterar därför mycket kring hur vi kan ta hand om vår säkerhet själva.Många tror att de största riskerna för Sverige är cyberattacker och förgiftat dricksvatten. I själva verket är det du och jag som är den svaga punkten. Därför tycker Thom att vi alla skall bli lite mer paranoida för husbehov.Vi pratar också om att Sverige är ett av fem länder i världen som kan utveckla stridsflygplan och vad det betyder för oss, hur Iran, Ryssland, Kina och självaste USA spionerar på Sverige, skillnaden mellan brunt och vitt heroin, varför public service är viktigt, att vara tullare i Ryssland och hur det kom sig att han som barn skjutsat runt Kronprinsessan Victoria på en grön cykel. Hosted on Acast. See acast.com/privacy for more information.

Inläst: KTH-student hackade Verisures hemlarm – och hittade allvarliga säkerhetsbrister. "Kan göra sitt inbrott i lugn och ro". Lyssna på en artikel av Sara L Bränström.

Med klingande fransk brytning presenterar Emmanuel Macron jättesatsningar på AI. Men samtidigt är det rätt tyst från svenskt håll. Henning Eklund ringer upp statsminister Ulf Kristersson och frågar varför. Och Elon Musk rör om i politiken med sitt Doge. Björn Jeffery granskar Silicon Valley-filosofin som nu tagit sig in i maktens korridorer. Dessutom: Kendrick vs Drake, fast för de som pluggat på KTH. SvD Tech brief är en podd från Svenska Dagbladet. Feedback: techbrief@svd.se Signa upp dig för nyhetsbrevet: https://www.svd.se/story/tech-brief-nyhetsbrev

Sprängningar och skjutningar får bostadsköpare att tveka. Bottenplan går bort, och det är svårt att få lägenheterna sålda. Samtidigt har bostadsrättsföreningarna små möjligheter att kasta ut kriminella medlemmar som kan vara måltavlor. Lyssna på alla avsnitt i Sveriges Radio Play. På flera av de adresser där det varit sprängningar har det också varit lägenheter till salu. Enligt en tidigare studie från KTH kan värdet på en bostad minska kraftigt om det varit en skjutning i närheten.Trygghet allt viktigare – köpare kollar upp grannarnaSamtidigt visar en annan undersökning att trygghet seglat upp som den allra viktigaste faktorn när man väljer var man ska flytta, och fastighetsmäklare märker också att köparna har börjat kolla upp vilka grannar som bor på adressen innan de kommer på visningen. Begreppet ”läge, läge, läge” har fått en ny innebörd.Räntan sänks igenI veckan sänktes styrräntan igen. Men frågan är om det var för sista gången, och vad det innebär för bostadspriserna i stort. Vissa analytiker tror på kraftig prisuppgång i år, andra är mer skeptiska.Programledare och producent:Hanna MalmodinMedverkande och röster i programmet:Tor Borg, analyschef CityMark Analys & ByggfaktaThomas Heldmark, reporter P4 StockholmJoakim Lusensky, analys- och kommunikationschef MäklarsamfundetErik Holmberg, analytiker HemnetUlrika Blomqvist, vd BostadsrätternaKonstantin Åström, fastighetsmäklare i AkallaAdi Stukan, fastighetsmäklare i Enskedeekonomiekotextra@sverigesradio.se

I det här fortsatta samtalet med Emilia Poole Jönsson, ordförande för Sveriges Arkitekter Studenterna vid LTH, samt Andréa Caceres Ramirez och Axel Larsen från KTH, dyker vi djupare in i studenternas perspektiv på arkitekturutbildning och karriärmöjligheter i branschen. Vi diskuterar frågor som: Vad är nästa steg för er studenter? Vad uppskattar ni mest med arkitekturutbildningen på KTH? Vad skulle ni vilja se mer av i utbildningen? Vi reflekterar också kring branschens framtid, inklusive den aktuella arbetslösheten på cirka 10%, och våra gäster delar sina tankar om hur studenter och yrkesverksamma kan navigera dessa utmaningar. Avslutningsvis får de ge ett inspirerande medskick till både studenter och branschkollegor som lyssnar. Lyssna på avsnitt nummer 497 om du har missat mitt första samtal med studenterna. 497. SWE idéutlysningen Stadsbyggnad Genom Samarbete, samtal med vinnare _____ Keep Up the Good Work. Keep Loving Cities ❤️️ All opinions expressed in each episode are personal to the guest and do not represent the Host of Urbanistica Podcast unless otherwise stated. Let's connect and talk further about this episode ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Mustafa Sherif Linkedin⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Visit  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Mustafasherif.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ for collaborations and nominations or email me at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠info@mustafasherif.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Follow Urbanistica on ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Instagram⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠TikTok⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Facebook⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ & ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Youtube channel⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Thanks to Urbanistica Podcast partner AFRY (Urban Planning and Design) AFRY is an international engineering and design company providing sustainable solutions in the fields of energy, industry, and infrastructure.

I detta avsnitt intervjuar Mustafa Emilia Poole Jönsson, ordförande för Sveriges Arkitekter Studenterna vid LTH, samt vinnarna av idéutlysningen "Stadsbyggnad Genom Samarbete" – Andréa Caceres Ramirez och Axel Larsen från KTH. Vi pratar om idéutlysningen som hösten 2024 bjöd in arkitektur- och stadsbyggnadsintresserade studenter att ta fram nytänkande förslag för utvecklingen av stadsdelen Tensta i Stockholm. Initiativet, arrangerat av Sveriges Arkitekter Studenterna i samarbete med Arwidssonstiftelsen, resulterade i 16 inspirerande förslag. Vi djupdyker i det vinnande bidraget Kvinnonavet – Hjärtat i Bärkingeplan och diskuterar visionerna bakom en mer hållbar stadsutveckling. Läs mer om tävlingen och bidraget här https://www.arkitekt.se/tavling/stadsbyggnad-genom-samarbete/ _____ Keep Up the Good Work. Keep Loving Cities ❤️️ All opinions expressed in each episode are personal to the guest and do not represent the Host of Urbanistica Podcast unless otherwise stated. Let's connect and talk further about this episode ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Mustafa Sherif Linkedin⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Visit  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Mustafasherif.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ for collaborations and nominations or email me at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠info@mustafasherif.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Follow Urbanistica on ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Instagram⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠TikTok⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Facebook⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ & ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Youtube channel⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Thanks to Urbanistica Podcast partner AFRY (Urban Planning and Design) AFRY is an international engineering and design company providing sustainable solutions in the fields of energy, industry, and infrastructure.

In this episode, the co-founder and CEO of Climatize, Will Wiseman discusses how Climatize is helping everyday Americans fund solar, energy efficiency, and EV projects via their platform while allowing investors to earn up to 10% annually. Will also discusses what a Trump 2025 presidency means for the United States in terms of renewable energy investments and infrastructure. Founded in 2023, Climatize is an SEC-registered impact investing platform that allows investors to fund renewable energy projects while earning up to 10% annually. Climatize has helped to fund millions of dollars worth of solar projects across the United States. Climatize works with dozens of renewable energy developers across the United States to source projects for its platform. Climatize's investing platform allows any investor in the United States over the age of 18 to invest in renewable energy projects. Climatize was a finalist in Fast Company's 2024 World Changing Ideas list for both the Company of the Year and Impact Investing categories. Climatize is also a 2024 Keeling Curve Prize winner. For more information about Climatize please visit https://www.climatize.earth/. During the course of his 10+ years in the industry, Will has had a hand in every function of the solar energy business including, but not limited to finance, project management & construction where he built 15 solar arrays. He holds two MSc in Renewable Energy Engineering from KTH, the Royal Institute of Technology. Will Wiseman and his co-founder, Alba Forns, are 2023 Forbes 30 under 30 recipients.

In this episode, the co-founder and CEO of Climatize, Will Wiseman discusses how Climatize is helping everyday Americans fund solar, energy efficiency, and EV projects via their platform while allowing investors to earn up to 10% annually. Will also discusses what a Trump 2025 presidency means for the United States in terms of renewable energy investments and infrastructure. Founded in 2023, Climatize is an SEC-registered impact investing platform that allows investors to fund renewable energy projects while earning up to 10% annually. Climatize has helped to fund millions of dollars worth of solar projects across the United States. Climatize works with dozens of renewable energy developers across the United States to source projects for its platform. Climatize's investing platform allows any investor in the United States over the age of 18 to invest in renewable energy projects. Climatize was a finalist in Fast Company's 2024 World Changing Ideas list for both the Company of the Year and Impact Investing categories. Climatize is also a 2024 Keeling Curve Prize winner. For more information about Climatize please visit www.climatize.earth/. During the course of his 10+ years in the industry, Will has had a hand in every function of the solar energy business including, but not limited to finance, project management & construction where he built 15 solar arrays. He holds two MSc in Renewable Energy Engineering from KTH, the Royal Institute of Technology. Will Wiseman and his co-founder, Alba Forns, are 2023 Forbes 30 under 30 recipients.

Snö och kyla är del av vilka vi är. Nu när glaciärer smälter och snödagarna bli färre väcks nya tankar om vår historia, identitet och kultur. Vilka blir vi utan snö och kyla? Lyssna på alla avsnitt i Sveriges Radio Play. Snö och kyla har väckt intresse genom historien hos vetenskapsmän, filosofer och konstnärer.På 1500-talet skrev kyrkomannen Olaus Magnus boken Historia om de nordiska folken, där han i patriotiska ordalag beskrev människornas liv och vanor i det nordliga landskapet. Under 1600-talet började filosofin intressera sig för snö och kyla. Descartes, som myten säger avskydde kyla, var mycket fascinerad av skönheten hos snökristaller och is och förundras av deras stora variationer och vädrets oförutsägbarhet. Även inom konsten har vintervita landskap fångat konstnärernas och betraktarnas beundran, ofta med romantiska och nationalistiska förtecken. Vårt sätt att se på frusen natur har ändrats både inom filosofin och konsten. Klimatförändringarnas som innebär att glaciärer smälter och snögränserna förflyttas har väckt nya frågor. Människans relation och ansvar till naturen betonas. Annan kunskap om snö och kyla som många urfolk besitter lyfts fram. Ett begrepp som solastalgi har myntats för att beskriva den sorg som uppstår när den miljö man lever i förändras för alltid. Vad betyder snö och kyla för människan? Vilka lärdomar kan vi ta med oss från historien och vad händer med vår identitet när snö och is smälter?Medverkande: Cecilia Sjöholm, professor i estetik vid Södertörns högskola och Sverker Sörlin, professor i miljöhistoria vid KTH och författare, nu senast till boken Snö - en historia.Programledare: Cecilia Strömberg WallinProducent: Marie LiljedahlResearch: Anton ÅhlbergVeckans tips:Böcker:How Forests Think: Toward an Anthropology Beyond the Human - Eduardo KohnJuice - Tim Winton

Rosa Danenberg (PhD, Stadsplanerare, Stockholm, Sverige) Vilken roll spelar bottenvåningar och hur kan planering, design och förvaltning främja skapandet av anpassningsbara och resilienta huvudgator? Rosa pratar om sin doktorsavhandling "Main streets as resilient public spaces: Zooming in on ground floors in Stockholm". Avhandlingen försvarades vid KTH i fjol, vid avdelningen för urbana och regionala studier. I avhandlingen redovisas resultatet av en djupgående social och rumslig socio-spatial analys av hur bottenvåningar på huvudgator i Stockholm förändrats mellan 2009 och 2018 och deras anpassningsbarhet och resiliens, i syfte att förstå hur planering, design och förvaltning kan stödja huvudgatornas fortsatta existens i framtiden. Läs mer om Rosas forskning ⁠https://www.studiodanenberg.com/publications⁠ Mer om Rosa https://www.kth.se/en/som/nyheter/congratulations-rosa-danenberg-1.1303252 _____ Keep Up the Good Work. Keep Loving Cities ❤️️ All opinions expressed in each episode are personal to the guest and do not represent the Host of Urbanistica Podcast unless otherwise stated. Let's connect and talk further about this episode ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Mustafa Sherif Linkedin⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Visit  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Mustafasherif.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ for collaborations and nominations or email me at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠info@mustafasherif.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Follow Urbanistica on ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Instagram⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠⁠⁠⁠⁠TikTok⁠⁠⁠⁠⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Facebook⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ & ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Youtube channel⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Thanks to Urbanistica Podcast partner AFRY (Urban Planning and Design) AFRY is an international engineering and design company providing sustainable solutions in the fields of energy, industry, and infrastructure.

I detta avsnitt dyker vi ner i den fascinerande svenska rymdhistorien tillsammans med rymdlegendaren Sven Grahn. Vi brukar gilla att spana framåt i den här serien, och hålla koll på vad som händer just nu inom rymdområdet. Men då och då behöver vi också blicka bakåt, och se tillbaka på vad det är som gjort att vi står där vi står. Hur ser Sveriges rymdhistoria ut egentligen? I det här avsnittet pratar vi med en person som varit med på resan, i princip ända sedan starten. Den svenske rymdlegendaren Sven Grahn tog examen som civilingenjör inom teknisk fysik vid KTH 1969, har ägnat ett decennium åt atmosfärisk fysik vid Stockholms universitet, jobbat i 31 år på Rymdbolaget, och är nu tillbaka på KTH där han leder studentsatellitprojektet MIST. Han ger oss inblick i ett helt arbetsliv i rymdens tjänst, och bjuder på både egna citat och sådana hämtade från andra rymdhjältar. Han ger oss en unik inblick i de första rymdprojekten och skapandet av Esrange, och vi får också höra om hur den svenska rymdsektorn har blivit allt mer kommersiell och hur det militära intresset för rymdteknologi har ökat.Vill du veta mer om rymdprogram och rymdstrategi? Hur påverkar rymdengagemanget vår förståelse för universum? I Har vi åkt till Mars än? får du svaren på dessa frågor och mycket mer. Låt dig inspireras av berättelser om marsrovrar, rymdstationer och den mänskliga kolonisering av Mars som kan bli verklighet i framtiden.Så luta dig tillbaka och följ med Susanna och Marcus på en resa genom rymden, där vi tillsammans utforskar de oändliga möjligheterna och utmaningarna som väntar i rymden. Missa inte detta avsnitt av Har vi åkt till Mars än? – en rymdpodd som lovar att väcka din nyfikenhet och ge dig en djupare förståelse för vår plats i solsystemet!Har vi åkt till Mars än? görs på Beppo av Rundfunk Media i samarbete med Saab.Hosted by Ausha. See ausha.co/privacy-policy for more information.

Hur går det att vara forskare och entreprenör samtidigt; att å ena sidan söka vetenskaplig kunskap och å andra sidan kanske tjäna pengar på denna kunskap som företagare? Samhället väntar ständigt på fler och bättre innovationer som resultat från forskning – samtidigt som forskaren har sitt oberoende och sin trovärdighet att värna om. Hör innovationsrådgivaren Mats Wictorsson på SLU Holding, SLU-forskarna Torgny Näsholm och Mariette Andersson och KTH-forskaren Fredrik Gröndahl – samtliga också entreprenörer.

A Chinese vessel is the centre of attention as authorities investigate two damaged cables in Baltic Sea. It's been described as potential sabotage, but this is rarely proven says Hans Liwång from the Swedish Defence University and KTH. And: Northvolt files for Chapter 11 bankruptcy protection as its CEO Peter Carlsson steps down.Also: Ever wondered why so much of your personal information is out in the open, posted on websites like Ratsit and MrKoll? Change could be on the way to limit this.And: Despite warnings from the Migration Agency, the National Audit Office says they could find no evidence of widespread abuse of study permits among international students from outside the EU.Presenters: Michael Walsh and Dave RussellProducer: Kris Boswell

Tänk om vi kunde ta hissen upp till rymden! I detta spännande avsnitt av Har vi åkt till Mars än? dyker vi ner i det fascinerande konceptet med rymdhissar, hållfasthet och material. Tillsammans med Gunnar Tibert, universitetslektor i rymdteknik på KTH, utforskar vi hur dessa futuristiska strukturer skulle kunna revolutionera våra rymdupplevelser och göra resor till Mars mer tillgängliga än någonsin. Och när man bygger för rymden är hållfasthet viktigt. Vi träffar Sindra Petersson Årsköld, fysiker, kemist, biofysiker och sedan 13 år senior forskningsrådgivare på ESS, European Spallation Source, utanför Lund, där de använder neutroner för att mäta olika material.Oavsett om du är en rymdentusiast, en astronaut i hjärtat, eller bara nyfiken på rymdteknologi, kommer detta avsnitt av Har vi åkt till Mars än? att ge dig en nyfikenhet för rymdforskning och en insikt i framtidens rymdresor. Missa inte chansen att följa med på denna fantastiska resa genom universum!```Har vi åkt till Mars än? görs på Beppo av Rundfunk Media i samarbete med Saab.Hosted by Ausha. See ausha.co/privacy-policy for more information.

Vi ger oss ut på en fascinerande resa genom den svenska rymdhistorien. Tillsammans med Anna Rathsman, generaldirektör för Rymdstyrelsen, utforskar vi hur Sverige har bidragit till rymdforskning och rymdteknologi. Rathsman, som har en bakgrund som ingenjör från KTH, delar med sig av sin inspirerande resa in i rymdbranschen och berättar om sina erfarenheter av att arbeta med svenska satelliter som Freja och Astrid. Dessa projekt har varit avgörande för Sveriges rymdverksamhet och visar hur långt vi har kommit inom rymdvetenskap.Vi får också en kort kommentar från den nyss utsedde generaldirektören Ella Carlsson om hennes förväntningar på jobbet och framtiden för svensk rymdverksamhet. Har vi åkt till Mars än? görs på Beppo, av Rundfunk Media i samarbete med Saab.Hosted by Ausha. See ausha.co/privacy-policy for more information.

7 november. Kan små, modulära reaktorer vara ett sätt att få känkraft på plats förhållandevis snabbt och billigt? Vilka är möjligheterna, och vilka är hindren? Jesper Sandström diskuterar med Janne Wallenius, professor i reaktorfysik vid KTH, och medgrundare av SMR-tillverkaren Blykalla.

På vägen mot Mars tar vi idag en liten avstickare och dyker ner i mysterierna kring Venus, vår närmaste granne i solsystemet. Moa Persson, postdoktor vid Institutet för rymdfysik, tar oss med på en fascinerande resa där vi utforskar Venus som en jordliknande planet, men som samtidigt är en av de mest ogästvänliga platserna i vår närhet. Med en yttemperatur som når upp till 460 grader Celsius och ett atmosfärstryck som är 93 gånger högre än på jorden, kallas Venus ofta för jordens elaka tvilling. Vi pratar om olika Venusmissioner och träffar också Carl-Mikael Zetterling, professor i elektronik och inbyggda system på KTH, där han bland annat har lett projektet Working on Venus.Vi besöker också Fotografiska Stockholm och pratar med konstnären Cecilia Ömalm och astronomen Göran Östlin som berättar om sitt projekt Ad Lucem som de ställer ut delar av på museet.Har vi åkt till Mars än? görs på Beppo, av Rundfunk Media i sammarbete med Saab.Hosted by Ausha. See ausha.co/privacy-policy for more information.

Der er ingen tvivl om, at datacentrenes computere og deres kolossale energiforbrug er en af af de største aktuelle udfordringer med især generativ AI.Men måske lurer en helt ny type af computere i baggrunden, som potentielt kan være med til at løse problemet. De kaldes neuromorfiske computere, og bliver bygget efter samme principper som biologiske hjerner – og de er ekstremt energieffektive, sammenlignet med de computere vi kender.Dagens gæst er Jens Egholm Pedersen, Phd-studerende ved KTH i Stockholm. Jens' forskningsfokus drejer sig især om hvordan man kan lave programmeringssprog og andre værktøjer til neuromorfiske computere – når de så småt begynder at blive virkelighed…I Siden Sidst skal vi høre om det nye danske grundforskningscenter TEXT, om YouTube-AI-licenser, og så er der selvfølgelig mere ballade i OpenAI.Lyt med

Hur kan vi samarbeta smartare så att allas perspektiv och kompetens kommer till sin rätt?Helheten är större än summan av än delarna brukar man säga. När fler perspektiv och kompetenser bidrar presterar vi bättre på jobbet. Men hur gör man för att få det att funka?Vi fick ett samtal på temat kollektiv intelligens med Alexander Löfgren som är doktor i industriell ekonomi och organisation vid KTH. Alexander är också författare och konsult på Influence och hjälper till att utveckla kollektiv intelligens i offentlig och privat sektor. Han betonar vikten av att hitta enkla sätt att samarbeta i en komplex värld.Förmågan att fatta de bästa beslutenKollektiv intelligens baseras på forskning från bland annat Handelshögskolan. Det handlar om förmågan att kunna fatta de bästa besluten och att också agera på dem. Det kan handla om att lösa vanliga vardagsproblem men också om hur vi tar tag i större utmaningar och problem med hjälp av all kompetens och alla perspektiv som finns i organisationen.För att spränga silos mellan grupper i en organisation behöver vi ofta utmana invanda strukturer och processer. Däremot kan vi inte jobba i ett tomrum, så någon form av struktur behövs förstås. Alexander ger exempel som liknar agil metodik, när man gör saker i små steg, med mycket samverkan, i snabba återkopplingsloopar.Mikrosystem för mikrobeslutEtt bra sätt att börja är att se över vilka som är beroende av varandra på vilka sätt. Han rekommenderar att skapa något han kallar mikrosystem med mikroarenor, för att kunna fatta mikrobeslut. Det är tillfälliga strukturer, som till exempel återkommande möten under en begränsad period, där människor från olika delar av organisationen ses och delar med sig av tankar och förslag och där beslut kan fattas i steg, Det här sättet att jobba frigör handlingskraft.Vi behöver också sätta vår karta och vår kompass för ett sånt här samarbete. Vilka spelregler gäller och hur ska vi samarbeta över olika roller och kompetenser? Vad krävs av var och en? Vad krävs av just mig för att jag ska kunna bidra till gruppen på bästa sätt?Alexander rekommenderar att se till att processen är meningsskapande. Ibland är vi lite väl snabba i prestationsdimensionen och det gör att slutmålet ofta är mycket tydligare än vägen dit. Om vi tar ett steg tillbaka och diskuterar syftet och var och ens motivation för att bidra, uppstår meningsfullheten. Blir du nyfiken att lära dig mer om det här kan du läsa Alexanders bok Smart samarbete.Vår samarbetspartner Twitch Health ser till att hälsan blir av på arbetsplatser. De vet lika väl som du och jag att chefen är en nyckelperson för hälsa på arbetsplatsen. Men det är inte alltid så lätt för chefen själv att få till hälsa som blir av. Snarare har många chefer det svårt att balansera sin egen arbetsbelastning och stress samtidigt som de ska hjälpa sina medarbetare som ofta är under tryck. Det blir en paradox: en chefparadox! De här frågorna från Twitch Health kan hjälpa dig att hantera den här paradoxen. Hosted on Acast. See acast.com/privacy for more information.

Erik Almlöf har forskat om vad de självkörande bilarna kan betyda för samhället, när de väl kommer ut på vägarna. En effekt är att det kan bli mer biltrafik om också de som inte har körkort kan ta bilen. Lyssna på alla avsnitt i Sveriges Radio Play. Självkörande bilar framställs ofta som en positiv framtid för den som sitter i bilen, men vad det blir för effekter i själva samhället har det inte forskats lika mycket om. Det insåg Erik Almlöf, som jobbade i femton år som analytiker av kollektivtrafik, med prognoser om framtiden. Ofta fick han frågor om vad förarlösa fordon kunde innebära, när de väl kommer i trafiken.Så han började själv forska om det och har nyligen doktorerat vid KTH med en avhandling om vad just de förarlösa fordonen kan betyda för samhället.Förutom att påverka trafiken kan det påverka folkhälsan om fler börjar ta bilen, som annars kanske gått till buss och tåg, eller cyklat, menar han. Det kan också ställa till oreda i trafiken eftersom förarlösa bilar inte fantasi eller flexibilitet när det kan behövas i krångliga situationer.Och självkörande bilar skulle också kunna bli ett nytt mål för terrorangrepp, säger Erik Almlöf.Reporter: Björn Gunérbjorn.guner@sverigesradio.seProducent: Lars Broströmlars.brostrom@sverigesradio.se

På andra sidan pandemin fortsätter många svenskar att distansarbeta, men frågan har blivit något av en dragkamp mellan anställda och arbetsgivare. Hur bra fungerar det egentligen för anställda, chefer och för arbetet som ska göras? Lyssna på alla avsnitt i Sveriges Radio Play. Nu vill arbetsgivare få tillbaka sina anställda till kontoren mer än de anställda vill återvända dit. Uppåt 40% av svenskarna arbetar nu i någon utsträckning hemifrån, och forskning både före och efter pandemin visar att flexibilitet och möjlighet att delvis arbeta hemifrån är bra för både arbetsgivare och anställd, säger professor Andrea Eriksson på KTH. Men på många arbetsplatser pågår ännu diskussioner och förhandlingar om hur man ska ha det, säger professor Stefan Tengblad på Handelshögskolan i Göteborg. Och Kristina Palm, professor i arbetsvetenskap vid Karlstads universitet, vill öka medvetenheten om hur vi fördelar arbetsplatserna när båda jobbar hemma.Medverkande: Andrea Eriksson, professor ergonomi KTH; Kristina Palm, professor arbetsvetenskap Karlstads universitet; Stefan Tengblad, professor human resource management Handelshögskolan Göteborg; Mona Nilsson, gymägare Örnsköldsvik; Elsa Anell, student på yrkeshögskola.Reporter: Ylva Carlqvist WarnborgProducent: Camilla Widebeckcamilla.widebeck@sr.se

⁠Chero Eliassi⁠ (Landscape Architect & PhD Candidate at KTH Royal Institute of Technology, Sweden) We are talking about Chero's PhD research: -The outdoor environments built during the Swedish Million Program: -Highlights about the Swedish Million Program -What does Chero's research investigate? -What methodology is he using to find answers to his questions? -What are the findings? For more contact and information on Chero's research at KTH ⁠⁠here Follow the research on Instagram at @_researchero_ About Chero Chero Eliassi graduated with a Master´s degree in Landscape Architecture in 2019 at the Swedish University of Agricultural Sciences (SLU) in Uppsala. Eliassi has worked since 2021 as a doctoral student in Jennifer Mack's research project entitled 'Parks around the Towers: Landscape as Resource in the Urban Periphery from the Record Years to the Future'. From a historical perspective, the research investigates how the outdoor environments of the Million Programme have been transformed, used, and formed after the record years (1961-1975) and how these landscapes can be viewed as a part of the Swedish cultural heritage. With the title '“A Culture of Place” in Swedish Allotments: Gardens as Therapy and Threat in Holma, Malmö', Eliassi captures and investigates how cultivation in and adjacent to Million Programme areas have created social and therapeutic values, as well as a sense of collective belonging. The research is based on on-site studies in Malmö and other Swedish cities. In 'Voices and Visions of Norrlidsparken', Eliassi explores the welfare neighborhood park in Norrliden: Norrlidsparken. The research begins with a microhistory of the sand in the park, what values it has registered, and what it has witnessed since the park was constructed. Further, it presents Norrlidsparken's transformations from the early 1970s – in the form of physical, spatial, social, and material changes; planning regulations and guidelines; and political impact – until the present time. Eliassi is also currently studying how spatial cultural practices occur in the Million Programme's outdoor environments. The research, entitled 'The transnational spatial practice of Newroz: an analysis of the practice amongst the Kurdish diaspora in Järva Field and Diyarbakır (Amed)' is a research topic that focuses on the manifestation and values of the spatial practice of Newroz in Järva field, in Stockholm, in comparison with the practice in the Kurdish-populated city of Diyarbakir, Turkey. ______ Keep Up the Good Work. Keep Loving Cities ❤️️ All opinions expressed in each episode are personal to the guest and do not represent the Host of Urbanistica Podcast unless otherwise stated. Let's connect and talk further about this episode ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Mustafa Sherif Linkedin⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Visit  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Mustafasherif.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ for collaborations and nominations or email me at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠info@mustafasherif.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Follow Urbanistica on ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Instagram⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠⁠TikTok⁠⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Facebook⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ & ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Youtube channel⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Thanks to Urbanistica Podcast partner AFRY (Urban Planning and Design) AFRY is an international engineering and design company providing sustainable solutions in the fields of energy, industry, and infrastructure. --- Send in a voice message: https://podcasters.spotify.com/pod/show/urbanistica-podcast/message

Chero Eliassi (Landscape Architect & PhD Candidate at KTH Royal Institute of Technology, Sweden) We are talking about: -How is it to do a PhD?-What are the challenges?-What are the fun parts of doing a PhD?-What is the process of becoming a PhD candidate? For more contact and information on Chero's research at KTH ⁠here. ⁠ Follow the research on Instagram at: @_researchero_ ______ Keep Up the Good Work. Keep Loving Cities ❤️️ All opinions expressed in each episode are personal to the guest and do not represent the Host of Urbanistica Podcast unless otherwise stated. Let's connect and talk further about this episode ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Mustafa Sherif Linkedin⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Visit  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Mustafasherif.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ for collaborations and nominations or email me at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠info@mustafasherif.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Follow Urbanistica on ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Instagram⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠⁠TikTok⁠⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Facebook⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ & ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Youtube channel⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Thanks to Urbanistica Podcast partner AFRY (Urban Planning and Design) AFRY is an international engineering and design company providing sustainable solutions in the fields of energy, industry, and infrastructure. --- Send in a voice message: https://podcasters.spotify.com/pod/show/urbanistica-podcast/message

Björn Berggren (Skolchef vid Skolan för arkitektur och samhällsbyggnad, KTH, Stockholm, Sverige) Vi pratar om: -Hur var undervisningen under COVID? -Hur undervisar KTH nu? Fysisk vs. digital undervisning. -Relationen mellan akademi och praktik: Hur når vi ut med det som akademin producerar till praktiker? Vad behöver vi göra? -Björns ledarskap som skolchef vid Skolan för arkitektur och samhällsbyggnad på KTH. ______ Keep Up the Good Work. Keep Loving Cities ❤️️ All opinions expressed in each episode are personal to the guest and do not represent the Host of Urbanistica Podcast unless otherwise stated. Let's connect and talk further about this episode ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Mustafa Sherif Linkedin⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Visit  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Mustafasherif.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ for collaborations and nominations or email me at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠info@mustafasherif.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Follow Urbanistica on ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Instagram⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠TikTok⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Facebook⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ & ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Youtube channel⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Thanks to Urbanistica Podcast partner AFRY (Urban Planning and Design) AFRY is an international engineering and design company providing sustainable solutions in the fields of energy, industry, and infrastructure. --- Send in a voice message: https://podcasters.spotify.com/pod/show/urbanistica-podcast/message

I'm not a financial advisor; Superpowers for Good should not be considered investment advice. Seek counsel before making investment decisions.Watch the show on television by downloading the e360tv channel app to your Roku, AppleTV or AmazonFireTV. You can also see it on YouTube.When you purchase an item, launch a campaign or invest after clicking a link here, we may earn a commission. Engage to support our work.Devin: What is your superpower?Will: I can teach myself anything.In today's episode of Superpowers for Good, I had the pleasure of speaking with Will Wiseman, CEO and Co-Founder of Climatize. Will's journey from witnessing the 2019 climate strikes in Barcelona to founding a groundbreaking crowdfunding platform for renewable energy is nothing short of inspiring.During our conversation, Will shared a pivotal moment from the climate strikes that sparked his realization. "Seeing over 100,000 people protesting for climate action, I was struck by the sad realization that traditional activism lacked the tangible change necessary to solve this macro problem," he said. This insight led him to create Climatize, a platform enabling anyone to invest in renewable energy projects with as little as $5.Climatize's mission is clear: to make impact investing accessible to everyone. “Climate change is an all-hands-on-deck problem,” Will emphasized. “We need everybody at any capacity to become a participant.” By allowing investments to start at just $5, Climatize ensures that virtually anyone can contribute to combating climate change and be part of the energy transition.The success of Climatize speaks volumes. Since its launch in May 2023, the platform has catalyzed nearly $3.5 million of investments into 11 solar and storage projects across seven states. These projects are projected to avoid emissions equivalent to 65 million vehicle miles. Investors are not only contributing to environmental solutions but also seeing tangible impacts of their investments. One of the standout features of Climatize is the transparency it offers. Investors can see the direct impact of their contributions, from project development to installation. This level of engagement fosters trust and encourages more people to participate. “Knowing that your money went and helped this family as well as created environmental impact is what we've found to be very catalytic,” Will explained.Will's dedication and innovative approach have turned Climatize into a beacon for those wanting to make a real difference. As he said, “This is one of the largest wealth creation opportunities of our lifetime, and it's incredibly important that everybody has the potential to participate as an active stakeholder in the energy transition.”In this episode, we delved into how Climatize is reshaping the landscape of renewable energy investments, proving that with the right platform, small contributions can lead to significant change.AI Episode Summary1. Will Wiseman is the CEO of Climatize, involved in Crowdfunding for climate solutions.2. Will was inspired to start Climatize after witnessing the 2019 climate strikes in Barcelona and realizing traditional activism was insufficient.3. Climatize is an SEC-registered funding portal enabling anyone to invest in renewable energy projects with as little as $5.4. Since launching in May 2023, Climatize has catalyzed nearly $3.5 million in investments into 11 projects across seven states.5. These projects are projected to avoid emissions equivalent to 65 million vehicle miles.6. Crowdfunding allows investors to see the tangible impact of their money, different from traditional ESG investments.7. Climatize has a strong trust factor with investors, resulting in an average check size of $6,000, compared to the industry average of $2,000.8. Projects on Climatize are often funded quickly, some in as little as two hours.9. Will attributes his success to aligning his skills with his passions and his ability to self-teach.10. To encourage investment, new users can receive a $10 credit on Climatize, enabling them to start investing right away.How to Develop Passionate Self-Teaching As a SuperpowerSummary of Will's Superpower:Will's superpower is his ability to align his passions with his skills, driven by a deep curiosity that fuels his continuous self-education. This combination allows him to tackle challenges and acquire new knowledge effectively.Illustrative Story:In the interview, Will shared how he delved into the renewable energy tax credit space following the Inflation Reduction Act. This new area allowed tax credits from renewable projects to be transferred. Despite the market existing for only about nine months, it scaled rapidly to $9 billion. Will taught himself the intricacies of this emerging field by voraciously consuming information from podcasts, readings, and thought leaders. This self-directed learning enabled him to incorporate tax credit transactions into Climatize's offerings, demonstrating his superpower in action.Tips for Developing This Superpower:1. Follow Your Curiosity: Engage with topics that naturally interest you to maintain motivation and drive.2. Consume Relevant Content: Listen to industry-specific podcasts and read extensively to build fluency and stay informed.3. Identify Knowledge Gaps: Seek out and master areas where your understanding is lacking.4. Incremental Learning: Tackle complexities step by step, continually pushing your understanding.5. Emulate Industry Leaders: Use thought leaders as benchmarks and learn from their insights and strategies.6. Maintain Consistent Effort: Treat learning like training for a sport, with structured and regular efforts to improve.Conclusion:By following Will Wiseman's example and advice, you can make passionate self-teaching a skill. With practice and effort, you could make it a superpower that enables you to do more good in the world.Remember, however, that research into success suggests that building on your own superpowers is more important than creating new ones or overcoming weaknesses. You do you!Guest ProfileWill Wiseman (he/him):CEP & Co-Founder, ClimatizeAbout Climatize: Climatize enables you to invest in sustainability and reduce your tax liability in one platform. It is an SEC-registered Funding Portal that allows it to issue debt securities and leverage tax credit transferability. This creates a comprehensive platform where renewable energy developers can receive full-capital stack finance for their projects.Website: www.climatize.earthX/Twitter Handle: @Climatize_earthCompany Facebook Page: fb.com/climatize.earth/Linkedin: linkedin.com/company/climatize-earth/Other URL: Your App StoreBiographical Information: Will has a 10-year track record in renewable energy, particularly solar, with experience in every role, including finance, engineering, project management, and construction, where he has built 15 solar farms. His company, Climatize, makes it incredibly simple to invest in renewable energy projects across the US with as little as $10 while earning up to 10% annually. As the CEO and Co-Founder of Climatize, Will has built a community of over 780 investors who have invested over $3,400,000 in 11 community solar projects in 7 states.He holds a Double MSc in Renewable Energy Engineering from KTH, the Royal Institute of Technology.Will was among the 2023 Forbes 30 Under 30 honorees in the Social Impact category & selected among the Young Global Changers by the World Policy Forum in 2022.Will's goal is to fund $1 billion per year of renewable energy projects within 5 years. Together with the team at Climatize, he's building the financial network for climate action that enables anyone to invest in any renewable energy project from anywhere in the world.X/Twitter Handle: @MrWwwisemanLinkedin: https://www.linkedin.com/in/will-wiseman/ Instagram Handle: @climatize.earthUpcoming SuperCrowd Event CalendarIf a location is not noted, the events below are virtual.* Impact Cherub Club Meeting hosted by The Super Crowd, Inc., a public benefit corporation, on May 21, 2024, at 1:00 PM Eastern. Each month, the Club meets to review new offerings for investment consideration and to conduct due diligence on previously screened deals. To join the Impact Cherub Club, you must first become an Impact Member of the SuperCrowd.* SuperCrowdHour, June 19, 2024, at 1:00 Eastern. Each month, we host a value-laden webinar for aspiring impact investors or social entrepreneurs. At this month's webinar, Angela Barbash of Revalue will share insights about moving money from Wall Street to Main Street. Register here.* SuperCrowdChicago, June 12, 2024. This in-person event at Columbia College Chicago features some of Chicago's prominent citizens and community leaders, along with crowdfunding experts. Use the discount code “SuperCrowd” to save 30 percent!* Recently, we created an AI GPT to help you learn more about The Super Crowd, Inc., a public benefit corporation, and our upcoming events. Click here to try it.SuperCrowd Community Event Calendar* Successful Funding with Karl Dakin, Tuesdays at 10:00 AM ET * KingsCrowd's upcoming Demo Day, (Today!) Thursday, May 16th at 12:00 am ET/9:00 am PT* Crowdfunding Professional Association Webinar, May 29, 2:00 PM ET* The Reg A & Crowdfunding Conference, June 20, Westchester Country Club (Save 20% with the code Super20)* Crowdfunding Professional Association, Summit in DC, October 22-23If you would like to submit an event for us to share with the 4,500+ members of the SuperCrowd, click here.We use AI to help us write compelling recaps of each episode. Get full access to Superpowers for Good at www.superpowers4good.com/subscribe

Conrad Hildebrand var en lovande elitsimmare när han som 16-åring bröt nacken i ett parkourhopp och blev förlamad. Efter gymnasiet tog Conrad examen från KTH och är idag rankad som en av världens bästa rullstolsrugbyspelare och är tillbaka i vattnet som parasimmare med siktet inställt på Paralympics.

Per Pallav's website, he studied physics in college at KTH in Stockholm, Sweden (where I'm from). As a PhD student in the lab of Julio Fernandez at Columbia University, he studied the mechanics of protein folding and discovered that we can modulate this process to alter the elasticity of muscles. He then moved to Harvard University as a postdoc in the lab of Xiaowei Zhuang, where he used DNA to invent and build nanosensors that make it possible to see molecular movements. Since starting my lab at the Salk Institute in 2021, he has been excited about building a diverse and thriving research community, while training future leaders in biophysics. When I'm not in the lab, you can find him rock climbing, skiing, or learning to surf. --- Send in a voice message: https://podcasters.spotify.com/pod/show/fromwheredoesitstem/message

Vi kickstartar veckans podd med Claes Beckman, professor och forskare på KTH specialiserad inom antenn- och mikrovågsteknik. Claes har varit involverad i utvecklingen av 5G och i det här avsnittet får vi höra hur resan från tidigare teknologier till dagens 5G har sett ut. Därefter vänder vi blicken mot Fredrik Ekström, VD på Maven Wireless, ett företag som erbjuder lösningar för att förbättra 5G-täckningen i tunnlar och byggnader. Efterfrågan av utrustning för att möjliggöra 5G uppkoppling i dessa utrymmen är stort och kommer fortsätta öka i och med utrullningen av 5G.  Vi avslutar med en intervju med Fredrik Lundberg, VD för Waystream, ett företag som fokuserar på switchar för fiberuppkoppling. Vi undersöker den centrala roll som fiber kommer att ha i 5G-landskapet och diskuterar hur dessa två teknologier kompletterar varandra. Missa inte detta avsnitt, lyssna här!

Mycket har hänt i tech-sfären och det nya näringslivet de senaste dagarna. I Breakit Podcast berättar reporter-duon Julia Lundin och Åsa Johansson om allt du behöver ha koll på.I avsnittet diskuteras: (1:49) Julia tar ett snack med doldisen som är ny vd på hajpade beautytech-bolaget: “Dags att sluta blöda pengar”(10:41) Åsa pratar med entreprenören som vill rädda småbarnsföräldrar från sömnlösa nätter: “Stort behov av appar för målgruppen”(14:51) Fem snabba nyheter från veckan:# Tesla planerar att säga upp personal – 14.000 kan få gå# Serverhallar har använts för att utvinna kryptovaluta# E-handeln bryter nio kvartal av depp# Europas Open AI-utmanare är på väg mot ny monsterrunda# KTH, Handelshögskolan och Försvarshögskolan går ihop för att stärka försvaret(18:06) Tandborstar, tandkräm och munskölj i guld – vi analyserar hur den nya svenska uppstickaren inom lyx kan lyckas(28:30) Breakit besökte tech-konferensen för kvinnor – här är de hetaste snackisarnaOch du - glöm inte att ge feedback till podcast@breakit.se. Hosted on Acast. See acast.com/privacy for more information.

I veckan tog sig klimataktivister in på SAS årsstämma och vädrade sitt missnöje med bolagets klimatarbete. De senaste decennierna har koldioxidutsläppen minskat i Sverige genom politiska beslut, men nu får regeringens klimatpolitik stenhård kritik av Klimatpolitiska rådet. Vilken roll spelar politiken, ägarna och kunderna för att få ner företagens klimatutsläpp? Lyssna på alla avsnitt i Sveriges Radio Play. Programledare:Philip RamqvistMedverkande och röster i programmet:Annika Digreus, klimatreporter, EkotChristian Thomann, docent i företagsekonomi på KTH, gästforskare, Handelshögskolan i Stockholm.Åsa Persson, ordförande, Klimatpolitiska rådet,Ebba Busch, energiminister (KD)Romina Pourmokhtari, klimatminister (L)Daniel Helldén, språkrör (MP)Anton Foley och Greta Thunberg, klimataktivister Larry Fink, vd, Blackrock Dan Yergin, Standard and Poor GlobalProducent:Olof WijnbladhTekniker:Victor Ubeiraekonomiekotextra@sverigesradio.se

Fiskar kan känna smärta och kan vara vid medvetande länge trots att vi tror att de är döda. Och paleontolog Elisabeth Einarsson tar oss till Skåne under Kritaperioden. Lyssna på alla avsnitt i Sveriges Radio Play. Denna marsmorgon, 2024, finns fältreporter Lisa Henkow på Ivö klack i Skåne tillsammans med paleontologen Elisabeth Einarsson. Hur såg det ut just här, fast för 80 miljoner år sedan? Det har Elisabeth Einarsson undersökt i sin forskning och hon berättar att här levde dinosaurier, mosasaurier, svanhalsödlor, vattenlevande fåglar, krokodiler och sköldpaddor. Hon lär oss också tidsmedvetenhet med hjälp av bläckfiskfossil och om hur skolbarns naturliga intresse för dinosaurier kan ge förståelse för hållbar utveckling och klimatförändringar och öppna upp för naturvetenskapliga studier.Kan fiskar känna smärta? Ja, de har smärtreceptorer bland annat runt munnen, berättar Albin Gräns, zoofysiolog på Sveriges Lantbruksuniversitet. I ett reportage av Jenny Berntson Djurvall får vi veta hur fisken upplever att bli uppfiskad och att fisken kan vara vid medvetande en lång stund efter att man skurit huvudet av den.Ja, går det att få en fiskeupplevelse utan att fånga fisken på en krok och dra upp den? Vi pratar med Erik Sandelin, doktorand på Konstfack och KTH i Stockholm, som undersökt det i sin avhandling.Ebba Hagbom välkomnar varje vår kattugglor i två holkar utanför huset i södra Värmland. Men nu har en av holkarna hamnat på sned. Hur ska hon göra - ska hon ta bort den gamla när en ny sätts upp, och hur ska den nya placeras? Vi ringer upp Johan Nilsson på Lunds universitet för att få svar. Han jobbar på något som heter Kattuggleprojektet och har koll på sisådär hundra olika kattuggleholkar i sin forskning.I kråkvinkeln sjunger Thomas Öberg de våta markernas lov.Programledare är Karin Gyllenklev.

Most green energy projects, no matter how admirable they could be, are often impeded by a lack of funding and government leverage. Thankfully, there is one efficient way to support them using your own money: crowdfunding. Corinna Bellizzi is joined by Will Wiseman, who is making this process much easier and accessible for everyone through Climatize. Will shares how they help renewable energy developments grow and prosper, especially those small-scale and community-based ones, by giving people the power to pick specific projects to put their money into. He also talks about their transparency approach that allows Climatize users to see (or even personally visit) the tangible outputs of their money. About Guest:Will has spent the past 10 years in renewable energy during which time he has played every role in the solar industry across finance, project management & construction where he built 15 solar arrays. As CEO & Co-Founder of Climatize Will has financed over $2 million of community solar projects. He holds a MSc in Renewable Energy Engineering from KTH, the Royal Institute of Technology. Will is a Santa Cruz native & resident who enjoys spending as much time as possible in our mountains & ocean. Guest LinkedIn: https://www.linkedin.com/company/climatize-earth/ Guest Website: https://www.climatize.earth/Guest Social:https://www.instagram.com/climatize.earth/https://www.facebook.com/climatize.earthhttps://www.youtube.com/channel/UCuSeK0a8ilhHLfw6qGiQKBQhttps://tiktok.com/@climatize.earthAdditional Resources Mentioned: apps.apple.com/us/app/climatize/id1625951422 Please subscribe on your favorite podcasting platform - and join the Care More Be Better Community! When you visit our website and join our email list, you'll receive a FREE 5-Step Guide To Unleash Your Inner Activist!Website: https://www.caremorebebetter.com YouTube: https://www.youtube.com/@caremorebebetter Instagram: https://www.instagram.com/CareMore.BeBetter/Facebook: https://www.facebook.com/CareMoreBeBetterLinkedIn: https://www.linkedin.com/company/care-more-be-betterTwitter: https://twitter.com/caremorebebettr Support Care More. Be Better: A Social Impact + Sustainability PodcastCare More. Be Better. is not backed by any company. We answer only to our collective conscience. As a listener, reader, and subscriber you are part of this pod and this community and we are honored to have your support. If you can, please help finance the show (https://www.caremorebebetter.com/donate). Thank you, now and always, for your support as we get this thing started!

Elina Eriksson Associate Professor at KTH (profile) came on the podcast and we talked about the work she's been doing with her students at the Swedish Royal Institute of Technology around transformation and transition. We speak of nudging, counterfactional scenarios, university studies as learning not merely graduating, the paradigm shift, the new role of the teacher, voulnerability, how transformative questions can also come in the form of 'how are you?' We also speak about futures and what we can do to spark movement now, work Elina and her team has been doing with the Transition movement. Enjoy!

Nyligen kom nyheten att den första patienten som fått chippet Neuralink inopererat i hjärnan kan styra en datormus med sina tankar. Många forskar idag på olika typer av hjärnchip, också i Sverige. Men vad ska tekniken användas till? Hur fungerar det och vad är teknikens potential? Lyssna på alla avsnitt i Sveriges Radio Play. Medverkande; Karim Jebari, filosof och forskare vid institutet för framtidsstudier, Anna Herland, professor i nanobioteknologi på KTH och KI och Jens Schouenberg, professor i Neurofysilogi vid Lunds universitet.Ljudtekniker Elvira BjörnfotProgramledare: Björn Gunérbjorn.guner@sr.seProducent och reporter: Blenda Setterwall Klingertblenda.klingert@sr.se

We're writing this one day after the monster release of OpenAI's Sora and Gemini 1.5. We covered this on ‘s ThursdAI space, so head over there for our takes.IRL: We're ONE WEEK away from Latent Space: Final Frontiers, the second edition and anniversary of our first ever Latent Space event! Also: join us on June 25-27 for the biggest AI Engineer conference of the year!Online: All three Discord clubs are thriving. Join us every Wednesday/Friday!Almost 12 years ago, while working at Spotify, Erik Bernhardsson built one of the first open source vector databases, Annoy, based on ANN search. He also built Luigi, one of the predecessors to Airflow, which helps data teams orchestrate and execute data-intensive and long-running jobs. Surprisingly, he didn't start yet another vector database company, but instead in 2021 founded Modal, the “high-performance cloud for developers”. In 2022 they opened doors to developers after their seed round, and in 2023 announced their GA with a $16m Series A.More importantly, they have won fans among both household names like Ramp, Scale AI, Substack, and Cohere, and newer startups like (upcoming guest!) Suno.ai and individual hackers (Modal was the top tool of choice in the Vercel AI Accelerator):We've covered the nuances of GPU workloads, and how we need new developer tooling and runtimes for them (see our episodes with Chris Lattner of Modular and George Hotz of tiny to start). In this episode, we run through the major limitations of the actual infrastructure behind the clouds that run these models, and how Erik envisions the “postmodern data stack”. In his 2021 blog post “Software infrastructure 2.0: a wishlist”, Erik had “Truly serverless” as one of his points:* The word cluster is an anachronism to an end-user in the cloud! I'm already running things in the cloud where there's elastic resources available at any time. Why do I have to think about the underlying pool of resources? Just maintain it for me.* I don't ever want to provision anything in advance of load.* I don't want to pay for idle resources. Just let me pay for whatever resources I'm actually using.* Serverless doesn't mean it's a burstable VM that saves its instance state to disk during periods of idle.Swyx called this Self Provisioning Runtimes back in the day. Modal doesn't put you in YAML hell, preferring to colocate infra provisioning right next to the code that utilizes it, so you can just add GPU (and disk, and retries…):After 3 years, we finally have a big market push for this: running inference on generative models is going to be the killer app for serverless, for a few reasons:* AI models are stateless: even in conversational interfaces, each message generation is a fully-contained request to the LLM. There's no knowledge that is stored in the model itself between messages, which means that tear down / spin up of resources doesn't create any headaches with maintaining state.* Token-based pricing is better aligned with serverless infrastructure than fixed monthly costs of traditional software.* GPU scarcity makes it really expensive to have reserved instances that are available to you 24/7. It's much more convenient to build with a serverless-like infrastructure.In the episode we covered a lot more topics like maximizing GPU utilization, why Oracle Cloud rocks, and how Erik has never owned a TV in his life. Enjoy!Show Notes* Modal* ErikBot* Erik's Blog* Software Infra 2.0 Wishlist* Luigi* Annoy* Hetzner* CoreWeave* Cloudflare FaaS* Poolside AI* Modular Inference EngineChapters* [00:00:00] Introductions* [00:02:00] Erik's OSS work at Spotify: Annoy and Luigi* [00:06:22] Starting Modal* [00:07:54] Vision for a "postmodern data stack"* [00:10:43] Solving container cold start problems* [00:12:57] Designing Modal's Python SDK* [00:15:18] Self-Revisioning Runtime* [00:19:14] Truly Serverless Infrastructure* [00:20:52] Beyond model inference* [00:22:09] Tricks to maximize GPU utilization* [00:26:27] Differences in AI and data science workloads* [00:28:08] Modal vs Replicate vs Modular and lessons from Heroku's "graduation problem"* [00:34:12] Creating Erik's clone "ErikBot"* [00:37:43] Enabling massive parallelism across thousands of GPUs* [00:39:45] The Modal Sandbox for agents* [00:43:51] Thoughts on the AI Inference War* [00:49:18] Erik's best tweets* [00:51:57] Why buying hardware is a waste of money* [00:54:18] Erik's competitive programming backgrounds* [00:59:02] Why does Sweden have the best Counter Strike players?* [00:59:53] Never owning a car or TV* [01:00:21] Advice for infrastructure startupsTranscriptAlessio [00:00:00]: Hey everyone, welcome to the Latent Space podcast. This is Alessio, partner and CTO-in-Residence at Decibel Partners, and I'm joined by my co-host Swyx, founder of Smol AI.Swyx [00:00:14]: Hey, and today we have in the studio Erik Bernhardsson from Modal. Welcome.Erik [00:00:19]: Hi. It's awesome being here.Swyx [00:00:20]: Yeah. Awesome seeing you in person. I've seen you online for a number of years as you were building on Modal and I think you're just making a San Francisco trip just to see people here, right? I've been to like two Modal events in San Francisco here.Erik [00:00:34]: Yeah, that's right. We're based in New York, so I figured sometimes I have to come out to capital of AI and make a presence.Swyx [00:00:40]: What do you think is the pros and cons of building in New York?Erik [00:00:45]: I mean, I never built anything elsewhere. I lived in New York the last 12 years. I love the city. Obviously, there's a lot more stuff going on here and there's a lot more customers and that's why I'm out here. I do feel like for me, where I am in life, I'm a very boring person. I kind of work hard and then I go home and hang out with my kids. I don't have time to go to events and meetups and stuff anyway. In that sense, New York is kind of nice. I walk to work every morning. It's like five minutes away from my apartment. It's very time efficient in that sense. Yeah.Swyx [00:01:10]: Yeah. It's also a good life. So we'll do a brief bio and then we'll talk about anything else that people should know about you. Actually, I was surprised to find out you're from Sweden. You went to college in KTH and your master's was in implementing a scalable music recommender system. Yeah.Erik [00:01:27]: I had no idea. Yeah. So I actually studied physics, but I grew up coding and I did a lot of programming competition and then as I was thinking about graduating, I got in touch with an obscure music streaming startup called Spotify, which was then like 30 people. And for some reason, I convinced them, why don't I just come and write a master's thesis with you and I'll do some cool collaborative filtering, despite not knowing anything about collaborative filtering really. But no one knew anything back then. So I spent six months at Spotify basically building a prototype of a music recommendation system and then turned that into a master's thesis. And then later when I graduated, I joined Spotify full time.Swyx [00:02:00]: So that was the start of your data career. You also wrote a couple of popular open source tooling while you were there. Is that correct?Erik [00:02:09]: No, that's right. I mean, I was at Spotify for seven years, so this is a long stint. And Spotify was a wild place early on and I mean, data space is also a wild place. I mean, it was like Hadoop cluster in the like foosball room on the floor. It was a lot of crude, like very basic infrastructure and I didn't know anything about it. And like I was hired to kind of figure out data stuff. And I started hacking on a recommendation system and then, you know, got sidetracked in a bunch of other stuff. I fixed a bunch of reporting things and set up A-B testing and started doing like business analytics and later got back to music recommendation system. And a lot of the infrastructure didn't really exist. Like there was like Hadoop back then, which is kind of bad and I don't miss it. But I spent a lot of time with that. As a part of that, I ended up building a workflow engine called Luigi, which is like briefly like somewhat like widely ended up being used by a bunch of companies. Sort of like, you know, kind of like Airflow, but like before Airflow. I think it did some things better, some things worse. I also built a vector database called Annoy, which is like for a while, it was actually quite widely used. In 2012, so it was like way before like all this like vector database stuff ended up happening. And funny enough, I was actually obsessed with like vectors back then. Like I was like, this is going to be huge. Like just give it like a few years. I didn't know it was going to take like nine years and then there's going to suddenly be like 20 startups doing vector databases in one year. So it did happen. In that sense, I was right. I'm glad I didn't start a startup in the vector database space. I would have started way too early. But yeah, that was, yeah, it was a fun seven years as part of it. It was a great culture, a great company.Swyx [00:03:32]: Yeah. Just to take a quick tangent on this vector database thing, because we probably won't revisit it but like, has anything architecturally changed in the last nine years?Erik [00:03:41]: I'm actually not following it like super closely. I think, you know, some of the best algorithms are still the same as like hierarchical navigable small world.Swyx [00:03:51]: Yeah. HNSW.Erik [00:03:52]: Exactly. I think now there's like product quantization, there's like some other stuff that I haven't really followed super closely. I mean, obviously, like back then it was like, you know, it's always like very simple. It's like a C++ library with Python bindings and you could mmap big files and into memory and like they had some lookups. I used like this kind of recursive, like hyperspace splitting strategy, which is not that good, but it sort of was good enough at that time. But I think a lot of like HNSW is still like what people generally use. Now of course, like databases are much better in the sense like to support like inserts and updates and stuff like that. I know I never supported that. Yeah, it's sort of exciting to finally see like vector databases becoming a thing.Swyx [00:04:30]: Yeah. Yeah. And then maybe one takeaway on most interesting lesson from Daniel Ek?Erik [00:04:36]: I mean, I think Daniel Ek, you know, he started Spotify very young. Like he was like 25, something like that. And that was like a good lesson. But like he, in a way, like I think he was a very good leader. Like there was never anything like, no scandals or like no, he wasn't very eccentric at all. It was just kind of like very like level headed, like just like ran the company very well, like never made any like obvious mistakes or I think it was like a few bets that maybe like in hindsight were like a little, you know, like took us, you know, too far in one direction or another. But overall, I mean, I think he was a great CEO, like definitely, you know, up there, like generational CEO, at least for like Swedish startups.Swyx [00:05:09]: Yeah, yeah, for sure. Okay, we should probably move to make our way towards Modal. So then you spent six years as CTO of Better. You were an early engineer and then you scaled up to like 300 engineers.Erik [00:05:21]: I joined as a CTO when there was like no tech team. And yeah, that was a wild chapter in my life. Like the company did very well for a while. And then like during the pandemic, yeah, it was kind of a weird story, but yeah, it kind of collapsed.Swyx [00:05:32]: Yeah, laid off people poorly.Erik [00:05:34]: Yeah, yeah. It was like a bunch of stories. Yeah. I mean, the company like grew from like 10 people when I joined at 10,000, now it's back to a thousand. But yeah, they actually went public a few months ago, kind of crazy. They're still around, like, you know, they're still, you know, doing stuff. So yeah, very kind of interesting six years of my life for non-technical reasons, like I managed like three, four hundred, but yeah, like learning a lot of that, like recruiting. I spent all my time recruiting and stuff like that. And so managing at scale, it's like nice, like now in a way, like when I'm building my own startup. It's actually something I like, don't feel nervous about at all. Like I've managed a scale, like I feel like I can do it again. It's like very different things that I'm nervous about as a startup founder. But yeah, I started Modal three years ago after sort of, after leaving Better, I took a little bit of time off during the pandemic and, but yeah, pretty quickly I was like, I got to build something. I just want to, you know. Yeah. And then yeah, Modal took form in my head, took shape.Swyx [00:06:22]: And as far as I understand, and maybe we can sort of trade off questions. So the quick history is started Modal in 2021, got your seed with Sarah from Amplify in 2022. You just announced your Series A with Redpoint. That's right. And that brings us up to mostly today. Yeah. Most people, I think, were expecting you to build for the data space.Erik: But it is the data space.Swyx:: When I think of data space, I come from like, you know, Snowflake, BigQuery, you know, Fivetran, Nearby, that kind of stuff. And what Modal became is more general purpose than that. Yeah.Erik [00:06:53]: Yeah. I don't know. It was like fun. I actually ran into like Edo Liberty, the CEO of Pinecone, like a few weeks ago. And he was like, I was so afraid you were building a vector database. No, I started Modal because, you know, like in a way, like I work with data, like throughout my most of my career, like every different part of the stack, right? Like I thought everything like business analytics to like deep learning, you know, like building, you know, training neural networks, the scale, like everything in between. And so one of the thoughts, like, and one of the observations I had when I started Modal or like why I started was like, I just wanted to make, build better tools for data teams. And like very, like sort of abstract thing, but like, I find that the data stack is, you know, full of like point solutions that don't integrate well. And still, when you look at like data teams today, you know, like every startup ends up building their own internal Kubernetes wrapper or whatever. And you know, all the different data engineers and machine learning engineers end up kind of struggling with the same things. So I started thinking about like, how do I build a new data stack, which is kind of a megalomaniac project, like, because you kind of want to like throw out everything and start over.Swyx [00:07:54]: It's almost a modern data stack.Erik [00:07:55]: Yeah, like a postmodern data stack. And so I started thinking about that. And a lot of it came from like, like more focused on like the human side of like, how do I make data teams more productive? And like, what is the technology tools that they need? And like, you know, drew out a lot of charts of like, how the data stack looks, you know, what are different components. And it shows actually very interesting, like workflow scheduling, because it kind of sits in like a nice sort of, you know, it's like a hub in the graph of like data products. But it was kind of hard to like, kind of do that in a vacuum, and also to monetize it to some extent. I got very interested in like the layers below at some point. And like, at the end of the day, like most people have code to have to run somewhere. So I think about like, okay, well, how do you make that nice? Like how do you make that? And in particular, like the thing I always like thought about, like developer productivity is like, I think the best way to measure developer productivity is like in terms of the feedback loops, like how quickly when you iterate, like when you write code, like how quickly can you get feedback. And at the innermost loop, it's like writing code and then running it. And like, as soon as you start working with the cloud, like it's like takes minutes suddenly, because you have to build a Docker container and push it to the cloud and like run it, you know. So that was like the initial focus for me was like, I just want to solve that problem. Like I want to, you know, build something less, you run things in the cloud and like retain the sort of, you know, the joy of productivity as when you're running things locally. And in particular, I was quite focused on data teams, because I think they had a couple unique needs that wasn't well served by the infrastructure at that time, or like still is in like, in particular, like Kubernetes, I feel like it's like kind of worked okay for back end teams, but not so well for data teams. And very quickly, I got sucked into like a very deep like rabbit hole of like...Swyx [00:09:24]: Not well for data teams because of burstiness. Yeah, for sure.Erik [00:09:26]: So like burstiness is like one thing, right? Like, you know, like you often have this like fan out, you want to like apply some function over very large data sets. Another thing tends to be like hardware requirements, like you need like GPUs and like, I've seen this in many companies, like you go, you know, data scientists go to a platform team and they're like, can we add GPUs to the Kubernetes? And they're like, no, like, that's, you know, complex, and we're not gonna, so like just getting GPU access. And then like, I mean, I also like data code, like frankly, or like machine learning code like tends to be like, super annoying in terms of like environments, like you end up having like a lot of like custom, like containers and like environment conflicts. And like, it's very hard to set up like a unified container that like can serve like a data scientist, because like, there's always like packages that break. And so I think there's a lot of different reasons why the technology wasn't well suited for back end. And I think the attitude at that time is often like, you know, like you had friction between the data team and the platform team, like, well, it works for the back end stuff, you know, why don't you just like, you know, make it work. But like, I actually felt like data teams, you know, or at this point now, like there's so much, so many people working with data, and like they, to some extent, like deserve their own tools and their own tool chains, and like optimizing for that is not something people have done. So that's, that's sort of like very abstract philosophical reason why I started Model. And then, and then I got sucked into this like rabbit hole of like container cold start and, you know, like whatever, Linux, page cache, you know, file system optimizations.Swyx [00:10:43]: Yeah, tell people, I think the first time I met you, I think you told me some numbers, but I don't remember, like, what are the main achievements that you were unhappy with the status quo? And then you built your own container stack?Erik [00:10:52]: Yeah, I mean, like, in particular, it was like, in order to have that loop, right? You want to be able to start, like take code on your laptop, whatever, and like run in the cloud very quickly, and like running in custom containers, and maybe like spin up like 100 containers, 1000, you know, things like that. And so container cold start was the initial like, from like a developer productivity point of view, it was like, really, what I was focusing on is, I want to take code, I want to stick it in container, I want to execute in the cloud, and like, you know, make it feel like fast. And when you look at like, how Docker works, for instance, like Docker, you have this like, fairly convoluted, like very resource inefficient way, they, you know, you build a container, you upload the whole container, and then you download it, and you run it. And Kubernetes is also like, not very fast at like starting containers. So like, I started kind of like, you know, going a layer deeper, like Docker is actually like, you know, there's like a couple of different primitives, but like a lower level primitive is run C, which is like a container runner. And I was like, what if I just take the container runner, like run C, and I point it to like my own root file system, and then I built like my own virtual file system that exposes files over a network instead. And that was like the sort of very crude version of model, it's like now I can actually start containers very quickly, because it turns out like when you start a Docker container, like, first of all, like most Docker images are like several gigabytes, and like 99% of that is never going to be consumed, like there's a bunch of like, you know, like timezone information for like Uzbekistan, like no one's going to read it. And then there's a very high overlap between the files are going to be read, there's going to be like lib torch or whatever, like it's going to be read. So you can also cache it very well. So that was like the first sort of stuff we started working on was like, let's build this like container file system. And you know, coupled with like, you know, just using run C directly. And that actually enabled us to like, get to this point of like, you write code, and then you can launch it in the cloud within like a second or two, like something like that. And you know, there's been many optimizations since then, but that was sort of starting point.Alessio [00:12:33]: Can we talk about the developer experience as well, I think one of the magic things about Modal is at the very basic layers, like a Python function decorator, it's just like stub and whatnot. But then you also have a way to define a full container, what were kind of the design decisions that went into it? Where did you start? How easy did you want it to be? And then maybe how much complexity did you then add on to make sure that every use case fit?Erik [00:12:57]: I mean, Modal, I almost feel like it's like almost like two products kind of glued together. Like there's like the low level like container runtime, like file system, all that stuff like in Rust. And then there's like the Python SDK, right? Like how do you express applications? And I think, I mean, Swix, like I think your blog was like the self-provisioning runtime was like, to me, always like to sort of, for me, like an eye-opening thing. It's like, so I didn't think about like...Swyx [00:13:15]: You wrote your post four months before me. Yeah? The software 2.0, Infra 2.0. Yeah.Erik [00:13:19]: Well, I don't know, like convergence of minds. I guess we were like both thinking. Maybe you put, I think, better words than like, you know, maybe something I was like thinking about for a long time. Yeah.Swyx [00:13:29]: And I can tell you how I was thinking about it on my end, but I want to hear you say it.Erik [00:13:32]: Yeah, yeah, I would love to. So to me, like what I always wanted to build was like, I don't know, like, I don't know if you use like Pulumi. Like Pulumi is like nice, like in the sense, like it's like Pulumi is like you describe infrastructure in code, right? And to me, that was like so nice. Like finally I can like, you know, put a for loop that creates S3 buckets or whatever. And I think like Modal sort of goes one step further in the sense that like, what if you also put the app code inside the infrastructure code and like glue it all together and then like you only have one single place that defines everything and it's all programmable. You don't have any config files. Like Modal has like zero config. There's no config. It's all code. And so that was like the goal that I wanted, like part of that. And then the other part was like, I often find that so much of like my time was spent on like the plumbing between containers. And so my thing was like, well, if I just build this like Python SDK and make it possible to like bridge like different containers, just like a function call, like, and I can say, oh, this function runs in this container and this other function runs in this container and I can just call it just like a normal function, then, you know, I can build these applications that may span a lot of different environments. Maybe they fan out, start other containers, but it's all just like inside Python. You just like have this beautiful kind of nice like DSL almost for like, you know, how to control infrastructure in the cloud. So that was sort of like how we ended up with the Python SDK as it is, which is still evolving all the time, by the way. We keep changing syntax quite a lot because I think it's still somewhat exploratory, but we're starting to converge on something that feels like reasonably good now.Swyx [00:14:54]: Yeah. And along the way you, with this expressiveness, you enabled the ability to, for example, attach a GPU to a function. Totally.Erik [00:15:02]: Yeah. It's like you just like say, you know, on the function decorator, you're like GPU equals, you know, A100 and then or like GPU equals, you know, A10 or T4 or something like that. And then you get that GPU and like, you know, you just run the code and it runs like you don't have to, you know, go through hoops to, you know, start an EC2 instance or whatever.Swyx [00:15:18]: Yeah. So it's all code. Yeah. So one of the reasons I wrote Self-Revisioning Runtimes was I was working at AWS and we had AWS CDK, which is kind of like, you know, the Amazon basics blew me. Yeah, totally. And then, and then like it creates, it compiles the cloud formation. Yeah. And then on the other side, you have to like get all the config stuff and then put it into your application code and make sure that they line up. So then you're writing code to define your infrastructure, then you're writing code to define your application. And I was just like, this is like obvious that it's going to converge, right? Yeah, totally.Erik [00:15:48]: But isn't there like, it might be wrong, but like, was it like SAM or Chalice or one of those? Like, isn't that like an AWS thing that where actually they kind of did that? I feel like there's like one.Swyx [00:15:57]: SAM. Yeah. Still very clunky. It's not, not as elegant as modal.Erik [00:16:03]: I love AWS for like the stuff it's built, you know, like historically in order for me to like, you know, what it enables me to build, but like AWS is always like struggle with developer experience.Swyx [00:16:11]: I mean, they have to not break things.Erik [00:16:15]: Yeah. Yeah. And totally. And they have to build products for a very wide range of use cases. And I think that's hard.Swyx [00:16:21]: Yeah. Yeah. So it's, it's easier to design for. Yeah. So anyway, I was, I was pretty convinced that this, this would happen. I wrote, wrote that thing. And then, you know, I imagine my surprise that you guys had it on your landing page at some point. I think, I think Akshad was just like, just throw that in there.Erik [00:16:34]: Did you trademark it?Swyx [00:16:35]: No, I didn't. But I definitely got sent a few pitch decks with my post on there and it was like really interesting. This is my first time like kind of putting a name to a phenomenon. And I think this is a useful skill for people to just communicate what they're trying to do.Erik [00:16:48]: Yeah. No, I think it's a beautiful concept.Swyx [00:16:50]: Yeah. Yeah. Yeah. But I mean, obviously you implemented it. What became more clear in your explanation today is that actually you're not that tied to Python.Erik [00:16:57]: No. I mean, I, I think that all the like lower level stuff is, you know, just running containers and like scheduling things and, you know, serving container data and stuff. So like one of the benefits of data teams is obviously like they're all like using Python, right? And so that made it a lot easier. I think, you know, if we had focused on other workloads, like, you know, for various reasons, we've like been kind of like half thinking about like CI or like things like that. But like, in a way that's like harder because like you also, then you have to be like, you know, multiple SDKs, whereas, you know, focusing on data teams, you can only, you know, Python like covers like 95% of all teams. That made it a lot easier. But like, I mean, like definitely like in the future, we're going to have others support, like supporting other languages. JavaScript for sure is the obvious next language. But you know, who knows, like, you know, Rust, Go, R, whatever, PHP, Haskell, I don't know.Swyx [00:17:42]: You know, I think for me, I actually am a person who like kind of liked the idea of programming language advancements being improvements in developer experience. But all I saw out of the academic sort of PLT type people is just type level improvements. And I always think like, for me, like one of the core reasons for self-provisioning runtimes and then why I like Modal is like, this is actually a productivity increase, right? Like, it's a language level thing, you know, you managed to stick it on top of an existing language, but it is your own language, a DSL on top of Python. And so language level increase on the order of like automatic memory management. You know, you could sort of make that analogy that like, maybe you lose some level of control, but most of the time you're okay with whatever Modal gives you. And like, that's fine. Yeah.Erik [00:18:26]: Yeah. Yeah. I mean, that's how I look at about it too. Like, you know, you look at developer productivity over the last number of decades, like, you know, it's come in like small increments of like, you know, dynamic typing or like is like one thing because not suddenly like for a lot of use cases, you don't need to care about type systems or better compiler technology or like, you know, the cloud or like, you know, relational databases. And, you know, I think, you know, you look at like that, you know, history, it's a steadily, you know, it's like, you know, you look at the developers have been getting like probably 10X more productive every decade for the last four decades or something that was kind of crazy. Like on an exponential scale, we're talking about 10X or is there a 10,000X like, you know, improvement in developer productivity. What we can build today, you know, is arguably like, you know, a fraction of the cost of what it took to build it in the eighties. Maybe it wasn't even possible in the eighties. So that to me, like, that's like so fascinating. I think it's going to keep going for the next few decades. Yeah.Alessio [00:19:14]: Yeah. Another big thing in the infra 2.0 wishlist was truly serverless infrastructure. The other on your landing page, you called them native cloud functions, something like that. I think the issue I've seen with serverless has always been people really wanted it to be stateful, even though stateless was much easier to do. And I think now with AI, most model inference is like stateless, you know, outside of the context. So that's kind of made it a lot easier to just put a model, like an AI model on model to run. How do you think about how that changes how people think about infrastructure too? Yeah.Erik [00:19:48]: I mean, I think model is definitely going in the direction of like doing more stateful things and working with data and like high IO use cases. I do think one like massive serendipitous thing that happened like halfway, you know, a year and a half into like the, you know, building model was like Gen AI started exploding and the IO pattern of Gen AI is like fits the serverless model like so well, because it's like, you know, you send this tiny piece of information, like a prompt, right, or something like that. And then like you have this GPU that does like trillions of flops, and then it sends back like a tiny piece of information, right. And that turns out to be something like, you know, if you can get serverless working with GPU, that just like works really well, right. So I think from that point of view, like serverless always to me felt like a little bit of like a solution looking for a problem. I don't actually like don't think like backend is like the problem that needs to serve it or like not as much. But I look at data and in particular, like things like Gen AI, like model inference, like it's like clearly a good fit. So I think that is, you know, to a large extent explains like why we saw, you know, the initial sort of like killer app for model being model inference, which actually wasn't like necessarily what we're focused on. But that's where we've seen like by far the most usage. Yeah.Swyx [00:20:52]: And this was before you started offering like fine tuning of language models, it was mostly stable diffusion. Yeah.Erik [00:20:59]: Yeah. I mean, like model, like I always built it to be a very general purpose compute platform, like something where you can run everything. And I used to call model like a better Kubernetes for data team for a long time. What we realized was like, yeah, that's like, you know, a year and a half in, like we barely had any users or any revenue. And like we were like, well, maybe we should look at like some use case, trying to think of use case. And that was around the same time stable diffusion came out. And the beauty of model is like you can run almost anything on model, right? Like model inference turned out to be like the place where we found initially, well, like clearly this has like 10x like better agronomics than anything else. But we're also like, you know, going back to my original vision, like we're thinking a lot about, you know, now, okay, now we do inference really well. Like what about training? What about fine tuning? What about, you know, end-to-end lifecycle deployment? What about data pre-processing? What about, you know, I don't know, real-time streaming? What about, you know, large data munging, like there's just data observability. I think there's so many things, like kind of going back to what I said about like redefining the data stack, like starting with the foundation of compute. Like one of the exciting things about model is like we've sort of, you know, we've been working on that for three years and it's maturing, but like this is so many things you can do like with just like a better compute primitive and also go up to stack and like do all this other stuff on top of it.Alessio [00:22:09]: How do you think about or rather like I would love to learn more about the underlying infrastructure and like how you make that happen because with fine tuning and training, it's a static memory. Like you exactly know what you're going to load in memory one and it's kind of like a set amount of compute versus inference, just like data is like very bursty. How do you make batches work with a serverless developer experience? You know, like what are like some fun technical challenge you solve to make sure you get max utilization on these GPUs? What we hear from people is like, we have GPUs, but we can really only get like, you know, 30, 40, 50% maybe utilization. What's some of the fun stuff you're working on to get a higher number there?Erik [00:22:48]: Yeah, I think on the inference side, like that's where we like, you know, like from a cost perspective, like utilization perspective, we've seen, you know, like very good numbers and in particular, like it's our ability to start containers and stop containers very quickly. And that means that we can auto scale extremely fast and scale down very quickly, which means like we can always adjust the sort of capacity, the number of GPUs running to the exact traffic volume. And so in many cases, like that actually leads to a sort of interesting thing where like we obviously run our things on like the public cloud, like AWS GCP, we run on Oracle, but in many cases, like users who do inference on those platforms or those clouds, even though we charge a slightly higher price per GPU hour, a lot of users like moving their large scale inference use cases to model, they end up saving a lot of money because we only charge for like with the time the GPU is actually running. And that's a hard problem, right? Like, you know, if you have to constantly adjust the number of machines, if you have to start containers, stop containers, like that's a very hard problem. Starting containers quickly is a very difficult thing. I mentioned we had to build our own file system for this. We also, you know, built our own container scheduler for that. We've implemented recently CPU memory checkpointing so we can take running containers and snapshot the entire CPU, like including registers and everything, and restore it from that point, which means we can restore it from an initialized state. We're looking at GPU checkpointing next, it's like a very interesting thing. So I think with inference stuff, that's where serverless really shines because you can drive, you know, you can push the frontier of latency versus utilization quite substantially, you know, which either ends up being a latency advantage or a cost advantage or both, right? On training, it's probably arguably like less of an advantage doing serverless, frankly, because you know, you can just like spin up a bunch of machines and try to satisfy, like, you know, train as much as you can on each machine. For that area, like we've seen, like, you know, arguably like less usage, like for modal, but there are always like some interesting use case. Like we do have a couple of customers, like RAM, for instance, like they do fine tuning with modal and they basically like one of the patterns they have is like very bursty type fine tuning where they fine tune 100 models in parallel. And that's like a separate thing that modal does really well, right? Like you can, we can start up 100 containers very quickly, run a fine tuning training job on each one of them for that only runs for, I don't know, 10, 20 minutes. And then, you know, you can do hyper parameter tuning in that sense, like just pick the best model and things like that. So there are like interesting training. I think when you get to like training, like very large foundational models, that's a use case we don't support super well, because that's very high IO, you know, you need to have like infinite band and all these things. And those are things we haven't supported yet and might take a while to get to that. So that's like probably like an area where like we're relatively weak in. Yeah.Alessio [00:25:12]: Have you cared at all about lower level model optimization? There's other cloud providers that do custom kernels to get better performance or are you just given that you're not just an AI compute company? Yeah.Erik [00:25:24]: I mean, I think like we want to support like a generic, like general workloads in a sense that like we want users to give us a container essentially or a code or code. And then we want to run that. So I think, you know, we benefit from those things in the sense that like we can tell our users, you know, to use those things. But I don't know if we want to like poke into users containers and like do those things automatically. That's sort of, I think a little bit tricky from the outside to do, because we want to be able to take like arbitrary code and execute it. But certainly like, you know, we can tell our users to like use those things. Yeah.Swyx [00:25:53]: I may have betrayed my own biases because I don't really think about modal as for data teams anymore. I think you started, I think you're much more for AI engineers. My favorite anecdotes, which I think, you know, but I don't know if you directly experienced it. I went to the Vercel AI Accelerator, which you supported. And in the Vercel AI Accelerator, a bunch of startups gave like free credits and like signups and talks and all that stuff. The only ones that stuck are the ones that actually appealed to engineers. And the top usage, the top tool used by far was modal.Erik [00:26:24]: That's awesome.Swyx [00:26:25]: For people building with AI apps. Yeah.Erik [00:26:27]: I mean, it might be also like a terminology question, like the AI versus data, right? Like I've, you know, maybe I'm just like old and jaded, but like, I've seen so many like different titles, like for a while it was like, you know, I was a data scientist and a machine learning engineer and then, you know, there was like analytics engineers and there was like an AI engineer, you know? So like, to me, it's like, I just like in my head, that's to me just like, just data, like, or like engineer, you know, like I don't really, so that's why I've been like, you know, just calling it data teams. But like, of course, like, you know, AI is like, you know, like such a massive fraction of our like workloads.Swyx [00:26:59]: It's a different Venn diagram of things you do, right? So the stuff that you're talking about where you need like infinite bands for like highly parallel training, that's not, that's more of the ML engineer, that's more of the research scientist and less of the AI engineer, which is more sort of trying to put, work at the application.Erik [00:27:16]: Yeah. I mean, to be fair to it, like we have a lot of users that are like doing stuff that I don't think fits neatly into like AI. Like we have a lot of people using like modal for web scraping, like it's kind of nice. You can just like, you know, fire up like a hundred or a thousand containers running Chromium and just like render a bunch of webpages and it takes, you know, whatever. Or like, you know, protein folding is that, I mean, maybe that's, I don't know, like, but like, you know, we have a bunch of users doing that or, or like, you know, in terms of, in the realm of biotech, like sequence alignment, like people using, or like a couple of people using like modal to run like large, like mixed integer programming problems, like, you know, using Gurobi or like things like that. So video processing is another thing that keeps coming up, like, you know, let's say you have like petabytes of video and you want to just like transcode it, like, or you can fire up a lot of containers and just run FFmpeg or like, so there are those things too. Like, I mean, like that being said, like AI is by far our biggest use case, but you know, like, again, like modal is kind of general purpose in that sense.Swyx [00:28:08]: Yeah. Well, maybe I'll stick to the stable diffusion thing and then we'll move on to the other use cases for AI that you want to highlight. The other big player in my mind is replicate. Yeah. In this, in this era, they're much more, I guess, custom built for that purpose, whereas you're more general purpose. How do you position yourself with them? Are they just for like different audiences or are you just heads on competing?Erik [00:28:29]: I think there's like a tiny sliver of the Venn diagram where we're competitive. And then like 99% of the area we're not competitive. I mean, I think for people who, if you look at like front-end engineers, I think that's where like really they found good fit is like, you know, people who built some cool web app and they want some sort of AI capability and they just, you know, an off the shelf model is like perfect for them. That's like, I like use replicate. That's great. I think where we shine is like custom models or custom workflows, you know, running things at very large scale. We need to care about utilization, care about costs. You know, we have much lower prices because we spend a lot more time optimizing our infrastructure, you know, and that's where we're competitive, right? Like, you know, and you look at some of the use cases, like Suno is a big user, like they're running like large scale, like AI. Oh, we're talking with Mikey.Swyx [00:29:12]: Oh, that's great. Cool.Erik [00:29:14]: In a month. Yeah. So, I mean, they're, they're using model for like production infrastructure. Like they have their own like custom model, like custom code and custom weights, you know, for AI generated music, Suno.AI, you know, that, that, those are the types of use cases that we like, you know, things that are like very custom or like, it's like, you know, and those are the things like it's very hard to run and replicate, right? And that's fine. Like I think they, they focus on a very different part of the stack in that sense.Swyx [00:29:35]: And then the other company pattern that I pattern match you to is Modular. I don't know.Erik [00:29:40]: Because of the names?Swyx [00:29:41]: No, no. Wow. No, but yeah, yes, the name is very similar. I think there's something that might be insightful there from a linguistics point of view. Oh no, they have Mojo, the sort of Python SDK. And they have the Modular Inference Engine, which is their sort of their cloud stack, their sort of compute inference stack. I don't know if anyone's made that comparison to you before, but like I see you evolving a little bit in parallel there.Erik [00:30:01]: No, I mean, maybe. Yeah. Like it's not a company I'm like super like familiar, like, I mean, I know the basics, but like, I guess they're similar in the sense like they want to like do a lot of, you know, they have sort of big picture vision.Swyx [00:30:12]: Yes. They also want to build very general purpose. Yeah. So they're marketing themselves as like, if you want to do off the shelf stuff, go out, go somewhere else. If you want to do custom stuff, we're the best place to do it. Yeah. Yeah. There is some overlap there. There's not overlap in the sense that you are a closed source platform. People have to host their code on you. That's true. Whereas for them, they're very insistent on not running their own cloud service. They're a box software. Yeah. They're licensed software.Erik [00:30:37]: I'm sure their VCs at some point going to force them to reconsider. No, no.Swyx [00:30:40]: Chris is very, very insistent and very convincing. So anyway, I would just make that comparison, let people make the links if they want to. But it's an interesting way to see the cloud market develop from my point of view, because I came up in this field thinking cloud is one thing, and I think your vision is like something slightly different, and I see the different takes on it.Erik [00:31:00]: Yeah. And like one thing I've, you know, like I've written a bit about it in my blog too, it's like I think of us as like a second layer of cloud provider in the sense that like I think Snowflake is like kind of a good analogy. Like Snowflake, you know, is infrastructure as a service, right? But they actually run on the like major clouds, right? And I mean, like you can like analyze this very deeply, but like one of the things I always thought about is like, why does Snowflake arbitrarily like win over Redshift? And I think Snowflake, you know, to me, one, because like, I mean, in the end, like AWS makes all the money anyway, like and like Snowflake just had the ability to like focus on like developer experience or like, you know, user experience. And to me, like really proved that you can build a cloud provider, a layer up from, you know, the traditional like public clouds. And in that layer, that's also where I would put Modal, it's like, you know, we're building a cloud provider, like we're, you know, we're like a multi-tenant environment that runs the user code. But we're also building on top of the public cloud. So I think there's a lot of room in that space, I think is very sort of interesting direction.Alessio [00:31:55]: How do you think of that compared to the traditional past history, like, you know, you had AWS, then you had Heroku, then you had Render, Railway.Erik [00:32:04]: Yeah, I mean, I think those are all like great. I think the problem that they all faced was like the graduation problem, right? Like, you know, Heroku or like, I mean, like also like Heroku, there's like a counterfactual future of like, what would have happened if Salesforce didn't buy them, right? Like, that's a sort of separate thing. But like, I think what Heroku, I think always struggled with was like, eventually companies would get big enough that you couldn't really justify running in Heroku. So they would just go and like move it to, you know, whatever AWS or, you know, in particular. And you know, that's something that keeps me up at night too, like, what does that graduation risk like look like for modal? I always think like the only way to build a successful infrastructure company in the long run in the cloud today is you have to appeal to the entire spectrum, right? Or at least like the enterprise, like you have to capture the enterprise market. But the truly good companies capture the whole spectrum, right? Like I think of companies like, I don't like Datadog or Mongo or something that were like, they both captured like the hobbyists and acquire them, but also like, you know, have very large enterprise customers. I think that arguably was like where I, in my opinion, like Heroku struggle was like, how do you maintain the customers as they get more and more advanced? I don't know what the solution is, but I think there's, you know, that's something I would have thought deeply if I was at Heroku at that time.Alessio [00:33:14]: What's the AI graduation problem? Is it, I need to fine tune the model, I need better economics, any insights from customer discussions?Erik [00:33:22]: Yeah, I mean, better economics, certainly. But although like, I would say like, even for people who like, you know, needs like thousands of GPUs, just because we can drive utilization so much better, like we, there's actually like a cost advantage of staying on modal. But yeah, I mean, certainly like, you know, and like the fact that VCs like love, you know, throwing money at least used to, you know, add companies who need it to buy GPUs. I think that didn't help the problem. And in training, I think, you know, there's less software differentiation. So in training, I think there's certainly like better economics of like buying big clusters. But I mean, my hope it's going to change, right? Like I think, you know, we're still pretty early in the cycle of like building AI infrastructure. And I think a lot of these companies over in the long run, like, you know, they're, except it may be super big ones, like, you know, on Facebook and Google, they're always going to build their own ones. But like everyone else, like some extent, you know, I think they're better off like buying platforms. And, you know, someone's going to have to build those platforms.Swyx [00:34:12]: Yeah. Cool. Let's move on to language models and just specifically that workload just to flesh it out a little bit. You already said that RAMP is like fine tuning 100 models at once simultaneously on modal. Closer to home, my favorite example is ErikBot. Maybe you want to tell that story.Erik [00:34:30]: Yeah. I mean, it was a prototype thing we built for fun, but it's pretty cool. Like we basically built this thing that hooks up to Slack. It like downloads all the Slack history and, you know, fine-tunes a model based on a person. And then you can chat with that. And so you can like, you know, clone yourself and like talk to yourself on Slack. I mean, it's like nice like demo and it's just like, I think like it's like fully contained modal. Like there's a modal app that does everything, right? Like it downloads Slack, you know, integrates with the Slack API, like downloads the stuff, the data, like just runs the fine-tuning and then like creates like dynamically an inference endpoint. And it's all like self-contained and like, you know, a few hundred lines of code. So I think it's sort of a good kind of use case for, or like it kind of demonstrates a lot of the capabilities of modal.Alessio [00:35:08]: Yeah. On a more personal side, how close did you feel ErikBot was to you?Erik [00:35:13]: It definitely captured the like the language. Yeah. I mean, I don't know, like the content, I always feel this way about like AI and it's gotten better. Like when you look at like AI output of text, like, and it's like, when you glance at it, it's like, yeah, this seems really smart, you know, but then you actually like look a little bit deeper. It's like, what does this mean?Swyx [00:35:32]: What does this person say?Erik [00:35:33]: It's like kind of vacuous, right? And that's like kind of what I felt like, you know, talking to like my clone version, like it's like says like things like the grammar is correct. Like some of the sentences make a lot of sense, but like, what are you trying to say? Like there's no content here. I don't know. I mean, it's like, I got that feeling also with chat TBT in the like early versions right now it's like better, but.Alessio [00:35:51]: That's funny. So I built this thing called small podcaster to automate a lot of our back office work, so to speak. And it's great at transcript. It's great at doing chapters. And then I was like, okay, how about you come up with a short summary? And it's like, it sounds good, but it's like, it's not even the same ballpark as like, yeah, end up writing. Right. And it's hard to see how it's going to get there.Swyx [00:36:11]: Oh, I have ideas.Erik [00:36:13]: I'm certain it's going to get there, but like, I agree with you. Right. And like, I have the same thing. I don't know if you've read like AI generated books. Like they just like kind of seem funny, right? Like there's off, right? But like you glance at it and it's like, oh, it's kind of cool. Like looks correct, but then it's like very weird when you actually read them.Swyx [00:36:30]: Yeah. Well, so for what it's worth, I think anyone can join the modal slack. Is it open to the public? Yeah, totally.Erik [00:36:35]: If you go to modal.com, there's a button in the footer.Swyx [00:36:38]: Yeah. And then you can talk to Erik Bot. And then sometimes I really like picking Erik Bot and then you answer afterwards, but then you're like, yeah, mostly correct or whatever. Any other broader lessons, you know, just broadening out from like the single use case of fine tuning, like what are you seeing people do with fine tuning or just language models on modal in general? Yeah.Erik [00:36:59]: I mean, I think language models is interesting because so many people get started with APIs and that's just, you know, they're just dominating a space in particular opening AI, right? And that's not necessarily like a place where we aim to compete. I mean, maybe at some point, but like, it's just not like a core focus for us. And I think sort of separately, it's sort of a question of like, there's economics in that long term. But like, so we tend to focus on more like the areas like around it, right? Like fine tuning, like another use case we have is a bunch of people, Ramp included, is doing batch embeddings on modal. So let's say, you know, you have like a, actually we're like writing a blog post, like we take all of Wikipedia and like parallelize embeddings in 15 minutes and produce vectors for each article. So those types of use cases, I think modal suits really well for. I think also a lot of like custom inference, like yeah, I love that.Swyx [00:37:43]: Yeah. I think you should give people an idea of the order of magnitude of parallelism, because I think people don't understand how parallel. So like, I think your classic hello world with modal is like some kind of Fibonacci function, right? Yeah, we have a bunch of different ones. Some recursive function. Yeah.Erik [00:37:59]: Yeah. I mean, like, yeah, I mean, it's like pretty easy in modal, like fan out to like, you know, at least like 100 GPUs, like in a few seconds. And you know, if you give it like a couple of minutes, like we can, you know, you can fan out to like thousands of GPUs. Like we run it relatively large scale. And yeah, we've run, you know, many thousands of GPUs at certain points when we needed, you know, big backfills or some customers had very large compute needs.Swyx [00:38:21]: Yeah. Yeah. And I mean, that's super useful for a number of things. So one of my early interactions with modal as well was with a small developer, which is my sort of coding agent. The reason I chose modal was a number of things. One, I just wanted to try it out. I just had an excuse to try it. Akshay offered to onboard me personally. But the most interesting thing was that you could have that sort of local development experience as it was running on my laptop, but then it would seamlessly translate to a cloud service or like a cloud hosted environment. And then it could fan out with concurrency controls. So I could say like, because like, you know, the number of times I hit the GPT-3 API at the time was going to be subject to the rate limit. But I wanted to fan out without worrying about that kind of stuff. With modal, I can just kind of declare that in my config and that's it. Oh, like a concurrency limit?Erik [00:39:07]: Yeah. Yeah.Swyx [00:39:09]: Yeah. There's a lot of control. And that's why it's like, yeah, this is a pretty good use case for like writing this kind of LLM application code inside of this environment that just understands fan out and rate limiting natively. You don't actually have an exposed queue system, but you have it under the hood, you know, that kind of stuff. Totally.Erik [00:39:28]: It's a self-provisioning cloud.Swyx [00:39:30]: So the last part of modal I wanted to touch on, and obviously feel free, I know you're working on new features, was the sandbox that was introduced last year. And this is something that I think was inspired by Code Interpreter. You can tell me the longer history behind that.Erik [00:39:45]: Yeah. Like we originally built it for the use case, like there was a bunch of customers who looked into code generation applications and then they came to us and asked us, is there a safe way to execute code? And yeah, we spent a lot of time on like container security. We used GeoVisor, for instance, which is a Google product that provides pretty strong isolation of code. So we built a product where you can basically like run arbitrary code inside a container and monitor its output or like get it back in a safe way. I mean, over time it's like evolved into more of like, I think the long-term direction is actually I think more interesting, which is that I think modal as a platform where like I think the core like container infrastructure we offer could actually be like, you know, unbundled from like the client SDK and offer to like other, you know, like we're talking to a couple of like other companies that want to run, you know, through their packages, like run, execute jobs on modal, like kind of programmatically. So that's actually the direction like Sandbox is going. It's like turning into more like a platform for platforms is kind of what I've been thinking about it as.Swyx [00:40:45]: Oh boy. Platform. That's the old Kubernetes line.Erik [00:40:48]: Yeah. Yeah. Yeah. But it's like, you know, like having that ability to like programmatically, you know, create containers and execute them, I think, I think is really cool. And I think it opens up a lot of interesting capabilities that are sort of separate from the like core Python SDK in modal. So I'm really excited about C. It's like one of those features that we kind of released and like, you know, then we kind of look at like what users actually build with it and people are starting to build like kind of crazy things. And then, you know, we double down on some of those things because when we see like, you know, potential new product features and so Sandbox, I think in that sense, it's like kind of in that direction. We found a lot of like interesting use cases in the direction of like platformized container runner.Swyx [00:41:27]: Can you be more specific about what you're double down on after seeing users in action?Erik [00:41:32]: I mean, we're working with like some companies that, I mean, without getting into specifics like that, need the ability to take their users code and then launch containers on modal. And it's not about security necessarily, like they just want to use modal as a back end, right? Like they may already provide like Kubernetes as a back end, Lambda as a back end, and now they want to add modal as a back end, right? And so, you know, they need a way to programmatically define jobs on behalf of their users and execute them. And so, I don't know, that's kind of abstract, but does that make sense? I totally get it.Swyx [00:42:03]: It's sort of one level of recursion to sort of be the Modal for their customers.Erik [00:42:09]: Exactly.Swyx [00:42:10]: Yeah, exactly. And Cloudflare has done this, you know, Kenton Vardar from Cloudflare, who's like the tech lead on this thing, called it sort of functions as a service as a service.Erik [00:42:17]: Yeah, that's exactly right. FaSasS.Swyx [00:42:21]: FaSasS. Yeah, like, I mean, like that, I think any base layer, second layer cloud provider like yourself, compute provider like yourself should provide, you know, it's a mark of maturity and success that people just trust you to do that. They'd rather build on top of you than compete with you. The more interesting thing for me is like, what does it mean to serve a computer like an LLM developer, rather than a human developer, right? Like, that's what a sandbox is to me, that you have to redefine modal to serve a different non-human audience.Erik [00:42:51]: Yeah. Yeah, and I think there's some really interesting people, you know, building very cool things.Swyx [00:42:55]: Yeah. So I don't have an answer, but, you know, I imagine things like, hey, the way you give feedback is different. Maybe you have to like stream errors, log errors differently. I don't really know. Yeah. Obviously, there's like safety considerations. Maybe you have an API to like restrict access to the web. Yeah. I don't think anyone would use it, but it's there if you want it.Erik [00:43:17]: Yeah.Swyx [00:43:18]: Yeah. Any other sort of design considerations? I have no idea.Erik [00:43:21]: With sandboxes?Swyx [00:43:22]: Yeah. Yeah.Erik [00:43:24]: Open-ended question here. Yeah. I mean, no, I think, yeah, the network restrictions, I think, make a lot of sense. Yeah. I mean, I think, you know, long-term, like, I think there's a lot of interesting use cases where like the LLM, in itself, can like decide, I want to install these packages and like run this thing. And like, obviously, for a lot of those use cases, like you want to have some sort of control that it doesn't like install malicious stuff and steal your secrets and things like that. But I think that's what's exciting about the sandbox primitive, is like it lets you do that in a relatively safe way.Alessio [00:43:51]: Do you have any thoughts on the inference wars? A lot of providers are just rushing to the bottom to get the lowest price per million tokens. Some of them, you know, the Sean Randomat, they're just losing money and there's like the physics of it just don't work out for them to make any money on it. How do you think about your pricing and like how much premium you can get and you can kind of command versus using lower prices as kind of like a wedge into getting there, especially once you have model instrumented? What are the tradeoffs and any thoughts on strategies that work?Erik [00:44:23]: I mean, we focus more on like custom models and custom code. And I think in that space, there's like less competition and I think we can have a pricing markup, right? Like, you know, people will always compare our prices to like, you know, the GPU power they can get elsewhere. And so how big can that markup be? Like it never can be, you know, we can never charge like 10x more, but we can certainly charge a premium. And like, you know, for that reason, like we can have pretty good margins. The LLM space is like the opposite, like the switching cost of LLMs is zero. If all you're doing is like straight up, like at least like open source, right? Like if all you're doing is like, you know, using some, you know, inference endpoint that serves an open source model and, you know, some other provider comes along and like offers a lower price, you're just going to switch, right? So I don't know, to me that reminds me a lot of like all this like 15 minute delivery wars or like, you know, like Uber versus Lyft, you know, and like maybe going back even further, like I think a lot about like sort of, you know, flip side of this is like, it's actually a positive side, which is like, I thought a lot about like fiber optics boom of like 98, 99, like the other day, or like, you know, and also like the overinvestment in GPU today. Like, like, yeah, like, you know, I don't know, like in the end, like, I don't think VCs will have the return they expected, like, you know, in these things, but guess who's going to benefit, like, you know, is the consumers, like someone's like reaping the value of this. And that's, I think an amazing flip side is that, you know, we should be very grateful, the fact that like VCs want to subsidize these things, which is, you know, like you go back to fiber optics, like there was an extreme, like overinvestment in fiber optics network in like 98. And no one made money who did that. But consumers, you know, got tremendous benefits of all the fiber optics cables that were led, you know, throughout the country in the decades after. I feel something similar abou

Behovet av halvledare kan leda till stora problem för svenska företag visar en ny rapport från Business Sweden. Vad behövs för att minska riskerna? Lyssna på alla avsnitt i Sveriges Radio Play. Programledare: Erika MårtenssonMedverkande: Mikael Östling, professor i mikroelektronik KTH och Victor Jensen, ekonomireporter

Behovet av halvledare kan leda till stora problem för svenska företag visar en ny rapport från Business Sweden. Vad behövs för att minska riskerna? Lyssna på alla avsnitt i Sveriges Radio Play. Programledare: Erika MårtenssonMedverkande: Mikael Östling, professor i mikroelektronik KTH och Victor Jensen, ekonomireporter

From a KTH student to a visionary in green technology, Karim is changing the game to revolutionize eco-friendly chemical engineering for mass production. In this episode, Karim Englemark Cassimjee, CEO and co-founder of EnginZyme. A Swedish startup with the vision to make the chemical industry green by unlocking the potential in enzymes. Karim opens up about the growing opportunities in the biotech sector, juxtaposed with the fundraising difficulties that companies often face. Karim provides a glimpse into EnginZyme's groundbreaking technology, centered around self-biomanufacturing using enzymes. The technology aims to transform chemicals into greener alternatives, offering catalysts, processes, and end products that surpass traditional methods in terms of both cost-effectiveness and sustainability.Karim discusses the challenges in scaling up operations and finding reliable partners, while EnginZyme remains dedicated to reducing CO2 emissions. He also talks about the company's aim to replace fossil-based products with bio-based alternatives, aspiring to become a go-to partner in the chemical industry for biosolutions.Karim and EnginZyme are taking actionable steps to bring their vision to fruition. Listen and be inspired by the potential of EnginZyme's biosolutions in reshaping the future of the chemical industry and advancing sustainability goals.Episode Highlights: The main forces that have shaped Karim's business trajectoryThe challenges and difficulties faced by EnginZyme in raising funds in the capital marketThe novelty of EnginZyme's technology and its ability to transform the chemical industry The current stage of progress in the world of industrial biotech and enzymesThe ultimate vision of EnginZyme to have a significant impact on reducing CO2 emissions by replacing fossil-based products with bio-based alternatives is emphasized.The tangible action items for Karim, including continuing to scale up technology, focusing on commercialization, identifying reliable manufacturing partners, and working towards reducing CO2 equivalents.About our Guest: Karim is the inventor of EnginZyme's foundational technology and co-founded the company in 2014. He holds a PhD from KTH and a Postdoc from Stockholm University.Links Supporting This Episode:EnginZyme Website | www.enginzyme.comKarim LinkedIn | Karim Engelmark CassimjeeSimon Leich LinkedIn | Simon LeichCS Partners Website | www.cs-partners.net

Nu ska vår tredje svenske astronaut, Marcus Wandt, upp till den internationella rymdstationen. Den här gången är det kommersiella rymdbolag som sköter själva turen upp dit, hur fungerar det? Hur är läget med rymdstationen nu i krigstider - och vad är det Marcus Wandt ska upp dit och göra? Lyssna på alla avsnitt i Sveriges Radio Play. Efter Christer Fuglesang och svenskamerikanska Jessica Meir står nu Marcus Wandt på tur för ett två veckors besök på rymdstationen ISS. Eftersom den numera är färdigbyggd så kommer han i huvudsak att ägna sig åt forskning under sitt besök. Det handlar om hur hjärnan fungerar i en så trång och stökig arbetsmiljö, om sömn och om stamceller, och resultaten kan vara till nytta både på jorden och på framtida längre rymdfärder, säger forskarna som han samarbetar med. Wandt blir förste svensk att åka upp i en farkost byggd och ägd av ett kommersiellt bolag, Spacex, och det är även ett privat företag som säljer biljetten till ESA som han representerar. Lite som kommunal snöröjning på entreprenad, eller dagens avreglerade tågmarknad, säger rymdfartsexperten Sven Grahn. Medverkande: Sven Grahn, senior forskare, KTH; Sara Sällström, reporter VetenskapsradionLjudtekniker: Elvira BjörnfotProgramledare: Lena Nordlundlena.nordlund@sr.seProducent: Björn Gunérbjorn.guner@sr.se

Därför behöver Linnea Wikblad damblöja! David Druid undrar om det bland alla vårdhjältar finns slackers! Vi pratar om det uppmärksammade mordet på Dee Dee Blanchard och frisläppningen av Gypsy Rose, tillsammans med kulturjournalisten Ayan Jamal! Linnea läser en makaber nyhet! David ber om ursäkt för sitt språkbråk! Vi får kontakt med Sveriges Metallsökarförening! KTH-forskaren Sverker Sörlin lär oss allt om snö! Babs Drougge på P3 Nyheter om Helveteskön på E22:an & därför avgår Harvards rektor. Lyssna på alla avsnitt i Sveriges Radio Play. Programledare: David Druid och Linnea Wikblad

Del 4. Vid förra sekelskiftet var elbilar vanligare än bilar med förbränningsmotor. I många städer var det just elbilar som ersatte hästdroskorna och särskilt som taxibilar var de populära. Sedan kom T-forden. Lyssna på alla avsnitt i Sveriges Radio Play. Och om Henry Ford hade valt att satsa på de elmotorer som han faktiskt experimenterade med, ja då hade kanske förbränningsmotorn blivit en kuriös sak från förra sekelskiftet som vi nu fick gå till museer för att påminna oss om.Mike Ward på transportmuseet i Alford i Skottland och många andra menar nämligen att just T-forden, världens första masstillverkade bil, avgjorde saken till bensinmotorernas fördel. Därför kom 1900-talets frihetssymbol nummer ett, personbilen, att lukta bensin och diesel. Men är det hela sanningen, och varför blev det som det blev?Programmet är en repris från 26/10 2021.Medverkande: Mike Ward, fd curator på transportmuseet i Alford i Skottland; Alex Kemp, professor i petroleumekonomi, Aberdeen; Mikael Höök, docent i naturresurser och hållbar utveckling, Uppsala Universitet, och Arne Kaijser, professor emeritus i teknikhistoria, KTH.Reporter: Björn Gunérbjorn.guner@sr.seProducent Peter Normarkpeter.normark@sr.se

Går det att bygga en fungerande datormodell av människans hjärna? Det fick en karismatisk forskare EU-kommissionen att satsa på, men projektet havererade. Vad hände sedan? Och supermaterialet grafen lovade också stort, men vad har det blivit av miljardsatsningen? Lyssna på alla avsnitt i Sveriges Radio Play. De kallas flaggskepp, projekten som får miljardanslag från EU och som ska skapa framtidens teknik med siktet mot högt ställda mål. Två av dem är nu avslutade, men allt har inte gått enligt plan. Först ut, för tio år sedan, gällde det forskning på det då helt nya materialet grafen och avancerad hjärnforskning. Med 1 miljard euro vardera under tio år var förväntningarna höga. Grafen skulle revolutionera tillvaron sades det, och hjärnprojektet siktade mot att bygga en realistiskt fungerande digital människohjärna. Flaggskeppen var tänkta som EU:s sätt att möta konkurrensen från USA och Asien. Med stora anslag, visionärt tänkande och internationellt samarbete ville EU-kommissionen mobilisera Europas samlade potential inom forskning och vetenskap. Framför allt ville man få forskning och industri att mötas på nya sätt och skapa kunskap och teknik som kunde bli framgångsrika avancerade produkter.Nu har de första projekten avslutats. Grafenforskningen har inte gett några stora sensationer, men ett hundratal nya produkter och fler syns vid horisonten.För hjärnforskningen däremot gick det inte som planerat. Konflikter inom projektet har lett till radikala förändringar och de ursprungliga målen fick överges. Men ytterligare två flaggskepp har kommit igång under tiden: ett för kvantteknik och det senaste för batteriforskning. Kanske lite mindre visionära, men med tydligare målinriktning.Medverkande: Patrik Johansson, professor i fysik Chalmers Göteborg; Mats Benner, professor forskningspolitik Lunds universitet; Göran Johansson, professor i fysik Chalmers; Jonas Bylander, docent i fysik Chalmers, Kristina Edström, professor i kemi Uppsala universitet; Tamara Patranika, doktorand kemi Uppsala universitet; Sten Grillner, professor neurovetenskap Karolinska institutet; Jeanette Hellgren Kotaleski, professor neurovetenskap KTH.Reporter: Tomas LindbladProducent: Björn Gunérbjorn.guner@sr.se

Del 3. Att gå till jobbet, passa tider, resa och att ha fritid är nytt för människan på 1800-talet. Det var fossila bränslen som födde hela denna nya livsstil. Lyssna på alla avsnitt i Sveriges Radio Play. Den industriella revolutionen och utvecklingen av järnvägar och ångfartyg på 1800-talet satte fart på de fossila utsläppen från kolet som eldades, men bidrog också till att ställa om hela samhället, med lönearbete och massproduktion på fabriker och helt ny pålitlighet för transporter som blev oberoende av vädret och nu kunde börja följa tidtabeller. Mycket av detta har levt kvar in i vår tid och bidrar till att det nu är svårt att ställa om. Dessutom finns all den koldioxid som släpptes ut under 1800-talet kvar i atmosfären. Men var det en oundviklig utveckling eller hade det kunnat gå annorlunda?- Den tidens människor valde inte att hamna här i smogen lika lite som vi har valt att leva under klimatkrisen, säger Sarah Baines på The Science and Industry Museum i Manchester. Men, säger hon, det är viktigt att inte se en utveckling som oundviklig, allt handlar om ett antal beslut som människor och samhällen fattar, och framför allt så har vi idag möjligheten att tänka annorlunda och fatta bra beslut för vår framtid utifrån den kunskap vi har, menar hon.Det här är tredje delen i serien "Den fossila fällan - hur vi skapade klimatkrisen".Medverkande: Arne Kaijser, professor emeritus i teknikhistoria, KTH; Mikael Höök, docent i naturresurser och hållbar utveckling, Uppsala Universitet och Sarah Baines, curator of engineering, The Science and Industry Museum, Manchester.Programmet är en repris från 25/10 2021.Reporter: Björn Gunérbjorn.guner@sr.seProducent: Peter Normarkpeter.normark@sr.se

Del 2. Det är världens första riktiga energikris med galopperande vedpriser som får européerna och särskilt britterna att börja gräva upp fossilt kol i stor skala. Lyssna på alla avsnitt i Sveriges Radio Play. Det nya bränslet eldar på övergången från medeltid till tidigmodern tid, när Storbritannien seglar upp som det kommande stora imperiet. Samtidigt tas de första stegen in i industrialismen, där kolet blir avgörande för att de allra första industristäderna ska växa fram i nordvästra England.Det var en revolution i sig när denna ”sammanpressade superved” från underjorden befriade människor från det tidskrävande arbetet att ständigt samla ved, och ytterligare en revolution när de svarta stenliknande klumparna, istället för människors och djurs kroppsstyrka, kunde få maskiner att röra sig. Och så småningom kunde fossilt bränsle också inleda en tredje revolution, den industriella, där detta kombinerades, och skapade nytt välstånd och makt i Storbritannien och andra länder.Men samtidigt krävdes tusentals lågbetalda människors hårda kroppsarbete vid maskinerna, och även om ingen anade att det här var ett viktigt steg mot dagens klimatkris, så märkte folk i industristäderna tydligt de negativa hälsoeffekterna av den svarta röken från de tusentals skorstenarna. ”Folk beskrev det som att kliva in i helvetet”, säger Sarah Baines vid muséet för industri och vetenskap i Manchester.Det här är andra delen i serien "Den fossila fällan - hur vi skapade klimatkrisen".Medverkande: Arne Kaijser, professor emeritus i teknikhistoria, KTH; Ray Hudson, professor emeritus i geografi vid Durham University; Mikael Höök, docent i naturresurser och hållbar utveckling, Uppsala Universitet och Sarah Baines, curator of engineering, The Science and Industry Museum, Manchester.Programmet är en repris från 19/10 2021.Reporter: Björn Gunérbjorn.guner@sr.seProducent: Peter Normarkpeter.normark@sr.se

Del 1. Redan strax efter Kristi födelse bröt och använde romare fossilt kol i närmast industriell skala i England, och tog därmed det kanske första kända steget på vägen mot dagens klimatkris. Lyssna på alla avsnitt i Sveriges Radio Play. När man ser en bit stenkol är det inte självklart att man förstår att den kan brinna, och ännu mindre att den skulle kunna orsaka klimatförändringar. Men en gång i tiden måste en sådan svart sten hamnat i en brasa och tänt en första mänsklig aptit för fossila bränslen, som sedan växt in i vår moderna tid.Vi besöker kolfälten i norra England där det hela kan ha börjat, och där det finns tydliga spår på att redan romarna bröt och eldade fossilt kol på vad arkeologen Andrew Birley kallar industriellt sätt. Vid fortet Vindolanda bröt romarna också metaller som de använde kolet för att bearbeta, och Birley menar att fossilt kol till och med var viktigt i bygget av Hadrianus mur, som än idag är det största byggnadsverket i Storbritannien.Det här är första delen i serien "Den fossila fällan - hur vi skapade klimatkrisen".Medverkande: Arne Kaijser, professor emeritus i teknikhistoria, KTH; Ray Hudson, professor i geografi vid Durham University, och Andrew Birley, chef för de arkeologiska utgrävningarna vid Vindolanda.Programmet är en repris från 18/10 2021. Reporter: Björn Gunérbjorn.guner@sr.seProducent: Peter Normarkpeter.normark@sr.se

Dagens avsnitt är speciellt för mig då jag sätter mig ned med min föredetta lärare på KTH, Mikael Bergquist. Mikael har gjort det mesta inom arkitektur och med sin djupgående expertis inom Josef Franks verk, är han en av de mest pålästa personerna jag träffat. Vi disskuterar tankegångarna bakom den komplexa utbyggnaden av Svenskt Tenn, hans fascinerande arbete med Josef Franks ikoniska villor och och hur han applicerar sina erfarenheter både i sin arkitektur och i sin roll som lärare på KTH. I avsnittet diskuterar vi en rad olika projekt som Mikael Bergquist har arbetat med, både hans många villor, samt bland anant arbetet med Josef Franks verk Villa Wehtje och Villa Carlsten. Om du är intresserad av att få en visuell upplevelse av vårt samtal, kan du följa oss på Instagram under namnet Architecture.Talk. Hosted on Acast. See acast.com/privacy for more information.