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Industrial Talk is onsite at Xcelerate 2025 and talking to Tom Wilk, Editor in Chief at Endeavor Business Media about "Emerging Industrial Technology". Scott MacKenzie and Tom Wilk discuss the Xcelerate 2025 conference in Austin, Texas, highlighting the importance of asset management, maintenance, and reliability. Tom shares his experience with Plant Services Magazine and the evolution of the conference, emphasizing the adoption of Fluke's E-Maint system by SKF, which is rolling out to 81 plants. They discuss the benefits of a CMMS for sustaining best practices and the importance of AI and mobile components in modern maintenance. Tom also notes the growing interest among younger workers in professional certifications and the need for universities to adapt to industry changes. Action Items [ ] Reach out to Tom Wilk (T Wilk) at Endeavor B2B.com or on LinkedIn to further discuss the topics covered in the meeting. Outline Introduction and Welcome to Industrial Talk Podcast Speaker 1 introduces Scott MacKenzie as a passionate industry professional dedicated to transferring cutting-edge industry innovations and trends. Scott MacKenzie welcomes listeners to the Industrial Talk Podcast, celebrating industry professionals worldwide. Scott MacKenzie thanks the audience for their support and highlights the importance of innovation, collaboration, and making the world a better place. The podcast is broadcasting from Xcelerate 2025 in Austin, Texas, hosted by Fluke Reliability. Introduction of Tom Wilkes and His Role Scott MacKenzie introduces Tom Wilkes, who has been with Plant Services Magazine for 10 years. Tom Wilkes shares his background, including his role at Plant Services Magazine and his involvement in the Accelerate conference. Tom discusses the evolution of the conference from an EMA user group to a thought leadership event focusing on plant floor operations and best practices. Scott MacKenzie and Tom discuss the importance of connected reliability and the various solutions offered by Fluke Reliability. Customer Success Stories and Implementation of E-Main Tom shares a press briefing from SKF about their successful implementation of E-Main across 81 plants worldwide. The success of E-Main led SKF's management to mandate its use across all plants due to the return on investment and streamlined work processes. Tom highlights the various ways different plants are using E-Main to optimize their maintenance programs and data management. Scott MacKenzie and Tom discuss the sustainability of these solutions and the importance of a CMMS in maintaining best practices and collective memory for the plant. Challenges and Solutions in Reliability and Maintenance Scott MacKenzie and Tom discuss the challenges of finding skilled individuals and the impact of the "silver tsunami" on organizational knowledge. Tom emphasizes the importance of investing in systems like E-Main to reduce the learning curve for new employees and maintain organizational knowledge. The mobile aspect of CMMS systems is highlighted as a key factor in getting buy-in from younger technicians. Scott MacKenzie and Tom discuss the importance of having a system like E-Main to capture and maintain organizational knowledge. Evolution of the Xcelerate Conference and Customer Focus Tom notes the subtle but significant change in the messaging at the Xcelerate conference this year, focusing more on tools already being used rather than future...

Vi befinner oss mitt i en historisk rotation från USA-börserna till Europa. Samtidigt kommer nya tullutspel från USA:s president Donald Trump varje dag. Hur agerar man då som fondförvaltare? Detta svarar Marcus Plyhr från Norron på i Börslunch. Dessutom snackar vi Nibe, Hexpol, SKF, Sandvik och Trelleborg.Programledare: Kelly Connelin

Under åren 1870 till 1970 gick Sverige från att vara ett av de fattigaste länderna i Europa till det fjärde rikaste landet i världen. Sveriges industrialisering kom sent, men blev oerhört framgångsrik. Svenska innovationer skulle sprida sig över världen.Grunden var tydlig äganderätt, jordbruksreformer, allmän folkskola samt näringsfrihet.Tillväxtmaskinen började inte hacka förrän på 1970-talet när oljekrisen, skattetryck och allt fler regleringar blev början på Sveriges fall från toppen.I detta avsnitt av podden Historia Nu samtalar programledaren Urban Lindstedt med Andreas Bergh, lektor vid nationalekonomiska institutionen vid Lunds universitet. Han har skrivit boken Den kapitalistiska välfärdsstaten.Forskningen visar att Sverige kunde kombinera effektiv kapitalism med en utvecklad välfärdsstat tack vare stabila spelregler och en rationell arbetsfördelning mellan politik och näringsliv. Flera faktorer bidrog till Sveriges ekonomiska framgång under denna hundraårsperiod:Under 1800-talet genomfördes omfattande reformer som moderniserade Sverige. En av de mest betydelsefulla var införandet av näringsfrihet 1864, vilket avskaffade gamla skråsystem och öppnade upp för entreprenörskap. Demokratins utveckling, med rösträttsreformer och en starkare riksdag, skapade också stabila institutioner som gynnade långsiktig ekonomisk tillväxt.Införandet av folkskolan 1842 och en stark satsning på teknisk utbildning, som Chalmers tekniska högskola och Kungliga Tekniska högskolan, lade grunden för en välutbildad arbetskraft. Teknologiska innovationer, som Alfred Nobels uppfinning av dynamiten och Lars Magnus Ericssons telekommunikationsteknik, stärkte Sveriges konkurrenskraft på den globala marknaden.Sveriges rikliga naturresurser – skogar, järnmalm och vattenkraft – spelade en avgörande roll i industrialiseringen. Tack vare export av högkvalitativt stål, pappersmassa och andra industriprodukter växte den svenska ekonomin i snabb takt. Svenska företag som SKF, ASEA och senare Volvo och Ericsson blev globala aktörer och symboler för svensk industriexport.Under 1930-talet etablerades det så kallade "Saltsjöbadsavtalet", en kompromiss mellan arbetsgivare och fackföreningar som bidrog till en stabil arbetsmarknad. Denna samförståndsanda mellan arbetsmarknadens parter, tillsammans med en stark socialdemokratisk politik, gjorde att Sverige kunde kombinera hög tillväxt med relativt små inkomstklyftor.Under 1900-talet lade Sverige stor vikt vid att bygga upp ett omfattande välfärdssystem, vilket inkluderade sjukvård, pensioner och utbildning. Detta bidrog till att stärka den sociala sammanhållningen och skapa en arbetskraft som både var frisk och välutbildad.Bild: Gjuteriet vid Bolinders kring 1890. Gjutare i Bolinders Mekaniska Verkstads vid Klara sjö på Kungsholmen i Stockholm. Stockholms stadsmuseum. Wikipedia. Public Domain.Musik: Mischief And Consequence. Av: Jon Presstone. Storyblocks Audio.Klippare: Emanuel Lehtonen Vill du stödja podden och samtidigt höra ännu mer av Historia Nu? Gå med i vårt gille genom att klicka här: https://plus.acast.com/s/historianu-med-urban-lindstedt. Hosted on Acast. See acast.com/privacy for more information.

durée : 00:03:38 - Licencié de SKF à Avallon, Damien a su rebondir et trouver une reconversion professionnelle - Matinée spéciale ce mercredi 12 février sur l'emploi et la réindustrialisation. "ici Auxerre" a rencontré un ancien salarié de SKF à Avallon. Damien a travaillé 14 ans chez le fabricant de roulements à billes pour les éoliennes. Aujourd'hui, il s'est reconvertit dans l'informatique.

JM, SKF och Hexagon är några av de många bolag som i dag rapporterar för sitt fjärde kvartal, och stämningen på börsen är spretig med kraftiga upp- och nedgångar inom framförallt bygg, fastighet och förvärv. Börslunch programledare Elin Wiker och Gabriel Mellqvist navigerar i flödet tillsammans med aktiemäklaren Adam Thelander från Kepler Chevreux och analytikern Anders Roslund från Pareto.

Es ist eine große Aufgabe, ein Pflegekind in die eigene Familie aufzunehmen und damit in sein Leben zu lassen. In dieser Episode besucht Christoph Grätz eine Familie, die sich auf dieses Wagnis gleich mehrfach eingelassen hat. Er spricht mit den beiden Pflegeeltern Saskia (28) und Benjamin (37) Karkutt über ihr Leben als fast normale Familie. Bei den Karkutts leben neben ihren zwei leiblichen Kindern Celine (15) und Noah (6) noch drei Pflegekinder. Für das jüngste einjährige Kind haben die Karkutts eine Bereitschaftspflege übernommen, für das dreijährige Geschwisterkind eine Kurzzeitpflege und für ein vierjähriges Kind die Vollzeitpflege. Die Namen dürfen wir aus Datenschutzgründen nicht nennen. Saskia erinnert sich, wie es für sie war, als sie vor ein paar Jahren die Zusage bekamen, ein Pflegekind aufnehmen zu dürfen. Wie es überhaupt dazu kam und welche Vorbilder sie hatten, ist für Saskia und Benjamin ein wichtiger Punkt. Saskia berichtet, wie ein typischer Tag bei den Karkutts abläuft und wie sie Familie und Berufsleben unter einen Hut bekommen. Bei der großen Verantwortung für die eigenen und weitere Kinder ist die Pflege der Beziehung der Eheleute untereinander wichtig. Als Ausgleich zum Familienleben tanzen Saskia und Benjamin im Karnevalsverein. Benjamin Karkutt, der selbst Pflegekind war, berichtet, wie die Kontakte der Kinder zu ihren leiblichen Eltern gepflegt werden und ist glücklich, dass die Eltern ihres Dauerpflegekindes gut mit ihnen zusammenarbeiten. Er sagt, vor der Aufnahme eines Pflegekindes sollten Menschen sich selbst einige Fragen ehrlich beantworten. Saskia und Benjamin erklären, welche Gründe für und welche gegen die Aufnahme eines Pflegekindes sprechen und welche Eigenschaften man als Pflegeeltern mitbringen sollte, damit der Alltag gelingt. Bei kurzzeitigen Pflegeverhältnissen kommt irgendwann der Zeitpunkt, Abschied von den Kindern und Geschwistern auf Zeit zu nehmen. Wie die Karkutts damit umgehen und wie sie vom Pflegekinderdienst der Caritas begleitet werden, ist auch Thema dieser Episode. Sie berichten, wie sie auf die Aufgabe als Pflegeeltern vorbereitet wurden und wie sie sich mit anderen Pflegeeltern austauschen. Was viele vielleicht nicht wissen: Es gibt verschiedene Modelle und Möglichkeiten, die Pflegschaft für ein Kind zu übernehmen. Von der klassischen Vollzeitpflege bis zu einer kurzzeitigen Aufnahme. Wenn Sie jetzt denken, ein Pflegekind aufzunehmen, das wäre auch etwas für Sie, dann melden Sie sich doch einfach mal unverbindlich zu einem Informationsgespräch in einer unserer Fachstellen der Adoptions- und Pflegekinderdienste. Die Kolleginnen und Kollegen dort freuen sich auf Ihre Mail oder Ihren Anruf. Adressen und weitere Informationen zu den Adoptions- und Pflegekinderdiensten im Netzwerk der Caritas in NRW finden Sie hier Im Bistum Essen https://www.caritas-essen.de/dioezesangeschaeftsstelle/abteilungen/beratungerziehungfamilie/pflegekinderhilfe-adoptionswesen/pflegekinderhilfe-adoptionswesen Im Bistum Münster https://www.caritas.de/adressen/sozialdienst-katholischer-frauen-e.-v.-muenster/adoptions-und-pflegekinderdienst/48155-muenster/92832 Im Erzbistum Köln https://www.caritasnet.de/onlineberatung/beratungsangebote/adoption-und-pflegekinder/index.html Im Bistum Aachen https://www.caritas-ac.de/so-helfen-wir-ihnen/kinder-jugend-eltern-und-familie/kinder-jugendhilfe/adoption-und-pflege/adoption-und-pflege Im Kreis Paderborn https://skf-paderborn.de/beratungsdienstleistungen/adoptionsvermittlung-und-pflegekinderhilfe/ Hören Sie zum Thema auch die caritalks-Episode #76 Platz für ein Kind, im Haus und im Herzen. Markus Lahrmann spricht mit Melanie Plag, die den Pflegekinderdienst des SkF in Ahlen leitet.

This podcast hit paid subscribers' inboxes on Nov. 30. It dropped for free subscribers on Dec. 7. To receive future episodes as soon as they're live, and to support independent ski journalism, please consider an upgrade to a paid subscription. You can also subscribe to the free tier below:WhoMike Taylor, Owner of Holiday Mountain, New YorkRecorded onNovember 18, 2024About Holiday MountainClick here for a mountain stats overviewOwned by: Mike TaylorLocated in: Monticello, New YorkYear founded: 1957Pass affiliations: NoneClosest neighboring ski areas: Villa Roma (:37), Ski Big Bear (:56), Mt. Peter (:48), Mountain Creek (:52), Victor Constant (:54)Base elevation: 900 feetSummit elevation: 1,300 feetVertical drop: 400 feetSkiable acres: 60Average annual snowfall: 66 inchesTrail count: 9 (5 beginner, 2 intermediate, 2 advanced)Lift count: 3 (1 fixed-grip quad, 1 triple, 1 carpet - view Lift Blog's inventory of Holiday Mountain's lift fleet)Why I interviewed himNot so long ago, U.S. ski areas swung wrecking ball-like from the necks of founders who wore them like amulets. Mountain and man fused as one, each anchored to and propelled by the other, twin forces mirrored and set aglow, forged in some burbling cauldron and unleashed upon the public as an Experience. This was Killington and this was Mammoth and this was Vail and this was Squaw and this was Taos, each at once a mountain and a manifestation of psyche and soul, as though some god's hand had scooped from Pres and Dave and Pete and Al and Ernie their whimsy and hubris and willfulness and fashioned them into a cackling live thing on this earth. The men were the mountains and the mountains were the men. Everybody knew this and everybody felt this and that's why we named lifts and trails after them.This is what we've lost in the collect-them-all corporate roll-up of our current moment. I'm skeptical of applying an asteroid-ate-the-dinosaurs theory to skiing, but even I'll acknowledge this bit. When the caped founder, who stepped into raw wilderness and said “here I will build an organized snowskiing facility” and proceeded to do so, steps aside or sells to SnowCo or dies, some essence of the mountain evaporates with him. The snow still hammers and the skiers still come and the mountain still lets gravity run things. The trails remain and the fall lines still fall. The mountain is mostly the same. But nobody knows why it is that way, and the ski area becomes a disembodied thing, untethered from a human host. This, I think, is a big part of the appeal of Michigan's Mount Bohemia. Ungroomed, untamed, absent green runs and snowguns, accessible all winter on a $109 season pass, Boho is the impossible storybook of the maniac who willed it into existence against all advice and instinct: Lonie Glieberman, who hacked this thing from the wilderness not in some lost postwar decade, but in 2000. He lives there all winter and everybody knows him and they all know that this place that is the place would not exist had he not insisted that it be so. For the purposes of how skiers consider the joint, Lonie is Mount Bohemia. And someday when he goes away the mountain will make less sense than it does right now.I could write a similar paragraph about Chip Chase at White Grass Touring Center in West Virginia. But there aren't many of those fellas left. Since most of our ski areas are old, most of our founders are gone. They're not coming back, and we're not getting more ski areas. But that doesn't mean the era of the owner-soul keeper is finished. They just need to climb a different set of monkey bars to get there. Rather than trekking into the mountains to stake out and transform a raw wilderness into a piste digestible to the masses, the modern mountain incarnate needs to drive up to the ski area with a dump truck full of hundred dollar bills, pour it out onto the ground, and hope the planted seeds sprout money trees.And this is Mike Taylor. He has resources. He has energy. He has manpower. And he's going to transform this dysfunctional junkpile of a ski area into something modern, something nice, something that will last. And everyone knows it wouldn't be happening without him.What we talked aboutThe Turkey Trot chairlift upgrade; why Taylor re-engineered and renovated a mothballed double chair just to run it for a handful of days last winter before demolishing it this summer; Partek and why skiing needs an independent lift manufacturer; a gesture from Massanutten; how you build a chairlift when your chairlift doesn't come with a bottom terminal; Holiday Mountain's two new ski trails for this winter; the story behind Holiday Mountain's trail names; why a rock quarry is “the greatest neighbors we could ever ask for”; big potential future ski expansion opportunities; massive snowmaking upgrades; snowmaking is hard; how a state highway spurred the development of Holiday Mountain; “I think we've lost a generation of skiers”; vintage Holiday Mountain; the ski area's long, sad decline; pillage by flood; restoring abandoned terrain above the Fun Park; the chairlift you see from Route 17 is not actually a chairlift; considering a future when 17 converts into Interstate 86; what would have happened to Holiday had the other bidders purchased it; “how do we get kids off their phones and out recreating again?”; advice from Plattekill; buying a broken ski area in May and getting it open by Christmas (or trying); what translates well from the business world into running a ski area; how to finance the rebuild and modernization of a failing ski area; “when you talk to a bank and use the word ‘ski area,' they want nothing to do with it”; how to make a ski area make money; why summer business is hard; Holiday's incredible social media presence; “I always thought good grooming was easy, like mowing a lawn”; how to get big things done quickly but well; ski racing returns; “I don't want to do things half-assed and pay for it in the long run”; why season two should be better than season one; “you can't make me happier than to see busloads of kids, improving their skills, and enjoying something they're going to do for the rest of their life”; why New York State has a challenging business environment, and how to get things done anyway; the surprise labor audit that shocked New York skiing last February – “we didn't realize the mistakes we were making”; kids these days; the State of New York owns and subsidizes three ski areas – how does that complicate things?; why the state subsidizing independent ski areas isn't the answer; the problem with bussing kids to ski areas; and why Holiday Mountain doesn't feel ready to join the Indy Pass.Why I thought that now was a good time for this interviewI met Taylor in a Savannah bar last year, five minutes after he'd bought a ski area and seven months before he needed to turn that ski area into a functional business. Here was the new owner of Holiday Mountain, rolling with the Plattekill gang, more or less openly saying, “I have no idea what the hell I'm doing, but I'm going to do it. I'm going to save Holiday Mountain.”The National Ski Areas Association's annual show, tucked across the river that week, seemed like a good place to start. Here were hundreds of people who could tell Taylor exactly how hard it was to run a ski area, and why. And here was this guy, accomplished in so many businesses, ready to learn. And all I could think, having skied the disaster that was Holiday Mountain in recent years, was thank God this dude is here. Here's my card. Let's talk.I connected with Taylor the next month and wrote a story about his grand plans for Holiday. Then I stepped back and let that first winter happen. It was, by Taylor's own account, humbling. But it did not seem to be humiliating, which is key. Pride is the quickest path to failure in skiing. Instead of kicking things, Taylor seemed to regard the whole endeavor as a grand and amusing puzzle. “Well let's see here, turns out snowmaking is hard, grooming is hard, managing teenagers is hard… isn't that interesting and how can I make this work even though I already had too much else to do at my other 10 jobs?”Life may be attitude above all else. And when I look at ski area operators who have recycled garbage into gold, this is the attribute that seems to steer all others. That's people like Rick Schmitz, who talked two Wisconsin ski areas off the ledge and brought another back from its grave; Justin Hoppe, who just traded his life in to save a lost UP ski area; James Coleman, whose bandolier of saved ski areas could fill an egg carton; and Danielle and Laszlo Vajtay, who for 31 years have modernized their ridiculously steep and remote Catskills ski area one snowgun at a time.There are always plenty of people who will tell you why a thing is impossible. These people are boring. They lack creativity or vision, an ability to see the world as something other than what it is. Taylor is the opposite. All he does is envision how things can be better, and then work to make them that way. That was clear to me immediately. It just took him a minute to prove he could do it. And he did.What I got wrong* Mike said he needed a chairlift with “about 1,000 feet of vertical rise” to replace the severed double chair visible from Route 17. He meant length. According to Lift Blog, the legacy lift rose 232 vertical feet over 1,248 linear feet.* We talk a bit about New York's declining population, but the real-world picture is fuzzier. While the state's population did fall considerably, from 20.1 million to 19.6 million over the past four years, those numbers include a big pandemic-driven population spike in 2020, when the state's population rose 3.3 percent, from 19.5 million to that 20.1 million number (likely from city refugees camping out in New York's vast and bucolic rural reaches). The state's current population of 19,571,216 million is still larger than it was at any point before 2012, and not far off its pre-pandemic peak of 19,657,321.* I noted that Gore's new Hudson high-speed quad cost “about $10 million.” That is probably a fair estimate based upon the initial budget between $8 and $9 million, but an ORDA representative did not immediately respond to a request for the final number.Why you should ski Holiday MountainI've been reconsidering my television pitch for Who Wants to Own a Ski Area? Not because the answer is probably “everybody reading this newsletter except for the ones that already own a ski area, because they are smart enough to know better.” But because I think the follow-up series, Ski Resort Rebuild, would be even more entertaining. It would contain all the elements of successful unscripted television: a novel environment, large and expensive machinery, demolition, shouting, meddlesome authorities, and an endless sequence of puzzles confronting a charismatic leader and his band of chain-smoking hourlies.The rainbow arcing over all of this would of course be reinvention. Take something teetering on apocalyptic set-piece and transform it into an ordered enterprise that makes the kids go “wheeeeee!” Raw optimism and self-aware naivete would slide into exasperation and despair, the launchpad for stubborn triumphalism tempered by humility. Cut to teaser for season two.Though I envision a six- or eight-episode season, the template here is the concise and satisfying Hoarders, which condenses a days-long home dejunking into a half-hour of television. One minute, Uncle Frank's four-story house is filled with his pizza box collection and every edition of the Tampa Bay Bugle dating back to 1904. But as 15 dumpster trucks from TakeMyCrap.com drive off in convoy, the home that could only be navigated with sonar and wayfinding canines has been transformed into a Flintstones set piece, a couch and a wooly mammoth rug accenting otherwise empty rooms. I can watch these chaos-into-order transformations all day long.Roll into Holiday Mountain this winter, and you'll essentially be stepping into episode four of this eight-part series. The ski area's most atrocious failures have been bulldozed, blown-up, regraded, covered in snow. The two-seater chairlift that Columbus shipped in pieces on the Nina, the Pinta, and the Santa Maria has finally been scrapped and replaced with a machine that does not predate modern democracy. The snowguns are no longer powered by hand-cranks. A ski area that, just 18 months ago, was shrinking like an island in rising water is actually debuting two brand-new trails this winter.But the job's not finished. On your left as you drive in is a wide abandoned ridge where four ski lifts once spun. On the open hills, new snowguns glimmer and new-used chairlifts and cats hum, but by Taylor's own admission, his teams are still figuring out how to use all these fancy gadgets. Change is the tide climbing up the beach, but we haven't fully smoothed out the tracked sand yet, and it will take a few more hours to get there.It's fun to be part of something like this, even as an observer. I'll tell you to visit Holiday Mountain this winter for the same reason I'll tell you to go ride Chair 2 at Alpental or the triple at Bluewood or the Primo and Segundo Riblet doubles at Sunlight. By next autumn, each of these lifts, which have dressed their mountains for decades, will make way for modern machines. This is good, and healthy, and necessary for skiing's long-term viability. But experiencing the same place in different forms offers useful lessons in imagination, evolution, and the utility of persistence and willpower. It's already hard to picture that Holiday Mountain that teetered on the edge of collapse just two years ago. In two more years, it could be impossible, so thorough is the current renovation. So go. Bonus: they have skiing.Podcast NotesOn indies sticking togetherDespite the facile headlines, conglomerates are not taking over American skiing. As of my last count, about 73 percent of U.S. ski areas are still independently operated. And while these approximately three-quarters of active ski areas likely account for less than half of all skier visits, consumers do still have plenty of choice if they don't want to go Epkonic.New York, in particular, is a redoubt of family-owned and -operated mountains. Other than Vail-owned Hunter and state-owned Belleayre, Gore, and Whiteface, every single one of the state's 51 ski areas is under independent management. Taylor calls out several of these New York owners in our conversation, including many past podcast guests. These are all tremendous conversations, all streaked with the same sincere determination and grit that's obvious in Taylor's pod.Massachusetts is also a land of independent ski areas, including the Swiss watch known as Wachusett:On PartekPartek is one of the delightful secrets of U.S. skiing. The company, founded in 1993 by Hagen Schulz, son of the defunct Borvig lifts President Gary Schulz, installs one or two or zero new chairlifts in a typical year. Last year, it was a fixed-grip quad at Trollhaugen, Wisconsin and a triple at Mt. Southington, Connecticut. The year before, it was the new Sandy quad at Saddleback. Everyone raves about the quality of the lifts and the experience of working with Partek's team. Saddleback GM Jim Quimby laid this out for us in detail when he joined me on the podcast last year:Trollhaugen owner and GM Jim Rochford, Jr. was similarly effusive:I'm underscoring this point because if you visit Partek's website, you'll be like “I hope they have this thing ready for Y2K.” But this is your stop if you need a new SKF 6206-2RS1, which is only $17!On the old Catskills resort hotels with ski areasNew York is home to more ski areas (51) than any state in America, but there are still far more lost ski areas here than active ones. The New York Lost Ski Areas Project estimates that the ghosts of up to 350 onetime ski hills haunt the state. This is not so tragic as it sounds, as the vast majority of these operations consisted of a goat pulling a toboggan up 50 vertical feet beside Fiesty Pete's dairy barn. These operated for the lifespan of a housefly and no one missed them when they disappeared. On the opposite end were a handful of well-developed, multi-lift ski areas that have died in modernity: Scotch Valley (1988), Shu Maker (1999), Cortina (mid-90s), and Big Tupper (2012). But in the middle sat dozens of now-defunct surface-tow bumps, some with snowmaking, some attached to the famous and famously extinct Borsch Belt Catskills resorts.It is this last group that Taylor and I discuss in the podcast. He estimates that “probably a dozen” ski areas once operated in Sullivan County. Some of these were standalone operations like Holiday, but many were stapled to large resort hotels like The Nevele and Grossingers. I couldn't find a list of the extinct Catskills resorts that once offered skiing, and none appeared to have bothered drawing a trailmap.While these add-on ski areas are a footnote in the overall story of U.S. skiing, an activity-laying-around-to-do-at-a-resort can have a powerful multiplier effect. Here are some things that I only do if I happen across a readymade setup: shoot pool, ice skate, jet ski, play basketball, fish, play minigolf, toss cornhole bags. I enjoy all of these things, but I won't plan ahead to do them on purpose. I imagine skiing acted in this fashion for much of the Bortsch Belt crowd, like “oh let's go try that snowskiing thing between breakfast and our 11:00 baccarat game.” And with some of these folks, skiing probably became something they did on purpose.The closest thing modernity delivers to this is indoor skiing, which, attached to a mall – as Big Snow is in New Jersey – presents itself as Something To Do. Which is why I believe we need a lot more such centers, and soon.On shrinking Holiday MountainSome ski areas die all at once. Holiday Mountain curdled over decades, to the husk Taylor purchased last year. Check the place out in 2000, with lifts zinging all over the place across multiple faces:A 2003 flood smashed the terrain near the entrance, and by 2007, Holiday ran just two lifts:At some indeterminant point, the ski area also abandoned the Turkey Trot double. This 2023 trailmap shows the area dedicated to snowtubing, though to my knowledge no such activity was ever conducted there at scale.On the lift you see from Route 17Anyone cruising NY State 17 can see this chairlift rising off the northwest corner of the ski area:This is essentially a billboard, as Taylor left the terminal in place after demolishing the lower part of the long-inactive lift.Taylor intends to run a lift back up this hill and re-open all the old terrain. But first he has to restore the slopes, which eroded significantly in their last life as a Motocross course. There is no timeline for this, but Taylor works fast, and I wouldn't be shocked to see the terrain come back online as soon as 2025.On NY 17's transformation into I-86New York 17 is in the midst of a decades-long evolution into Interstate 86, with long stretches of the route that spans southern New York already signed as such. But the interstate designation comes with standards that define lane number and width, bridge height, shoulder dimensions, and maximum grade, among many other particulars, including the placement and length of exit and entrance ramps. Exit 108, which provides direct eastbound access to and egress from Holiday Mountain, is fated to close whenever the highway gods close the gap that currently splits I-86 into segments.On Norway MountainHoliday is the second ski area comeback story featured on the pod in recent months, following the tale of dormant-since-2017 Norway Mountain, Michigan:On Holiday's high-energy social media accountsTaylor has breathlessly documented Holiday's comeback on the ski area's Instagram and Facebook accounts. They're incredible. Follow recommended. On Tuxedo RidgeThis place frustrates me. Once a proud beginners-oriented ski center with four chairlifts and a 450-foot vertical drop, the bump dropped dead around 2014 without warning or explanation, despite a prime location less than an hour from New York City.I hiked the place in 2020, and wrote about it:On Ski Areas of New YorkSki Areas of New York, or SANY, is one of America's most effective state ski area organizations. I've hosted the organization's president, Scott Brandi, on the podcast a couple of times:Compulsory mention of ORDAThe Olympic Regional Development Authority, which manages New York State-owned Belleayre, Gore, and Whiteface mountains, lost $47.3 million in its last fiscal year. One ORDA board member, in response to the report, said that it's “amazing how well we are doing,” according to the Adirondack Explorer. Which makes a lot of the state's independent ski area operators say things like, “Huh?” That's probably a fair response, since $47.3 million would likely be sufficient for the state to simply purchase every ski area in New York other than Hunter, Windham, Holiday Valley, and Bristol.On high-speed ropetowsI'll keep writing about these forever because they are truly amazing and there should be 10 of them at every ski area in America:Welch Village, Minnesota. Video by Stuart Winchester.The Storm explores the world of lift-served skiing year-round. Join us.The Storm publishes year-round, and guarantees 100 articles per year. This is article 82/100 in 2024, and number 582 since launching on Oct. 13, 2019. Get full access to The Storm Skiing Journal and Podcast at www.stormskiing.com/subscribe

Laut repräsentativen Befragungen erleben zwei von drei Frauen in ihrem Leben sexuelle Belästigung. Wie diese Übergriffe aussehen können, ist ganz unterschiedlich. Im Gespräch mit Kristina Gottlöber von Imma e.V. sowie den Sozialpädagoginnen Michaela Seifert und Lea Heimerl vom SkF und der Psychologin Eleni Kimourtzaki vom SkF im Haus Maria Thalkirchen wird deutlich, wie Frauen und Mädchen sich gegen Belästigung und übergriffiges Verhalten wappnen können, wo Betroffene Hilfe und Unterstützung finden sowie welche Veränderungen bei Männern, Frauen und gesamtgesellschaftlich notwendig sind, damit Übergriffe nicht mehr für so viele Frauen zum Alltag gehören.

In der heutigen Folge von „Alles auf Aktien“ sprechen die Finanzjournalisten Anja Ettel und Holger Zschäpitz über die Fettweg-Enttäuschung bei Amgen, süße Gewinne für JM Smucker und klingelnde Kassen bei Novo Nordisk und Eli Lilly. Außerdem geht es um Bayer, Cooper Companies, Johnson&Johnson, Alcon, Crowdstrike, Workday, Dell, Rigetti, Quantum Computing, D-Wave Quantum, Coinbase, General Motors, Stellantis, Ford, Assa Abloy, Signify, Volkswagen, Mercedes, BMW, Legrand, Schneider Electric, Siemens, Nibe, SKF, NKT, Atlas Copco, Volvo, Metso, Daimler Trucks und ishares S&P Small Cap 600 (WKN A0Q1YY), Xtrackers Russel 2000 (WKN: A1XEJT). Wir freuen uns an Feedback über aaa@welt.de. Ab sofort gibt es noch mehr "Alles auf Aktien" bei WELTplus und Apple Podcasts – inklusive aller Artikel der Hosts und AAA-Newsletter.[ Hier bei WELT.](https://www.welt.de/podcasts/alles-auf-aktien/plus247399208/Boersen-Podcast-AAA-Bonus-Folgen-Jede-Woche-noch-mehr-Antworten-auf-Eure-Boersen-Fragen.html.) [Hier] (https://open.spotify.com/playlist/6zxjyJpTMunyYCY6F7vHK1?si=8f6cTnkEQnmSrlMU8Vo6uQ) findest Du die Samstagsfolgen Klassiker-Playlist auf Spotify! Disclaimer: Die im Podcast besprochenen Aktien und Fonds stellen keine spezifischen Kauf- oder Anlage-Empfehlungen dar. Die Moderatoren und der Verlag haften nicht für etwaige Verluste, die aufgrund der Umsetzung der Gedanken oder Ideen entstehen. Hörtipps: Für alle, die noch mehr wissen wollen: Holger Zschäpitz können Sie jede Woche im Finanz- und Wirtschaftspodcast "Deffner&Zschäpitz" hören. Außerdem bei WELT: Im werktäglichen Podcast „Das bringt der Tag“ geben wir Ihnen im Gespräch mit WELT-Experten die wichtigsten Hintergrundinformationen zu einem politischen Top-Thema des Tages. +++ Werbung +++ Du möchtest mehr über unsere Werbepartner erfahren? [**Hier findest du alle Infos & Rabatte!**](https://linktr.ee/alles_auf_aktien) Impressum: https://www.welt.de/services/article7893735/Impressum.html Datenschutz: https://www.welt.de/services/article157550705/Datenschutzerklaerung-WELT-DIGITAL.html

We are recording our next big recap episode and taking questions! Submit questions and messages on Speakpipe here for a chance to appear on the show!Also subscribe to our calendar for our Singapore, NeurIPS, and all upcoming meetups!In our first ever episode with Logan Kilpatrick we called out the two hottest LLM frameworks at the time: LangChain and Dust. We've had Harrison from LangChain on twice (as a guest and as a co-host), and we've now finally come full circle as Stanislas from Dust joined us in the studio.After stints at Oracle and Stripe, Stan had joined OpenAI to work on mathematical reasoning capabilities. He describes his time at OpenAI as "the PhD I always wanted to do" while acknowledging the challenges of research work: "You're digging into a field all day long for weeks and weeks, and you find something, you get super excited for 12 seconds. And at the 13 seconds, you're like, 'oh, yeah, that was obvious.' And you go back to digging." This experience, combined with early access to GPT-4's capabilities, shaped his decision to start Dust: "If we believe in AGI and if we believe the timelines might not be too long, it's actually the last train leaving the station to start a company. After that, it's going to be computers all the way down."The History of DustDust's journey can be broken down into three phases:* Developer Framework (2022): Initially positioned as a competitor to LangChain, Dust started as a developer tooling platform. While both were open source, their approaches differed – LangChain focused on broad community adoption and integration as a pure developer experience, while Dust emphasized UI-driven development and better observability that wasn't just `print` statements.* Browser Extension (Early 2023): The company pivoted to building XP1, a browser extension that could interact with web content. This experiment helped validate user interaction patterns with AI, even while using less capable models than GPT-4.* Enterprise Platform (Current): Today, Dust has evolved into an infrastructure platform for deploying AI agents within companies, with impressive metrics like 88% daily active users in some deployments.The Case for Being HorizontalThe big discussion for early stage companies today is whether or not to be horizontal or vertical. Since models are so good at general tasks, a lot of companies are building vertical products that take care of a workflow end-to-end in order to offer more value and becoming more of “Services as Software”. Dust on the other hand is a platform for the users to build their own experiences, which has had a few advantages:* Maximum Penetration: Dust reports 60-70% weekly active users across entire companies, demonstrating the potential reach of horizontal solutions rather than selling into a single team.* Emergent Use Cases: By allowing non-technical users to create agents, Dust enables use cases to emerge organically from actual business needs rather than prescribed solutions.* Infrastructure Value: The platform approach creates lasting value through maintained integrations and connections, similar to how Stripe's value lies in maintaining payment infrastructure. Rather than relying on third-party integration providers, Dust maintains its own connections to ensure proper handling of different data types and structures.The Vertical ChallengeHowever, this approach comes with trade-offs:* Harder Go-to-Market: As Stan talked about: "We spike at penetration... but it makes our go-to-market much harder. Vertical solutions have a go-to-market that is much easier because they're like, 'oh, I'm going to solve the lawyer stuff.'"* Complex Infrastructure: Building a horizontal platform requires maintaining numerous integrations and handling diverse data types appropriately – from structured Salesforce data to unstructured Notion pages. As you scale integrations, the cost of maintaining them also scales. * Product Surface Complexity: Creating an interface that's both powerful and accessible to non-technical users requires careful design decisions, down to avoiding technical terms like "system prompt" in favor of "instructions." The Future of AI PlatformsStan initially predicted we'd see the first billion-dollar single-person company in 2023 (a prediction later echoed by Sam Altman), but he's now more focused on a different milestone: billion-dollar companies with engineering teams of just 20 people, enabled by AI assistance.This vision aligns with Dust's horizontal platform approach – building the infrastructure that allows small teams to achieve outsized impact through AI augmentation. Rather than replacing entire job functions (the vertical approach), they're betting on augmenting existing workflows across organizations.Full YouTube EpisodeChapters* 00:00:00 Introductions* 00:04:33 Joining OpenAI from Paris* 00:09:54 Research evolution and compute allocation at OpenAI* 00:13:12 Working with Ilya Sutskever and OpenAI's vision* 00:15:51 Leaving OpenAI to start Dust* 00:18:15 Early focus on browser extension and WebGPT-like functionality* 00:20:20 Dust as the infrastructure for agents* 00:24:03 Challenges of building with early AI models* 00:28:17 LLMs and Workflow Automation* 00:35:28 Building dependency graphs of agents* 00:37:34 Simulating API endpoints* 00:40:41 State of AI models* 00:43:19 Running evals* 00:46:36 Challenges in building AI agents infra* 00:49:21 Buy vs. build decisions for infrastructure components* 00:51:02 Future of SaaS and AI's Impact on Software* 00:53:07 The single employee $1B company race* 00:56:32 Horizontal vs. vertical approaches to AI agentsTranscriptAlessio [00:00:00]: Hey everyone, welcome to the Latent Space podcast. This is Alessio, partner and CTO at Decibel Partners, and I'm joined by my co-host Swyx, founder of Smol.ai.Swyx [00:00:11]: Hey, and today we're in a studio with Stanislas, welcome.Stan [00:00:14]: Thank you very much for having me.Swyx [00:00:16]: Visiting from Paris.Stan [00:00:17]: Paris.Swyx [00:00:18]: And you have had a very distinguished career. It's very hard to summarize, but you went to college in both Ecopolytechnique and Stanford, and then you worked in a number of places, Oracle, Totems, Stripe, and then OpenAI pre-ChatGPT. We'll talk, we'll spend a little bit of time about that. About two years ago, you left OpenAI to start Dust. I think you were one of the first OpenAI alum founders.Stan [00:00:40]: Yeah, I think it was about at the same time as the Adept guys, so that first wave.Swyx [00:00:46]: Yeah, and people really loved our David episode. We love a few sort of OpenAI stories, you know, for back in the day, like we're talking about pre-recording. Probably the statute of limitations on some of those stories has expired, so you can talk a little bit more freely without them coming after you. But maybe we'll just talk about, like, what was your journey into AI? You know, you were at Stripe for almost five years, there are a lot of Stripe alums going into OpenAI. I think the Stripe culture has come into OpenAI quite a bit.Stan [00:01:11]: Yeah, so I think the buses of Stripe people really started flowing in, I guess, after ChatGPT. But, yeah, my journey into AI is a... I mean, Greg Brockman. Yeah, yeah. From Greg, of course. And Daniela, actually, back in the days, Daniela Amodei.Swyx [00:01:27]: Yes, she was COO, I mean, she is COO, yeah. She had a pretty high job at OpenAI at the time, yeah, for sure.Stan [00:01:34]: My journey started as anybody else, you're fascinated with computer science and you want to make them think, it's awesome, but it doesn't work. I mean, it was a long time ago, it was like maybe 16, so it was 25 years ago. Then the first big exposure to AI would be at Stanford, and I'm going to, like, disclose a whole lamb, because at the time it was a class taught by Andrew Ng, and there was no deep learning. It was half features for vision and a star algorithm. So it was fun. But it was the early days of deep learning. At the time, I think a few years after, it was the first project at Google. But you know, that cat face or the human face trained from many images. I went to, hesitated doing a PhD, more in systems, eventually decided to go into getting a job. Went at Oracle, started a company, did a gazillion mistakes, got acquired by Stripe, worked with Greg Buckman there. And at the end of Stripe, I started interesting myself in AI again, felt like it was the time, you had the Atari games, you had the self-driving craziness at the time. And I started exploring projects, it felt like the Atari games were incredible, but there were still games. And I was looking into exploring projects that would have an impact on the world. And so I decided to explore three things, self-driving cars, cybersecurity and AI, and math and AI. It's like I sing it by a decreasing order of impact on the world, I guess.Swyx [00:03:01]: Discovering new math would be very foundational.Stan [00:03:03]: It is extremely foundational, but it's not as direct as driving people around.Swyx [00:03:07]: Sorry, you're doing this at Stripe, you're like thinking about your next move.Stan [00:03:09]: No, it was at Stripe, kind of a bit of time where I started exploring. I did a bunch of work with friends on trying to get RC cars to drive autonomously. Almost started a company in France or Europe about self-driving trucks. We decided to not go for it because it was probably very operational. And I think the idea of the company, of the team wasn't there. And also I realized that if I wake up a day and because of a bug I wrote, I killed a family, it would be a bad experience. And so I just decided like, no, that's just too crazy. And then I explored cybersecurity with a friend. We're trying to apply transformers to cut fuzzing. So cut fuzzing, you have kind of an algorithm that goes really fast and tries to mutate the inputs of a library to find bugs. And we tried to apply a transformer to that and do reinforcement learning with the signal of how much you propagate within the binary. Didn't work at all because the transformers are so slow compared to evolutionary algorithms that it kind of didn't work. Then I started interested in math and AI and started working on SAT solving with AI. And at the same time, OpenAI was kind of starting the reasoning team that were tackling that project as well. I was in touch with Greg and eventually got in touch with Ilya and finally found my way to OpenAI. I don't know how much you want to dig into that. The way to find your way to OpenAI when you're in Paris was kind of an interesting adventure as well.Swyx [00:04:33]: Please. And I want to note, this was a two-month journey. You did all this in two months.Stan [00:04:38]: The search.Swyx [00:04:40]: Your search for your next thing, because you left in July 2019 and then you joined OpenAI in September.Stan [00:04:45]: I'm going to be ashamed to say that.Swyx [00:04:47]: You were searching before. I was searching before.Stan [00:04:49]: I mean, it's normal. No, the truth is that I moved back to Paris through Stripe and I just felt the hardship of being remote from your team nine hours away. And so it kind of freed a bit of time for me to start the exploration before. Sorry, Patrick. Sorry, John.Swyx [00:05:05]: Hopefully they're listening. So you joined OpenAI from Paris and from like, obviously you had worked with Greg, but notStan [00:05:13]: anyone else. No. Yeah. So I had worked with Greg, but not Ilya, but I had started chatting with Ilya and Ilya was kind of excited because he knew that I was a good engineer through Greg, I presume, but I was not a trained researcher, didn't do a PhD, never did research. And I started chatting and he was excited all the way to the point where he was like, hey, come pass interviews, it's going to be fun. I think he didn't care where I was, he just wanted to try working together. So I go to SF, go through the interview process, get an offer. And so I get Bob McGrew on the phone for the first time, he's like, hey, Stan, it's awesome. You've got an offer. When are you coming to SF? I'm like, hey, it's awesome. I'm not coming to the SF. I'm based in Paris and we just moved. He was like, hey, it's awesome. Well, you don't have an offer anymore. Oh, my God. No, it wasn't as hard as that. But that's basically the idea. And it took me like maybe a couple more time to keep chatting and they eventually decided to try a contractor set up. And that's how I kind of started working at OpenAI, officially as a contractor, but in practice really felt like being an employee.Swyx [00:06:14]: What did you work on?Stan [00:06:15]: So it was solely focused on math and AI. And in particular in the application, so the study of the larger grid models, mathematical reasoning capabilities, and in particular in the context of formal mathematics. The motivation was simple, transformers are very creative, but yet they do mistakes. Formal math systems are of the ability to verify a proof and the tactics they can use to solve problems are very mechanical, so you miss the creativity. And so the idea was to try to explore both together. You would get the creativity of the LLMs and the kind of verification capabilities of the formal system. A formal system, just to give a little bit of context, is a system in which a proof is a program and the formal system is a type system, a type system that is so evolved that you can verify the program. If the type checks, it means that the program is correct.Swyx [00:07:06]: Is the verification much faster than actually executing the program?Stan [00:07:12]: Verification is instantaneous, basically. So the truth is that what you code in involves tactics that may involve computation to search for solutions. So it's not instantaneous. You do have to do the computation to expand the tactics into the actual proof. The verification of the proof at the very low level is instantaneous.Swyx [00:07:32]: How quickly do you run into like, you know, halting problem PNP type things, like impossibilities where you're just like that?Stan [00:07:39]: I mean, you don't run into it at the time. It was really trying to solve very easy problems. So I think the... Can you give an example of easy? Yeah, so that's the mass benchmark that everybody knows today. The Dan Hendricks one. The Dan Hendricks one, yeah. And I think it was the low end part of the mass benchmark at the time, because that mass benchmark includes AMC problems, AMC 8, AMC 10, 12. So these are the easy ones. Then AIME problems, somewhat harder, and some IMO problems, like Crazy Arm.Swyx [00:08:07]: For our listeners, we covered this in our Benchmarks 101 episode. AMC is literally the grade of like high school, grade 8, grade 10, grade 12. So you can solve this. Just briefly to mention this, because I don't think we'll touch on this again. There's a bit of work with like Lean, and then with, you know, more recently with DeepMind doing like scoring like silver on the IMO. Any commentary on like how math has evolved from your early work to today?Stan [00:08:34]: I mean, that result is mind blowing. I mean, from my perspective, spent three years on that. At the same time, Guillaume Lampe in Paris, we were both in Paris, actually. He was at FAIR, was working on some problems. We were pushing the boundaries, and the goal was the IMO. And we cracked a few problems here and there. But the idea of getting a medal at an IMO was like just remote. So this is an impressive result. And we can, I think the DeepMind team just did a good job of scaling. I think there's nothing too magical in their approach, even if it hasn't been published. There's a Dan Silver talk from seven days ago where it goes a little bit into more details. It feels like there's nothing magical there. It's really applying reinforcement learning and scaling up the amount of data that can generate through autoformalization. So we can dig into what autoformalization means if you want.Alessio [00:09:26]: Let's talk about the tail end, maybe, of the OpenAI. So you joined, and you're like, I'm going to work on math and do all of these things. I saw on one of your blog posts, you mentioned you fine-tuned over 10,000 models at OpenAI using 10 million A100 hours. How did the research evolve from the GPD 2, and then getting closer to DaVinci 003? And then you left just before ChatGPD was released, but tell people a bit more about the research path that took you there.Stan [00:09:54]: I can give you my perspective of it. I think at OpenAI, there's always been a large chunk of the compute that was reserved to train the GPTs, which makes sense. So it was pre-entropic splits. Most of the compute was going to a product called Nest, which was basically GPT-3. And then you had a bunch of, let's say, remote, not core research teams that were trying to explore maybe more specific problems or maybe the algorithm part of it. The interesting part, I don't know if it was where your question was going, is that in those labs, you're managing researchers. So by definition, you shouldn't be managing them. But in that space, there's a managing tool that is great, which is compute allocation. Basically by managing the compute allocation, you can message the team of where you think the priority should go. And so it was really a question of, you were free as a researcher to work on whatever you wanted. But if it was not aligned with OpenAI mission, and that's fair, you wouldn't get the compute allocation. As it happens, solving math was very much aligned with the direction of OpenAI. And so I was lucky to generally get the compute I needed to make good progress.Swyx [00:11:06]: What do you need to show as incremental results to get funded for further results?Stan [00:11:12]: It's an imperfect process because there's a bit of a... If you're working on math and AI, obviously there's kind of a prior that it's going to be aligned with the company. So it's much easier than to go into something much more risky, much riskier, I guess. You have to show incremental progress, I guess. It's like you ask for a certain amount of compute and you deliver a few weeks after and you demonstrate that you have a progress. Progress might be a positive result. Progress might be a strong negative result. And a strong negative result is actually often much harder to get or much more interesting than a positive result. And then it generally goes into, as any organization, you would have people finding your project or any other project cool and fancy. And so you would have that kind of phase of growing up compute allocation for it all the way to a point. And then maybe you reach an apex and then maybe you go back mostly to zero and restart the process because you're going in a different direction or something else. That's how I felt. Explore, exploit. Yeah, exactly. Exactly. Exactly. It's a reinforcement learning approach.Swyx [00:12:14]: Classic PhD student search process.Alessio [00:12:17]: And you were reporting to Ilya, like the results you were kind of bringing back to him or like what's the structure? It's almost like when you're doing such cutting edge research, you need to report to somebody who is actually really smart to understand that the direction is right.Stan [00:12:29]: So we had a reasoning team, which was working on reasoning, obviously, and so math in general. And that team had a manager, but Ilya was extremely involved in the team as an advisor, I guess. Since he brought me in OpenAI, I was lucky to mostly during the first years to have kind of a direct access to him. He would really coach me as a trainee researcher, I guess, with good engineering skills. And Ilya, I think at OpenAI, he was the one showing the North Star, right? He was his job and I think he really enjoyed it and he did it super well, was going through the teams and saying, this is where we should be going and trying to, you know, flock the different teams together towards an objective.Swyx [00:13:12]: I would say like the public perception of him is that he was the strongest believer in scaling. Oh, yeah. Obviously, he has always pursued the compression thesis. You have worked with him personally, what does the public not know about how he works?Stan [00:13:26]: I think he's really focused on building the vision and communicating the vision within the company, which was extremely useful. I was personally surprised that he spent so much time, you know, working on communicating that vision and getting the teams to work together versus...Swyx [00:13:40]: To be specific, vision is AGI? Oh, yeah.Stan [00:13:42]: Vision is like, yeah, it's the belief in compression and scanning computes. I remember when I started working on the Reasoning team, the excitement was really about scaling the compute around Reasoning and that was really the belief we wanted to ingrain in the team. And that's what has been useful to the team and with the DeepMind results shows that it was the right approach with the success of GPT-4 and stuff shows that it was the right approach.Swyx [00:14:06]: Was it according to the neural scaling laws, the Kaplan paper that was published?Stan [00:14:12]: I think it was before that, because those ones came with GPT-3, basically at the time of GPT-3 being released or being ready internally. But before that, there really was a strong belief in scale. I think it was just the belief that the transformer was a generic enough architecture that you could learn anything. And that was just a question of scaling.Alessio [00:14:33]: Any other fun stories you want to tell? Sam Altman, Greg, you know, anything.Stan [00:14:37]: Weirdly, I didn't work that much with Greg when I was at OpenAI. He had always been mostly focused on training the GPTs and rightfully so. One thing about Sam Altman, he really impressed me because when I joined, he had joined not that long ago and it felt like he was kind of a very high level CEO. And I was mind blown by how deep he was able to go into the subjects within a year or something, all the way to a situation where when I was having lunch by year two, I was at OpenAI with him. He would just quite know deeply what I was doing. With no ML background. Yeah, with no ML background, but I didn't have any either, so I guess that explains why. But I think it's a question about, you don't necessarily need to understand the very technicalities of how things are done, but you need to understand what's the goal and what's being done and what are the recent results and all of that in you. And we could have kind of a very productive discussion. And that really impressed me, given the size at the time of OpenAI, which was not negligible.Swyx [00:15:44]: Yeah. I mean, you've been a, you were a founder before, you're a founder now, and you've seen Sam as a founder. How has he affected you as a founder?Stan [00:15:51]: I think having that capability of changing the scale of your attention in the company, because most of the time you operate at a very high level, but being able to go deep down and being in the known of what's happening on the ground is something that I feel is really enlightening. That's not a place in which I ever was as a founder, because first company, we went all the way to 10 people. Current company, there's 25 of us. So the high level, the sky and the ground are pretty much at the same place. No, you're being too humble.Swyx [00:16:21]: I mean, Stripe was also like a huge rocket ship.Stan [00:16:23]: Stripe, I was a founder. So I was, like at OpenAI, I was really happy being on the ground, pushing the machine, making it work. Yeah.Swyx [00:16:31]: Last OpenAI question. The Anthropic split you mentioned, you were around for that. Very dramatic. David also left around that time, you left. This year, we've also had a similar management shakeup, let's just call it. Can you compare what it was like going through that split during that time? And then like, does that have any similarities now? Like, are we going to see a new Anthropic emerge from these folks that just left?Stan [00:16:54]: That I really, really don't know. At the time, the split was pretty surprising because they had been trying GPT-3, it was a success. And to be completely transparent, I wasn't in the weeds of the splits. What I understood of it is that there was a disagreement of the commercialization of that technology. I think the focal point of that disagreement was the fact that we started working on the API and wanted to make those models available through an API. Is that really the core disagreement? I don't know.Swyx [00:17:25]: Was it safety?Stan [00:17:26]: Was it commercialization?Swyx [00:17:27]: Or did they just want to start a company?Stan [00:17:28]: Exactly. Exactly. That I don't know. But I think what I was surprised of is how quickly OpenAI recovered at the time. And I think it's just because we were mostly a research org and the mission was so clear that some divergence in some teams, some people leave, the mission is still there. We have the compute. We have a site. So it just keeps going.Swyx [00:17:50]: Very deep bench. Like just a lot of talent. Yeah.Alessio [00:17:53]: So that was the OpenAI part of the history. Exactly. So then you leave OpenAI in September 2022. And I would say in Silicon Valley, the two hottest companies at the time were you and Lanktrain. What was that start like and why did you decide to start with a more developer focused kind of like an AI engineer tool rather than going back into some more research and something else?Stan [00:18:15]: Yeah. First, I'm not a trained researcher. So going through OpenAI was really kind of the PhD I always wanted to do. But research is hard. You're digging into a field all day long for weeks and weeks and weeks, and you find something, you get super excited for 12 seconds. And at the 13 seconds, you're like, oh, yeah, that was obvious. And you go back to digging. I'm not a trained, like formally trained researcher, and it wasn't kind of a necessarily an ambition of me of creating, of having a research career. And I felt the hardness of it. I enjoyed a lot of like that a ton. But at the time, I decided that I wanted to go back to something more productive. And the other fun motivation was like, I mean, if we believe in AGI and if we believe the timelines might not be too long, it's actually the last train leaving the station to start a company. After that, it's going to be computers all the way down. And so that was kind of the true motivation for like trying to go there. So that's kind of the core motivation at the beginning of personally. And the motivation for starting a company was pretty simple. I had seen GPT-4 internally at the time, it was September 2022. So it was pre-GPT, but GPT-4 was ready since, I mean, I'd been ready for a few months internally. I was like, okay, that's obvious, the capabilities are there to create an insane amount of value to the world. And yet the deployment is not there yet. The revenue of OpenAI at the time were ridiculously small compared to what it is today. So the thesis was, there's probably a lot to be done at the product level to unlock the usage.Alessio [00:19:49]: Yeah. Let's talk a bit more about the form factor, maybe. I think one of the first successes you had was kind of like the WebGPT-like thing, like using the models to traverse the web and like summarize things. And the browser was really the interface. Why did you start with the browser? Like what was it important? And then you built XP1, which was kind of like the browser extension.Stan [00:20:09]: So the starting point at the time was, if you wanted to talk about LLMs, it was still a rather small community, a community of mostly researchers and to some extent, very early adopters, very early engineers. It was almost inconceivable to just build a product and go sell it to the enterprise, though at the time there was a few companies doing that. The one on marketing, I don't remember its name, Jasper. But so the natural first intention, the first, first, first intention was to go to the developers and try to create tooling for them to create product on top of those models. And so that's what Dust was originally. It was quite different than Lanchain, and Lanchain just beat the s**t out of us, which is great. It's a choice.Swyx [00:20:53]: You were cloud, in closed source. They were open source.Stan [00:20:56]: Yeah. So technically we were open source and we still are open source, but I think that doesn't really matter. I had the strong belief from my research time that you cannot create an LLM-based workflow on just one example. Basically, if you just have one example, you overfit. So as you develop your interaction, your orchestration around the LLM, you need a dozen examples. Obviously, if you're running a dozen examples on a multi-step workflow, you start paralyzing stuff. And if you do that in the console, you just have like a messy stream of tokens going out and it's very hard to observe what's going there. And so the idea was to go with an UI so that you could kind of introspect easily the output of each interaction with the model and dig into there through an UI, which is-Swyx [00:21:42]: Was that open source? I actually didn't come across it.Stan [00:21:44]: Oh yeah, it wasn't. I mean, Dust is entirely open source even today. We're not going for an open source-Swyx [00:21:48]: If it matters, I didn't know that.Stan [00:21:49]: No, no, no, no, no. The reason why is because we're not open source because we're not doing an open source strategy. It's not an open source go-to-market at all. We're open source because we can and it's fun.Swyx [00:21:59]: Open source is marketing. You have all the downsides of open source, which is like people can clone you.Stan [00:22:03]: But I think that downside is a big fallacy. Okay. Yes, anybody can clone Dust today, but the value of Dust is not the current state. The value of Dust is the number of eyeballs and hands of developers that are creating to it in the future. And so yes, anybody can clone it today, but that wouldn't change anything. There is some value in being open source. In a discussion with the security team, you can be extremely transparent and just show the code. When you have discussion with users and there's a bug or a feature missing, you can just point to the issue, show the pull request, show the, show the, exactly, oh, PR welcome. That doesn't happen that much, but you can show the progress if the person that you're chatting with is a little bit technical, they really enjoy seeing the pull request advancing and seeing all the way to deploy. And then the downsides are mostly around security. You never want to do security by obfuscation. But the truth is that your vector of attack is facilitated by you being open source. But at the same time, it's a good thing because if you're doing anything like a bug bountying or stuff like that, you just give much more tools to the bug bountiers so that their output is much better. So there's many, many, many trade-offs. I don't believe in the value of the code base per se. I think it's really the people that are on the code base that have the value and go to market and the product and all of those things that are around the code base. Obviously, that's not true for every code base. If you're working on a very secret kernel to accelerate the inference of LLMs, I would buy that you don't want to be open source. But for product stuff, I really think there's very little risk. Yeah.Alessio [00:23:39]: I signed up for XP1, I was looking, January 2023. I think at the time you were on DaVinci 003. Given that you had seen GPD 4, how did you feel having to push a product out that was using this model that was so inferior? And you're like, please, just use it today. I promise it's going to get better. Just overall, as a founder, how do you build something that maybe doesn't quite work with the model today, but you're just expecting the new model to be better?Stan [00:24:03]: Yeah, so actually, XP1 was even on a smaller one that was the post-GDPT release, small version, so it was... Ada, Babbage... No, no, no, not that far away. But it was the small version of GDPT, basically. I don't remember its name. Yes, you have a frustration there. But at the same time, I think XP1 was designed, was an experiment, but was designed as a way to be useful at the current capability of the model. If you just want to extract data from a LinkedIn page, that model was just fine. If you want to summarize an article on a newspaper, that model was just fine. And so it was really a question of trying to find a product that works with the current capability, knowing that you will always have tailwinds as models get better and faster and cheaper. So that was kind of a... There's a bit of a frustration because you know what's out there and you know that you don't have access to it yet. It's also interesting to try to find a product that works with the current capability.Alessio [00:24:55]: And we highlighted XP1 in our anatomy of autonomy post in April of last year, which was, you know, where are all the agents, right? So now we spent 30 minutes getting to what you're building now. So you basically had a developer framework, then you had a browser extension, then you had all these things, and then you kind of got to where Dust is today. So maybe just give people an overview of what Dust is today and the courtesies behind it. Yeah, of course.Stan [00:25:20]: So Dust, we really want to build the infrastructure so that companies can deploy agents within their teams. We are horizontal by nature because we strongly believe in the emergence of use cases from the people having access to creating an agent that don't need to be developers. They have to be thinkers. They have to be curious. But anybody can create an agent that will solve an operational thing that they're doing in their day-to-day job. And to make those agents useful, there's two focus, which is interesting. The first one is an infrastructure focus. You have to build the pipes so that the agent has access to the data. You have to build the pipes such that the agents can take action, can access the web, et cetera. So that's really an infrastructure play. Maintaining connections to Notion, Slack, GitHub, all of them is a lot of work. It is boring work, boring infrastructure work, but that's something that we know is extremely valuable in the same way that Stripe is extremely valuable because it maintains the pipes. And we have that dual focus because we're also building the product for people to use it. And there it's fascinating because everything started from the conversational interface, obviously, which is a great starting point. But we're only scratching the surface, right? I think we are at the pong level of LLM productization. And we haven't invented the C3. We haven't invented Counter-Strike. We haven't invented Cyberpunk 2077. So this is really our mission is to really create the product that lets people equip themselves to just get away all the work that can be automated or assisted by LLMs.Alessio [00:26:57]: And can you just comment on different takes that people had? So maybe the most open is like auto-GPT. It's just kind of like just trying to do anything. It's like it's all magic. There's no way for you to do anything. Then you had the ADAPT, you know, we had David on the podcast. They're very like super hands-on with each individual customer to build super tailored. How do you decide where to draw the line between this is magic? This is exposed to you, especially in a market where most people don't know how to build with AI at all. So if you expect them to do the thing, they're probably not going to do it. Yeah, exactly.Stan [00:27:29]: So the auto-GPT approach obviously is extremely exciting, but we know that the agentic capability of models are not quite there yet. It just gets lost. So we're starting, we're starting where it works. Same with the XP one. And where it works is pretty simple. It's like simple workflows that involve a couple tools where you don't even need to have the model decide which tools it's used in the sense of you just want people to put it in the instructions. It's like take that page, do that search, pick up that document, do the work that I want in the format I want, and give me the results. There's no smartness there, right? In terms of orchestrating the tools, it's mostly using English for people to program a workflow where you don't have the constraint of having compatible API between the two.Swyx [00:28:17]: That kind of personal automation, would you say it's kind of like an LLM Zapier type ofStan [00:28:22]: thing?Swyx [00:28:22]: Like if this, then that, and then, you know, do this, then this. You're programming with English?Stan [00:28:28]: So you're programming with English. So you're just saying, oh, do this and then that. You can even create some form of APIs. You say, when I give you the command X, do this. When I give you the command Y, do this. And you describe the workflow. But you don't have to create boxes and create the workflow explicitly. It just needs to describe what are the tasks supposed to be and make the tool available to the agent. The tool can be a semantic search. The tool can be querying into a structured database. The tool can be searching on the web. And obviously, the interesting tools that we're only starting to scratch are actually creating external actions like reimbursing something on Stripe, sending an email, clicking on a button in the admin or something like that.Swyx [00:29:11]: Do you maintain all these integrations?Stan [00:29:13]: Today, we maintain most of the integrations. We do always have an escape hatch for people to kind of custom integrate. But the reality is that the reality of the market today is that people just want it to work, right? And so it's mostly us maintaining the integration. As an example, a very good source of information that is tricky to productize is Salesforce. Because Salesforce is basically a database and a UI. And they do the f**k they want with it. And so every company has different models and stuff like that. So right now, we don't support it natively. And the type of support or real native support will be slightly more complex than just osing into it, like is the case with Slack as an example. Because it's probably going to be, oh, you want to connect your Salesforce to us? Give us the SQL. That's the Salesforce QL language. Give us the queries you want us to run on it and inject in the context of dust. So that's interesting how not only integrations are cool, and some of them require a bit of work on the user. And for some of them that are really valuable to our users, but we don't support yet, they can just build them internally and push the data to us.Swyx [00:30:18]: I think I understand the Salesforce thing. But let me just clarify, are you using browser automation because there's no API for something?Stan [00:30:24]: No, no, no, no. In that case, so we do have browser automation for all the use cases and apply the public web. But for most of the integration with the internal system of the company, it really runs through API.Swyx [00:30:35]: Haven't you felt the pull to RPA, browser automation, that kind of stuff?Stan [00:30:39]: I mean, what I've been saying for a long time, maybe I'm wrong, is that if the future is that you're going to stand in front of a computer and looking at an agent clicking on stuff, then I'll hit my computer. And my computer is a big Lenovo. It's black. Doesn't sound good at all compared to a Mac. And if the APIs are there, we should use them. There is going to be a long tail of stuff that don't have APIs, but as the world is moving forward, that's disappearing. So the core API value in the past has really been, oh, this old 90s product doesn't have an API. So I need to use the UI to automate. I think for most of the ICP companies, the companies that ICP for us, the scale ups that are between 500 and 5,000 people, tech companies, most of the SaaS they use have APIs. Now there's an interesting question for the open web, because there are stuff that you want to do that involve websites that don't necessarily have APIs. And the current state of web integration from, which is us and OpenAI and Anthropic, I don't even know if they have web navigation, but I don't think so. The current state of affair is really, really broken because you have what? You have basically search and headless browsing. But headless browsing, I think everybody's doing basically body.innertext and fill that into the model, right?Swyx [00:31:56]: MARK MIRCHANDANI There's parsers into Markdown and stuff.Stan [00:31:58]: FRANCESC CAMPOY I'm super excited by the companies that are exploring the capability of rendering a web page into a way that is compatible for a model, being able to maintain the selector. So that's basically the place where to click in the page through that process, expose the actions to the model, have the model select an action in a way that is compatible with model, which is not a big page of a full DOM that is very noisy, and then being able to decompress that back to the original page and take the action. And that's something that is really exciting and that will kind of change the level of things that agents can do on the web. That I feel exciting, but I also feel that the bulk of the useful stuff that you can do within the company can be done through API. The data can be retrieved by API. The actions can be taken through API.Swyx [00:32:44]: For listeners, I'll note that you're basically completely disagreeing with David Wan. FRANCESC CAMPOY Exactly, exactly. I've seen it since it's summer. ADEPT is where it is, and Dust is where it is. So Dust is still standing.Alessio [00:32:55]: Can we just quickly comment on function calling? You mentioned you don't need the models to be that smart to actually pick the tools. Have you seen the models not be good enough? Or is it just like, you just don't want to put the complexity in there? Like, is there any room for improvement left in function calling? Or do you feel you usually consistently get always the right response, the right parametersStan [00:33:13]: and all of that?Alessio [00:33:13]: FRANCESC CAMPOY So that's a tricky product question.Stan [00:33:15]: Because if the instructions are good and precise, then you don't have any issue, because it's scripted for you. And the model will just look at the scripts and just follow and say, oh, he's probably talking about that action, and I'm going to use it. And the parameters are kind of abused from the state of the conversation. I'll just go with it. If you provide a very high level, kind of an auto-GPT-esque level in the instructions and provide 16 different tools to your model, yes, we're seeing the models in that state making mistakes. And there is obviously some progress can be made on the capabilities. But the interesting part is that there is already so much work that can assist, augment, accelerate by just going with pretty simply scripted for actions agents. What I'm excited about by pushing our users to create rather simple agents is that once you have those working really well, you can create meta agents that use the agents as actions. And all of a sudden, you can kind of have a hierarchy of responsibility that will probably get you almost to the point of the auto-GPT value. It requires the construction of intermediary artifacts, but you're probably going to be able to achieve something great. I'll give you some example. We have our incidents are shared in Slack in a specific channel, or shipped are shared in Slack. We have a weekly meeting where we have a table about incidents and shipped stuff. We're not writing that weekly meeting table anymore. We have an assistant that just go find the right data on Slack and create the table for us. And that assistant works perfectly. It's trivially simple, right? Take one week of data from that channel and just create the table. And then we have in that weekly meeting, obviously some graphs and reporting about our financials and our progress and our ARR. And we've created assistants to generate those graphs directly. And those assistants works great. By creating those assistants that cover those small parts of that weekly meeting, slowly we're getting to in a world where we'll have a weekly meeting assistance. We'll just call it. You don't need to prompt it. You don't need to say anything. It's going to run those different assistants and get that notion page just ready. And by doing that, if you get there, and that's an objective for us to us using Dust, get there, you're saving an hour of company time every time you run it. Yeah.Alessio [00:35:28]: That's my pet topic of NPM for agents. How do you build dependency graphs of agents? And how do you share them? Because why do I have to rebuild some of the smaller levels of what you built already?Swyx [00:35:40]: I have a quick follow-up question on agents managing other agents. It's a topic of a lot of research, both from Microsoft and even in startups. What you've discovered best practice for, let's say like a manager agent controlling a bunch of small agents. It's two-way communication. I don't know if there should be a protocol format.Stan [00:35:59]: To be completely honest, the state we are at right now is creating the simple agents. So we haven't even explored yet the meta agents. We know it's there. We know it's going to be valuable. We know it's going to be awesome. But we're starting there because it's the simplest place to start. And it's also what the market understands. If you go to a company, random SaaS B2B company, not necessarily specialized in AI, and you take an operational team and you tell them, build some tooling for yourself, they'll understand the small agents. If you tell them, build AutoGP, they'll be like, Auto what?Swyx [00:36:31]: And I noticed that in your language, you're very much focused on non-technical users. You don't really mention API here. You mention instruction instead of system prompt, right? That's very conscious.Stan [00:36:41]: Yeah, it's very conscious. It's a mark of our designer, Ed, who kind of pushed us to create a friendly product. I was knee-deep into AI when I started, obviously. And my co-founder, Gabriel, was a Stripe as well. We started a company together that got acquired by Stripe 15 years ago. It was at Alain, a healthcare company in Paris. After that, it was a little bit less so knee-deep in AI, but really focused on product. And I didn't realize how important it is to make that technology not scary to end users. It didn't feel scary to me, but it was really seen by Ed, our designer, that it was feeling scary to the users. And so we were very proactive and very deliberate about creating a brand that feels not too scary and creating a wording and a language, as you say, that really tried to communicate the fact that it's going to be fine. It's going to be easy. You're going to make it.Alessio [00:37:34]: And another big point that David had about ADAPT is we need to build an environment for the agents to act. And then if you have the environment, you can simulate what they do. How's that different when you're interacting with APIs and you're kind of touching systems that you cannot really simulate? If you call it the Salesforce API, you're just calling it.Stan [00:37:52]: So I think that goes back to the DNA of the companies that are very different. ADAPT, I think, was a product company with a very strong research DNA, and they were still doing research. One of their goals was building a model. And that's why they raised a large amount of money, et cetera. We are 100% deliberately a product company. We don't do research. We don't train models. We don't even run GPUs. We're using the models that exist, and we try to push the product boundary as far as possible with the existing models. So that creates an issue. Indeed, so to answer your question, when you're interacting in the real world, well, you cannot simulate, so you cannot improve the models. Even improving your instructions is complicated for a builder. The hope is that you can use models to evaluate the conversations so that you can get at least feedback and you could get contradictive information about the performance of the assistance. But if you take actual trace of interaction of humans with those agents, it is even for us humans extremely hard to decide whether it was a productive interaction or a really bad interaction. You don't know why the person left. You don't know if they left happy or not. So being extremely, extremely, extremely pragmatic here, it becomes a product issue. We have to build a product that identifies the end users to provide feedback so that as a first step, the person that is building the agent can iterate on it. As a second step, maybe later when we start training model and post-training, et cetera, we can optimize around that for each of those companies. Yeah.Alessio [00:39:17]: Do you see in the future products offering kind of like a simulation environment, the same way all SaaS now kind of offers APIs to build programmatically? Like in cybersecurity, there are a lot of companies working on building simulative environments so that then you can use agents like Red Team, but I haven't really seen that.Stan [00:39:34]: Yeah, no, me neither. That's a super interesting question. I think it's really going to depend on how much, because you need to simulate to generate data, you need to train data to train models. And the question at the end is, are we going to be training models or are we just going to be using frontier models as they are? On that question, I don't have a strong opinion. It might be the case that we'll be training models because in all of those AI first products, the model is so close to the product surface that as you get big and you want to really own your product, you're going to have to own the model as well. Owning the model doesn't mean doing the pre-training, that would be crazy. But at least having an internal post-training realignment loop, it makes a lot of sense. And so if we see many companies going towards that all the time, then there might be incentives for the SaaS's of the world to provide assistance in getting there. But at the same time, there's a tension because those SaaS, they don't want to be interacted by agents, they want the human to click on the button. Yeah, they got to sell seats. Exactly.Swyx [00:40:41]: Just a quick question on models. I'm sure you've used many, probably not just OpenAI. Would you characterize some models as better than others? Do you use any open source models? What have been the trends in models over the last two years?Stan [00:40:53]: We've seen over the past two years kind of a bit of a race in between models. And at times, it's the OpenAI model that is the best. At times, it's the Anthropic models that is the best. Our take on that is that we are agnostic and we let our users pick their model. Oh, they choose? Yeah, so when you create an assistant or an agent, you can just say, oh, I'm going to run it on GP4, GP4 Turbo, or...Swyx [00:41:16]: Don't you think for the non-technical user, that is actually an abstraction that you should take away from them?Stan [00:41:20]: We have a sane default. So we move the default to the latest model that is cool. And we have a sane default, and it's actually not very visible. In our flow to create an agent, you would have to go in advance and go pick your model. So this is something that the technical person will care about. But that's something that obviously is a bit too complicated for the...Swyx [00:41:40]: And do you care most about function calling or instruction following or something else?Stan [00:41:44]: I think we care most for function calling because you want to... There's nothing worse than a function call, including incorrect parameters or being a bit off because it just drives the whole interaction off.Swyx [00:41:56]: Yeah, so got the Berkeley function calling.Stan [00:42:00]: These days, it's funny how the comparison between GP4O and GP4 Turbo is still up in the air on function calling. I personally don't have proof, but I know many people, and I'm probably part of them, to think that GP4 Turbo is still better than GP4O on function calling. Wow. We'll see what comes out of the O1 class if it ever gets function calling. And Cloud 3.5 Summit is great as well. They kind of innovated in an interesting way, which was never quite publicized. But it's that they have that kind of chain of thought step whenever you use a Cloud model or Summit model with function calling. That chain of thought step doesn't exist when you just interact with it just for answering questions. But when you use function calling, you get that step, and it really helps getting better function calling.Swyx [00:42:43]: Yeah, we actually just recorded a podcast with the Berkeley team that runs that leaderboard this week. So they just released V3.Stan [00:42:49]: Yeah.Swyx [00:42:49]: It was V1 like two months ago, and then they V2, V3. Turbo is on top.Stan [00:42:53]: Turbo is on top. Turbo is over 4.0.Swyx [00:42:54]: And then the third place is XLAM from Salesforce, which is a large action model they've been trying to popularize.Stan [00:43:01]: Yep.Swyx [00:43:01]: O1 Mini is actually on here, I think. O1 Mini is number 11.Stan [00:43:05]: But arguably, O1 Mini has been in a line for that. Yeah.Alessio [00:43:09]: Do you use leaderboards? Do you have your own evals? I mean, this is kind of intuitive, right? Like using the older model is better. I think most people just upgrade. Yeah. What's the eval process like?Stan [00:43:19]: It's funny because I've been doing research for three years, and we have bigger stuff to cook. When you're deploying in a company, one thing where we really spike is that when we manage to activate the company, we have a crazy penetration. The highest penetration we have is 88% daily active users within the entire employee of the company. The kind of average penetration and activation we have in our current enterprise customers is something like more like 60% to 70% weekly active. So we basically have the entire company interacting with us. And when you're there, there is so many stuff that matters most than getting evals, getting the best model. Because there is so many places where you can create products or do stuff that will give you the 80% with the work you do. Whereas deciding if it's GPT-4 or GPT-4 Turbo or et cetera, you know, it'll just give you the 5% improvement. But the reality is that you want to focus on the places where you can really change the direction or change the interaction more drastically. But that's something that we'll have to do eventually because we still want to be serious people.Swyx [00:44:24]: It's funny because in some ways, the model labs are competing for you, right? You don't have to do any effort. You just switch model and then it'll grow. What are you really limited by? Is it additional sources?Stan [00:44:36]: It's not models, right?Swyx [00:44:37]: You're not really limited by quality of model.Stan [00:44:40]: Right now, we are limited by the infrastructure part, which is the ability to connect easily for users to all the data they need to do the job they want to do.Swyx [00:44:51]: Because you maintain all your own stuff.Stan [00:44:53]: You know, there are companies out thereSwyx [00:44:54]: that are starting to provide integrations as a service, right? I used to work in an integrations company. Yeah, I know.Stan [00:44:59]: It's just that there is some intricacies about how you chunk stuff and how you process information from one platform to the other. If you look at the end of the spectrum, you could think of, you could say, oh, I'm going to support AirByte and AirByte has- I used to work at AirByte.Swyx [00:45:12]: Oh, really?Stan [00:45:13]: That makes sense.Swyx [00:45:14]: They're the French founders as well.Stan [00:45:15]: I know Jean very well. I'm seeing him today. And the reality is that if you look at Notion, AirByte does the job of taking Notion and putting it in a structured way. But that's the way it is not really usable to actually make it available to models in a useful way. Because you get all the blocks, details, et cetera, which is useful for many use cases.Swyx [00:45:35]: It's also for data scientists and not for AI.Stan [00:45:38]: The reality of Notion is that sometimes you have a- so when you have a page, there's a lot of structure in it and you want to capture the structure and chunk the information in a way that respects that structure. In Notion, you have databases. Sometimes those databases are real tabular data. Sometimes those databases are full of text. You want to get the distinction and understand that this database should be considered like text information, whereas this other one is actually quantitative information. And to really get a very high quality interaction with that piece of information, I haven't found a solution that will work without us owning the connection end-to-end.Swyx [00:46:15]: That's why I don't invest in, there's Composio, there's All Hands from Graham Newbig. There's all these other companies that are like, we will do the integrations for you. You just, we have the open source community. We'll do off the shelf. But then you are so specific in your needs that you want to own it.Swyx [00:46:28]: Yeah, exactly.Stan [00:46:29]: You can talk to Michel about that.Swyx [00:46:30]: You know, he wants to put the AI in there, but you know. Yeah, I will. I will.Stan [00:46:35]: Cool. What are we missing?Alessio [00:46:36]: You know, what are like the things that are like sneakily hard that you're tackling that maybe people don't even realize they're like really hard?Stan [00:46:43]: The real parts as we kind of touch base throughout the conversation is really building the infra that works for those agents because it's a tenuous walk. It's an evergreen piece of work because you always have an extra integration that will be useful to a non-negligible set of your users. I'm super excited about is that there's so many interactions that shouldn't be conversational interactions and that could be very useful. Basically, know that we have the firehose of information of those companies and there's not going to be that many companies that capture the firehose of information. When you have the firehose of information, you can do a ton of stuff with models that are just not accelerating people, but giving them superhuman capability, even with the current model capability because you can just sift through much more information. An example is documentation repair. If I have the firehose of Slack messages and new Notion pages, if somebody says, I own that page, I want to be updated when there is a piece of information that should update that page, this is not possible. You get an email saying, oh, look at that Slack message. It says the opposite of what you have in that paragraph. Maybe you want to update or just ping that person. I think there is a lot to be explored on the product layer in terms of what it means to interact productively with those models. And that's a problem that's extremely hard and extremely exciting.Swyx [00:48:00]: One thing you keep mentioning about infra work, obviously, Dust is building that infra and serving that in a very consumer-friendly way. You always talk about infra being additional sources, additional connectors. That is very important. But I'm also interested in the vertical infra. There is an orchestrator underlying all these things where you're doing asynchronous work. For example, the simplest one is a cron job. You just schedule things. But also, for if this and that, you have to wait for something to be executed and proceed to the next task. I used to work on an orchestrator as well, Temporal.Stan [00:48:31]: We used Temporal. Oh, you used Temporal? Yeah. Oh, how was the experience?Swyx [00:48:34]: I need the NPS.Stan [00:48:36]: We're doing a self-discovery call now.Swyx [00:48:39]: But you can also complain to me because I don't work there anymore.Stan [00:48:42]: No, we love Temporal. There's some edges that are a bit rough, surprisingly rough. And you would say, why is it so complicated?Swyx [00:48:49]: It's always versioning.Stan [00:48:50]: Yeah, stuff like that. But we really love it. And we use it for exactly what you said, like managing the entire set of stuff that needs to happen so that in semi-real time, we get all the updates from Slack or Notion or GitHub into the system. And whenever we see that piece of information goes through, maybe trigger workflows to run agents because they need to provide alerts to users and stuff like that. And Temporal is great. Love it.Swyx [00:49:17]: You haven't evaluated others. You don't want to build your own. You're happy with...Stan [00:49:21]: Oh, no, we're not in the business of replacing Temporal. And Temporal is so... I mean, it is or any other competitive product. They're very general. If it's there, there's an interesting theory about buy versus build. I think in that case, when you're a high-growth company, your buy-build trade-off is very much on the side of buy. Because if you have the capability, you're just going to be saving time, you can focus on your core competency, etc. And it's funny because we're seeing, we're starting to see the post-high-growth company, post-SKF company, going back on that trade-off, interestingly. So that's the cloud news about removing Zendesk and Salesforce. Do you believe that, by the way?Alessio [00:49:56]: Yeah, I did a podcast with them.Stan [00:49:58]: Oh, yeah?Alessio [00:49:58]: It's true.Swyx [00:49:59]: No, no, I know.Stan [00:50:00]: Of course they say it's true,Swyx [00:50:00]: but also how well is it going to go?Stan [00:50:02]: So I'm not talking about deflecting the customer traffic. I'm talking about building AI on top of Salesforce and Zendesk, basically, if I understand correctly. And all of a sudden, your product surface becomes much smaller because you're interacting with an AI system that will take some actions. And so all of a sudden, you don't need the product layer anymore. And you realize that, oh, those things are just databases that I pay a hundred times the price, right? Because you're a post-SKF company and you have tech capabilities, you are incentivized to reduce your costs and you have the capability to do so. And then it makes sense to just scratch the SaaS away. So it's interesting that we might see kind of a bad time for SaaS in post-hyper-growth tech companies. So it's still a big market, but it's not that big because if you're not a tech company, you don't have the capabilities to reduce that cost. If you're a high-growth company, always going to be buying because you go faster with that. But that's an interesting new space, new category of companies that might remove some SaaS. Yeah, Alessio's firmSwyx [00:51:02]: has an interesting thesis on the future of SaaS in AI.Alessio [00:51:05]: Service as a software, we call it. It's basically like, well, the most extreme is like, why is there any software at all? You know, ideally, it's all a labor interface where you're asking somebody to do something for you, whether that's a person, an AI agent or whatnot.Stan [00:51:17]: Yeah, yeah, that's interesting. I have to ask.Swyx [00:51:19]: Are you paying for Temporal Cloud or are you self-hosting?Stan [00:51:22]: Oh, no, no, we're paying, we're paying. Oh, okay, interesting.Swyx [00:51:24]: We're paying way too much.Stan [00:51:26]: It's crazy expensive, but it makes us-Swyx [00:51:28]: That's why as a shareholder, I like to hear that. It makes us go faster,Stan [00:51:31]: so we're happy to pay.Swyx [00:51:33]: Other things in the infrastack, I just want a list for other founders to think about. Ops, API gateway, evals, you know, anything interesting there that you build or buy?Stan [00:51:41]: I mean, there's always an interesting question. We've been building a lot around the interface between models and because Dust, the original version, was an orchestration platform and we basically provide a unified interface to every model providers.Swyx [00:51:56]: That's what I call gateway.Stan [00:51:57]: That we add because Dust was that and so we continued building upon and we own it. But that's an interesting question was in you, you want to build that or buy it?Swyx [00:52:06]: Yeah, I always say light LLM is the current open source consensus.Stan [00:52:09]: Exactly, yeah. There's an interesting question there.Swyx [00:52:12]: Ops, Datadog, just tracking.Stan [00:52:14]: Oh yeah, so Datadog is an obvious... What are the mistakes that I regret? I started as pure JavaScript, not TypeScript, and I think you want to, if you're wondering, oh, I want to go fast, I'll do a little bit of JavaScript. No, don't, just start with TypeScript. I see, okay.Swyx [00:52:30]: So interesting, you are a research engineer that came out of OpenAI that bet on TypeScript.Stan [00:52:36]: Well, the reality is that if you're building a product, you're going to be doing a lot of JavaScript, right? And Next, we're using Next as an example. It's

In diesem Monat feiert der Sozialdienst Katholischer Frauen in Olpe das 100-jährige Bestehen. Die Gründerfrauen aus Olpe engagierten sich aus ihrer christlichen Überzeugung und ihrer gesellschaftlichen Stellung heraus für die in Not geratenen Mädchen, Frauen und Kinder besonders in den Zeiten während und nach den beiden Weltkriegen. Sie haben ein soziales Netz geschaffen, das bis heute besteht. Durch die Fachbereiche des Sozialdienstes Katholischer Frauen und des Sozialdienstes Katholischer Männer wurde hier in Olpe der gemeinsame Katholische Sozialdienst gebildet.Heute Nachmittag wird zunächst ein Wortgottesdienst gefeiert um Dank zu sagen: Gott, unter dessen Segen vieles gelingen konnte, den vielen Frauen und Männern, die sich in den vergangenen 100 Jahren engagiert und eingesetzt haben und den heutigen haupt- und ehrenamtlich Mitarbeitenden, die die vielfältigen Dienste für Menschen leisten. Die Gründungsidee des SkF, der 1899 von Agnes Neuhaus in Dortmund ins Leben gerufen worden ist, war, dass es Not- und Konfliktsituationen gibt, von denen Frauen besonders betroffen sind und in denen Frauen anderen Frauen in besonderer Weise helfen können. Diese Idee ist damals wie heute von außerordentlicher Aktualität. Der SkF arbeitet, dem Gründungskonzept folgend, in vielfältigen sozialen Bereichen: Beratung und Hilfe im Rahmen der Kinder- und Jugendhilfe, Beratung und Hilfe für Frauen und Familien in besonderen Belastungssituationen, für psychisch Kranke und Betreuung und für Menschen mit Behinderungen. Aus diesem Anlass findet unter dem Motto "Ein Netz, das trägt" eine Bilderausstellung in der Hl. Geistkirche in Olpe statt. Die Bilder und Texte erzählen aus der Geschichte und der Gegenwart des SKF. Vielleicht haben Sie am Wochenende ja Zeit und Lust, sich diese Ausstellung anzuschauen und sich darüber zu informieren, wie vielleicht auch Sie in Ihrem Umfeld in diesen Anliegen für Mitmenschen tätig sein, für sie beten oder auch mit einer Spende hilfreich sein können.

Meer weten over de mogelijkheden bij Trade Republic? Kijk dan op: https://traderepublic.com/nl-nl?adjust_referrer=adjust_reftag=cAS8MFJXLi9sY&utm_campaign=NL_INFL__DEAANDEELHOUDER&utm_content=June&utm_medium=INFL&utm_source=DEAANDEELHOUDER Meer weten over het Sustainable Dividends Value Fund? Kijk dan op: https://www.sustainabledividends.com/en/ In de wekelijkse podcast van DeAandeelhouder ontvangt Albert Jellema diverse experts uit de financiële wereld om te praten over de beurs, beleggen en aandelen. Deze week ontvangen we Simon van Veen van het Sustainable Dividends Value Fund en Erik Mauritz van Trade Republic. Onderwerpen die aan bod komen in deze aflevering zijn: Brembo, Medistim, Fastned, Asml, Besi, Asmi, Aalberts, Banken, SKF, Sif, Just eat, Vopak & Rente Volg DeAandeelhouder op andere kanalen: Website: https://www.deaandeelhouder.nl/ Twitter (X): / https://x.com/deaandeelhouder TikTok: / https://www.tiktok.com/@deaandeelhouder Instagram: / https://www.instagram.com/deaandeelhouder/ Facebook: / https://www.facebook.com/DeAandeelHouder/ LinkedIn: / https://www.linkedin.com/company/de-aandeelhouder-nl/ Ontvang al onze exclusieve analyses, video's en beurscontent: https://www.deaandeelhouder.nl/premium/ Met een premium abonnement krijgt u wekelijks exclusieve video's en uitleg over potentieel koopwaardige aandelen, regelmatig artikelen met tips om op een verstandige manier met uw geld om te gaan, verder krijgt u tweewekelijks toegang tot de chatsessie met Nico Inberg en als klap op de vuurpijl krijgt u iedere zaterdag ons online magazine. Een kleine investering, voor een veel mooier rendement. Tijdslijn: 00:00 - 00:58 Intro 00:58 - 08:30 Rentebesluit 08:30 - 10:50 Small Caps 10:50 - 14:23 Verbazing Simon 14:23 - 16:47 Verbazing Erik 16:47 - 20:16 Prinsjesdag 20:16 - 23:48 FNV 23:48 - 24:53 Vopak 24:53 - 32:53 Fastned 32:53 - 35:00 “Dividend is een sigaar uit eigen doos” 35:00 - 39:00 Acc of Dist ETF's + Kosten ETF's 39:00 - 44:44 Bal onder water + Medistim 44:44 - 50:32 AI-bubbel + Chippers 50:32 - 53:48 Comeback van cyclische aandelen 53:48 - 56:21 Hoeveel geld heb ik nodig om te beleggen in ETF's 56:21 - 58:30 Welke ETF moet ik kopen? 58:30 - 01:02:00 Begrip van de week “Payout ratio” 01:02:00 - 01:04:35 SKF 01:04:35 - Outro #beursnieuws #beleggen #aandelen #aex #beursupdate #investeren #kopen #verkopen #analyseren #Nico #Inberg #Jordy #Albert #DAH #Deaandeelhouder #Aandeelhouder #Degiro #Tips #beurskoers #Kopen #verkopen #degiro #analyseren #Aex #ETF #Tips #obligaties #S&P500 #opties #crypto#Tesla #JustEat #Takeaway #BasicFit #ING #Besi #NVIDIA #ASML #Aegon #Alibaba #Adyen #Shell #Philips #Asmi #NNgroup #ABNAmro #VanEck #Nio #Amazon #Apple #AMD #Intel #Microsoft #Google #Meta #LVMH #Goud #Bitcoin #grondstoffen #Alfen #Pharming #Galapagos #DSM #Ebusco #PostNL #Bam #Randstad #ASR #FlowTraders #TKH #Aalberts #Argenx #Netflix,

Sunnyboy ist ein Flat Coated Retriever, ein großer, schwarzer Hund mit lieben, braunen Augen. Er war mit seinem Frauchen, der Sozialpädagogin Karina Brändlin zu Gast im Studio. Sie und Sunnyboy sind in der Straffälligenhilfe des SkF im Einsatz und fahren regelmäßig in die JVA nach Aichach. Sunny schafft es nicht nur, dass sich die Insassinnen öffnen und Vertrauen in ihr Gegenüber fassen. Sondern er hilft auch dabei, dass die Frauen ihr eigenes Verhalten reflektieren, dass ihr Selbstwertgefühl gestärkt wird und sie auch für die Zeit nach der Haft besser im Leben stehen. Mit welchen Übungen das gelingt, das gibt's in dieser Folge von Total Sozial.

In dieser spannenden Podcastfolge diskutieren Jan und Clemens über aktuelle Ereignisse wie den Katholikentag, die Europameisterschaft und Wahlen in Europa. Sie beleuchten die Arbeit der Sozialverbände SKM und SKF und deren Bedeutung in der Gesellschaft. Ein zentrales Thema ist die Geschlechterdifferenzierung in der Erziehung und die Rolle von religiösen Werten in der Prävention von Delinquenz (Straffälligkeit). Jan teilt seine Erfahrungen als neues Vorstandsmitglied des SKM und spricht über die Herausforderungen und Ziele, die vor ihm liegen. Hören Sie rein für tiefgehende Einblicke und interessante Diskussionen!

I det här avsnittet får vi lära känna Epirocs ordförande Ronnie Leten. Han är inget mindre än en legend inom svenskt näringsliv vars resa började i Atlas Copco redan 1985. Han är från Belgien och har en förkärlek för kompressorer men hunnit med att testa på det mesta. 24 år senare tog han över vd-posten i bolaget, närmare bestämt 2009 och ruvade på posten fram till 2017. Därefter tog han över som ordförande för avknoppningen och särnoteringen Epiroc (2018), men var det självklart?Ronnie berättar om det enorma värdeskapandet i Atlas Copco genom åren som förvandlat en investering på 10 000 kr år 1987 till hela 93 miljoner kronor idag. Dessutom får vi veta nästan allt om dagens Epiroc som i dagarna firar 6 år som självständigt bolag. Hur ser kulturen ut och hur ser man till att inte bli fat and happy när man är bäst i klassen? Vad har han lärt sig i styrelserummen hos SKF, Electrolux, Ericsson och Piab som han har användning för och står vi inför en supercykel för kopparn? Det och mycket mer i detta välfyllda avsnitt!Kuriosa: Ronnie är ju en belgare i ett svenskt börsbolag men faktum är att Copco i namnet Atlas Copco (som även Epiroc är sprunget ur) faktiskt kommer från ett förvärv som gjordes en gång i tiden i Belgium.Trevlig lyssning,Nicklas Hosted on Acast. See acast.com/privacy for more information.

Annika Ölme, CTO and SVP of SKF, speaks about technological innovation and the industrial future. Drawing from her SKF Group tenure and leadership roles at Arcam and SAAB Radar Solutions, she highlights the importance of diversity in driving innovation. Join her for insights into navigating the evolving landscape of technology and industry.

Direkt hinter dem Kreuzgang des alten Franziskanerklosters in Ingolstadt, an der Schrannenstraße 1a, befindet sich seit einigen Wochen ein neues Café: Café Neuhaus. Es ist ein Angebot des Sozialdiensts katholischer Frauen (SkF) für Frauen, die von der Obdachlosigkeit bedroht sind oder tatsächlich buchstäblich auf der Straße leben. Beraterinnen des SkF sind vor Ort und können weiterhelfen. Aber das ganze Café könnte nicht funktionieren, wenn es nicht eine Reihe von Ehrenamtlichen gebe, die sich in ihrer Freizeit dafür engagieren. Bernhard Löhlein berichtet.

Die Weltstadt mit Herz ist leider auch die teuerste Stadt Deutschlands. Das macht es für Menschen, die finanziell nicht so gut dastehen oft schwierig, eine Wohnung zu bezahlen. Für einige endet der Weg in der Obdachlosigkeit. Das Münchner Netzwerk Wohnungslosenhilfe hat in dieser Woche eine Sonderfahrt mit einer Tram auf die Reise geschickt, um auf die Situation dieser Menschen aufmerksam zu machen. Brigitte Strauß ist mitgefahren und hat die vielen Facetten des Themas mitbekommen. [Mehr Infos zum Netzwerk Wohnungslosenhilfe ](https://www.wohnungslosenhilfe-muenchen.net/vereine-verbaende.html)

We are actually recording in person this episode! And in true SKF fashion, we had audio issues. So bear with us

Am zweiten Sonntag im Mai ist Muttertag und wir widmen uns heute mal den werdenden Müttern. Es geht jetzt nämlich um Schwangerschaftsberatung. Die ist aber nicht nur für Schwangere gedacht. Nach einer Statistik die 2022 von der Caritas und dem Sozialdienst Katholischer Frauen veröffentlicht wurde, gehen sogar immer mehr Männer zur Schwangerschaftsberatung. Was genau die Schwangerschaftsberatung alles macht, das hat jetzt Moritz Benecke für uns. Und noch ein paar Informationen wo man Schwangerschaftsberatung bekommen kann: Beinahe überall, denn man ist nicht verpflichtet Katholisch zu sein, um zu der Beratungsstelle des SKF zu gehen oder evangelisch, wenn man zu der Stelle der Diakonie geht. Schwangerschaftsberatung kümmert sich um jeden, der kommt. Egal welchen Alters, welcher Herkunft und welcher Konfession oder Religion man angehört. Wenn Ihr also jemanden kennt, der die Dienste einer Schwangerschaftsberatung gebrauchen könnte, dann schickt sie zur Webseite https://www.familienplanung.de/. Wenn man da gleich auf der Startseite etwas runter scrollt unter dem Punkt Beratung findet Ihr eine Suchmaschine. Dort gebt Ihr Eure Postleitzahl ein, um die nächstgelegene Beratungsstelle zu finden.

Yenen faller förbi 156-nivån mot amerikanska dollarn. SKF, Diös och Electrolux rapporterar. Lyssna på Di Morgonkoll med Sophie Gräsberg.

„Keiner muss perfekt sein, und das erwartet auch niemand. Aber wer ein Pflegekind aufnehmen will, sollte offen und reflektiert sein“, sagt Melanie Plag vom Sozialdienst katholischer Frauen (SkF) in Ahlen. Pflegefamilien können vielfältig sein. Oft sind es Menschen, die vielleicht selber gar keine Kinder bekommen können, oder Familien, die schon leibliche Kinder haben und einem weiteren Kind ein Zuhause geben wollen. Auch gleichgeschlechtliche Paare oder Alleinstehende nehmen Pflegekinder auf. Das Alter spielt dabei nur bedingt eine Rolle. So sind es zum Teil auch schon etwas ältere Menschen, die sagen: „Ich habe da einfach noch etwas zu geben und ich habe Platz für ein Kind, im Haus und im Herzen.“ Die Aufnahme eines Pflegekindes in eine Familie, ist ein intensiver Prozess. Die angehenden Pflegeeltern werden dabei aber nicht alleine gelassen. In Gruppenschulungen, wie sie der SkF in Ahlen anbietet, werden sie auf diese Aufgabe vorbereitet und setzen sich mit ihrer eigenen Biographie auseinander. Sie werden über rechtliche Themen aufgeklärt und über die beteiligten Institutionen, wie Jugendämter und Amtsvormünder. In der Regel sollen die Pflegekinder auch eine Beziehung zu ihren Herkunftsfamilien behalten, weil es für sie wichtig ist, zu wissen, wo ihre Wurzeln sind. Die Pflegekinderdienste schauen sehr genau hin, in welche Familien sie Kinder vermitteln. „Unser oberstes Ziel ist, für die Kinder ein sicheres und geborgenes Zuhause zu finden. Wir suchen keine Kinder für Familien“, sagt Melanie Plag. Pflegeeltern werden dringend gesucht. Die Kolleginnen und Kollegen in den Pflegekinderdiensten im Caritas-Netzwerk freuen sich über jeden Anruf von Menschen, die sich vorstellen können, ein Pflegekind aufzunehmen. Wenn wir Ihr Interesse geweckt haben, melden Sie sich bei Fragen einfach telefonisch oder per E-Mail. Wir empfehlen Ihnen die Suchmaschine des Deutschen Caritasverbandes https://www.caritas.de/suche. Hier finden Sie über die Eingabe Ihrer Postleitzahl und den Suchbegriff „Pflegekinderdienst“ Kontaktdaten von Diensten in Ihrer Nähe.

➡ Bli ⁠STØTTEMEDLEM⁠ og støtt podcasten med 49,- per mnd. Anne Kalvig er religionsviter, og var professor i religionsvitenskap ved Universitetet i Stavanger frem til 2023. Hun er tidl. nestleder i Women's Declaration International i Norge. Kalvig er aktuell med boken Kjønnstru – Kampen om røynda, som du kan kjøpe her: https://www.annekalvig.no SPONSOR: Denne episoden er sponset av Kristent Ressursenter. Les mer om dem her: https://kressurs.no ► STØTT HENRIK BECKHEIM PODCAST Om du ønsker å støtte arbeidet med denne podcasten, kan du bidra med et stort eller lite beløp, etter eget ønske. All støtte settes pris på, og du bidrar til arbeidet med å lage flere episoder. ► Du kan støtte podden ved å donere et beløp til: ➡ Vipps (lenke for mobil) eller bruk Vippsnummer: #823278 ➡ Bli STØTTEMEDLEM og støtt med 49,- per mnd. ► Omtale/rating: Legg gjerne igjen en omtale/rating på ⁠⁠Spotify⁠⁠ & ⁠⁠Apple Podcasts⁠⁠.  Det hjelper podcasten med å bli synlig for flere. ► Facebook-gruppe: Bli med i Facebook-gruppen her ► Linker: ⁠⁠Youtube⁠⁠ | Google | ⁠⁠Nettside⁠⁠ | ⁠⁠TikTok⁠⁠ | ⁠⁠Instagram⁠⁠ | Podimo | ⁠⁠Facebook⁠⁠ | ⁠⁠Apple 00:00 Ingen forlag ville gi ut Kjønnstru 07:00 Hvorfor avfeies kristne bøker som irrelevante? 11:30 Kjønnsideologi er et sirkulært selv-refererende system 18:45 Hvorfor er vi ikke opptatt av evidens innenfor kjønn? 21:30 Lov om endring av juridisk kjønn, og Yogyakarta prinsipper 26:00 Mye penger og lobbyisme i kjønnsideologi 28:00 Transhumanisme, «the apartheid of sex» og udødelig liv 35:00 Frykt for egen dødelighet, så du må bli din egen Gud 39:00 Kvinner kan ikke bli fedre, og menn kan ikke bli mødre 41:00 Sex og Politikk og Planned Parenthood 50:20 Kjønnsidentitet er navlebeskuende og narsissistisk prosjekt 54:14 Grenser er positivt 01:00:26 Organisasjonen FRI og den skeive bevegelsen vil senke seksuell lavalder til 10 år. 01:16:33 Fellestrekk mellom religion og kjønnsideologi? 01:23:55 Kvinnesaken vs. feminisme 01:30:50 Virker som man ikke ønsker at kvinner skal eksistere 01:38:28 Ekstrem transideologi er misantropisk og anti-humant 01:44:00 Paradoksalt at de som kritiserer alternativ behandling, støtter transideologi 01:59:04 Sex og Politikk forts. 02:01:47 Annes historie, og hva som skjedde ved Stavanger Universitet 02:13:23 Varsel mot Anne fra Senter for Kjønnsforskning (SKF)

Episode 308: At HDAW'24, we had the privilege of sitting down with some of the heavy-duty industry's biggest names. Kent Jones, President of SAF-Holland, shared exclusive insights into their merger with Haldex. Additionally, Tim Bauer, VP of Aftermarket for North America at Eaton, and Cengiz Shevket, President of Aftermarket Sales for North America at SKF, discussed their cutting-edge software and top-of-the-line products designed to enhance efficiency for end-users.Join the discussion for an exclusive look at the strategies driving industry titans and discover the latest product and technologies that can streamline operations, reduce downtime, and improve overall fleet efficiency.Show Notes: Visit HeavyDutyPartsReport.com for complete show notes of this episode and to subscribe to all our content.Sponsors of this EpisodeFinditParts: Are you looking to purchase heavy-duty parts and get your commercial vehicle repaired? Get access to the largest source of heavy-duty truck and trailer parts in the United States and Canada. Buy your parts from FinditParts.comHengst Filtration: There's a new premium filter option for fleets. If you're responsible for a fleet, you won't believe how much using Hengst filters will save you. But you've got to go to HeavyDutyPartsReport.com/Hengst to find out how much.HDA Truck Pride: They're the heart of the independent parts and service channel. They have 750 parts stores and 450 service centers conveniently located across the US and Canada. Visit HeavyDutyPartsReport.com/HDATruckPride today to find a location near you.Disclaimer: This content and description may contain affiliate links, which means that if you click on one of the product links, The Heavy Duty Parts Report may receive a commission.  Sign up for our weekly email so you never miss out on an episode: Follow the Show

Im Februar dieses Jahres hat der SkF im Ingolstädter Zentrum ein Café für Frauen in drohender oder akuter Wohnungsnot eröffnet – das „Café NeuHaus“. Im Erdgeschoss des alten Franziskanerklosters an der Schrannenstraße 1a, in der direkten Nachbarschaft der Geschäftsstelle des SkF, werden künftig Frauen in Not Beratung, Austausch, Ruhe und Unterstützung finden. Gesucht werden noch ehrenamtliche Mitarbeiterinnen. Bernhard Löhlein berichtet. (Weitere Informationen unter: skf-ingolstadt.de)

Det är en rapporttung morgonen med rapporter från bland annat SKF, SSAB och H&M. Ikväll ser vi fram mot Fed:s räntebesked. Lyssna på Di Morgonkoll med Alexander Klaar.

On the second week of Christmas, SKF brought to me: a portrait from a stalker, candies filled with jizz, and some nasty lotion from Dollar Tree! This week we cover the worst gifts you've been given. And we had a blast. Thank you for sharing all the drama. We love it. And love getting EVERY story submission. Also, the podcast we wouldn't stop talking about (Scream Queer) is https://podcasts.apple.com/us/podcast/scream-queer-podcast/id1654663138. Check him out!

Das Jugendamt und der Sozialdienst katholischer Frauen (SkF) Essen suchen Menschen, die für unbegleitete minderjährige Flüchtlinge Paten- und Vormundschaften übernehmen. "Das kann sehr erfüllend sein", sagt SkF-Geschäftsführer Enno Hermanns. Von WDR5.

Erstmals sind Frauen an der Weltbischofssynode in Rom nicht nur Zaungäste, sondern dürfen mit abstimmen. Dass von den rund 50 stimmberechtigen Kirchenfrauen eine aus der Schweiz sein würde, war eine echte Überraschung. In Perspektiven treffen wir Helena Jeppesen-Spuhler zur Synodenhalbzeit in Rom. Wir begleiten die stimmberechtige Delegierte Helena Jeppesen-Spuhler einen Tag lang im Vatikan. Über einen Monat verbringt die langjährige Fastenaktion-Mitarbeiterin in Rom. Wir fragen, ob sich das lohnt: für die Frauen in der Kirche? Und ob die römisch-katholische Kirche hier noch eine letzte Chance kriegt? Die Skepsis, ob diese «Weltsynode» nun endlich den Durchbruch und Reformen bringe, ist gross. Schliesslich darf die Versammlung mit 275 Bischöfen und neu eben auch einigen Laien den Papst ja nur beraten. Welche Reformen dann wirklich kommen, entscheidet Papst Franziskus allein. Doch der Druck auf die Weltsynode ist gross, nicht nur aus der Schweiz, und nicht nur wegen der vielen Missbrauchsfälle und ihrer Vertuschung durch Bischöfe. Am Rand der Weltsynode treten darum auch Jugendliche, Frauen und Basisgruppen auf, um ihre Anliegen in Rom loszuwerden. Jeppesen-Spuhler ist sich ihrer Verantwortung bewusst. Die Delegierte trifft in Rom darum auch katholische Schweizerinnen vom SKF und der progressiven «Allianz Gleichwürdig Katholisch». Autorin: Judith Wipfler Das SRF-Interview im Vorfeld der Weltsynode mit Bischof Felix Gmür in Rom: https://www.srf.ch/audio/srf-4-news/es-ist-ein-versuchslabor-bischof-felix-gmuer-an-der-weltsynode?uuid=04f13617-8436-4f82-a845-ca53f3001f8e Sendung Fromme Törtchen vom 15.10.23: https://www.srf.ch/play/tv/sternstunde-religion/video/lesbisch--katholisch-geht-das----fromme-toertchen?urn=urn:srf:video:80ef1453-e380-4a90-9f66-eb7815664cc8 Sendung Kontext vom 17.10.23: https://www.srf.ch/audio/kontext/austritt-ist-auch-k-eine-loesung?id=12470880 Wir freuen uns über Ihre Post und Anregungen auf redaktion.religion@srf.ch

BONUS EPISODES ARE BACK! The first monday of every month you can expect to hear from us. Just a little thank you from the SKF crew. This bonus episode is all kinds of inappropriate. We talk about tattoos we're thinking of getting, the Colleen Ballinger drama, and a true story about road rage told by James.

In this episode, Matt and Brad welcome on Bonafide lead kayak designer Hans Nutz to talk about the newly announced  @bonafidefish  SKF 117. Sponsored by:  @darkhorsetackle8267  Use promo code THECATCH5OFF to save $5 off your first monthly subscription. Click the link below. https://www.darkhorsetackle.com/subscribe/?cart_synced=True&return_url=https%3A%2F%2Fwww.darkhorsetackle.com%2Fsubscribe%2Fhttps://bonafidefishing.com/pages/skf117-series --- Support this podcast: https://podcasters.spotify.com/pod/show/the-catch-pod/support

På mindre än ett århundrade blev det fattiga jordbrukslandet Sverige en ledande tekniknation. Motorn i utveckling var ingenjörerna som gick från praktiker med tekniska aftonskolor i botten till vetenskapligt skolade entreprenörer.Ingenjörerna blev också bärare av en framtidstro där tekniken skulle lösa alla samhällets problem. En optimism som gick en allvarlig törn med atombomben och senare förödande kärnkraftsolyckor.I denna nymixade repris av podden Historia Nu samtalar programledare Urban Lindstedt med Gunnar Wetterberg, historiker och diplomat, aktuell med boken Ingenjörerna.Snilleföretagen som Asea, Alfa Laval, LM Ericsson, SKF och så vidare startades av praktiskt sinnade ingenjörer. De fick också draghjälp av statliga investeringar och beställningar som sköttes av statligt anställda ingenjörer.De första ingenjörerna var universalsnillen som byggde försvarsanläggningar och anlade städer. Även den svenska gruvnäringen blev ett viktigt drivhus för den tekniska utvecklingen.I mitten av 1800-talet blev ingenjörerna allt fler. Ingenjörerna skiljer sig från hantverkaren genom att använda vetenskapen som verktyg. Först utbildade vi olika tekniska institut samt tekniska aftonskolor och med tiden vid högskolor med en vetenskaplig inriktning.Bild: Erik Wallenberg uppfann 1944 som anställd på nuvarande Tetra Pak den första Tetra Pak-förpackningen i form av en tetraeder.Musik: Impetuoso Con Fuoco av Emanuele Dentoni Vill du stödja podden och samtidigt höra ännu mer av Historia Nu? Gå med i vårt gille genom att klicka här: https://plus.acast.com/s/historianu-med-urban-lindstedt. Hosted on Acast. See acast.com/privacy for more information.

SKF: Transform Your Maintenance Strategy: Learn From the Experts at SKF 

Você sabia que um rolamento usado pode voltar a ser novo?   A SKF é pioneira em oferecer serviços de repotencialização de rolamentos industriais e ferroviários, começamos há mais de 30 anos. A repotencialização é um processo de restauração da condição normal de trabalho do rolamento, ou seja, o rolamento que seria descartado após o seu período de uso pode ser novo outra vez. Neste episódio do podcast SKF, Thiago Bernardinelli, coordenador do Centro de Serviços da SKF, conta como nossos clientes têm reduzido custos e disponibilidade dos ativos, gerando menos lixo. #SKF #Sustentabilidade #EconomiaCircular #ESG #Rolamento

Beim Sozialdienst katholischer Frauen können Ehrenamtliche eine Patenschaft übernehmen für ein Kind, bei dem ein Elternteil psychisch krank ist. Mittlerweile gibt es rund 50 Paten mit Patenkindern. Jetzt wird das Projekt mit dem Bürgerpreis des Bayrischen Landtags ausgezeichnet. [Und hier gibt´s alle Infos zum Projekt](https://www.skf-muenchen.de/unser-angebot/patenschaften/patenschaften-fuer-kinder-psychisch-erkrankter-eltern.html)

Idag pratar analytiker Anders Roslund om Assa Abloy's och SKF's inför den kommande rapportsäsongen. Disclaimer: ”Informationen i denna video ska inte ses som investeringsråd. Tänk på att placeringar i värdepapper alltid medför en risk. Historisk avkastning är ingen garanti för framtida avkastning. De pengar som placeras i värdepapper kan både öka och minska i värde och det är inte säkert att du får tillbaka hela det insatta kapitalet. Det är viktigt att fortlöpande bevaka sitt innehav och vid behov ta initiativ till åtgärder för att minska risken för förlust.” http://share.paretosec.com/download/c...

En gång fanns det snillrika uppfinnare som grundade framgångsrika svenska industrier. Nobel, Tetra Pak, SKF, ABB föddes alla ur smarta innovationer. Men vilka svenska idéer leder till nya företag idag? Sverige ligger högt på listor över innovativa länder. Till exempel är vi ett av de länder som söker flest patent, räknat per invånare. Men av alla de patenten står enbart Ericsson för nästan en tredjedel. Utan Ericsson är vi inte lika högt rankade.Trots det är vi fortfarande ett framgångsrikt innovationsland, säger Måns Marklund, innovationsanalytiker. Men han tycker att vi trots det kunde vara bättre, med ett bättre stöd till innovatörer, och en tydligare politisk styrning. Enskilda uppfinnare har det svårt idag, säger han. Något som innovationsforskaren Eugenia Perez Vico håller med om. Det krävs stora resurser för att skapa och lansera nya produkter idag, säger hon, vilket är svårt att åstadkomma för en ensam uppfinnare.Den erfarne uppfinnaren Johan Ullman instämmer. Hans erfarenhet säger honom att den ensamme uppfinnarens tid är förbi.Medverkande: Magnus Frodigh, forskningschef på Ericsson; Måns Marklund, innovationsanalytiker Cascelotte AB; Johan Ullman, uppfinnare och Eugenia Perez Vico, innovationsforskare Högskolan Halmstad.Reporter: Tomas LindbladProducent: Björn Gunérbjorn.guner@sr.se

I detta omfattande poddavsnitt djupdyker vi i ett gäng bolag som nu rapporterar och får ta del av analytikernas reflektioner. Därutöver diskuterar vi utvecklingen av massapriserna och vad som nu händer inom verkstad och på stålmarknaden. Bland de diskuterade bolagen finns Epiroc, SKF, Fingerprint, Beijer Group, Rottneros, Midway, SSAB, Kindred, Evolution, Upsales, Mentice, KebNi och Beijer Alma. Avsnittet leds av Alexander Gustafsson.

Augmented reveals the stories behind the new era of industrial operations, where technology will restore the agility of frontline workers. In this episode of the podcast, the topic is "A Scandinavian Perspective on Industrial Operator Independence." Our guest is Johan Stahre (https://www.linkedin.com/in/jstahre/), Professor and Chair of Production Systems at Chalmers University in Sweden. In this conversation, we talk about how the field of human-centered automation has evolved, the contemporary notion of operator 4.0, Scandinavian worker independence, shop floor innovation at Volvo, factories of the future, modern production systems, robots, and cobots in manufacturing. If you like this show, subscribe at augmentedpodcast.co (https://www.augmentedpodcast.co/). If you like this episode, you might also like Episode 84 on The Evolution of Lean with Professor Torbjørn Netland from ETH Zürich (https://www.augmentedpodcast.co/84). Augmented is a podcast for industry leaders, process engineers, and shop floor operators, hosted by futurist Trond Arne Undheim (https://trondundheim.com/) and presented by Tulip (https://tulip.co/). Follow the podcast on Twitter (https://twitter.com/AugmentedPod) or LinkedIn (https://www.linkedin.com/company/75424477/). Trond's Takeaway: Human-centered automation is the only kind of automation that we should be thinking about, and this is becoming more and more clear. Operators are fiercely independent, and so should they be. This is the only way they can spot problems on the shop floor, by combining human skills with automation in new ways augmenting workers. It seems the workforce does not so much need engagement as they need enablement. Fix that, and a lot can happen. Transcript: TROND: Welcome to another episode of the Augmented Podcast. Augmented brings industrial conversations that matter, serving up the most relevant conversations on industrial tech. Our vision is a world where technology will restore the agility of frontline workers. In this episode of the podcast, the topic is A Scandinavian Perspective on Industrial Operator Independence. Our guest is Johan Stahre, Professor and Chair of Production Systems at Chalmers University in Sweden. In this conversation, we talk about how the field of human-centered automation has evolved, the contemporary notion of operator 4.0, Scandinavian worker independence, shop floor innovation at Volvo, factories of the future, modern production systems, robots, and cobots in manufacturing. Augmented is a podcast for industrial leaders, process engineers, and shop floor operators hosted by futurist Trond Arne Undheim and presented by Tulip. Johan, Welcome. How are you? JOHAN: I'm fine, thank you, Trond. It's really nice to see you. TROND: Yeah, likewise. JOHAN: Fellow Nordic person. TROND: Fellow Nordic person. And I apologize for this very American greeting, you know, how are you? As you know, I'm from the Nordic region. I actually mean it, [laughs] you know, it was a question. So I do wonder. [laughs] JOHAN: I'm actually fine. It's just ending the vacation, so I'm a little bit sad about that because everyone...but it's a very nice time now because the rest of the world seems to be on vacation, so you can get a lot of work done. TROND: I concur; that is a wonderful time. Johan, I wanted to just briefly talk about your exciting background. You are an engineer, a mechanical engineer from Sweden. And you had your initial degree from Linköping University. Then you went on to do your Ph.D. a while back in manufacturing automation, and this was at Chalmers, the University in Sweden. And that's where you have done your career in manufacturing research. You are, I think, the first Scandinavian researcher certainly stationed currently in Sweden that we've had on the podcast. So I'm kind of curious, what is manufacturing like in Scandinavia? And what is it that fascinated you about this topic so that you have moved so deeply into it? JOHAN: Manufacturing in Sweden is the core; it's the backbone of our country in a sense. We have statistically too many large manufacturing companies in Sweden as compared to, I mean, we're only 10 million people, but we have like 10, 12 pretty large companies in the manufacturing area in automotive but also in electronics like Ericsson, you have Volvo, we have SKF. We have a lot of big companies. Sweden has an industrial structure that we have several small companies and a couple of large companies, not so many in the middle section there. This happened, actually, in the 1800s somewhere. There was a big growth of big companies, and there was a lot of effort from the government to support this, and that has been continued. So the Swedish government has supported the growth of industry in Sweden, and therefore we have a very strong industry and also quite good digital growth and maturity. TROND: So the Scandinavian background to me when I was there, I remember that one of the things that at least Scandinavian researchers think is distinct about Scandinavia is worker independence. And it's something that I kind of wanted to just tease out a little bit in the beginning of this podcast. Am I wrong in this, or is there something distinct about the relationship between, I guess, workers and managers in Scandinavia, particularly? One speaks about the Scandinavian model. Can you outline a little bit what that means in manufacturing if it still exists? It's an open question. JOHAN: From my perspective, Sweden usually ranks very high in innovation, also when it comes to international rankings. And I think some of that has to do with the openness and the freedom of thinking in a sense and not so hierarchical, more consensus-oriented, ability to test and check and experiment at work without getting repercussions from top management. And it is much easier. In fact, if you are at one department in a manufacturing company or in university as such and you want to collaborate with another colleague across the aisle, if you have a two hierarchical system, you need to go three levels up in order to be able to do that. But here, I think it's easier to just walk across the aisle to have this collaboration and establish a cooperative environment. I think that that's part of the reason. Also, we're not so many; I mean, I think historically, we needed to do a lot of things ourselves in Sweden. We were a country up north with not so many people, and we have harsh environments, and I think it's the same as Norway. I mean, you need to be self-sustainable in that sense, and that creates, I think, environmental collaboration. TROND: We'll go more deeply into your research on manufacturing and to what extent a question I asked here matters to that. But do you have a sense just at the outset here that this type of worker and operators sort of independence, relative independence, perhaps compared to other regions, is it changing at all? Or is this kind of a feature that is a staple of Scandinavian culture and will be hard to change both for good and for bad? JOHAN: I think that as everything...digitalization has sort of erased a lot of the cultural differences across the world in that sense. Because when I was a student, there was not this expressed digital environment, of course. The information environment was less complex. But I think now all the young people, as well as my mother, does her banking...she's 90, but she does her banking on her iPad; I mean, it's very well-spread. And I think that we are all moving towards a similar culture, and the technology is spreading so quick. So you cannot really have cultural differences in that sense. But I think that's still the way that we're using this. And I think that the collaborative sense I think that that is still there. The reason why Sweden is comparatively innovative still is that we still maintain our culture and use the technology to augment that capability. TROND: So, Johan, we'll talk about a bunch of your experiences because you obviously are based in Sweden. And because of Sweden's industrial situation, you have some examples, you know, Volvo, a world-famous company obviously, and also famous for its management practices, and its factory practices, we'll get into that. But you've also worked, and you're advising entities such as the World Economic Forum, and you are active on the European stage with the European Institute of Technology. Your activity clearly goes way, way beyond these borders. But why don't we maybe start with some of these Scandinavian experiences and research projects that you've done maybe with Volvo? What is it with Volvo that captured people's attention early on? And what sort of experience and research have you done with Volvo? JOHAN: I think that Volvo is very innovative, and Volvo today is two types of companies; one is the car company that has now gone fully electric. It was introduced at the stock market, most recently owned by a Chinese company, and before that, it was owned by Ford, and before that, it was also public. But you also have the other part, which is the Volvo Group, which is looking at trucks, and boats, and things like that. And they both share a high level of innovation, ambition, innovation, and power, I think, using the experiences already from the '60s, where you had a lot of freedom as an employee. And also very good collaboration with the union in investments and in all the changes in the company I think that has been very beneficial. And it's made them...what is now Volvo Cars was very, very early, for example, with digital twins. They were experimenting with digital twins already in the 1990s. And we work together with Volvo but also with SKF, which is a roller-bearing company here to look at how we can support frontline workers and augment their capabilities because they're very skilled and they're very experienced. But sometimes you need to have sensor input, and you need to have structures, and rules, and procedures, and instructions. So we worked quite early with them already, maybe in 2009, 2010, to see how can we transform their work situation, provide them with work instructions through wearable devices. It was very popular at that time. MIT was experimenting with cyborgs. And the people that were...I think it was Thad Starner; he was trying to put on a lot of computer equipment. Then he went through the security at the airport and had some problems there. But that's not the case for the operators. But it was a little bit too early, I think. We tried to experiment with some of the maintenance people at Volvo cars. And they were very interested in the technology, but the use for it was a little bit obscure. And this was at the time when you had the mobile connectivity was 9,600 kilobits through a mobile phone or in the modem, so Wi-Fi more or less did not exist. And the equipment: the batteries weighed two kilos, and the computer weighed one kilo. And then you had a headset that looked like you came from deployment in a war zone. So it was a little bit...it looked a little bit too spacy for them to be actually applicable. And then some 10 years later, we actually did a similar experiment with SKF, the roller bearing company where we deployed the first iPod touch, I think they were called. That was right before the iPhone. I think it was an experiment by Steve Jobs to see how can we create what then became the iPhone screen. And we put that on the arms of the operators and tried to see how can we give them an overview of the process situation. So they were constantly aware, and they were quite happy about this. And then, we wanted to finish the experiment. The operators actually said, "Well, we don't want to give the equipment back." And then we said, "Well, we need to have it back. Of course, you can use the software." So they brought their own phones, and they downloaded the software. And they're still using it, actually, not on their own phones anymore. But they use this kind of software that we developed at that time together with them. So that was quite interesting. TROND: That's fascinating. Extrapolating from some of these early experiences up until now, I wanted to just ask you this from a research perspective, but also, I guess, from a management perspective. So you work on production systems. What is really the goal here, or what has the objective been early on? You talked about these early MIT experiments. And I know control systems is a very old area of research. And from what I understand, in the early days, the use cases weren't just factories; they were also on spacecraft and things. But to your point, especially earlier, we were working with very, very different technology interfaces. But now, obviously, we are starting to roll out 5G, which gives a whole other type of richness. But does it really matter how rich the technology interface is? Or does it matter more what the objective is with these various types of augmentations that have been attempted really throughout the decades? Can you just give us a little sense of what researchers and yourself what you were trying to augment and how that depends or doesn't depend on the quality of technology? JOHAN: First, we need to realize that the manufacturing industry has always been a very, very early adopter. The first computers were used for war simulations and for making propellers for submarines to see how you can program the milling machines. This was in the 1950s. And the industrial robots in the '60s in the '70s were also very early applications of digitalization. Before anything else had computers, the manufacturing industry was using it, and that's still the case. That might surprise some people. When they walk out into a shop floor, they see no computers around because all the computers are built into the machines already. What is still missing is the link, perhaps to the people. So they are still using the screens. And they are the ones...people are the key components of handling complex and unforeseeable situations. So you need to provide them, I think...to be really productive, you need to provide the frontline staff with the equipment for them to avoid and to foresee and to handle unforeseen situations because that's what differs between the man and machine or a human and the machine. People are much more apt to solve a complex situation that was not programmed before. That's the augmentation part here; how can we augment the human capabilities? And people talk about augmented reality; I mean, I don't think it's the reality that needs to be augmented; it's the human to be handling the reality that needs to be augmented. TROND: Johan, this is so fascinating because, first of all, it's quite easy to dismiss manufacturing a little bit these days because, to the untrained eye, all the excitement is in the consumer space because that's where the new devices get released, and that's, obviously, where all the attention is these days unless you obviously are in manufacturing. But can you bring us back to those early days of computing when a lot of the use cases for computing were first explored with manufacturing? So you talked about MIT, and back at MIT and at Stanford, all the way back to the '60s, they were exploring this new and fascinating field of even artificial intelligence, but before that, just regular control systems, electronic interfaces. What fork in the road would you say happened there? Because clearly, the fascination has been with digitalizing everything and software kind of one for 30 years, but in manufacturing, it's more complicated. You say people, so it's people, and then it's kind of these production systems that you research. That's not the same as the use case of an individual with their phone, and they're sort of talking to people. There are many, many more variables in play here. What is the real difference? JOHAN: Last year actually the European Commission put forth industry 5.0, which should be the follower after industry 4.0. And they based that on three main challenges. One is sustainability, one is resilience, and the various kinds of resilience towards the shock of the war but also by climate, et cetera. And the third one is actually human-centeredness to see how can we really fully deploy human capabilities in a society and also in industry, of course. I think what you're referring to is the two guys at Stanford in the '60s; one was John McCarthy. He was the inventor of the artificial intelligence concept. His aim then was to replace human work. That was the ambition with the artificial intelligence because human work is not as productive as computing work, but it still has some drawbacks. But in the same place not so far away, in another department at Stanford, was a guy called Douglas Engelbart. And he was actually the father of...he called it intelligence augmentation. So it was AI and IA at that time. But his ambition was to augment human work to see how can you have this. And he was the one that invented hypertext and the mouse. And he put up the first hypermedia set in Silicon Valley. So this was a guy that inspired companies like Apple, and Xerox PARC, those kinds of institutions that had a huge bearing. There was a book by a research colleague at Oxford. He was comparing that over time, from the early industrial days and then forward, technology that replaces people always has more complications when introduced and scaled than technology that augments people. If you look at the acceptance and the adoption of the iPhone, that took months, or weeks, or whatever, seconds for some people, for me, for example. If you look at what happened in the industrial revolutions in the 1800s and the 1700s, you had a lot of upheaval, and already in the 1960s...I'm starting to sound like a university professor. But in '96, in the U.S., there was a Senate hearing about is automation taking the jobs from people or not? And the conclusion was that it is not, it is actually creating companies that then employ more people because of the productivity gains and the innovation gains. And you allow people to use the automation as augmentation, not only cognitive augmentation. We think a lot about augmentation as something that you do with your eyes and your brain. But robots are also augmenting people. It lifts heavy objects like cars or big containers, whatever. That's the kind of augmentation that maybe you don't consider when you look at it from an artificial or an augmented reality perspective. TROND: Well, so many things to pick up here. But the variety of meanings of augmentation are kind of astounding, aren't they? And you've written about this operator 4.0 several times. There's obviously cognitive augmentation, and then there's physical augmentation. Are there other types of augmentation that you can speak of? JOHAN: I really can't think of any. TROND: But those are the main ones. So it's either kind of your mentality or sort of your knowledge. So the work instruction parts go to the skills-based, I guess, augmentation, which perhaps is an additional one. Or I'm just thinking if manufacturing wants to make progress in these things, it would perhaps make sense to really verify what workers at any moment actually themselves express that they need. And I guess that's what I was fishing for a little bit here in this history of all of this, whether the technology developers at all moments really have a clear idea of what it is that the workers are saying themselves they're missing or that they obviously are missing. Because automation and augmentation, I mean, do you find them diametrically opposed, or are they merely complementary when it works well? JOHAN: I mean, automation traditionally has been the way to scale, and, I mean, in the beginning, you want to see what the machine is doing, right? And then you really don't want to see it. You just want it to work. So it's really helping you to scale up your work. And in that sense, automation, like collaborative robots, for example, which people are talking about robots, are something that is replacing jobs, but if you look at it, it is a very small portion of statistics. In Singapore, which is the highest user of robots installed, there were 950 maybe robots per 10,000 employees. And the average in the Americas is 100 robots per 10,000 employees, and that's not really a lot. And so there is plenty of space for robots to be the tools for people. So if you don't treat them as something that will replace you but something that will actually augment you, I think it would be much easier. What could happen, though, and I think that is maybe part of your question, is that, well, these tools are becoming so complex that you cannot use them unless you increase your skill. How do you do that? Because no company would like to end up in a situation where the tools that you have bought and invested a lot of money in are too complex for your employees to use. That's a lost investment. It's like you're building a big factory out in a very remote place, and you don't have enough electric power to run it. You don't want to end up in that situation. Like you expressed, I think that maybe what's missing and what's trending right now is that the upskilling of the workforce is becoming extremely important. TROND: And how do you do that, Johan? Because there's obviously...there's now an increased attention on upskilling. But that doesn't mean that everyone has the solution for it. And employers are always asking for other people to pay for it, for example, governments, or the initiative of the worker, perhaps. It seems like Europe has taken this challenge head-on. Germany, at least, is recognized as a leader in workforce training. The U.S. is a latecomer to the game from that perspective. But it typically shows up in a big way. So something is going to happen here in the U.S. when it comes to workforce training. What is the approach? I mean, there seems to be two approaches to me; one is to simplify the technology, so you need less training. And the other would be obviously an enormous reskilling effort that either is organized, perhaps ideally in the workplace itself, so it's not removed from the tasks. Or some enormous schooling effort that is highly efficient and perhaps online. What do you think are the winning approaches to re-skilling that entire manufacturing workforce continuously? Because it's not like you have to rescale them once, you have to rescale them every time. JOHAN: Well, I can only guess. I think that you need to do all of these, all of the above. One complicating factor is the demographics of, especially Japan; of course, we know that from a long time that, they have an aging population. But Europe is now becoming the new Japan in that sense. We have a very big problem in terms of aging populations, especially countries like Italy and perhaps Germany but also in northern countries. And we don't have perhaps...there's a lot of discussion on immigration right now. But actually, the workforce would need a lot of immigration to be able to respond to the needs of our industry in the forthcoming situation. I think that China is maybe 4 or 5 years behind Europe, and the U.S. is maybe 10-12 years behind Europe as well. So that will happen...the only non-affected regions right now are India and Africa. And that means that the European, and Chinese, and U.S. industries will have to compete with a rather young population in Africa and India. And so that will become over time, but it is a long time, so that means that it's not always on the political agenda. Things that take a long time are usually not the things that you speak about when you have election times that we have in Sweden right now. It's mostly what's on the table. So I think that how to do that is really complex. We had some collaboration within the World Economic Forum. It is a fantastic organization because it spans the whole globe. So that means that the information comes from different parts of the world, and you can see different aspects of this. And a country that has done a lot about this is Singapore, very good experiments, very nice projects, initiatives regarding upskilling. And Europe is now launching an innovation program where they want to go deeper into deep tech to try to...the commissioner for research and education in June launched a big initiative around innovation and how that can be supported by deep technology. So we'll see what comes out of that. It'll be very, very interesting to see. MID-ROLL AD: In the new book from Wiley, Augmented Lean: A Human-Centric Framework for Managing Frontline Operations, serial startup founder Dr. Natan Linder and futurist podcaster Dr. Trond Arne Undheim deliver an urgent and incisive exploration of when, how, and why to augment your workforce with technology, and how to do it in a way that scales, maintains innovation, and allows the organization to thrive. The key thing is to prioritize humans over machines. Here's what Klaus Schwab, Executive Chairman of the World Economic Forum, says about the book: "Augmented Lean is an important puzzle piece in the fourth industrial revolution." Find out more on www.augmentedlean.com, and pick up the book in a bookstore near you. TROND: Speaking about the World Economic Forum for a minute, Johan, you have been part of this group project called the Augmented Workforce Initiative. You told me when we spoke earlier that, in your opinion, this initiative couldn't have existed even just five years ago. Can you explain what you mean by that? Because augmentation, the way that you've been speaking about it now, is a perspective that was nascent, even in the early days of computing and manufacturing control systems. Yet, it seems to have disappeared a little bit, at least from the top end of the political and research agenda. Yet here we are and you said this initiative couldn't have existed five years ago. Can you explain what you meant by that? JOHAN: That is a very, very nice initiative by the World Economic Forum, and it's run by the forum and Cambridge University, who has a very, very good group on this and some very nice people. And I'm honored to be part of that group together with my colleague from Mexico, David Romero. You may know him as well. And I think that what they're looking at is the increased understanding. And that was actually one of the sessions at this World Economic Forum, you know, the Davos days that were run this year. And it was actually part of those days as a theme about how to engage, and how to support, and to augment the workforce, which has never happened before on that level. So it's really, really high on the agenda. The Forum has been running previous projects also on the future of work and how the demographic situation is affecting or how the skill situation is affecting the companies. They have come up with suggestions that more or less half the workforce needs to be upskilled within the next couple of years. And that's a huge undertaking. TROND: The novelty here is that the world's elite managers, I guess, who are represented at the World Economic Forum are increasingly aware of the complexity of workforce issues generally, and then specifically of upskilling, and maybe even upskilling in this very specific meaning of augmenting a worker which, I guess to my mind, is a little bit different from just generally speaking about robotic automation and hammering these efficiency points. But obviously, it's a much more challenging debate because it's one thing to find a budget for an automation effort and introduce a lot of computers or introduce a lot of whatever technology, usually hardware, but what we're talking about here is a lot more challenging because you need to tailor it to these workers. And there are many workers, obviously, so it's a complicated phenomenon. How is that going? What would you say are some of the findings of the Augmented Workforce Initiative? JOHAN: I think that companies like Tulip, companies like Black & Decker, and others have a lot of good use cases actually already, which may or may not before have been labeled augmentation. It might have been labeled as operator support, or decision-making support, or things like that, or upskilling. But I think that the findings are that there is a lot out there, but it's not emphasized as something that is really important for the company's survival in that sense. TROND: It wasn't so glorified before. A lot of the decision support systems were viewed as lower-level systems that were just kind of more like HR systems or just tinkering with necessary stuff that people had to know kind of a thing. And so you're saying it's been elevated now, yeah, as having a much more essential impact on the quality of work. JOHAN: It has a leveraging impact for the whole company, I would say, but that's also part of this industry 4.0 approach. And you have the hierarchical integration of companies where the CEO should be aware of what's going on on the shop floor and vice versa, as well as the horizontal integration where you have the companies up and down the supply chain and value chain knowing what's going on early. And that is really something that maybe stopped at mid-management level before, but now it needs to be distributed out to the places where the complexity is higher, and that's the frontline workers. Maybe...now I'm guessing, but I think that also the understanding that the investments done by this company in complex manufacturing equipment could be at risk if you don't have the right skills to use them is now penetrating, I think, a lot of the companies. In Europe, in 2019 or something like that, there were almost 30 million people employed in the manufacturing industry. And if you look at the number of...if you say that half of these need to be upskilled somehow over a period of three years...and I actually made a mock calculation that the re-skilling need for in-person months in Europe if we were to fulfill this is 50 million person-months, 50 million person-months, just the time for the people to participate in these trainings. So that's a huge undertaking. And I think that that scares companies as well as governments because just imagine taking 50 million person-months out of productivity or the production equation. But the alternative might be worse. If you lose your capability to use your equipment, that might even be worse. TROND: Wow, these are daunting things. I guess that brings me to the last section here and some thoughts from you on the future outlook. When it comes to technology and these tools for human augmentation, what are the timelines for, well, either making the improvements or, as you said, not losing competitiveness because of this skills crisis? What are we looking at here? Is there some imminent challenge and opportunity? Or is this going to play out over 25 years? JOHAN: I think that in 25 years, the demographic situations will have changed again, so I assume that they will look different. But right now, we have a problem with an aging population. And we have a lot of people going into retirement. A lot of knowledge will disappear unless we can store it somehow. A lot of people will not go into industry. I mean, when I talk to colleagues, they say, "Well, we need to make the manufacturing industry more sexy. It should be cleaner, or it should be nicer because young people don't go to industry." But if I go to the healthcare section, they will say the same thing, "Oh, we need to make it much better because people are not applying for these educations." TROND: [laughs] Where are people applying, the tech companies? JOHAN: No, that's the problem. They don't exist. They were never born. TROND: [laughs] Right. JOHAN: So the demographic bomb is that they are actually not there. So you cannot rely on employing young people because they are not existing in Europe and soon not in the U.S. to the extent that they were before. So therefore, you need to focus on the older people. So you need to re-upskill not only the middle-aged people but the people in their 50s and even in their 60s. That adds to the complexity. In the next 5 to 10 years, there will be a lot of discussions on how to fill the missing places in industry to remain competitive. I also think that you can see the augmentation here as a fantastic tool together with the upskilling because upskilling the new skills together with the augmented tools like collaborative robots, like cognitive support, like whatever you can put in an iPhone, or whatever phone, or tool, or watch, or whatever, you can add the capability to make decisions. And that's the augmentation you will see. And you will see a lot of digital twins try to foresee problems. You will see a lot of transversal technologies going from different high-tech industry into manufacturing industry to support especially the frontline people and to enable their innovation capabilities. TROND: Johan, you said earlier that the complexity is higher at the level of frontline workers. Did you mean that, basically, the complexity of frontline work of itself at an individual level is also underestimated? Or were you simply saying that because there are so many frontline workers and the various situations of various types of frontline workers is so different that it's obviously an underappreciated management challenge? Or were you truly saying that frontline work in and of itself is either complicated or becoming more complex? JOHAN: If a task was not automated, it is inherently complex. So you couldn't automate it, right? TROND: Right. JOHAN: Because if you can teach a robot or whatever to do tasks, then it's not difficult, and you can foresee the results. There was a lady called Lisanne Bainbridge. She put out The Paradox of Automation that the more you automate, the more dependent you become on the few people that are still there to handle the situations that are so complex that you could not foresee them. So everything that is programmed is programmed by a programmer, and the programmer tries to foresee every foreseeable situation, and to that extent, the robots and the automation works. But if these situations go out of hand, if they're too complex, and something happens, then there is no robot that can fix that. Unfortunately, AI is not there yet. TROND: Well, you said, "Unfortunately, AI is not there yet," but I would also conjecture that, fortunately, AI is not there yet because you're pointing to something missing, I think. And a lot of the AI debate is starting to come back now. And it was there in the '60s because people realized that for lots of different reasons, to have a human oversight over robotic processes is actually a good thing. And you talked to me earlier about the experiments with imagining a trip to Mars and having to execute robotic actions on Mars in a control system environment where you actually had to foresee the action and plan; it was always a supervised type of situation. So the supervisory control concept has been there from the beginning of computing. If you were to think of a future where AI actually does get more advanced, and a lot of people feel like that's imminent, maybe you and I don't, but in any case, let's imagine that it does become more advanced and becomes sort of a challenge, how do we maintain human control over those kinds of decisions? I mean, there are researchers that have imagined, you know, famously in Superintelligence, Bostrom imagines this paperclip factory that goes amok and starts to optimize for producing paperclips, and everyone is suddenly producing, you know, and the machine then just reallocates resources to this enormously ridiculous task of producing only paper clips. It's a very memorable example. But a lot of people feel that AI could soon or at some point reach that level. How do we, as a failsafe, avoid that that becomes an issue? Or do you see it as such a far-fetched topic in manufacturing that it would be decades, if not centuries, away? JOHAN: I think that AI has been seasonal if you allow the expression. There's talk about these AI winters every now and then, and they tend to come every 10 or 15 years, and that matches two Ph.D. lifetimes, Ph.D. development. I mean, people tend to forget the problems, and then they tend to use these Gartner curves. If you look at the Gartner curve, you have the expectation part. I'm not being arrogant towards the AI research. I think that AI is fantastic, but it should be seen, from my perspective, as what it is, as an advanced form of automation that can be used as an augmentation tool. I think it was Kasparov that started to collaborate with a chess computer maker or developer, and they won every tournament because the combination of the human and the chess computer was astounding. And now I think there are even competitions with chess computers plus chess experts comes with them. There was, I think, in the 1800s, there was a traveling exhibitionist where they had the Mechanical Turk, I think it was called. It was a chess player that was competing then against the people in the audience. And actually, inside this box, there was a small human that was making all the chess moves. And they were beating all the chess champions. So there was a man inside this. I think that there is still a man inside a lot of the automation. TROND: A man and a woman. I wanted to just lastly end on a more positive note because you told me earlier that you are more optimistic now than ten years ago on behalf of your industry that you've researched for so many years. Why is that? JOHAN: I think that the technology, I mean, I'm a techno-optimist. And I think that we have also the full scale, the full attention from the ICT industry on various industrial processes right now. It was a lot of service-oriented. And I think that that is playing out now in the platform wars, the different services, but these different services are actually making a lot of good in the manufacturing and the tougher industries. And so, there is a bigger focus now on creating CO2-less steel. And there's an exploration of different industries that are going across; you look at the electrification of vehicles which is cutting across several sectors in the industry, automotive industry, electronics industry. And I think that the problems in industry are becoming so complex. So the ICT attention is on industry now more than perhaps on consumers, as it were, and I think that that's promising. I see companies like Ericsson promoting 5G. I see companies doing the Amazon Web Services and such companies looking at services that are useful for industry. And that's also augmenting the people's capability in that sense, so that's why I'm so positive. I see all the sensors coming. I see all the computing power coming into the hands of the frontline operators. And I see also the use for the upskilling and the skilling technologies that are emerging. How do you do that? What they do in Matrix when the leading lady downloads the instructions for the helicopter or motorcycle or whatever it is. But how do you do that in real life? How do you prepare for something that's coming in the next few minutes? That is something that people are now looking at using technologies, augmenting technologies, digital twins, and things like that in a completely different way than they were five years ago. TROND: Wow. So these are exciting moments for learning in manufacturing with perhaps wide-ranging consequences if we succeed. Johan, I thank you so much for these reflections. You've spent a career investigating production systems, and manufacturing, and workers. And these are very rich debates. And it seems like they're not over, Johan. So, hopefully, we'll have you back when something happens. And we'll have you comment on some developments. Thank you very much. JOHAN: Thank you, Trond. Thank you for a very interesting discussion. You always learn a lot by being asked a lot of questions, so thank you so much for this learning experience. Thank you. TROND: You're very gracious. Thank you, Johan. You have just listened to another episode of the Augmented Podcast with host Trond Arne Undheim. The topic was a Scandinavian Perspective on Industrial Operator Independence. Our guest was Johan Stahre, Professor and Chair of Production Systems at Chalmers University of Sweden. In this conversation, we talked about how the field of human-centered automation has evolved. My takeaway is that human-centered automation is the only kind of automation that we should be thinking about, and this is becoming more and more clear. Operators are fiercely independent, and so should they be. This is the only way they can spot problems on the shop floor, by combining human skills with automation in new ways augmenting workers. It seems the workforce does not so much need engagement as they need enablement. Fix that, and a lot can happen. Thanks for listening. If you liked the show, subscribe at augmentedpodcast.co or in your preferred podcast player, and rate us with five stars. If you liked this episode, you might also like Episode 84 on The Evolution of Lean with Professor Torbjørn Netland from ETH Zürich. Hopefully, you'll find something awesome in these or in other episodes and if so, do let us know by messaging us. We would love to share your thoughts with other listeners. The Augmented Podcast is created in association with Tulip, the frontline operation platform that connects people, machines, devices, and systems in a production or logistics process in a physical location. Tulip is democratizing technology and empowering those closest to operations to solve problems. Tulip is also hiring, and you can find Tulip at tulip.co. Please share this show with colleagues who care about where industry and especially about where industrial tech is heading. To find us on social media is easy; we are Augmented Pod on LinkedIn and Twitter and Augmented Podcast on Facebook and YouTube. Augmented — industrial conversations that matter. See you next time. Special Guest: Johan Stahre.

In der heutigen Folge „Alles auf Aktien“ sprechen die Finanzjournalisten Anja Ettel und Holger Zschäpitz über die britische Notenbank als Kavallerie der Märkte, die Gaspreisdeckel-Klatsche für Energiefresser und frischen Wind fürs Depot. Außerdem geht es um Porsche, Biogen, Eisai, Roche, Morphosys, Eli Lilly, ThyssenKrupp, Salzgitter, Commerzbank, Deutsche Bank, Apple, VW, Glencore, Ginkgo Bioworks, Invitae, Twist, 10x Genomics, Uipath, Invesco Wind Energy (WKN: A3DP7S), Global X Wind Energy (WKN: A3C9MA), Orsted, Siemens Gamesa, Vestas, Boralex, Axiona Energias Renovables, Ming Yang Smart Energy, SGL Carbon, SKF, Encavis, Energiekontor und Brookfield Renwable. Wir freuen uns an Feedback über aaa@welt.de. Disclaimer: Die im Podcast besprochenen Aktien und Fonds stellen keine spezifischen Kauf- oder Anlage-Empfehlungen dar. Die Moderatoren und der Verlag haften nicht für etwaige Verluste, die aufgrund der Umsetzung der Gedanken oder Ideen entstehen. Für alle, die noch mehr wissen wollen: Holger Zschäpitz können Sie jede Woche im Finanz- und Wirtschaftspodcast "Deffner&Zschäpitz" hören. Impressum: https://www.welt.de/services/article7893735/Impressum.html Datenschutz: https://www.welt.de/services/article157550705/Datenschutzerklaerung-WELT-DIGITAL.html

On the ninety-third episode of Collecting Real Estate, we interviewed Michael & Lindsey Duguet from Clover Key Capital.Michael & Lindsey became interested in Real Estate Investing in 2018. They started their educational journey by reading REI books, listening to podcasts & being active on Bigger Pockets. They joined Real Estate Elevated for intensive training & founded Duguet Estates March 2019.  Their first off-market single family homes were purchased in May 2019, followed by a duplex in June 2019. They started direct mail campaigns and bought a 4-plex & 3 single family homes throughout the rest of 2019. 10-plex bought with off-market advertising in December 2020. All acquisitions completely remodeled (most full gut jobs) & now are stabilized and all cash-flowing. They have enjoyed huge equity gains through forced appreciation. They have successfully BRRRR'd with 100%+ cash out refinances on half of their portfolio which they have rolled over into new deals.  Michael & Lindsey MIH Mastermind in 2022 and formed Clover Key Capital in May 2022. Their first syndication deal closed June 2022 in Indianapolis, IN. They and their partners have $5.5 million prefunded & thousands of units owned together. They are actively looking for C+ to B+ class value-add, 1960+ build apartment complexes. Michael Duguet Michael was born and raised in France. He completed his Master's Degree from Centrale Nantes. Mechanical Engineer for SKF & immigrated to the US as Project manager overseeing multimillion dollar projects as well as designing applications for the railway industry. Owner and founder of Menfashion.com; a high-end Men's dresswear company. Michael met Lindsey while living in Philadelphia & they married in 2016. Michael enjoys beating personal records on the Peloton bike, playing on soccer leagues, spending time with his family and cooking (his parents own restaurants in France and he grew up in the restaurant business). He is now working full-time for their REI portfolio as a master underwriter, asset manager & IT specialist. Together Lindsey & Michael are the parents of three beautiful children. They are focused on generational wealth syndications for their family. Contact (484)999-3001  Michael@DuguetEstates.com DuguetEstates.com Lindsey Duguet Lindsey was born and raised in Pennsylvania. She received her bachelor's degree in Neuroscience Psychology & Biology from Pennsylvania State University. Graduated from Philadelphia College of Osteopathic Medicine with Doctor of Medicine degree. Completed Emergency Medicine Residency with Geisinger Medical Center. Currently an Emergency Medicine & Trauma Physician at Geisinger Wyoming Valley & Director Geriatric Emergency Department. Lindsey enjoys personal fitness with the Peloton bike, creating artwork (graphite, pen & ink drawings, acrylic & oil paintings), outdoor activities (hiking, horseback riding) & spending time with family. Currently focused on broker relations, deal finding, capital raising & investor relations. Motivated go-givers who are accelerating the health and wealth of themselves & others! Contact (484)999-3222  Lindsey@DuguetEstates.com CloverKeyCapital.com  

In der heutigen Folge „Alles auf Aktien“ sprechen der Finanzjournalist Holger Zschäpitz und Tech-Ikone Philipp Klöckner über das nächste große Politik-Risiko für die Märkte, Massenentlassungen bei Robin Hood und den Rücktritt des Bitcoin-Jüngers. Außerdem geht es um Zalando, Rheinmetall, Symrise, Uber, AirBnB, Robinhood, Paypal, Oatly, Teamviewer, Mercado Libre, Lufthansa, Apple, Tesla, AMD, Intel, Micron, Nvidia, Broadcom, Qualcom, NXP, Texas Instruments, Albermale, Livent, 3M, Dupont, Emerson Electric, Nike, Starbucks, Wolfspeed, LVMH, Hermes, Kering, Adidas, Moncler, Puma, Richemont, Remy Contreaux, VW, Mercedes, BMW, Airbus, ASML, Infineon, Rio Tinto, Anglo American, Merck, Astrazeneca, Atlas Copco, Kone, SKF, Knorr Bremse, WisdomTree Cloud Computing ETF (WKN: A2PQVE), WisdomTree Cybersecurity (WKN: A2QGAH). Wir freuen uns an Feedback über aaa@welt.de. Disclaimer: Die im Podcast besprochenen Aktien und Fonds stellen keine spezifischen Kauf- oder Anlage-Empfehlungen dar. Die Moderatoren und der Verlag haften nicht für etwaige Verluste, die aufgrund der Umsetzung der Gedanken oder Ideen entstehen. Für alle, die noch mehr wissen wollen: Holger Zschäpitz können Sie jede Woche im Finanz- und Wirtschaftspodcast "Deffner&Zschäpitz" hören. Impressum: https://www.welt.de/services/article7893735/Impressum.html Datenschutz: https://www.welt.de/services/article157550705/Datenschutzerklaerung-WELT-DIGITAL.html

Fallgropar i den kommande rapportperioden, varför Sandvik slår SKF, Nordens aktiedrottning och hur fondförvaltare agerar under rapportdagarna. I detta avsnitt av Placerapodden gästas Martin Blomgren av förvaltarna Lotta Faxén och Peter Lagerlöf från Lannebo Fonder.

In der heutigen Folge „Alles auf Aktien“ sprechen die Finanzjournalisten Daniel Eckert und Holger Zschäpitz über eine spannende Dekarbonisierungs-Wette, die neueste Wortkreation der EZB und verraten günstige Urlaubsziele Außerdem geht es um Gerresheimer, HP, Berkshire Hathawy, Bitcoin, Mercedes-Benz Group, Verbio, Meta, Vodafone, Allianz, Bâloise Holding, Legal & General, Münchener Rück, Telenor, Elisa, SKF, Securitas, Electrolux, Husqvarna, Unilever, Deutsche Post, UPM Kymene, EDP, Sanofi, Fuchs Petrolub, Evonik, TAG Immobilien. Cewe, Bechtle, VIN Immobilien, LEG Immobilien, Xtrackers SLI ETF (WKN DBX1AA), Arero Der Weltfonds (WKN DWS0R4). Link zur Podcast-Abstimmung: https://www.deutscher-podcastpreis.de/podcasts/aaa-alles-auf-aktien/ Wir freuen uns an Feedback über aaa@welt.de. Disclaimer: Die im Podcast besprochenen Aktien und Fonds stellen keine spezifischen Kauf- oder Anlage-Empfehlungen dar. Die Moderatoren und der Verlag haften nicht für etwaige Verluste, die aufgrund der Umsetzung der Gedanken oder Ideen entstehen. Hörtipps: Für alle, die noch mehr wissen wollen: Holger Zschäpitz können Sie jede Woche im Finanz- und Wirtschaftspodcast "Deffner&Zschäpitz" hören. Außerdem bei WELT: Im werktäglichen Podcast „Kick-off Politik - Das bringt der Tag“ geben wir Ihnen im Gespräch mit WELT-Experten die wichtigsten Hintergrundinformationen zu einem politischen Top-Thema des Tages. Mehr auf welt.de/kickoff und überall, wo es Podcasts gibt. +++Werbung+++ Hier geht's zur App: Scalable Capital ist der Broker mit Flatrate. Unbegrenzt Aktien traden und alle ETFs kostenlos besparen – für nur 2,99 € im Monat, ohne weitere Kosten. Und jetzt ab aufs Parkett, die Scalable App downloaden und loslegen. Hier geht's zur App: https://bit.ly/3abrHQm Impressum: https://www.welt.de/services/article7893735/Impressum.html Datenschutz: https://www.welt.de/services/article157550705/Datenschutzerklaerung-WELT-DIGITAL.html

Atlas Copco, Sandvik och SKF säljer utrustning till ryska tillverkare av kärnvapen Svenska verkstadsbjässarna Atlas Copco, Sandvik och SKF har sålt utrustning som använts i Rysslands kärnvapentillverkning, enligt Expressen som hänvisar till dokument och avtal från ryska upphandlingar. Bland annat kom den ryska federationens nukleära center att under förra året göra flera upphandlingar för att köpa in utrustning från bolagen. Atlas Copco bekräftar försäljningen och säger att man brustit i sina kontroller. ”Här har vi brustit i våra kontroller då vi innan försäljning ska säkerställa att vår leverans endast avser civila ändamål i de fall kunden verkar både inom civil och militär industri”, sade kommunikationsdirektören Sara Hägg Liljedal till Expressen. Atlas Copco har inlett en utredning. Från Sandviks håll konstateras det att återförsäljarna inte levt upp till reglerna. Samtidigt rapporterar Dagens industri om att bolagets vändskär använts i tillverkningen av raketartillerisystemet Grad. Detta tillverkas vid en vapenfabrik i ryska Perm och har använts i Ukrainakriget. Sandvik förnekade inte affärsrelationen när Di tog upp kontakten. Svaret till tidningen blev att man ”genomför i dagsläget inga leveranser eller tecknar nya avtal i Ryssland”. Till förvåning för ingen alls i dessa dagar... #CarlNorberg #DeFria De Fria är en folkrörelse som jobbar för demokrati genom en upplyst och medveten befolkning! Stöd oss: SWISH: 070 - 621 19 92 (mottagare Sofia S) PATREON: https://patreon.com/defria_se HEMSIDA: https://defria.se FACEBOOK: https://facebook.com/defria.se

Welche ökonomischen Auswirkungen haben Deglobalisierungszenarien für den Maschinenbau, und wie sähe die Zukunft dieser Branche aus, wenn die Globalisierung zurückgedreht würde?  Die Märkte müssen offenbleiben, sagt Dr. Ralph Wiechers, Chef-Volkswirt des VDMA. Susanna Schneeberger, zuletzt Digital-Vorstand von KION und Aufsichtsrat bei SKF, beleuchtet den operativen Ansatz, und Martin Neuhold, Partner bei EY, rundet die spannende Diskussion mit der strategischen Perspektive ab.   Wir freuen uns auf euer Feedback! Schreibt uns an podcast@de.ey.com

Die Märkte müssen offenbleiben, sagt Dr. Ralph Wiechers, Chef-Volkswirt des VDMA. Susanna Schneeberger, zuletzt Digital-Vorstand von KION und Aufsichtsrat bei SKF, beleuchtet den operativen Ansatz, und Martin Neuhold, Partner bei EY, rundet die spannende Diskussion mit der strategischen Perspektive ab.   Wir freuen uns auf euer Feedback! Schreibt uns an podcast@de.ey.com

This week on The Blitz, we sit down with University of South Carolina Sumter athletic director and head softball coach Adrienne Cataldo to talk about what it's like to juggle both of those roles, how she's tried to help her athletes navigate the pandemic and what she's looking forward to the most about getting back to normal. If you're looking for an update on the state of Fire Ant athletics, you're not going to want to miss this episode.We're on Spotify and iTunes too!The Blitz is a part of The Item Podcast Network proudly presnted by SKF Sumter. Welcome to the world of reliable rotation! To apply today go to SKF.com

With iPhone and custom apps developed with the SAP Cloud Platform SDK for iOS, SKF has simplified core business processes, increased employee productivity, and eliminated production errors in the channel. Factory workers are more mobile and enjoy a user experience that simply wasn't possible before with seamless access to SAP systems.