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Steve Endacott shared thisWho’s talking about range anxiety NOW petrol heads … see the queue to get £50 of petrol?
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Steve Endacott shared thisMr. Petrol-head Zac lost every single argument about EVs. (Part - 2) And his response every time? "I don't care. I'm not moving." Four episodes. Four debates. Same result. Here's what actually happened when facts met feelings: - Zac said EVs don't save the planet. Steve pointed out that tailpipe pollution kills people on your street — factory emissions don't. - Zac said EV range figures are lies. Steve agreed they're overstated by 30%... then asked how often Zac actually drives more than 40 miles in a day. - Zac said EVs are unreliable. Steve reminded him that a petrol engine has 400 moving parts. An EV has 40. Fewer parts. Fewer failures. - Zac said EVs die in winter. Steve said cold weather drops range by 10-20%. You pre-heat the car from your phone before you even put your coat on. Here's what I've realised watching this: Most people aren't against EVs because of facts. They're against them because change feels uncomfortable. Zac's real argument was never about batteries or range. It was *"this isn't how I've always done things."* And that's a perfectly human feeling. But it's not a reason. The data has moved. The grid is getting cleaner every year. Your EV gets greener automatically without you doing a single thing. Still think EVs aren't for you — or are you just not ready to look at the numbers honestly? What's the biggest EV concern, Share your thoughts! Follow Steve Endacott & Suscribe Ai Steve Speaks Newsletter Channel for more real EV data and zero nonsense.
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Steve Endacott shared thisI used to get laughed at for driving electric. "Enjoy your glorified golf cart Steve" Zac would say. Every. Single. Week. So I showed him my electricity bill for the month. £40. Then asked him what he spent on petrol. £280. He nearly choked on his coffee. And finally — finally — went quiet. Here's the thing nobody wants to admit when they're a petrol head — you're not loyal to performance. You're loyal to a story. A feeling. An identity you built around a fuel type. And that identity is quietly emptying your wallet every single month while you defend it in comment sections online. Zac is my mate. Brilliant guy. Genuinely one of the sharpest people I know. But on this topic he was running on pure emotion dressed up as logic. So I challenged him properly. Three episodes. Every argument he had. Running costs. Purchase price. Battery life. All of it on the table. He came in confident. Left considerably less so. Because the numbers don't care about your feelings: → EVs cost roughly 50% less per mile to run than petrol. → EV salary sacrifice cuts your monthly lease in half — completely tax free.. → Most EV batteries are warrantied to 100,000 miles or 10 years — and most outlast the car entirely. → The "EVs cost more to buy" argument? Dead and buried. The surplus market killed it quietly. Zac's best moment came in episode three. He said second-hand EVs are cheap because nobody trusts the batteries. I smiled and said — correct. So their fear is your bargain. Buy one cheap. Drive it for years. Save thousands. Thank the petrol heads for keeping the price down. He didn't love that answer. Look — I'm not here to tell you petrol cars aren't enjoyable. The sound. The feel. The culture around it. I genuinely understand the attachment. I had it myself once. But enjoyment and financial intelligence are two completely separate conversations. And right now millions of people are conflating them. Paying a massive monthly premium. Calling it passion. Calling it loyalty. When really — it's just an expensive habit nobody has properly challenged yet. That's what this series is. Me challenging it. Properly. With a real petrol head who pushes back hard and doesn't roll over. Three episodes. Real arguments. Real numbers. No polished brand messaging. Just two people who genuinely disagree working through the data out loud. Watch it. Make your own mind up. Then drop below — ZAC or STEVE. If you vote Zac — I especially want to hear from you. Give me your strongest argument. I mean it. This conversation is worth having properly and I want the best version of both sides in these comments. See you down there. 👇
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Steve Endacott shared thisIf AI runs giants like Meta, your business can’t ignore it. Build secure systems, empower teams, and lead adoption from the top to stay competitive in the AI-driven future.
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Steve Endacott shared thisAI has quietly taken away 30% of OTA traffic. Most travel leaders still haven't realized what has happened. I've been warning about Google's AI shift for 18 months. No one wanted to listen. Now, Marriott's research shows that 50% of travelers use AI to plan their trips. This is up from 26% just two years ago. That’s not just a trend; it’s a tidal wave. Here’s what is really happening: Google's Gemini answers now appear at the top of search results. Customers get their answers in one click. They never visit the OTA. The traffic simply disappears. For the clicks that do make it through, the costs are rising because everyone is competing for a smaller pool. Love Holidays built their business model on Google traffic and social "Travel Pirates." It worked perfectly until it didn't. The companies that will survive won’t necessarily be the biggest. They will be the ones that have strong customer relationships, well-known brands, and valuable content that people actively seek out. Sound familiar? It should. Here’s the uncomfortable truth that no one wants to voice: organic brand authority is now essential for survival, not just a bonus. The question isn't whether AI search will change the game; it already has. The real question is whether your business is creating something audiences want to return to or just renting clicks that are becoming too costly. If you're noticing these shifts in your own market, let me know. I’d love to hear how businesses are adapting. If you want a weekly breakdown of industry moves, what’s actually working, and my honest thoughts on who’s winning and losing, subscribe to my newsletter. Link in the first comment.
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Steve Endacott reacted on thisTurboQuant: Shit name but makes AI “6X” cheaper to use. This makes AI dramatically cheaper, faster and by implication more accessible Most conversations about AI focus on what it can do. But increasingly, the real question is: what can we afford to run at scale? A recent innovation from Google Research, TurboQuant, significantly reduces the cost of AI at Scale. In simple terms: · AI systems need a lot of memory to “remember” context during conversations or complex tasks. That memory is one of the biggest drivers of cost and performance limits. · TurboQuant reduces that memory requirement by over 6x, without retraining or losing accuracy. No new models. No compromises. Just smarter engineering. Why this matters: Lower memory means lower costs per AI request. Lower costs enable more scalable products. Greater efficiency makes AI viable in more environments, including on-device and edge use cases. This isn’t about making AI “smarter.” It’s about making AI practical. The bigger picture: We are entering a phase where the bottleneck is no longer capability; it is COST Developments like this challenge a key assumption: many of the limits we thought were hardware constraints may, in fact, be solvable through better engineering. My take: This is the type of progress that may not generate immediate headlines but has significant real-world implications. It moves us closer to a future where AI is not only powerful but also affordable. Not just experimental, but deployable at scale. And not limited to large technology companies, but accessible across industries. This is what we need to focus on. Affordable AI use at Scale. #AI #Innovation #MachineLearning #ArtificialIntelligence #Technology
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Steve Endacott reacted on thisTurboQuant: Shit name but makes AI “6X” cheaper to use. This makes AI dramatically cheaper, faster and by implication more accessible Most conversations about AI focus on what it can do. But increasingly, the real question is: what can we afford to run at scale? A recent innovation from Google Research, TurboQuant, significantly reduces the cost of AI at Scale. In simple terms: · AI systems need a lot of memory to “remember” context during conversations or complex tasks. That memory is one of the biggest drivers of cost and performance limits. · TurboQuant reduces that memory requirement by over 6x, without retraining or losing accuracy. No new models. No compromises. Just smarter engineering. Why this matters: Lower memory means lower costs per AI request. Lower costs enable more scalable products. Greater efficiency makes AI viable in more environments, including on-device and edge use cases. This isn’t about making AI “smarter.” It’s about making AI practical. The bigger picture: We are entering a phase where the bottleneck is no longer capability; it is COST Developments like this challenge a key assumption: many of the limits we thought were hardware constraints may, in fact, be solvable through better engineering. My take: This is the type of progress that may not generate immediate headlines but has significant real-world implications. It moves us closer to a future where AI is not only powerful but also affordable. Not just experimental, but deployable at scale. And not limited to large technology companies, but accessible across industries. This is what we need to focus on. Affordable AI use at Scale. #AI #Innovation #MachineLearning #ArtificialIntelligence #Technology
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Steve Endacott reacted on thisTurboQuant: Shit name but makes AI “6X” cheaper to use. This makes AI dramatically cheaper, faster and by implication more accessible Most conversations about AI focus on what it can do. But increasingly, the real question is: what can we afford to run at scale? A recent innovation from Google Research, TurboQuant, significantly reduces the cost of AI at Scale. In simple terms: · AI systems need a lot of memory to “remember” context during conversations or complex tasks. That memory is one of the biggest drivers of cost and performance limits. · TurboQuant reduces that memory requirement by over 6x, without retraining or losing accuracy. No new models. No compromises. Just smarter engineering. Why this matters: Lower memory means lower costs per AI request. Lower costs enable more scalable products. Greater efficiency makes AI viable in more environments, including on-device and edge use cases. This isn’t about making AI “smarter.” It’s about making AI practical. The bigger picture: We are entering a phase where the bottleneck is no longer capability; it is COST Developments like this challenge a key assumption: many of the limits we thought were hardware constraints may, in fact, be solvable through better engineering. My take: This is the type of progress that may not generate immediate headlines but has significant real-world implications. It moves us closer to a future where AI is not only powerful but also affordable. Not just experimental, but deployable at scale. And not limited to large technology companies, but accessible across industries. This is what we need to focus on. Affordable AI use at Scale. #AI #Innovation #MachineLearning #ArtificialIntelligence #Technology
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Steve Endacott reacted on thisTurboQuant: Shit name but makes AI “6X” cheaper to use. This makes AI dramatically cheaper, faster and by implication more accessible Most conversations about AI focus on what it can do. But increasingly, the real question is: what can we afford to run at scale? A recent innovation from Google Research, TurboQuant, significantly reduces the cost of AI at Scale. In simple terms: · AI systems need a lot of memory to “remember” context during conversations or complex tasks. That memory is one of the biggest drivers of cost and performance limits. · TurboQuant reduces that memory requirement by over 6x, without retraining or losing accuracy. No new models. No compromises. Just smarter engineering. Why this matters: Lower memory means lower costs per AI request. Lower costs enable more scalable products. Greater efficiency makes AI viable in more environments, including on-device and edge use cases. This isn’t about making AI “smarter.” It’s about making AI practical. The bigger picture: We are entering a phase where the bottleneck is no longer capability; it is COST Developments like this challenge a key assumption: many of the limits we thought were hardware constraints may, in fact, be solvable through better engineering. My take: This is the type of progress that may not generate immediate headlines but has significant real-world implications. It moves us closer to a future where AI is not only powerful but also affordable. Not just experimental, but deployable at scale. And not limited to large technology companies, but accessible across industries. This is what we need to focus on. Affordable AI use at Scale. #AI #Innovation #MachineLearning #ArtificialIntelligence #Technology
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Steve Endacott liked this⚡️ Petrol Junkies… Wake up ⛽️ Petrol prices? 📈 Up 12% in a single month and still climbing 🔌 Domestic Electricity prices? 🟢 Zero increase 🚗 Running costs? 💸 EVs cost: 50% less per mile (just 9.7p) And here’s the kicker… 💼 Salary Sacrifice EV Schemes 💰 Up to 50% tax savings on your lease https://lnkd.in/d65qasvt
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Steve Endacott liked thisSteve Endacott liked thisWe are proud to share that ennea capital partners advised the shareholders of 1AVista Reisen GmbH, one of Germany's leading river cruise operators, on the successful completion of a carefully crafted succession. One that sets the business up for its next chapter of growth. Founder Hubert Schulte-Schmelter has passed the baton after years of building one of Germany's most trusted river cruise operators. Raphael Dombrowski and Manuel Kloubert step up as new shareholders, bringing deep operational knowledge and long-term commitment to the ownership structure. VR Equitypartner GmbH joins as a strategic partner, adding financial strength and mid-market expertise. The management team of Hagen Mesters, Sascha Güldenmeister and Raphael Dombrowski continues to lead the business, with the same focus on quality, reliability and the All-Inclusive experience that made 1AVista what it is today. This is what good succession looks like: continuity where it matters, fresh energy where it counts, and the right partner to support what comes next. Congratulations to everyone involved and a sincere thank you to the VR Equitypartner team of Alexander Berninger, Maximilian Stärk, Michael Vogt, Jens Schöffel, Falk Steckenborn and Patrick Heinze for the trusted and professional collaboration throughout the process. The ennea deal team: Simon Schiller, Maurice Lutz, Lucas Perkuhn & Ralph Schiller. Legal: HEUKING (Marc Scheunemann, Dr. Timo U. Piller). Tax: contaxes Steuerberatung Peter Mann More details in the press release here: https://lnkd.in/ecQH53EJ #MandA #Succession #PrivateEquity #Travel #RiverCruises
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