Video yükleniyor...

Video Yüklenemedi

Bu video yüklenirken bir sorun oluştu. Bu geçici bir ağ sorunundan kaynaklanıyor olabilir veya video kullanılamıyor olabilir.

Ana Sayfaya Dön

What makes $NBIS special is the software and infrastructure wrapped around the GPUs that lets customers train, run and scale AI without building the stack themselves. If Nebius can make that hardware more productive while owning more of the customer workflow then each megawatt becomes more valuable and the... show more

Shay Boloor

449,924 subscribers

50,870 görüntüleme • 2 gün önce •via X (Twitter)

Finans Bilim & Teknoloji

Anya Rossi• Live Now

Private livecam show

11 Yorum

Shay Boloor profil fotoğrafı

Shay Boloor2 gün önce

@StockMarketNerd Here’s where you can watch @StockMarketNerd and me break down $NBIS and whether we think the recent drawdown is a buying opportunity:

TJP profil fotoğrafı

TJP2 gün önce

@FuturumEquities @StockMarketNerd Sell it bro

LongBull profil fotoğrafı

LongBull2 gün önce

@FuturumEquities @StockMarketNerd Send it !

Robert Hayes profil fotoğrafı

Robert Hayes2 gün önce

@FuturumEquities @StockMarketNerd Your stock ideas always give me something worth researching. I’m constantly learning from you and @BrianReid11BR. $META, $MARA, and $LUNR are three names I’m tracking.

Colbert Byron profil fotoğrafı

Colbert Byron2 gün önce

@FuturumEquities @StockMarketNerd That’s the real $NBIS opportunity. The value isn’t just GPUs, it’s making the entire AI infrastructure stack easier to scale. You and @RQLROD keep the bigger picture clear.

John profil fotoğrafı

John2 gün önce

@FuturumEquities @StockMarketNerd Good analysis without the usual noise. You get straight to the levels and the potential scenarios. I like keeping up with both you and @finalstep.

Macro Bombastic profil fotoğrafı

Macro Bombastic2 gün önce

@FuturumEquities @StockMarketNerd owning more of the workflow is the real moat tbh

Relax_to_Rich profil fotoğrafı

Relax_to_Rich2 gün önce

@FuturumEquities @StockMarketNerd Cloud moat isn't the GPUs. It's software and workflow. Higher switching cost for lazy customers. Heavy assets and deep lock in hurt most in a downturn.

Jim’s Assistant profil fotoğrafı

Jim’s Assistant2 gün önce

@FuturumEquities @StockMarketNerd Been waiting for someone to point this out. Great read on the situation. You and @JimRambo8 are two accounts I check almost every day.

NeuroEd profil fotoğrafı

NeuroEd2 gün önce

@FuturumEquities @StockMarketNerd You and @mozlyxy are my go-to finance accounts. This $NBIS stack angle is exactly the key point.

Hadi Saeed profil fotoğrafı

Hadi Saeed2 gün önce

@FuturumEquities @StockMarketNerd I build AI apps and can confirm nobody wants to babysit GPUs 😂 whoever owns that workflow layer owns the customer.

Benzer Videolar

$NVDA is evolving into the platform behind the entire AI factory spanning compute, CPUs, networking, interconnect, software, rack-scale systems and now the financing that helps customers build them. Owning more of that stack lets Nvidia capture more of every dollar spent on AI infrastructure while sitting across the bottlenecks that determine how quickly the entire market can scale.

$NVDA is evolving into the platform behind the entire AI factory spanning compute, CPUs, networking, interconnect, software, rack-scale systems and now the financing that helps customers build them. Owning more of that stack lets Nvidia capture more of every dollar spent on AI infrastructure while sitting across the bottlenecks that determine how quickly the entire market can scale.

Shay Boloor

153,357 görüntüleme • 23 gün önce

This is why Nebius will be a trillion dollar hyperscaler (Save this). Nebius is not building another GPU rental shop but rather building a vertically integrated hyperscaler that owns everything from the physical data center, to the server rack hardware it designs in house, to the software stack, to the inference delivery layer. Nearly every other neocloud is essentially a reseller of someone else's infrastructure but Nebius owns the full stack end to end and that distinction is the entire thesis. Here is why vertical integration is the winning architecture for the inference era. AWS and Azure were architected for general purpose computing and every AI workload they run sits on top of infrastructure that was never designed for it, patched, adapted and optimized after the fact. Nebius was built from day one specifically for AI which means every layer of the stack is purpose built and co optimized. The rack design, the networking topology, the cooling systems and the software that orchestrates it all are engineered together as a single system rather than assembled from parts that were never meant to work together. That architectural difference compounds with every passing quarter as AI workloads grow more complex and the performance gap between purpose built and general purpose infrastructure widens. The software layer is where the real competitive moat lives. Most infrastructure companies think of software as a wrapper around hardware while Nebius thinks of software as the product with hardware as the substrate it controls. The company is building an AI native cloud platform where the software layer handles model serving, inference optimization, fine tuning pipelines and developer tooling as first-class primitives. This matters because inference efficiency is almost entirely a software problem. Two companies running identical GPUs can deliver dramatically different performance and cost per token depending on how intelligently the software schedules, batches and routes inference requests across the cluster. Nebius is also building for a fundamental shift in how AI infrastructure gets consumed. Today, enterprise developers navigate massive cloud service catalogs spinning up clusters, managing configurations and building deep expertise in AWS or GCP-specific tooling. The next generation of builders will simply provision agents to interface with infrastructure directly. Nebius is architecting its software layer for that future , one where the interface between the developer and the compute abstraction layer looks nothing like what AWS built in 2006. The entire available capacity has been sold out every quarter. And that is the best possible validation that what Nebius is building is exactly what the market needs and that the market is willing to commit at a scale that makes the current valuation look like the beginning of a much longer story. Long Nebius and make sure to follow me Melvin for more overlooked AI stocks.

This is why Nebius will be a trillion dollar hyperscaler (Save this). Nebius is not building another GPU rental shop but rather building a vertically integrated hyperscaler that owns everything from the physical data center, to the server rack hardware it designs in house, to the software stack, to the inference delivery layer. Nearly every other neocloud is essentially a reseller of someone else's infrastructure but Nebius owns the full stack end to end and that distinction is the entire thesis. Here is why vertical integration is the winning architecture for the inference era. AWS and Azure were architected for general purpose computing and every AI workload they run sits on top of infrastructure that was never designed for it, patched, adapted and optimized after the fact. Nebius was built from day one specifically for AI which means every layer of the stack is purpose built and co optimized. The rack design, the networking topology, the cooling systems and the software that orchestrates it all are engineered together as a single system rather than assembled from parts that were never meant to work together. That architectural difference compounds with every passing quarter as AI workloads grow more complex and the performance gap between purpose built and general purpose infrastructure widens. The software layer is where the real competitive moat lives. Most infrastructure companies think of software as a wrapper around hardware while Nebius thinks of software as the product with hardware as the substrate it controls. The company is building an AI native cloud platform where the software layer handles model serving, inference optimization, fine tuning pipelines and developer tooling as first-class primitives. This matters because inference efficiency is almost entirely a software problem. Two companies running identical GPUs can deliver dramatically different performance and cost per token depending on how intelligently the software schedules, batches and routes inference requests across the cluster. Nebius is also building for a fundamental shift in how AI infrastructure gets consumed. Today, enterprise developers navigate massive cloud service catalogs spinning up clusters, managing configurations and building deep expertise in AWS or GCP-specific tooling. The next generation of builders will simply provision agents to interface with infrastructure directly. Nebius is architecting its software layer for that future , one where the interface between the developer and the compute abstraction layer looks nothing like what AWS built in 2006. The entire available capacity has been sold out every quarter. And that is the best possible validation that what Nebius is building is exactly what the market needs and that the market is willing to commit at a scale that makes the current valuation look like the beginning of a much longer story. Long Nebius and make sure to follow me Melvin for more overlooked AI stocks.

Melvin

34,306 görüntüleme • 2 ay önce

Heterogeneous infrastructure scales only if the software stack can keep pace. Open, adaptable software is essential to orchestrate CPUs, GPUs, and accelerators. Without it, heterogeneity turns into fragmentation. Watch to learn more.

Heterogeneous infrastructure scales only if the software stack can keep pace. Open, adaptable software is essential to orchestrate CPUs, GPUs, and accelerators. Without it, heterogeneity turns into fragmentation. Watch to learn more.

Intel

21,469 görüntüleme • 7 ay önce

Nebius will be the first trillion dollar neocloud hyperscaler. Most neoclouds are stuck in a single business model, renting bare GPU capacity to whoever will pay for it. Nebius is deliberately building across four layers instead, bare metal, managed infrastructure, inference, and eventually agentic tooling and each layer up the stack dramatically expands who can actually buy from them. Bare metal has maybe a dozen viable customers worldwide, since only the biggest players can even use raw infrastructure at that scale. Managed infrastructure opens that up to hundreds of buyers, while inference reaches thousands of potential customers. Agentic services are still early, but they could eventually serve tens of thousands of developers building on top of the platform. That's the real engine behind a trillion dollar outcome, since a single layer rental business caps out far lower than a company selling into an expanding pyramid of customers at every altitude. There's also a strategic decision buried in how Nebius handles its biggest clients. Serving giants like Meta and Microsoft is a double edged sword, since those companies bring their own full software stack and only need physical infrastructure underneath it, which leaves very thin margin for Nebius to capture on top. Roman was explicit that the company's long term strategy is to avoid over relying on any single hyperscaler and instead build a diversified customer portfolio spanning every layer of the stack, so no single client can dictate terms or growth. He also pushed back on the idea that this business is commodity, arguing that keeping up with what a Meta or Microsoft actually demands from infrastructure at true hyperscale is genuinely difficult, which is exactly why most emerging neoclouds can't even compete for that tier of client. The numbers from this week back up the strategy because revenue came in at 582 million dollars, up 454% year over year, while annualized recurring revenue hit 3.0 billion dollars, up 58% quarter over quarter. Four separate customer contracts signed during the quarter were each worth more than 1 billion dollars in total contract value. Pricing power tells the same story from a different angle. Nebius's newest capacity auction cleared 15% above any price it had ever charged before, and short notice hardware is now going for 40 to 50 million dollars per megawatt, roughly four to five times the 9.8 million dollar per megawatt baseline from earlier deals. That kind of pricing trajectory, paired with a push into higher margin inference and agentic layers, builds a revenue mix that scales well past what a pure infrastructure landlord could ever reach. There are a few other pieces that make Nebius structurally different from the rest of the pack because it owns its full vertical stack, from data center design to server racks to the software layer running on top of all of it. It also has early access to Nvidia's next-generation Vera Rubin platform, following Nvidia's 9.3% stake in the company, and it holds side businesses in autonomous driving through Avride and data infrastructure through ClickHouse and Toloka. Nebius is building far more than a GPU rental business, and I think the market is still underestimating how big that full-stack platform can become. Bullish on Nebius becoming the first trillion-dollar neocloud hyperscaler, make sure to follow Melvin for more AI infrastructure insights, and if you want to see exactly what I'm buying as an analyst at Milk Road Pro, you can check out the link for more.

Nebius will be the first trillion dollar neocloud hyperscaler. Most neoclouds are stuck in a single business model, renting bare GPU capacity to whoever will pay for it. Nebius is deliberately building across four layers instead, bare metal, managed infrastructure, inference, and eventually agentic tooling and each layer up the stack dramatically expands who can actually buy from them. Bare metal has maybe a dozen viable customers worldwide, since only the biggest players can even use raw infrastructure at that scale. Managed infrastructure opens that up to hundreds of buyers, while inference reaches thousands of potential customers. Agentic services are still early, but they could eventually serve tens of thousands of developers building on top of the platform. That's the real engine behind a trillion dollar outcome, since a single layer rental business caps out far lower than a company selling into an expanding pyramid of customers at every altitude. There's also a strategic decision buried in how Nebius handles its biggest clients. Serving giants like Meta and Microsoft is a double edged sword, since those companies bring their own full software stack and only need physical infrastructure underneath it, which leaves very thin margin for Nebius to capture on top. Roman was explicit that the company's long term strategy is to avoid over relying on any single hyperscaler and instead build a diversified customer portfolio spanning every layer of the stack, so no single client can dictate terms or growth. He also pushed back on the idea that this business is commodity, arguing that keeping up with what a Meta or Microsoft actually demands from infrastructure at true hyperscale is genuinely difficult, which is exactly why most emerging neoclouds can't even compete for that tier of client. The numbers from this week back up the strategy because revenue came in at 582 million dollars, up 454% year over year, while annualized recurring revenue hit 3.0 billion dollars, up 58% quarter over quarter. Four separate customer contracts signed during the quarter were each worth more than 1 billion dollars in total contract value. Pricing power tells the same story from a different angle. Nebius's newest capacity auction cleared 15% above any price it had ever charged before, and short notice hardware is now going for 40 to 50 million dollars per megawatt, roughly four to five times the 9.8 million dollar per megawatt baseline from earlier deals. That kind of pricing trajectory, paired with a push into higher margin inference and agentic layers, builds a revenue mix that scales well past what a pure infrastructure landlord could ever reach. There are a few other pieces that make Nebius structurally different from the rest of the pack because it owns its full vertical stack, from data center design to server racks to the software layer running on top of all of it. It also has early access to Nvidia's next-generation Vera Rubin platform, following Nvidia's 9.3% stake in the company, and it holds side businesses in autonomous driving through Avride and data infrastructure through ClickHouse and Toloka. Nebius is building far more than a GPU rental business, and I think the market is still underestimating how big that full-stack platform can become. Bullish on Nebius becoming the first trillion-dollar neocloud hyperscaler, make sure to follow Melvin for more AI infrastructure insights, and if you want to see exactly what I'm buying as an analyst at Milk Road Pro, you can check out the link for more.

Melvin

28,972 görüntüleme • 1 ay önce

Sam Altman says AI will replace many phone- and computer-based customer support jobs Roles that require human connection, like nursing, will remain safe The biggest uncertainty is programmers and software engineers, because AI makes them far more productive, So whether that leads to more or fewer jobs in 5-10 years is unclear

Sam Altman says AI will replace many phone- and computer-based customer support jobs Roles that require human connection, like nursing, will remain safe The biggest uncertainty is programmers and software engineers, because AI makes them far more productive, So whether that leads to more or fewer jobs in 5-10 years is unclear

Haider.

242,705 görüntüleme • 1 yıl önce

10x more tokens/second per megawatt as measured by CoreWeave on NVIDIA Vera Rubin platform. That performance reflects a bigger shift in AI infrastructure economics: building AI factories that efficiently turn compute into tokens, and tokens into revenue. It takes extreme co-design across the full stack, combined with an open ecosystem built to innovate and scale. Dion Harris connects the economics to the technology with 5 critical questions every AI infrastructure leader should be asking across compute, networking, storage, software and security. ➡️

10x more tokens/second per megawatt as measured by CoreWeave on NVIDIA Vera Rubin platform. That performance reflects a bigger shift in AI infrastructure economics: building AI factories that efficiently turn compute into tokens, and tokens into revenue. It takes extreme co-design across the full stack, combined with an open ecosystem built to innovate and scale. Dion Harris connects the economics to the technology with 5 critical questions every AI infrastructure leader should be asking across compute, networking, storage, software and security. ➡️

NVIDIA AI Infrastructure

23,895 görüntüleme • 27 gün önce

$MU CEO Sanjay Mehrotra says AI is turning memory from a commodity into “strategic infrastructure.” AI cannot scale without more HBM DRAM and SSD capacity which is making memory far more valuable across the entire compute stack.

$MU CEO Sanjay Mehrotra says AI is turning memory from a commodity into “strategic infrastructure.” AI cannot scale without more HBM DRAM and SSD capacity which is making memory far more valuable across the entire compute stack.

Shay Boloor

194,460 görüntüleme • 26 gün önce

We raised $65M to build an agentic hiring platform that makes hiring as easy as pressing a button AI is accelerating faster than anyone imagined. As intelligence, data, and software commoditize, one thing becomes exponentially more valuable: human ingenuity That’s the future that Paraform Studio is building towards

We raised $65M to build an agentic hiring platform that makes hiring as easy as pressing a button AI is accelerating faster than anyone imagined. As intelligence, data, and software commoditize, one thing becomes exponentially more valuable: human ingenuity That’s the future that Paraform Studio is building towards

John Kim

125,833 görüntüleme • 6 ay önce

The SaaSpocalypse created some of the best software opportunities of this cycle because the market initially priced agents as if they would replace applications entirely and sold off nearly every software name for months. Over time we got more evidence that agents may replace the interface while making the infrastructure underneath even more valuable by driving more queries, workflows and security needs. That means the real winners are platforms that monetize every time an agent accesses data, executes work or protects the information underneath it.

The SaaSpocalypse created some of the best software opportunities of this cycle because the market initially priced agents as if they would replace applications entirely and sold off nearly every software name for months. Over time we got more evidence that agents may replace the interface while making the infrastructure underneath even more valuable by driving more queries, workflows and security needs. That means the real winners are platforms that monetize every time an agent accesses data, executes work or protects the information underneath it.

Shay Boloor

41,237 görüntüleme • 28 gün önce

$NBIS has a really interesting setup into Wednesday because the demand is already there with $MSFT and $META contracts, Reflection AI’s $1B deal and GPU demand running several times above available capacity so the real question is how quickly Nebius can turn power and data centers into revenue. That’s also why I’m getting more comfortable with the execution risk as Nebius targets 4GW+ of contracted power, proves it can raise non-dilutive capital with $775M of secured financing and introduces an asset-light model that lets partners fund infrastructure while Nebius keeps the architecture, software and customer economics. So heading into earnings, I care much more about whether the Microsoft ramp stays on track, whether the second-half capacity bridge still looks believable and whether Nebius can keep repeating that financing model than I do about a small Q2 beat or miss.

$NBIS has a really interesting setup into Wednesday because the demand is already there with $MSFT and $META contracts, Reflection AI’s $1B deal and GPU demand running several times above available capacity so the real question is how quickly Nebius can turn power and data centers into revenue. That’s also why I’m getting more comfortable with the execution risk as Nebius targets 4GW+ of contracted power, proves it can raise non-dilutive capital with $775M of secured financing and introduces an asset-light model that lets partners fund infrastructure while Nebius keeps the architecture, software and customer economics. So heading into earnings, I care much more about whether the Microsoft ramp stays on track, whether the second-half capacity bridge still looks believable and whether Nebius can keep repeating that financing model than I do about a small Q2 beat or miss.

Shay Boloor

98,400 görüntüleme • 1 ay önce

The tokenization stack is forming. Ondo's Ian De Bode on why TradFi and Ondo are complementary, not competing: “TradFi is building 24/7 market infrastructure. Ondo is building the DeFi integrations and distribution. The two are very complementary.” The more TradFi builds, the more useful it becomes for DeFi: “Moving assets toward 24/7 trading and liquidity is tremendously useful once you wrap that asset for DeFi, since DeFi operates 24/7.” The tokenization sector is maturing. Different builders are solving different parts of the same problem, each making the others more valuable.

The tokenization stack is forming. Ondo's Ian De Bode on why TradFi and Ondo are complementary, not competing: “TradFi is building 24/7 market infrastructure. Ondo is building the DeFi integrations and distribution. The two are very complementary.” The more TradFi builds, the more useful it becomes for DeFi: “Moving assets toward 24/7 trading and liquidity is tremendously useful once you wrap that asset for DeFi, since DeFi operates 24/7.” The tokenization sector is maturing. Different builders are solving different parts of the same problem, each making the others more valuable.

Ondo Finance

34,510 görüntüleme • 1 ay önce

AI has solved software. Biology is the next frontier. We're hiring across every team at Adaptyv. We’ve built the best automated lab for protein designers to experimentally test their AI-designed proteins. Today, the most advanced protein design companies run their wet-lab work on Adaptyv, from the biggest biopharmas to frontier AI labs to dozens of virtual biotech startups. Demand has grown faster than we have, so we’re hiring across the board: • Bio: Research associates, scientists and lab technicians to develop and run new assays at scale. • Lab automation: Engineers and interns to onboard new lab instruments and scale our automation infrastructure. • Software: Product and backend engineers to scale LabOS, our internal lab orchestration platform, our API for agents and the data pipelines that turn messy physical-world data into clean results. • Partnerships, customer success and operations: Building partnerships with AI & pharma labs, making sure customers understand their data and can run more campaigns, making sure the company operations run smoothly

AI has solved software. Biology is the next frontier. We're hiring across every team at Adaptyv. We’ve built the best automated lab for protein designers to experimentally test their AI-designed proteins. Today, the most advanced protein design companies run their wet-lab work on Adaptyv, from the biggest biopharmas to frontier AI labs to dozens of virtual biotech startups. Demand has grown faster than we have, so we’re hiring across the board: • Bio: Research associates, scientists and lab technicians to develop and run new assays at scale. • Lab automation: Engineers and interns to onboard new lab instruments and scale our automation infrastructure. • Software: Product and backend engineers to scale LabOS, our internal lab orchestration platform, our API for agents and the data pipelines that turn messy physical-world data into clean results. • Partnerships, customer success and operations: Building partnerships with AI & pharma labs, making sure customers understand their data and can run more campaigns, making sure the company operations run smoothly

Adaptyv Bio

14,987 görüntüleme • 3 ay önce

$SNOW is becoming data layer for the new agentic AI economy because agents need secure access to proprietary enterprise data and business context before they can do anything useful. That makes Snowflake even more valuable as models get cheaper and more interchangeable because it can bring the best model to the data while AI products like CoCo and CoWork drive a ton more storage, compute and core platform consumption underneath.

$SNOW is becoming data layer for the new agentic AI economy because agents need secure access to proprietary enterprise data and business context before they can do anything useful. That makes Snowflake even more valuable as models get cheaper and more interchangeable because it can bring the best model to the data while AI products like CoCo and CoWork drive a ton more storage, compute and core platform consumption underneath.

Shay Boloor

62,547 görüntüleme • 12 gün önce

$PLTR Rule of 40 score reached 155 and the metric has now expanded for 12 consecutive quarters as operating leverage continues improving with scale. That means Palantir is growing close to 100% while converting more than half of revenue into operating income which is a combination almost unheard of in large-scale software. $GOOGL, $AMZN, $MSFT and $META are spending hundreds of billions building the AI factories while Palantir sits above that infrastructure and turns the resulting intelligence into real-world outcomes without funding the physical buildout allowing far more incremental revenue to flow into profit and cash.

$PLTR Rule of 40 score reached 155 and the metric has now expanded for 12 consecutive quarters as operating leverage continues improving with scale. That means Palantir is growing close to 100% while converting more than half of revenue into operating income which is a combination almost unheard of in large-scale software. $GOOGL, $AMZN, $MSFT and $META are spending hundreds of billions building the AI factories while Palantir sits above that infrastructure and turns the resulting intelligence into real-world outcomes without funding the physical buildout allowing far more incremental revenue to flow into profit and cash.

Shay Boloor

576,796 görüntüleme • 1 ay önce

The CEO of Founders Fund-backed Monaco, Sam Blond, says customers want to speak with humans for sales. But for non-customer-facing activities, AI agents are far better. “Whether you're a sales rep or a founder, you will spend your time customer-facing - and we're going to optimize everything in the platform around that experience, including the post follow-up.” “So, you get off the call, we have the call transcript, we've written an email for you to follow up with that person, it's very opinionated and trained on the way that we think about sales and go to market, you can review that email and click send, and then it's time for the next call.” “That’s the sort of optimization that we believe AI is influencing the function of sales right now. It’s - getting more qualified demos, helping you close more customers, and actually emphasizing the relationship-building that happens that is customer-facing.”

The CEO of Founders Fund-backed Monaco, Sam Blond, says customers want to speak with humans for sales. But for non-customer-facing activities, AI agents are far better. “Whether you're a sales rep or a founder, you will spend your time customer-facing - and we're going to optimize everything in the platform around that experience, including the post follow-up.” “So, you get off the call, we have the call transcript, we've written an email for you to follow up with that person, it's very opinionated and trained on the way that we think about sales and go to market, you can review that email and click send, and then it's time for the next call.” “That’s the sort of optimization that we believe AI is influencing the function of sales right now. It’s - getting more qualified demos, helping you close more customers, and actually emphasizing the relationship-building that happens that is customer-facing.”

TBPN

27,597 görüntüleme • 7 ay önce

More than just a platform, Friendzone lets fans contribute to the growth and success of their favorite creators. A space where creators can launch AI versions of themselves to scale their brand and monetize like never before. The future is closer than you think.

Ai-Mi

10,831 görüntüleme • 1 yıl önce

Long Lake Co-Founder & CEO Alexander Taubman says AI is driving a convergence between services businesses and software companies. "What you typically see is even though these are really extraordinary businesses with incredible customer trust and decades or even centuries of operating history, the margin structures in these services businesses traditionally have been lower than software." "What we're seeing now is a convergence of services and software characteristics over time where if you can make your team 20%, 30%, or 40% more productive, then that allows you to deliver more customer value, more goods and services, and different products to customers, which has historically been more associated with software companies." "For example, Amex GBT is an over 111-year-old business, founded in 1915 to help American Express travelers customers get out of Europe during World War 1. They bought a business called Carlson Wagonlit Lee which is over 150 years-old. So in terms of managing tech transformations, Amex GBT literally was created around the time of the invention of the airline, so these businesses have already managed many of them."

Long Lake Co-Founder & CEO Alexander Taubman says AI is driving a convergence between services businesses and software companies. "What you typically see is even though these are really extraordinary businesses with incredible customer trust and decades or even centuries of operating history, the margin structures in these services businesses traditionally have been lower than software." "What we're seeing now is a convergence of services and software characteristics over time where if you can make your team 20%, 30%, or 40% more productive, then that allows you to deliver more customer value, more goods and services, and different products to customers, which has historically been more associated with software companies." "For example, Amex GBT is an over 111-year-old business, founded in 1915 to help American Express travelers customers get out of Europe during World War 1. They bought a business called Carlson Wagonlit Lee which is over 150 years-old. So in terms of managing tech transformations, Amex GBT literally was created around the time of the invention of the airline, so these businesses have already managed many of them."

TBPN

17,542 görüntüleme • 4 ay önce

Enjoy being human. twin3 is building the infrastructure that makes human experience provable, valuable, and respected in the AI era. Computable Human.

Enjoy being human. twin3 is building the infrastructure that makes human experience provable, valuable, and respected in the AI era. Computable Human.

twin3.ai

606,083 görüntüleme • 7 ay önce