𝗪𝗵𝗶𝗰𝗵 𝗔𝗜 𝗦𝘁𝗮𝗿𝘁𝘂𝗽𝘀 𝗪𝗶𝗹𝗹 𝗪𝗶𝗻? The real opportunity is coming from what Sam Altman calls the Middle Layer. (not counting the infra - shoutout to my ai clouds the gpu slingers that will make this all possible. More on them later) Here’s why: If the LLM continues to be the model type that pushes forward the bleeding edge of innovation, the number of companies that will be able to finance the creation of the next best model will be maybe 3-5 total. Google, Meta, Microsoft, Apple, Maybe OAI if Altman can continue to swoon investors. The newer more capable models will begin to become so costly, that no one else will even try. These giants will provide base models for everyone else. But AI startups don’t need to build their own large models. Instead, they’ll focus on specialization—building on top of these base models to solve specific problems, whether that’s in healthcare, personal assistants, or industry-specific applications. Hyper niche use case/industry specific. fine tuned.. like very finely tuned. This Middle Layer will create real, long-term value by focusing on niche solutions that deliver measurable ROI. Because the debate is already heating up around AI’s actual impact on the bottom line. This shift ups the ante for your front-line teams. Which is good. It shouldn't be about having the coolest tech. It should be about solving real problems—better, faster, and more convincingly than anyone else. That’s why the AI startups that will win are: ➡ Specializing in niche use cases ➡ Clearly demonstrating how well they solve problems ➡ Empowering their GTM teams to communicate that value effectively ____ If you’re looking to build a high-performing GTM team to secure early customers and establish product-market fit—let’s talk. We’ve mapped over 2,000+ companies in AI, ML, data, GPU, compute, and cloud to find qualified GTM experts (sales, marketing, solutions, cs, etc.). Check out the pinned post on my profile for a sneak peek: https://t2m.io/QLhYDePw DM me if you need help.
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𝗜𝘀 𝘁𝗵𝗲𝗿𝗲 𝘀𝘂𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝘁 𝗽𝗼𝘁𝗲𝗻𝘁𝗶𝗮𝗹 𝘃𝗮𝗹𝘂𝗲 𝘁𝗼 𝗷𝘂𝘀𝘁𝗶𝗳𝘆 𝘁𝗵𝗲 𝗰𝗼𝘀𝘁 𝗼𝗳 𝗔𝗜? Consider this: $1.2 trillion is projected to be spent on AI infrastructure, with an expected 25% Return on Invested Capital (ROIC). On the surface, that sounds promising, especially when it's tied to examples like AI customer service agents, coding copilots, and recommendation engines. However, dive deeper, and you’ll find that only 25% of AI-exposed tasks are predicted to be cost-effective to automate in the next 10 years, translating into a mere 5% of global tasks. Some experts believe even if AI could generate significant benefits, a shortage of key inputs like chips and power would be an impediment to delivering the promise. This isn’t to say that AI’s potential should be dismissed outright. Joseph Briggs, a senior global economist, believes that AI will ultimately automate 25% of work tasks, boost productivity by 9%, and drive 6.1% GDP growth over the next decade. AI is no different from cloud computing or mobile connectivity in that no one buys a product just because it is cloud-enabled; they buy because of what value the product provides. So, what’s the take-home message for founders and investors? Simply put, don’t get caught in the AI hype. The focus should be on high-impact, targeted use cases where AI can deliver tangible results rather than a blanket adoption strategy. AI will drive value, but in a more incremental fashion than the transformative overhaul many are envisioning. Source: Coatue #Venturecapital #AI #Deeptech #Startups Follow us for strategies and resources for Deep Tech founders and VCs! And get access to exclusive content on deep tech startups like ATMOS Space Cargo, planqc, smedo GmbH, and SENISCA in our newsletter: https://t2m.io/EV2qHQuo
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I’ve noticed a lot of consultants, tech press, and even the wise folks at Gartner are starting to claim that AI is a bubble ready to pop. Well, I think they’re all wrong. Here’s why: 🎯 Follow the Money: The 7 biggest companies in the US—Microsoft, Nvidia, Apple, Amazon, Google, Meta, and Tesla—are all in on AI. Unlike the dot-com boom, these aren’t startups; these are giants that have been dominating for decades, and they’re doubling down on AI. 🎯 ROI Takes Time: Deploying AI at scale is costly and complex. The biggest companies in the world understand this. For them, this stage isn’t about short-term profits—it’s about a land grab, securing the biggest share of the pie, and gaining first-mover advantage. 🎯 Startups Folding? That’s Consolidation, Not a Crash: When small AI startups get swallowed up, it’s not the bubble bursting—it’s Big Tech getting stronger. The giants are taking over, and that’s a clear sign of how serious AI is. For the first time ever, the eight biggest companies in the S&P 500 are all playing in the same market—AI. 🎯 The Scale-Up is Coming: We’re yet to see big companies deploy AI at scale, but it’s coming. Companies need to invest in their people, training them to think differently and adapt to the AI-driven world. It’s not just about having the tech—it’s about rethinking how you work. The companies that get this right will dominate, leaving everyone else playing catch-up.
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AI startups are eyeing a $10 trillion market in "Service-as-a-Software"! 💰🚀 The flood of unstructured data has been a headache for businesses, slowing them down for ages. But guess what? AI is flipping the script! LLMs can now read and understand documents in any format. 📄🤖 This means massive time and cost savings for companies as processes speed up and staffing expenses drop. As Sequoia points out, we’re on the brink of a new era - the era of "agent reasoning." 🤔✨ Here’s what’s cooking: 1. The target market isn’t just software anymore; it’s service-based too—worth trillions! 💵 2. Industries are transforming from healthcare to law, logistics to finance—no one’s safe! 🏥⚖️📦💼 3. "Service-as-a-Software" is a playground for innovative startups to thrive! 🎉🌟 Experts estimate this market could hit $10 trillion. So, what does this mean for businesses? ❗️ Startups: An unprecedented chance to compete with giants by offering cutting-edge AI solutions! 🦸♂️💪 ❗️ Corporations: Time to adapt and integrate AI if they want to stay in the game! 🔄🏢 ❗️ Everyone: A total rethink of business processes and readiness for some serious changes ahead! 🔍🔧 [Get ready, folks—change is coming!](https://lnkd.in/e5gkdmBu) 🌊✨
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I only know of 4 ways to WIN in the market. 🏆 Here: An example of the rarest kind! When leaders tell me of their “winning” strategy, I try to match it to 1 of 4 ways to win. They are: 💪 Be better (at something specific) 🔒 Lock out competitors 🚀 Be legit in a hyper-growth space ♟️ Outsmart competitors Arguably, Outsmarting ♟️ is the best way. It works in any environment. It may be cheap. No (real) fight. But you rarely hear of companies doing it well. So I love this hack by Andreessen-Horowitz (“A16Z,” a major VC firm): #ai is the thing du jour, right? But it’s hard to win by 💪 being better when no one knows what that means 🔒 keeping competitors out, given open source 🚀 being legit when hot air sells more right now E.g., A16Z might have done things like 🤷♂️ funded even MORE AI startups, 🤷♂️ partnered with Open AI etc. directly 🤷♂️ bought server capacity But those are all bland. Meh. Won’t truly WIN. But buying 20,000+ AI computer chips: brilliant! ✅ Be more attractive to the best startups. ✅ Learn more about the space than you could have. ✅ Cut your own 3rd-party AI bill. And the best part? Almost — every — major — company could — have — done — it — too. They just didn’t (in most cases). That’s outsmarting in action. Photo credit: Brian Kostiuk on Unsplash
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The Power of AI in Startups: Growing the Right Way with Data AI is revolutionizing startups, enabling them to scale rapidly, enhance decision-making, and optimize operations. But AI’s true power comes from data. Startups must build a solid data foundation to fuel AI and drive growth effectively. 1. Data Strategy: Align your data strategy with business goals. Identify what data you need, how to collect it, and how to analyze it for actionable insights. 2. Quality Over Quantity: Focus on clean, accurate data. Poor data leads to poor decisions. Invest in data validation and governance. 3. Understand Customers: Use AI to analyze data and uncover customer needs, personalize experiences, and predict trends. 4. Monitor and Iterate: Continuously refine AI models to stay relevant in a changing market. AI and data are a winning combination for startup growth. Use them strategically, and your startup can achieve sustainable success. #AIinStartups #DataDriven #StartupGrowth #TechInnovation #DigitalTransformation
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IMHO this article points out(rather paints a wrong picture) that AI startups are struggling financially but I see there is much more than what meets the eye. The financial struggle is most probably a result of politically induced game of power to gain control on tech/company ‘at the right time’. So here’s my take on this… If you go back in time, this seems to be exactly like a part of a bigger shift like the dot-com boom or more-so-ever like the big fat useless mainframes… Irrelevant but the big loggerheads want to prove value and fuel them anyways. The giant traditional companies have to adapt AI services & offerings or risk falling behind...however at what cost? They already have a set process for Digital Transformation or BnM IT services or ‘some other jargon’ services…and now jumping onto the AI Bandwagon is practically impossible with like a hundred thousand employees needing training(as they are process oriented…they need trained folks…certified(my a**)), but having no clue what to train on in this rapidly changing AI landscape. But on the contrary this change gives smaller, lean more flexible companies a chance to shine and become the big players of tomorrow. AND THAT is what investors have realised, probably. They need power and control at the right time! Startups like StabilityAI and Anthropic are like young mustangs, and no doubt they have the potential to grow into powerful horses like the “Secretariat” of the AI world but unfortunately they already signed off their soul to the investors while they were non-existent. In reality we're not just seeing companies trying to survive financially; it's about who can adapt and innovate the fastest…and retain power! This shift in the business landscape, is going to be favoring those who embrace change and innovate boldly....and thats where we are! PS: As for competing with likes of Microsoft, Google is concerned, I think you don’t compete with them… you partner with them. Accept the fact that are going to be the main propellents in this era. https://lnkd.in/d775u682
A.I. Start-Ups Face a Rough Financial Reality Check
https://www.nytimes.com
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🚀 Navigating the Shift: As the AI investment frenzy cools, success in 2023 means digging deep for unique competitive edges. 💡 From leveraging proprietary data to solving holistic business challenges, find out how startups are building moats in the age of AI maturation. Dive into the insights from Adi Gozes of Entrée Capital and stay ahead in the evolving landscape. #AIInnovation #StartupStrategy #CompetitiveAdvantage" https://ow.ly/v9Su50QKLfl
The AI Gold Rush: How Startups Can Stake Their Claim In A Competitive Frontier
news.crunchbase.com
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