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Very interesting article from The New York Times about the cost of building AI. More and more startups are struggling to keep up with the bills and big companies are coming in to buy IP and recruit talent. 🔍 Key Insights: - Economic Challenges: The creation of large language models (LLMs) is not only expensive but also fiercely competitive. Only a few companies have managed to generate substantial revenue with profitable margins. - Corporate Shifts: Inflection AI, despite a massive funding of $1.5 billion, has ceased its primary operations due to financial underperformance. - Industry Impact: Veterans in the tech industry are shocked by the immense costs associated with AI development. This has led to significant financial burn, reminiscent of past tech booms. - Strategic Restructuring: Stability.AI is undergoing major restructuring to better navigate these financial and competitive pressures. 🌟 Why This Matters: - Funding vs. Execution: The highest-funded startups often face challenges in managing their expenses, underscoring that successful execution matters more than the amount raised. - Optimizing AI Use: Currently, costly LLMs are frequently used for relatively low-value tasks. This trend is shifting towards strategic utilization of small language models (SLMs) and selective use of LLMs to optimize cost-response quality per request. There are already many startups working on this! - Niche Focus: For startups, it's advantageous to target niche use cases by blending proprietary technology with established LLMs. This approach is more sustainable than competing head-on with well-funded enterprises attempting to dominate the market. - Pricing & Packaging: As the industry evolves, so too will pricing models. The future promises new strategies for aligning costs with pricing, which will be crucial for sustainable growth. - Sustainability: Like other technologies, the environmental impact of AI development is becoming an increasingly pressing issue. It’s imperative that companies consider sustainability early in their development process to address these challenges effectively. #ai #innovation #startup https://lnkd.in/g8ZFUGqs

I love this sentiment, but we need to break it down further. "AI First" is a great mantra, but it doesn't happen in a vacuum. AI is an incredibly "loaded" term. It means proper aligning and prioritizing the following as foundational elements simultaneously to serve your bottom line: 1) Data Strategy - no the data doesn't just exist in a usable form. 2) Access and Governance - if you won't give your trusted (and expensive) Data Scientists access, then how is running 3rd party "roughshod" algorithms over your infra a realistic expectation? 3) Invest in (and enable) talent - Trusted experts and innovation first thinkers are critical to succeed. 4) Focus on Value, not just project points and process - Data Scientists are not cheap...and wasting their time with waiting around for access and bureacracy is even less affordable. Empower them in a "safe space." If you treat the good ones like a "ticket completion factory" they will get bored and leave. 5) Method, Method, Method - This isnt just pushing data at functions and endpoints. You have to know what you are doing, you need A LOT of really advanced math, and you need to be pushing comfort zones. If part of you're brain isn't talking in Greek letters, you're doing it wrong. https://lnkd.in/eTj9REfY

Small Language Models (SLMs) and blending proprietary technology with established LLMs = strategic focus & profit optimization

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

In a discussion I had yesterday, it became abundantly clear that AI-focused startups have a real existential problem. What happens when the next evolution of AI is released? Everything that your AI was trained to do is now irrelevant as the new AI is better than the old and ought to be able to do everything your company was created to do. Let's take a couple of examples, but you can apply this to almost any company listed here https://lnkd.in/e6-bn7Ft: 1) Tome - Presentation creation software. 2) Together AI - AI model development tools. I know nothing about these companies...and I haven't even been to their website to learn specifically what they do. But it would seem to me that both of these companies have the problem. Tome raised $81M. Together raised $229M. I'm sure they have a head start. And I'm sure their technology would blow me away. But what happens when GPT 5.0 or 6.0 is released? Their compute will be better. Their capabilities will be better. Their ability to replicate other companies outputs will be better. So, investors will have spent hundreds of millions of dollars on these companies that overnight will become duplicable. The optimistic scenario is that these companies will become commodities, which is bad business. The pessimistic scenario is that these companies will be obsolete, which is worse. What's the solution? It's really hard to say. My feeling is that if you are playing in the AI space, you need to find a problem where the solution is powered by AI but there is also some secret sauce that AI can't solve. I would think that this ought to be a major concern for any investor in the space. Given the amount of money that is being deployed, my reasoning must be flawed.

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

AI-powered valuation tools are transforming how startups are assessed, offering precision and insights beyond traditional methods. Here's why they're game-changers: 1. 𝗗𝗮𝘁𝗮-𝗗𝗿𝗶𝘃𝗲𝗻 𝗣𝗿𝗲𝗰𝗶𝘀𝗶𝗼𝗻: AI analyzes vast datasets to provide accurate valuations, reducing human error and bias. 2. 𝗥𝗲𝗮𝗹-𝗧𝗶𝗺𝗲 𝗨𝗽𝗱𝗮𝘁𝗲𝘀: These tools offer real-time market insights, helping startups adapt quickly to changes. 3. 𝗦𝗰𝗮𝗹𝗮𝗯𝗹𝗲 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝘀: AI tools can handle valuations for startups of all sizes, from pre-seed to late-stage. 4. 𝗘𝗻𝗵𝗮𝗻𝗰𝗲𝗱 𝗣𝗿𝗲𝗱𝗶𝗰𝘁𝗶𝘃𝗲 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀: By forecasting future trends, AI helps investors make informed decisions. AI valuation tools are not just about numbers; they're about unlocking potential and driving innovation in the startup ecosystem. #AIValuation #StartupSuccess #InnovationInTech If you are a founder, an investment banker, a funding consultant, or an investor and feel that this post added some value, do follow me for more such updates!

Title: How Generative AI is Set to Transform the Supply Chain Startup Ecosystem As we navigate the evolving landscape of supply chain management, it's becoming increasingly clear that generative AI is not just a technological advancement—it's a game changer for the industry. I recently came across a compelling article that dives deep into the current slowdown in the emergence of supply chain startups in Europe and how generative AI is poised to ignite a new wave of innovation. Key takeaways for my fellow senior executives: 1. Current Market Dynamics: The article discusses the recent decline in new supply chain startups due to hesitancy in companies acting as launching customers. 2. Generative AI’s Role: There's a strong anticipation that generative AI will drive the next surge in tech companies, offering transformative solutions to longstanding supply chain challenges. 3. Investment Insights: With supply chains recognized as both crucial and vulnerable, the interest from corporate executives and investment funds is rapidly growing. This is reshaping where resources are being channeled in anticipation of future needs. 4. Operational Gaps: Many companies continue to rely on outdated systems like Excel for critical supply chain operations, underscoring a significant opportunity for disruption and efficiency gains through advanced AI technologies. For anyone involved in supply chain management, investment, or looking to stay ahead in the rapidly changing tech landscape, this article is a must-read. Check it out here and join the discussion on how we can better prepare for the future of our industries: Generative AI Will Be a Gamechanger in the Start-up Market. https://lnkd.in/d42bQJkv #SupplyChainInnovation #GenerativeAI #TechStartups #StrategicInvestment

I'm very sceptical: Is AI Really the Game-Changer for VC? 🤔 Yesterday I read an article in a German startup publication (will provide the link in comments) that celebrates AI as a major disruptor in the venture capital world. Here’s what the authors argue—and what skeptical me thinks: - Selection Process Magic: AI will supposedly revolutionize startup selection by automating due diligence. But can an algorithm really capture the nuances in unstructured data like pitch decks? I’m not convinced. - Speedy Decisions: Yes, AI will make data processing faster, but does speed equal better decisions? I’m doubtful. - Democratized Deal Access: AI is said to level the playing field by giving more investors access to top deals. Or will it just create more noise, making the best deals even harder to find? - The Network Still Reigns: The authors note that despite AI's rise, personal relationships will be even more critical. Yes. My takeaway? Sure, AI will improve processes, but VC will remain a relationship-driven business. Until AI sits on a board, founders will choose investors who bring value beyond just algorithms. I’d love to hear your thoughts. Is AI overrated in the VC world, or are we on the cusp of a major disruption? 🚀 ------------------------------------------------------------------------- I empower entrepreneurs and investors to make smarter decisions. Follow me for insights and inspiration. #VentureCapital #AI #StartupInsights

While they can generate significant value for enterprises, generative AI and AI still require substantial education and access to scarce resources. That's why many AI startups operate as consultancies rather than pure software businesses, given the complexity of AI technology and the need for specialized talent. These startups provide hands-on services like generating synthetic data and customizing AI models, directly addressing specific business needs. This consultancy approach helps generate immediate revenue and attract VC funding, even though it poses challenges for future transition to software-based models. Read more on The Information: "Why Many AI Startups Are Consultancies Posing as Software Businesses," by Stephanie Palazzolo: https://lnkd.in/gy5ijjSn #DigitalTransformation #GenerativeAI #Consultancy #AIStartups #BusinessGrowth