Zartis’ Post

Gen AI is on the cusp of transforming how businesses operate. Silicon Valley investors see generative AI as the next essential tool for enterprises, setting the stage for innovative advancements and competitive advantage. Are we ready to embrace this game-changer?

🚀 The AI Race: Fast Innovation vs. Furious Demand In the world of generative AI, we're witnessing a thrilling showdown between rapid innovators and eager end-users. It's "The Fast" (tech companies, System Integraters) vs. "The Furious" (businesses seeking immediate benefits). The stakes? A projected $280 billion in software revenue by 2033. But success isn't just about speed - it's about bridging the gap between cutting-edge tech and practical, scalable solutions. Key challenges: • Skills shortage • Unclear use cases • AI accuracy concerns • Data control & IP issues • Data quality & availability To harness AI's potential, consider these tips: 1. Identify clear use cases aligned with your business needs 2. Invest in upskilling your workforce 3. Prioritize data quality and governance 4. Start small, iterate, and scale gradually 5. Foster a culture of AI adoption and continuous learning Remember, AI isn't just about tech adoption - it's about achieving measurable outcomes and empowering your workforce. The change is more prominent🌟 As an end-user, dare to be 'furious' - demand solutions that deliver immediate benefits and scale with your needs. For tech providers, focus on creating intuitive, user-centric solutions that seamlessly integrate into existing workflows. The future of AI lies in the balance between rapid innovation and practical application. By bridging this gap, we can create a more productive, technologically empowered society. Are you ready to join the race? 🏁 At knowdroids.ai, we are helping the rapid innovators. Please reach out to discuss how our AI Agents can support your journey and get your organization to the next level. Please see the link to the article in The CEO Magazine Global in comments below: How practical utility and rapid advancement are influencing gen AI https://lnkd.in/euaMN7x7 #GenerativeAI #AIInnovation #FutureOfWork #TechTrends

💭 No matter how big an organisation is, when you’re implementing AI you need to think like a startup, says Mihail Cernei, CTO at Amdaris. "Innovation is essential, and so is being agile. In fact, doing some napkin maths - sketching out potential costs, benefits, and considerations - can be much quicker and more impactful than building out a detailed, longer plan," writes Cernei. "But when it comes to the real-world implications of AI, there are a number of questions CIOs need to consider." Read the full opinion piece over on our website here 👇 https://lnkd.in/d6NfCfV6 #theengineer #AI #business #engineering #technology #CIOs

🚀 How This AI Startup Secured a $5.5 Billion Valuation & What It Means for the Future of Enterprise AI🚀 In the ever-evolving world of AI, one company is making waves by focusing on what truly matters: transforming businesses. 🌟 Meet Cohere the brainchild of former Google researchers Aidan Gomez Nick Frosst and Ivan Zhang who are redefining the enterprise AI landscape. With a laser focus on customizing AI solutions for businesses, Cohere is not just another tech marvel; it's a game-changer. 🔍 What’s Inside the Blog? - Cohere's journey from Google AI labs to becoming a $5.5 billion enterprise AI powerhouse, led by visionary founders - The unique approach Cohere takes in tailoring AI for real-world business needs. - Strategic partnerships with industry giants like Fujitsu Oracle and Notion that are fueling Cohere’s global impact. - Insights into how Cohere’s cutting-edge technology is pushing the boundaries of AI, all while maintaining ethical standards. - The future of enterprise AI and how Cohere is positioned to lead the charge. Cohere isn’t just participating in the AI revolution—they’re reshaping it. If you're curious about the future of AI in business, this is a story you won't want to miss. 👉 Read the full story in the comments written by Akshay Kumar from Infyleads team and discover how Cohere is changing the rules of the AI game. #AI #EnterpriseAI #Cohere #TechInnovation #BusinessTransformation #ArtificialIntelligence #StartupSuccess #AIRevolution

From the desk? The buzz around GPT and GPT wrappers has been incredible! These tools, which can handle tasks from content creation to customer service automation, have quickly become key players in the digital world. Their ease of use has opened the door for many to leverage AI power, with the global AI market projected to hit $2.5 trillion by 2032. GPT wrappers are making it simpler than ever for businesses and individuals to access advanced AI capabilities. But it's not all smooth sailing. Industry leaders like Sam Altman have raised some valid concerns. In a recent Stanford interview, Altman noted that while GPT wrappers are easy to create, this also makes them easy to replicate, leading to a crowded market with many similar products. He emphasized that the real future of AI innovation lies in developing more complex and integrated solutions that offer unique value. As AI technology continues to evolve, Altman believes basic GPT wrappers will become less relevant, paving the way for more sophisticated applications that provide deeper insights and capabilities. Even with the AI market's projected growth, core AI companies will be the main drivers, not GPT wrappers. True innovation will come from those creating foundational models and advanced AI technologies. While GPT wrappers are popular now, their market influence is limited compared to the significant impact and investments in foundational AI technologies. The future of AI will be shaped by these core advancements, not just by the simpler applications packaging AI capabilities. #AI #GenAI #startups

While we may be witnessing a plateau in state-of-the-art (SOTA) AI models, it’s clear that the current generation of AI has immense untapped potential. These models already possess more than enough "intelligence" to unlock transformative value for businesses. However, we are barely scratching the surface—arguably utilizing less than 5% of their capabilities. The chat interface, which dominates much of the conversation, is only the first step in this revolution, akin to the early stages of internet technology in the mid-to-late 1990s. The current phase is exciting but saturated with hype, and it’s inevitable that the bubble will burst within the next five years. This correction will be a positive development, clearing the field of unsustainable ventures and enabling the truly innovative companies to flourish. The real challenge lies not in building better models, but in integrating the existing ones into systems that solve real-world problems. The question isn’t whether AI can do more—it’s whether we can evolve how we use it. https://lnkd.in/eDUJ_aEB

Business leaders are contemplating an important question for their AI projects: How much should this cost? The answer to that question depends on the scale and objectives of a company’s AI project. Building and training a proprietary large language AI model is a very expensive endeavor, with steep costs in hardware, energy, and engineering talent. The good news is that, for most businesses, there’s no need to build your own model. A broad industry of vendors already exists that allows businesses to leverage the latest AI innovations from the likes of Microsoft, Google, Amazon, and various AI startups. Many of the offerings also include open-source AI models, bringing the capabilities of these powerful generative AI tools to organizations that might not have the technical resources or skills to deploy it on their own. “The costs of the AI tools themselves, they really aren’t genuinely prohibitive,” says Phil Gilchrist, chief transformation officer of AI and sustainable materials at TE Connectivity, a maker of EV sensors and other electronic components. “What’s much more challenging is to recognize that we’re going to live in a world that will be an AI world going forward, and we have to recognize that we need to organize ourselves.” Read more:

Yesterday, Cognition Labs, the team that makes Devin, contacted me to ask how I could help them improve Devin's performance. The problem is - I can't stand the term, "Role." Rooooooole, ugh, it even sounds bad, phonetically. I just don't think the rigidity of the roles-based economy works in AI. Building AI solutions is about modeling context, not optimizing for economies of scale; we are not living in the days of Adam Smith or David Ricardo. Gains from generalization are key to AI, less so gains from specialization, as the entropy loss associated with the latter exceeds marginal returns to scale from the former. I write about this and a host of other points in my latest paper on Vertical Integration. https://lnkd.in/gQwi5Dks

"Across the economy, only 5% of American businesses say they are using AI in their products and services. Few AI startups are turning a profit. And the energy and data constraints on AI model-making are becoming steadily more painful. The disparity between investor enthusiasm and business reality looks untenable—which means 2025 is shaping up to be a crunch year. The race to make AI more efficient and more useful, before investors lose their enthusiasm, is on".

What does your business offer that's entirely unique? What are the chances AI swoops in and makes it more easily accessible? Even if chances are high (look to Chegg as a cautionary tale) AI-driven business growth is possible whether you're a startup or an established enterprise. If you need to talk about strategies to stay ahead of the curve, reach out. https://lnkd.in/egajnEXE #AI #EnterpriseAI #BusinessGrowth #AIAdoption