A Deep Dive Into The Business of AI скачать в хорошем качестве

A Deep Dive Into The Business of AI

In an economic slowdown, where capital gets much more expensive, financing moves toward startups that can show more straightforward commercial applications. Thus, money moves toward builders. In this context, the AI industry is exploding because it's offering a plethora of commercial applications at scale. That is why: Stability AI announced a few days ago $101 Million in Funding for Open-Source Artificial Intelligence. Jasper AI, a startup developing what it describes as an “AI content” platform, has raised $125 million at a $1.5 billion valuation. OpenAI, Valued at Nearly $20 Billion, is in advanced talks with Microsoft for more funding. Those commercial applications are lowering the cost of doing business, thus spurring various macro trends: 1. Content production becomes much cheaper. 2. Software is transitioning into AI. In the coming decade, when we talk about "software," we'll mean a company that employs AI algorithms as its foundation. 3. Coding will become more accessible, as we can generate code with natural language instructions. 4. Robotics, with robots able to perform more and more general-purpose tasks, will enable the transition of many retail businesses. 5. AR/VR, with the generation, curation, and maintenance of virtual worlds becoming much cheaper, will explode. The bet is that in the coming 5-10 years, we'll see more and more startups in many verticals. And those startups will be able to create much more value. It won't be surprising to see AI companies valued at $10-100 billion with very small teams. That is why it's critical to understand what the AI can but especially can't do. The way AI works today, it should not be seen as a replacement for humans - but rather as an enhancement. Yet, it will become a real competitive advantage only from the combination of humans and AI (human-in-the-loop AI). You'll see real competitive moats in the coming decade for those able to determine: First, what the AI can't do. Second, enable the proper context for the AI. Once the human understands the limitations of the AI model, it can craft the proper context for the machine to thrive. Thus, reformulating the problem to make it solvable by the machine! Third, by enabling the human to structure the problem in the first place. Humans can make sense of a problem worth solving in a dynamic, ambiguous context by understanding the structure of a changing environment. This is indeed opening up many interesting opportunities. I've been witnessing this incredible explosion in the last five years. So stay tuned because I'll tell you more in the coming weeks... Where is the AI right now? https://mailchi.mp/thebusinessenginee... The AI industrial revolution: https://mailchi.mp/1e033e9d191b/this-... The rise of AI creators: https://mailchi.mp/thebusinessenginee... Building AI services: https://mailchi.mp/673891c25bea/this-... AI Chips: https://mailchi.mp/d281e33dfd9c/this-... How do you price AI: https://mailchi.mp/673891c25bea/this-... Human-the-loop-AI: https://mailchi.mp/thebusinessenginee...