𝗧𝗵𝗲 𝗘𝘃𝗼𝗹𝘂𝘁𝗶𝗼𝗻 𝗼𝗳 𝗔𝗜 𝗶𝗻 𝟮𝟬𝟮𝟱: 𝗙𝗼𝘂𝗿 𝗗𝗶𝘀𝘁𝗶𝗻𝗰𝘁 𝗟𝗮𝘆𝗲𝗿𝘀 𝗘𝗺𝗲𝗿𝗴𝗶𝗻𝗴
As AI continues to mature, I've observed a significant shift in the landscape in the last 2 weeks. We're no longer just talking about AI as a monolithic entity; instead, four distinct layers have emerged, each with its own set of players and innovations.
𝗟𝗮𝘆𝗲𝗿 𝟭: 𝗛𝗮𝗿𝗱𝘄𝗮𝗿𝗲
The hardware layer is led by Nvidia. The interesting play is in cloud provider space. While no one can match Nvidia's hardware for the large models, we have seen local device driven models, SLMs, edge models emerge as a significant option. This layer is critical for the development of AI, and we can expect 2025 to define 2 separate paths.
𝗟𝗮𝘆𝗲𝗿 𝟮: 𝗟𝗮𝗿𝗴𝗲 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗠𝗼𝗱𝗲𝗹𝘀 (𝗟𝗟𝗠𝘀)
The LLM layer is no longer a three-horse race (OpenAI, Anthropic, Meta). With the recent release of Gemini, I've been pleasantly surprised by the quality of their tools, including Gemini Live (blew my mind), Germany Astra, etc. NotebookLM has always been a great app. We now have a four-horse race between OpenAI, Anthropic, Meta, and Google.
𝗟𝗮𝘆𝗲𝗿 𝟯: 𝗠𝗶𝗱𝗱𝗹𝗲𝘄𝗮𝗿𝗲
The middleware layer is heating up, with Google Cloud, Microsoft Azure, and Amazon Web Services (AWS) offering solutions. However, these platforms can be limiting for enterprises that want an open ecosystem. Palantir Technologies, Adya, and open-source middleware platforms are offering attractive alternatives.
𝗟𝗮𝘆𝗲𝗿 𝟰: 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗟𝗮𝘆𝗲𝗿
The application layer is where the magic happens. I've been blown away by the quality of applications like Suno, Reelcraft, Twinql AI, AudioPod AI, Clay, Minimax, HeyGen, and many others. These applications are built on top of third-party models, and the innovation is staggering.
As AI continues to evolve, we can expect these four layers to blossom, differentiate, and distinguish themselves further. I'm excited to see what 2025 brings!
#AI #ArtificialIntelligence #LLMs #Middleware #ApplicationLayer #Innovation #EmergingTechnologies
