🌟 𝐖𝐢𝐥𝐥 𝐰𝐞 𝐡𝐚𝐯𝐞 𝐋𝐥𝐚𝐦𝐚 𝟒 𝐛𝐲 𝐞𝐚𝐫𝐥𝐲 𝐧𝐞𝐱𝐭 𝐲𝐞𝐚𝐫?

By the looks of it, yes. 👀

From the recent conversation between Meta’s VP of AI and Analytics India Magazine, it’s clear that Meta is moving toward “𝑨𝒖𝒕𝒐𝒏𝒐𝒎𝒐𝒖𝒔 𝑴𝒂𝒄𝒉𝒊𝒏𝒆 𝑰𝒏𝒕𝒆𝒍𝒍𝒊𝒈𝒆𝒏𝒄𝒆” (𝑨𝑴𝑰) as its next big leap. 🚀

With models like OpenAI’s o1 pioneering “chain of thought” reasoning, it was only a matter of time before Meta brought the next upgrade to the Llama series. While OpenAI is laser-focused on achieving AGI (Artificial General Intelligence), Meta’s introduction of AMI adds a fresh twist to this space.

🔍 𝐈𝐬 𝐀𝐌𝐈 𝐭𝐡𝐞 𝐬𝐭𝐞𝐩𝐩𝐢𝐧𝐠 𝐬𝐭𝐨𝐧𝐞 𝐟𝐨𝐫 𝐀𝐆𝐈?
As we know, AI agents are set to play a critical role in the years ahead, driving adoption by classifying and executing tasks programmatically. Their ability to engage in deep thinking and emulate human decision-making will enable us to delegate a significant portion of low-value decisions, reducing the need for humans in the loop.

This sounds a lot like what AMI stands for—enabling autonomous decision-making, even if it’s not quite AGI yet. But it does raise an important question:

𝐀𝐆𝐈 𝐯𝐬. 𝐀𝐌𝐈: 𝐰𝐡𝐚𝐭’𝐬 𝐭𝐡𝐞 𝐝𝐢𝐟𝐟𝐞𝐫𝐞𝐧𝐜𝐞? 𝐓𝐰𝐨 𝐬𝐜𝐡𝐨𝐨𝐥𝐬 𝐨𝐟 𝐭𝐡𝐨𝐮𝐠𝐡𝐭 𝐡𝐞𝐫𝐞:

1️⃣ AGI as Cognitive Mastery: AGI will be achieved when machines can match or surpass human cognitive abilities—reasoning, learning, problem-solving, and adaptability across a wide range of tasks.
👉 If we go by this view, AMI and AGI could be considered identical.

2️⃣ AGI with Emotional Depth: Others argue that true AGI will require emotional intelligence, as human cognition is deeply intertwined with emotions that shape our decisions.
👉 In this case, AMI might represent our first real step toward AGI, bridging the gap with models that possess increasingly autonomous capabilities.

Ultimately, it all depends on how we define AGI.

Whether it’s AGI or AMI, one thing is clear: 2025 is shaping up to be the year of a Multi-Agent Ecosystem, where models like Llama 4 bring a “chain of thought” deep reasoning to open-source AI. 🌐