#苹果#苹果耳机#苹果产品#Apple#AppleProduct#AppleEarpods 苹果的入耳式耳机什么时候能解决骑行时��风噪问题!尤其是降噪模式(独处时光)
When will Apple's in-ear headphones resolve the issue of wind noise during cycling? Especially in noise cancellation mode ('Alone Time').
AI to programmers as if programmers to product manager . Product manager knows the business but no logical detail, programmers know what's that means after the business number. So, AI can writes the code for you but also it will take the soul from you!
𝗠𝗖𝗣 𝘃𝘀. 𝗔𝟮𝗔
Two days ago Google announced an open A2A (Agent2Agent) protocol in an attempt to normalise how we implement multi-Agent system communication.
As always, social media is going crazy about it, but why?
Let’s review the differences and how both protocols complement each other (read till the end).
𝘔𝘰𝘷𝘪𝘯𝘨 𝘱𝘪𝘦𝘤𝘦𝘴 𝘪𝘯 𝘔𝘊𝘗:
𝟭. MCP Host - Programs using LLMs at the core that want to access data through MCP.
❗️ When combined with A2A, an Agent becomes MCP Host.
𝟮. MCP Client - Clients that maintain 1:1 connections with servers.
𝟯. MCP Server - Lightweight programs that each expose specific capabilities through the standardized Model Context Protocol.
𝟰. Local Data Sources - Your computer’s files, databases, and services that MCP servers can securely access.
𝟱. Remote Data Sources - External systems available over the internet (e.g., through APIs) that MCP servers can connect to.
𝘌𝘯𝘵𝘦𝘳 𝘈2𝘈:
Where MCP falls short, A2A tries to help. In multi-Agent applications where state is not necessarily shared
𝟲. Agents (MCP Hosts) would implement and communicate via A2A protocol, that enables:
➡️ Secure Collaboration - MCP lacks authentication.
➡️ Task and State Management.
➡️ User Experience Negotiation.
➡️ Capability discovery - similar to MCP tools.
𝗛𝗼𝗻𝗲𝘀𝘁 𝘁𝗵𝗼𝘂𝗴𝗵𝘁𝘀:
❗️ I believe creators of MCP were planning to implement similar capabilities to A2A and expose agents via tools in long term.
❗️ We might just see a fight around who will win and become the standard protocol long term as both protocols might be expanding.
Let me know your thoughts in the comments. 👇
#LLM #AI #MachineLearning
Introducing our first set of Llama 4 models!
We’ve been hard at work doing a complete re-design of the Llama series. I’m so excited to share it with the world today and mark another major milestone for the Llama herd as we release the *first* open source models in the Llama 4 collection 🦙. Here are some highlights:
📌 The Llama series have been re-designed to use state of the art mixture-of-experts (MoE) architecture and natively trained with multimodality. We’re dropping Llama 4 Scout & Llama 4 Maverick, and previewing Llama 4 Behemoth.
📌 Llama 4 Scout is highest performing small model with 17B activated parameters with 16 experts. It’s crazy fast, natively multimodal, and very smart. It achieves an industry leading 10M+ token context window and can also run on a single GPU!
📌 Llama 4 Maverick is the best multimodal model in its class, beating GPT-4o and Gemini 2.0 Flash across a broad range of widely reported benchmarks, while achieving comparable results to the new DeepSeek v3 on reasoning and coding – at less than half the active parameters. It offers a best-in-class performance to cost ratio with an experimental chat version scoring ELO of 1417 on LMArena. It can also run on a single host!
📌 Previewing Llama 4 Behemoth, our most powerful model yet and among the world’s smartest LLMs. Llama 4 Behemoth outperforms GPT4.5, Claude Sonnet 3.7, and Gemini 2.0 Pro on several STEM benchmarks. Llama 4 Behemoth is still training, and we’re excited to share more details about it even while it’s still in flight.
A big thanks to all of our launch partners (full list in blog) for helping us bring Llama 4 to developers everywhere including @huggingface, @togethercompute, @SnowflakeDB, @ollama, @databricks and many others👏 This is just the start, we have more models coming and the team is really cooking – look out for Llama 4 Reasoning 😉
A few weeks ago, we celebrated Llama being downloaded over 1 billion times. Llama 4 demonstrates our long-term commitment to open source AI, the entire open source AI community, and our unwavering belief that open systems will produce the best small, mid-size and soon frontier models. Llama would be nothing without the global open source AI community & we are so ready to begin this next chapter with you. 🦙
Read more about the release here: https://t.co/7mbK3uggjO, and try it in our products today.