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NVIDIA's CEO Jensen Huang is set to take the stage for his GTC Taipei keynote at 8PM PT / 11PM ET. You can watch all the announcements here and embedded below. Rumors have been flying about what to expect from today's presentation, but the big one is the possibility of a partnership with Microsoft and […]
My eyes have seen the PC gaming promised land, and it's a beautifully bright world without a shred of blurriness. It's warm, it looks lovely, and it's impeccably sharp. Also, it's expensive as hell. I've dipped my toe in this world by testing a pre-production version of the upcoming Asus ROG Strix Scar 18, which […]
I’ve spent a lot of time lately thinking about why some LLM agents feel "intelligent" while others just feel like chatbots with a slightly better prompt. It almost always comes down to how the system handles memory. When we treat the context window as the only place for state, we hit a ceiling very quickly. To build an actual agent, we have to move away from "one big prompt" and toward a layered memory architecture. Agentic Memory can be categorized in 4 layers by their function: Working Memory: The current context window. It's our RAM—fast, essential, but wiped clean after every session. Semantic Memory: The Vector DB or knowledge base. This is where the "world rules" and global conventions live. It’s the reference manual the agent checks to stay aligned. Procedural Memory: The "how-to" layer. Instead of stuffing every tool description into the prompt, the agent maintains a lean index of skills and pulls in the full implementation only when a specific task triggers it. This keeps the context window clean. Episodic Memory: This is the hardest part. It's the ability to distill a past interaction into a reusable insight. The real engineering challenge here isn't storage—it's the "forgetting" logic. Deciding what is noise and what is a core pattern is where most frameworks still struggle. Depending on the use case, the architecture changes: Reflex Agents: Just Working Memory. Support Agents: Working + Procedural. Coding Agents: The full stack. The gap between a demo and a production-ready agent is usually the distance between simple RAG and a functioning episodic memory. The ability to compress experience into a usable state is still a significant hurdle. Which of these layers are you currently implementing, and how are you handling the "forgetting" logic in your episodic memory?
It's the world's worst kept secret that Nvidia is about to announce its own Arm-powered laptop chips at Computex this weekend, and now Microsoft, Nvidia, and Arm are all openly teasing the announcement. The Windows and Nvidia GeForce accounts on X both posted "A new era of PC" earlier today, and now Arm has followed […]
I pondered the other day what's next for Microsoft's Surface PC lineup, and it looks like we're about to find out. Windows and Surface chief Pavan Davuluri has just teased "something new is coming for developers," complete with a mysterious image of what looks like a curved display edge. Davuluri notes that whatever is coming […]
Acer is aiming to take on the MacBook Neo more directly with a new Swift Air 14, a new 14-inch laptop that starts at $699. The laptop will use Intel's lower-cost Core Series 3 "Wildcat Lake" chips - either Core 5 or Core 7 models, both of which are six-core processors. It comes in green, […]
Cloudflare recently added support for Claude Managed Agents, allowing developers to run and manage Claude agents within Cloudflare. Developers can connect agents to private systems, choose their runtime environment, and monitor agent activity using Cloudflare services. By Renato Losio