AI

In this tutorial, we build an advanced, end-to-end learning pipeline Atomic-Agents by combining typed agent interfaces, structured information, and a unified retrieval layer that supports results in original project documents. Also, we show how to organize the retrieval, retrieve the corresponding context, dynamically inject it into the responding agent, and use an interactive loop that … Read more

You sign up (a free tier is available), create a companion by customizing features and appearance, and jump into the conversation. The Ourdream AI dialog flows based on your selections and memory history. When you sign up, you open media-generating photos and short videos of your friend based on the context of the conversation or … Read more

Sixteen independent AI agents. Two weeks of continuous killing. About 100,000 lines of Rust code. That’s what it took for Anthropic to build a C compiler capable of compiling large real-world projects like the Linux kernel. There is a kicker here though. The project, internally referred to as Claude’s “agent teams”, was not written by … Read more

Running Large Language Models (LLMs) at scale is a major engineering challenge due to the management of the Key-Value (KV) repository. As models grow in size and processing power, KV’s cache footprint grows and becomes a major bottleneck in throughput and performance. In modern Transformers, this cache can take many gigabytes. NVIDIA researchers presented KVTC … Read more

Google Research proposes a new way to create accessible software with Natively Adaptive Interfaces (NAI), an agent framework where a multimodal AI agent becomes the main user interaction and adapts the application in real time to the skills and capabilities of each user. Instead of deploying a focused UI and adding accessibility as a separate … Read more

section(“6) pack unpack”) B, Cemb = 2, 128 class_token = torch.randn(B, 1, Cemb, device=device) image_tokens = torch.randn(B, 196, Cemb, device=device) text_tokens = torch.randn(B, 32, Cemb, device=device) show_shape(“class_token”, class_token) show_shape(“image_tokens”, image_tokens) show_shape(“text_tokens”, text_tokens) packed, ps = pack([class_token, image_tokens, text_tokens], “b * c”) show_shape(“packed”, packed) print(“packed_shapes (ps):”, ps) mixer = nn.Sequential( nn.LayerNorm(Cemb), nn.Linear(Cemb, 4 * Cemb), nn.GELU(), … Read more

Another month, another AI-powered trend taking over the internet, and this one is about making a caricature of yourself using ChatGPT Image. From LinkedIn feeds to group chats, people are sharing versions of themselves that capture not just their face, but their work, personality, and vibe. The best part is that you don’t need any … Read more

Alibaba Tongyi Lab’s research team has released ‘Zvec’, an open-source, in-process vector database that targets on-device performance and discovery. It is classified as a ‘data vector SQLite’ because it works as a library within your application and does not require any external service or daemon. It is designed for advanced retrieval generation (RAG), semantic search, … Read more

Whether the purpose is casual conversation, structured role-playing, or adult-oriented exchanges, Romantic AI Girlfriend Chat gives users control over how conversations develop while remaining accurate and accessible everywhere. ⚡️ FAVORITE CONVERSATIONS ⚡️ Candy AI Try Candy AI Unfiltered Chat with AI GirlsPictures and voice messagesVideo Generation My dream friend Try Mydreamcompanion Spicy AI ChattingText and … Read more

Text auto-completion and chat questions are no longer the only roles of AI agents. They now refactor repositories, create scripts, update code bases, and use unsupervised workflows, creating new challenges in connecting multiple agents without losing context, control, or code quality. Maestro, the latest AI Agents orchestration platform, addresses this need as an application that … Read more