This week, the Cohere AI team sent their first developer-facing code model called ‘Little North Code’. ‘North Mini Code’ is open-minded and focused on application developers. It is a mixture of experts (MoE) model with a total of 30B parameters. Only 3B of those parameters work per token. The release is positioned around “autonomous” AI. … Read more
Development has evolved from hand-typing code to defining intent and letting agents do the work. Today’s tools organize tasks, edit across files, run tests, open pull requests, and send to production — with limited oversight. There is no one tool that fits all needs. This guide walks through the platforms shaping AI-assisted development in 2026 … Read more
Anthropic released two models on June 9, 2026: Claude Fable 5 and Claude Mythos 5. Both are under the so-called “Mythos-class.” This category sits above the Opus category in strength. Myth 5 is a version that is said to be safe for general use. The Mythos 5 is the same model with some enhanced protections, … Read more
AI tools have gone from “fun to try” to part of daily work. There is an AI tool for almost everything these days, readily available to all. The problem is no longer access. It is optional. Every week, a new tool promises to save time, increase creativity, or replace half of your work. Most just … Read more
Remember the Claude Mythos preview? Yes, the same AI model announced by Anthropic earlier this year, which sent even governments around the world into a frenzy. A model that found security holes in almost any network it was tested on, and was so powerful that it had to be kept limited within the highly regulated … Read more
Google recently announced Gemini 3.5 Translate Live. It is their latest audio model for live speech-to-speech translation. Speech-to-speech means that spoken audio goes in, and translated spoken audio goes out. The model automatically detects more than 70 languages and produces translated speech. It preserves the speaker’s pitch, tempo, and pitch in the output. Turn-by-turn systems … Read more
print(“n” + “=” * 90) print(“[5] cuTile kernels are defined only if cuda.tile imports successfully”) print(“=” * 90) if cutile_import_ok: ConstInt = ct.Constant[int] @ct.kernel def cutile_vec_add_direct_kernel(a, b, c, TILE: ConstInt): bid = ct.bid(0) a_tile = ct.load(a, index=(bid,), shape=(TILE,)) b_tile = ct.load(b, index=(bid,), shape=(TILE,)) c_tile = a_tile + b_tile ct.store(c, index=(bid,), tile=c_tile) @ct.kernel def cutile_vec_add_gather_kernel(a, b, … Read more
New research in action from Perplexity and Harvard provides ground-breaking evidence on what AI agents are doing in information work. It draws on production data from two Perplexity products: Search and Computing. The setting is a natural comparison. Search is a conversational response engine. A computer is an agent that organizes and executes end-to-end operations. … Read more
Inference speed becomes a competitive metric for large language models. Xiaomi’s MiMo team has just released MiMo-V2.5-Pro-UltraSpeed, developed in collaboration with the TileRT programming team. It records faster than 1000 tokens per second in a trillion parameter model. The Xiaomi team describes this as starting on a multi-billion parameter scale. The demos show a production … Read more
We have all been in an emergency where every second counts. A person’s life is at risk, but when you panic. Now, imagine in this stressful situation where a helpline asks you to press numbers on your keypad to connect with the right agent? Pure chaos, right? Here, we just need someone who will listen … Read more