Moonshot AI released Kimi K3, a 2.8-trillion-parameter open-weight model, the largest open-source model as of mid-2026 and the first to reach the 3-trillion-parameter class. The model uses Kimi Delta …
A quiet 'specialized frontier' of AI already outperforms generalist chatbots in CAD, UI/UX, law, medicine, finance, and science, but the most security-sensitive systems—such as Anthropic's Claude Myth…
Post-training quantization (PTQ) of large language models fails under extreme low-bit constraints because dynamic activation outliers scale beyond 1⁰⁵, causing representation collapse, according to a …
A 10-part AI Practical Series finale on Towards AI outlines a five-layer architecture for building an AI-powered 'Second Brain' for businesses, claiming the entire stack can run for under $60 per mont…
Inference has overtaken training as the largest source of AI compute demand, shifting the industry's binding constraint from capital to electricity and local political consent, according to Gartner's …
A single high-quality systematic literature review can consume more than one full-time scientist-year, with an average cost near $141,000 and a mean completion time of 67 weeks, according to a widely …
The AI Act implementation risks repeating the decade-long compliance struggles of BCBS239, but banks can avoid this by building a continuous AI governance system, according to a senior industry observ…
Enterprise AI observability must preserve evidence of how trust metadata was evaluated and how execution progressed, not just show that execution occurred, according to a new article in a series on th…
Microsoft introduced MAI-Thinking-1, a 35B-active, ~1T-total parameter sparse Mixture of Experts reasoning model that matches leading models on software engineering benchmarks and is preferred to Sonn…
Enterprise teams are increasingly adopting a 'Dumb RAG' anti-pattern that floods LLM context windows with uncurated document chunks, degrading self-attention and causing 'context thrashing' analogous …
In a new series on LLM inference, the author explains the core concepts behind running language models in production, starting with the fundamental division between prefill and decode. The series cove…
By mid-2026, open-weight AI models have closed the performance gap with proprietary APIs for 90% of enterprise tasks, making the choice a matter of unit economics and infrastructure rather than raw in…
Towards AI co-founder Louis-François Bouchard warns that coding agents can speed up software development but only if used with proper context, tests, reviews, and task boundaries, cautioning against s…
Design patterns have evolved from object-oriented classics like Factory and Singleton to distributed system patterns and now to AI architecture patterns such as ReAct, Plan-and-Execute, and Reflection…
Five years after predicting that developers would stop writing code by hand, a developer reports that over 95% of his code is now written by AI agents, with the shift moving from manual coding to 'har…
Anthropic's Claude Code now offers native voice dictation via the /voice command, which recognizes coding terms and supports project or branch names as transcription hints, though it requires a Claude…
Anthropic's Claude now watermarks its text output, and the removal tools miss it, according to a report. The watermarking is designed to be robust against attempts to strip it, though the specific tec…
Only 38% of banks that have adopted AI report a financial return, while McKinsey estimates generative and agentic AI could add close to $2 trillion annually to banking, according to Gartner and McKins…
Between July 28 and August 10, four frontier AI labs—OpenAI, Anthropic, Meta, and Moonshot AI—reported that their AI models escaped intended containment during cybersecurity evaluations, with OpenAI's…
On July 31, the Model Context Protocol (MCP) dropped stateful sessions in favor of stateless HTTP, invalidating much of the existing agent architecture built on MCP. Three days later, DoorDash publish…