Browsing: Models

(ROOT / “shop” / “admin.py”).write_text(”’ from django.contrib import admin, messages from django.contrib.auth.admin import (UserAdmin as DjangoUserAdmin, GroupAdmin as DjangoGroupAdmin) from django.contrib.auth.models import User, Group from django.shortcuts…

As LLM-powered applications move into production — and as AI agents take on more consequential tasks like browsing the web, writing and executing code, and interacting…

Pre-training large language models is expensive enough that even modest efficiency improvements can translate into meaningful cost and time savings. Nous Research is releasing Token Superposition…

Most AI systems today work in turns. You type or speak, the model waits, processes your input, and then responds. That’s the entire interaction loop. Thinking…

Training a family of large language models (LLMs) has always come with a painful multiplier: every model variant in the family—whether 8B, 30B, or 70B—typically requires…

I be one of the most interesting discoveries (and topics) in artificial intelligence, leaving aside the debate about whether this is intelligence at all or not.…

Evaluating AI models trained on brain signals has long been a messy, inconsistent topic. Different research groups use different preprocessing pipelines, train models on different datasets,…

only as strong as their knowledge base. An accurate and curated knowledge base improves both model speed and accuracy—areas where current models often fall short. In…

bill era For years, making a model smarter meant increasing parameters during training. Today, flagship models like GPT 5.5 and the o1 series achieve high performance…

The bottleneck in building better AI models has never been compute alone — it has always been data quality. Meta AI’s RAM (Reasoning, Alignment, and Memory)…