Al, Analytics and Automation
Evaluating Perplexity on Language Models
A language model is a probability distribution over sequences of tokens. When you train a language model, you want to...
NVIDIA AI Researchers Release NitroGen: An Open Vision Action Foundation Model For Generalist Gaming Agents
NVIDIA AI research team released NitroGen, an open vision action foundation model for generalist gaming agents that learns to play...
Practical Agentic Coding with Google Jules
Practical Agentic Coding with Google JulesImage by Editor Introducing Google Jules If you have an interest in agentic coding, there’s...
Liquid AI’s LFM2-2.6B-Exp Uses Pure Reinforcement Learning RL And Dynamic Hybrid Reasoning To Tighten Small Model Behavior
Liquid AI has introduced LFM2-2.6B-Exp, an experimental checkpoint of its LFM2-2.6B language model that is trained with pure reinforcement learning...
Training a Model with Limited Memory using Mixed Precision and Gradient Checkpointing
Training a language model is memory-intensive, not only because the model itself is large but also because the long sequences...
How to Build Production-Grade Agentic Workflows with GraphBit Using Deterministic Tools, Validated Execution Graphs, and Optional LLM Orchestration
In this tutorial, we build an end-to-end, production-style agentic workflow using GraphBit that demonstrates how graph-structured execution, tool calling, and...
Train a Model Faster with torch.compile and Gradient Accumulation
Training a language model with a deep transformer architecture is time-consuming. However, there are techniques you can use to accelerate...
DarLink Chatbot Access, Pricing, and Feature Overview
Engaging with the AI models in DarLink creates the impression of a flowing dialogue instead of a rigid input-output process,...
From Gemma 3 270M to FunctionGemma, How Google AI Built a Compact Function Calling Specialist for Edge Workloads
Google has released FunctionGemma, a specialized version of the Gemma 3 270M model that is trained specifically for function calling...
Training a Model on Multiple GPUs with Data Parallelism
import dataclassesimport os import datasetsimport tqdmimport tokenizersimport torchimport torch.distributed as distimport torch.nn as nnimport torch.nn.functional as Fimport torch.optim.lr_scheduler as lr_schedulerfrom torch...
POPULAR NEWS
