Practical Agentic Coding with Google JulesImage by Editor Introducing Google Jules If you have an interest in agentic coding, there’s a pretty good chance you’ve heard of Google Jules by now. But if not, now’s the time to learn all…
Training a language model is memory-intensive, not only because the model itself is large but also because the long sequences in the training data batches. Training a model with limited memory is challenging. In this article, you will learn techniques…
Training a language model with a deep transformer architecture is time-consuming. However, there are techniques you can use to accelerate training. In this article, you will learn about: Using torch.compile() to speed up the model Using gradient accumulation to train…
import dataclasses import os import datasets import tqdm import tokenizers import torch import torch.distributed as dist import torch.nn as nn import torch.nn.functional as F import torch.optim.lr_scheduler as lr_scheduler from torch import Tensor from torch.nn.parallel import DistributedDataParallel as DDP from…
Google has released FunctionGemma, a specialized version of the Gemma 3 270M model that is trained specifically for function calling and designed to run as an edge agent that maps natural language to executable API actions. But, What is FunctionGemma?…
In this tutorial, we dive into the cutting edge of Agentic AI by building a “Zettelkasten” memory system, a “living” architecture that organizes information much like the human brain. We move beyond standard retrieval methods to construct a dynamic knowledge…
Just months after releasing M2—a fast, low-cost model designed for agents and code—MiniMax has introduced an enhanced version: MiniMax M2.1. M2 already stood out for its efficiency, running at roughly 8% of the cost of Claude Sonnet while delivering significantly…
In this tutorial, we build an advanced, fully autonomous logistics simulation in which multiple smart delivery trucks operate within a dynamic city-wide road network. We design the system so that each truck behaves as an agent capable of bidding on…
Agentic AI systems sit on top of large language models and connect to tools, memory, and external environments. They already support scientific discovery, software development, and clinical research, yet they still struggle with unreliable tool use, weak long horizon planning,…
Genomic prediction and design now require models that connect local motifs with megabase scale regulatory context and that operate across many organisms. Nucleotide Transformer v3, or NTv3, is InstaDeep’s new multi species genomics foundation model for this setting. It unifies…
