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100 articles

01
Synthesize Realistic 3D Medical Images at Scale to Ship Pre‑Trained Models
High‑quality 3D medical imaging data is the foundation of modern radiology AI, but access to it is often constrained by …
NVIDIA Developer BlogResearch#inference#coding#local
24d
02
Specialization Beats Scale: A Strategic Variable Most AI Procurement Decisions Overlook
Specialization Beats Scale: A Strategic Variable Most AI Procurement Decisions Overlook When a model’s training history …
Hugging Face BlogResearch#inference#benchmark#training
24d
03
Announcing VeRL-Omni: Easy, Fast, and Stable RL Training for Diffusion and Omni-Modality Models May 14, 2026 · 7 min read We are excited to announce the pre-release of VeRL-Omni, a general reinforcement learning (RL) post-training framework focused on multimodal generative models, built on top of verl and vllm-omni.
Announcing VeRL-Omni: Easy, Fast, and Stable RL Training for Diffusion and Omni-Modality Models We are excited to announ…
32d
04
An Engineer’s Post Protesting Laptop Surveillance Is Going Viral Inside Meta
Meta’s decision to track employee keystrokes and mouse data is causing an uproar within the company. “Selfishly, I don't…
Wired AIInfra#local#training
32d
05
Generating Beautiful UIs May 08, 2026
With contributions from Sherif Cherfa and Halley Chang There’s an intuitive skepticism we have toward AI-generated work.…
Cerebras BlogTutorial#inference#training
33d
06
Anthropic blames dystopian sci-fi for training AI models to act “evil”
Those with an interest in the concept of AI alignment (i.e., getting AIs to stick to human-authored ethical rules) may r…
Ars Technica AIResearch#claude#training#safety
33d
07
Building Blocks for Foundation Model Training and Inference on AWS
Building Blocks for Foundation Model Training and Inference on AWS Figure: Adapted from "AI's Three Scaling Laws, Explai…
Hugging Face BlogHardware#rag#inference#observability
35d
08
I Work in Hollywood. Everyone Who Used to Make TV Is Now Secretly Training AI
My name on the platform is ri611. Or h924092b12ee797f, depending on who’s paying me. I work as an AI trainer. I assess w…
35d
09
EMO: Pretraining mixture of experts for emergent modularity
EMO: Pretraining mixture of experts for emergent modularity Today we're releasing EMO, a new mixture-of-experts (MoE) mo…
Hugging Face BlogModel#fine-tuning#coding#training
38d
10
Real-Time Performance Monitoring and Faster Debugging with NCCL Inspector and Prometheus
Distributed deep learning depends on fast, reliable GPU-to-GPU communication using the NVIDIA Collective Communication L…
NVIDIA Developer BlogHardware#observability#training#gpu
39d
11
Model Quantization: Post-Training Quantization Using NVIDIA Model Optimizer
Model quantization is an effective method to reduce VRAM usage and improve inference performance on consumer devices suc…
NVIDIA Developer BlogHardware#inference#training#gpu
39d
12
Introducing Multi-LoRA on Cerebras Inference May 06, 2026
Today, we are launching Multi-LoRA—multi-adapter support for Low-Rank Adaptation—on Cerebras Inference in private previe…
Cerebras BlogTutorial#fine-tuning#inference#training
39d
13
Overcoming reward signal challenges: Verifiable rewards-based reinforcement learning with GRPO on SageMaker AI
Artificial Intelligence Overcoming reward signal challenges: Verifiable rewards-based reinforcement learning with GRPO o…
AWS Machine Learning BlogTutorial#coding#training
39d
14
Secure short-term GPU capacity for ML workloads with EC2 Capacity Blocks for ML and SageMaker training plans
Artificial Intelligence Secure short-term GPU capacity for ML workloads with EC2 Capacity Blocks for ML and SageMaker tr…
AWS Machine Learning BlogTutorial#inference#training
39d
15
How ChatGPT learns about the world while protecting privacy
How ChatGPT learns about the world while protecting privacy A plain-language guide to model training, privacy safeguards…
OpenAI BlogTutorial#gpt#local#training
40d
16
Unlocking large scale AI training networks with MRC (Multipath Reliable Connection)
Supercomputer networking to accelerate large scale AI training Frontier model training depends on reliable supercomputer…
OpenAI BlogInfra#training
41d
17
MoE at Scale: Making Sparse Models Fast on Real Hardware September 03, 2025
In this video we discuss scaling MoE models on modern hardware and address key optimization challenges. If you can’t ope…
Cerebras BlogTutorial#inference#training
41d
18
MoE Math Demystified: What Does 8x7B Actually Mean? October 14, 2025
This video breaks down MoE inference arithmetic and deployment bottlenecks across different hardware setups. If you can’…
Cerebras BlogTutorial#inference#training
41d
19
He Couldn’t Land a Job Interview. Was AI to Blame?
It was mid-October, peak leaf-peeping season in Hanover, New Hampshire, and Chad Markey was on a rare break between clin…
41d
20
Book publishers sue Meta over AI’s ‘word-for-word’ copying
Meta is facing a class action lawsuit filed by five major book publishers and one author over claims the company “engage…
The Verge AIModel#llama#training
41d
21
Granite 4.1 3B SVG Pelican Gallery
4th May 2026 - Link Blog Granite 4.1 3B SVG Pelican Gallery. IBM released their Granite 4.1 family of LLMs a few days ag…
Simon Willison BlogOpen Source#training
42d
22
Musk v. Altman Kicks Off, DOJ Guts Voting Rights Unit, and Is the AI Job Apocalypse Overhyped?
This week on Uncanny Valley, the team discusses the stakes behind the trial of Elon Musk against OpenAI’s leadership (an…
Wired AI#training
46d
23
This startup’s new mechanistic interpretability tool lets you debug LLMs
This startup’s new mechanistic interpretability tool lets you debug LLMs Goodfire wants to make training AI models more …
MIT Technology ReviewResearch#training
46d
24
Introducing AutoSP
Increasingly, Large-Language-Models (LLMs) are being trained for extremely long-context tasks, where token counts can ex…
PyTorch BlogHardware#coding#training
47d
25
Granite 4.1 LLMs: How They’re Built
Granite 4.1 LLMs: How They’re Built Authors: Granite Team, IBM TL;DR — Granite 4.1 is a family of dense, decoder‑only LL…
Hugging Face BlogInfra#training
47d2 views
26
‘It’s Undignified’: Hundreds of Workers Training Meta’s AI Could Be Laid Off
Hundreds of workers in Ireland tasked with refining Meta’s AI models have been told that their jobs are at risk as the c…
48d
27
4/24/2026 Notes on DeepSeek-V4's training system
On this page DeepSeek-V4 is interesting less for any single benchmark number than for the shape of the system around it.…
Fireworks AI BlogInfra#training
52d
28
Figma - MultiAgents April 16, 2026
Everything is easier now. I have been toying around with agent orchestration for a while now. I’m currently running 10-2…
Cerebras BlogTutorial#inference#training
53d
29
Advancing Emerging Optimizers for Accelerated LLM Training with NVIDIA Megatron
Higher-order optimization algorithms such as Shampoo have been effectively applied in neural network training for at lea…
NVIDIA Developer BlogInfra#qwen#inference#observability
54d
30
Google unveils two new TPUs designed for the "agentic era"
Most of the companies that have fully committed to building AI models are gobbling up every Nvidia AI accelerator they c…
Ars Technica AIHardware#agents#inference#training
54d
31
scosman/pelicans_riding_bicycles
21st April 2026 - Link Blog scosman/pelicans_riding_bicycles (via) I firmly approve of Steve Cosman's efforts to pollute…
Simon Willison BlogModel#training
55d
32
Report: Meta will train AI agents by tracking employees' mouse, keyboard use
Meta will begin tracking the mouse movements, clicks, and keystrokes of its US employees to generate high-quality traini…
Ars Technica AIModel#training
55d
33
Run High-Throughput Reinforcement Learning Training with End-to-End FP8 Precision
As LLMs transition from simple text generation to complex reasoning, reinforcement learning (RL) plays a central role. A…
NVIDIA Developer BlogInfra#inference#training
56d
34
Lessons learned from building multi-agent workflows April 16, 2026
I pay my upfront subscription ($200/month), write what I hope is the right prompt (prompt AND context engineer), and wai…
Cerebras BlogTutorial#agents#inference#training
56d
35
Optimizing Effective Training Time for Meta’s Internal Recommendation/Ranking Workloads
Motivation and Introduction Across the industry, teams training and serving large AI models face aggressive ROI targets …
PyTorch BlogInfra#inference#training
59d
36
Nova Forge SDK series part 2: Practical guide to fine-tune Nova models using data mixing capabilities
Artificial Intelligence Nova Forge SDK series part 2: Practical guide to fine-tune Nova models using data mixing capabil…
AWS Machine Learning BlogTutorial#fine-tuning#training
59d
37
Training and Finetuning Multimodal Embedding & Reranker Models with Sentence Transformers
Training and Finetuning Multimodal Embedding & Reranker Models with Sentence Transformers As a practical example, I'll w…
Hugging Face BlogInfra#fine-tuning#multimodal#training
60d
38
Cut Checkpoint Costs with About 30 Lines of Python and NVIDIA nvCOMP
Training LLMs requires periodic checkpoints. These full snapshots of model weights, optimizer states, and gradients are …
NVIDIA Developer BlogModel#rag#training#gpu
67d
39
SOTA Normalization Performance with torch.compile
Introduction Normalization methods (LayerNorm/RMSNorm) are foundational in deep learning and are used to normalize value…
PyTorch BlogResearch#training#gpu#safety
68d
40
Monarch: an API to your supercomputer
Getting distributed training jobs to run on huge clusters is hard! This is especially true when you start looking at mor…
PyTorch BlogInfra#training
68d
41
The Debate of MCP vs. CLI Centers on Speed April 06, 2026
MCP had a formative year. Then it had a turbulent week. Perplexity CTO Denis Yarats walked on stage at Ask 2026 and anno…
Cerebras BlogTutorial#inference#training
69d
42
4/6/2026 Own Your AI: Fireworks Training Preview
Fireworks Training is now in preview: an end-to-end platform for training and deploying frontier models at scale. Three …
Fireworks AI BlogInfra#fine-tuning#inference#training
70d
43
How Enterprise AI SaaS Closes Adoption Gaps with Multi-Agent Crews João (Joe) Moura Apr 6, 2026
How Enterprise AI SaaS Closes Adoption Gaps with Multi-Agent Crews Enterprise AI SaaS automates customer enablement with…
CrewAI BlogAgents#agents#training
70d
44
Why speed wins: faster inference is about more than just quicker answers–it’s the new path to accuracy February 19, 2026
Feb 19 2026 Why speed wins: faster inference is about more than just quicker answers–it’s the new path to accuracy Watch…
Cerebras BlogTutorial#inference#training
73d
45
4/3/2026 Scaling and Optimizing Frontier Model Training
On this page How Fireworks scales frontier model training and offers the broadest set of fine-tunable MoE models on any …
Fireworks AI BlogHardware#fine-tuning#inference#training
73d
46
Build and Stream Browser-Based XR Experiences with NVIDIA CloudXR.js
Delivering high-fidelity VR and AR experiences to enterprise users has typically required native application development…
NVIDIA Developer BlogTutorial#agents#coding#training
76d
47
TRL v1.0: Post-Training Library Built to Move with the Field
TRL v1.0: Post-Training Library Built to Move with the Field TRL now implements more than 75 post-training methods. But …
Hugging Face BlogRelease#training
76d
48
Training mRNA Language Models Across 25 Species for $165
Training mRNA Language Models Across 25 Species for $165 Part II: Building the Pipeline, From Structure Prediction to Co…
Hugging Face BlogHardware#agents#fine-tuning#coding
76d
49
3/28/2026 The Fine-Tuning Bottleneck Isn't the Algorithm
TL;DR: Integration friction and slow iteration cycles are the bottlenecks that actually stall fine-tuning — not the algo…
Fireworks AI BlogModel#fine-tuning#training
79d
50
Partner Spotlight: Armis + Cerebras Enable Teams Build and Secure Software Faster March 27, 2026
Mar 27 2026 Partner Spotlight: Armis + Cerebras Enable Teams Build and Secure Software Faster At Cerebras, we’ve always …
Cerebras BlogTutorial#inference#training
80d
51
Jais 2: A Blueprint for Sovereign AI December 09, 2025
Arabic is spoken by more than 400 million people, yet Arabic-centric Large Language Models (LLMs)still lag behind Englis…
Cerebras BlogTutorial#inference#training
81d
52
Cerebras is coming to AWS March 13, 2026
The world’s fastest inference is coming to the world’s leading cloud. Today we're announcing that Amazon Web Services is…
Cerebras BlogTutorial#inference#training
81d
53
The world’s fastest GLM-4.6 – now available on Cerebras November 18, 2025
Today, Cerebras is releasing GLM-4.6 — our most capable model yet on the Cerebras Inference API. GLM-4.6 brings major up…
Cerebras BlogTutorial#inference#training
82d
54
Introducing OpenAI GPT-5.3-Codex-Spark Powered by Cerebras February 12, 2026
Today, we’re announcing that OpenAI’s new GPT-5.3-Codex-Spark model, powered by Cerebras, is available in research previ…
Cerebras BlogTutorial#inference#training
82d
55
Enabling Up to 41% Faster Pre-training: MXFP8 and DeepEP for DeepSeek-V3 on B200 with TorchTitan
TL;DR In a joint effort between PyTorch and Nebius, we enabled training DeepSeek-V3 Mixture-of-Experts models (16B and 6…
PyTorch BlogHardware#training#gpu
82d
56
Designing Protein Binders Using the Generative Model Proteina-Complexa
Developing new protein-based therapies and catalysts involves the challenging task of designing protein binders, or prot…
NVIDIA Developer BlogTutorial#training#gpu
82d
57
The GPU Is Being Split in Half March 26, 2026
The entire way we run AI inference is being rearchitected right now. AWS and Cerebras just announced a partnership aroun…
Cerebras BlogTutorial#inference#training
82d
58
March 20, 2026 Why the AI Race Shifted to Speed Read blog post
For most of 2025, the AI race was about model intelligence. In the past three months, the race has shifted. Model intell…
Cerebras BlogTutorial#inference#training
82d
59
PyTorch 2.11 Release Blog
We are excited to announce the release of PyTorch® 2.11 (release notes)! The PyTorch 2.11 release features the following…
PyTorch BlogInfra#training
84d
60
3/23/2026 Frontier RL Is Cheaper Than You Think
On this page The conventional wisdom on RL infrastructure is wrong, and it is costing teams that could be competing at t…
Fireworks AI BlogInfra#training
84d
61
Build a Domain-Specific Embedding Model in Under a Day
Build a Domain-Specific Embedding Model in Under a Day With a single GPU and less than a day of training time, you can t…
Hugging Face BlogResearch#fine-tuning#training#embeddings
87d
62
TorchSpec: Speculative Decoding Training at Scale
Introduction Over the past year, large language models have rapidly expanded in both scale and capability. Frontier mode…
PyTorch BlogModel#qwen#coding#training
88d
63
ImportAI 449: LLMs training other LLMs; 72B distributed training run; computer vision is harder than generative text
ImportAI 449: LLMs training other LLMs; 72B distributed training run; computer vision is harder than generative text Wil…
Import AI (Jack Clark)Infra#multimodal#training
91d
64
Scale Synthetic Data and Physical AI Reasoning with NVIDIA Cosmos World Foundation Models
The next generation of AI-driven robots like humanoids and autonomous vehicles depends on high-fidelity, physics-aware t…
NVIDIA Developer BlogTutorial#agents#training#gpu
94d
65
Designing AI agents to resist prompt injection
Designing AI agents to resist prompt injection What social engineering teaches us about securing AI agents. AI agents ar…
OpenAI BlogAgents#gpt#agents#training
96d
66
Improving instruction hierarchy in frontier LLMs
Improving instruction hierarchy in frontier LLMs Introducing IH-Challenge, a training dataset that strengthens instructi…
OpenAI BlogInfra#coding#training#safety
97d
67
3/10/2026 Training-Inference Parity in MoE Models: Where Numerics Drift
On this page Kernel fusions that are mathematically equivalent can still drift numerically. Here are the parity bugs we …
Fireworks AI BlogInfra#qwen#inference#training
97d
68
Implementing Falcon-H1 Hybrid Architecture in NVIDIA Megatron Core
In the rapidly evolving landscape of large language model (LLM) development, NVIDIA Megatron Core has emerged as the fou…
NVIDIA Developer BlogModel#training#gpu
98d
69
Ulysses Sequence Parallelism: Training with Million-Token Contexts
Ulysses Sequence Parallelism: Training with Million-Token Contexts Ulysses Sequence Parallelism (part of the Arctic Long…
Hugging Face BlogResearch#fine-tuning#benchmark#training
98d
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Stop Shipping AI Slop: How Codex Spark Changes The Way You Code March 04, 2026
In the past few years, we've developed series of interesting workflows. Think Ralph loops and multi-agent orchestration …
Cerebras BlogTutorial#inference#coding#training
102d
71
Reasoning models struggle to control their chains of thought, and that’s good
Reasoning models struggle to control their chains of thought, and that’s good Why a limitation of frontier models is rea…
OpenAI BlogResearch#agents#observability#coding
102d
72
Cerebras February 2026 Highlights November 03, 2025
- OpenAI Codex-Spark launches, powered by Cerebras - UAE and India Advance Sovereign AI Infra with Cerebras - ExomeBench…
Cerebras BlogTutorial#inference#training
104d
73
Thinking Inside the Box: The Implicit Chain Transformer for Efficient State Tracking December 12, 2025
Dec 12 2025 Thinking Inside the Box: The Implicit Chain Transformer for Efficient State Tracking Motivation Large Langua…
Cerebras BlogTutorial#inference#training
104d
74
Cerebras October 2025 Highlights November 03, 2025
October was a month of momentum for Cerebras. With new launches, global events, and groundbreaking collaborations, we co…
Cerebras BlogTutorial#inference#training
104d
75
2026: Fast Inference Finds its Groove January 06, 2026
I met my wife learning to dance Argentine tango. In tango you cannot fake your way through the steps. You have to feel t…
Cerebras BlogTutorial#inference#training
104d
76
GLM-4.7: Frontier intelligence at record speed — now available on Cerebras January 08, 2026
Today, we’re announcing GLM-4.7, the latest GLM family model released from Z.ai, now available on Cerebras Inference Clo…
Cerebras BlogTutorial#inference#training
104d
77
PRX Part 3 — Training a Text-to-Image Model in 24h!
PRX Part 3 — Training a Text-to-Image Model in 24h! Introduction Welcome back 👋 In the last two posts (Part 1 and Part …
Hugging Face BlogHardware#inference#training
104d
78
Mixture of Experts (MoEs) in Transformers
Mixture of Experts (MoEs) in Transformers Introduction Over the past few years, scaling dense language models has driven…
Hugging Face BlogHardware#inference#training
109d
79
Creating an AI-powered Magic Studio
Canva Canva’s AI-powered Magic Studio used 5 billion times and counting. Canva is a visual communication platform, enjoy…
110d
80
Surging developer productivity with custom GPTs
Paf’s engineering team creates 85 custom GPTs to surge developer productivity Paf adopted ChatGPT Enterprise across its …
110d
81
ExomeBench: A Benchmark for Clinical Variant Interpretation in Exome Regions February 23, 2026
Feb 23 2026 ExomeBench: A Benchmark for Clinical Variant Interpretation in Exome Regions 1. What is ExomeBench? We are e…
Cerebras BlogTutorial#inference#benchmark#training
112d
82
Why we no longer evaluate SWE-bench Verified
Why SWE-bench Verified no longer measures frontier coding capabilities SWE-bench Verified is increasingly contaminated. …
OpenAI BlogResearch#coding#training
112d
83
Using NVFP4 Low-Precision Model Training for Higher Throughput Without Losing Accuracy
As the sizes of AI models and datasets continue to increase, relying only on higher-precision BF16 training is no longer…
NVIDIA Developer BlogInfra#inference#training
112d
84
Train AI models with Unsloth and Hugging Face Jobs for FREE
Train AI models with Unsloth and Hugging Face Jobs for FREE LiquidAI/LFM2.5-1.2B-Instruct ) through coding agents like C…
Hugging Face BlogInfra#claude#fine-tuning#coding
115d
85
Cerebras CS-3 vs. Groq LPU September 19, 2025
TL;DR The Cerebras CS-3 outperforms Groq’s LPU-based solution across almost all key metrics, delivering ~6x higher infer…
Cerebras BlogTutorial#inference#training
116d
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Cerebras CS-3 vs. Nvidia DGX B200 Blackwell September 19, 2025
Cerebras delivers the world’s fastest AI infrastructure TL;DR The Cerebras CS-3 system is 21x faster, 1/3 lower cost, an…
Cerebras BlogTutorial#inference#training#gpu
116d
87
3 Ways NVFP4 Accelerates AI Training and Inference
The latest AI models continue to grow in size and complexity, demanding increasing amounts of compute performance for tr…
NVIDIA Developer BlogInfra#inference#training
129d
88
StackAI × Cerebras: enabling the fastest inference for enterprise AI agents January 28, 2026
Jan 28 2026 StackAI × Cerebras: enabling the fastest inference for enterprise AI agents StackAI is a low-code enterprise…
Cerebras BlogTutorial#inference#training
132d
89
Accelerating Long-Context Model Training in JAX and XLA
Large language models (LLMs) are rapidly expanding their context windows, with recent models supporting sequences of 128…
NVIDIA Developer BlogModel#llama#training#gpu
132d
90
Training Design for Text-to-Image Models: Lessons from Ablations
Training Design for Text-to-Image Models: Lessons from Ablations Welcome back! This is the second part of our series on …
Hugging Face BlogTutorial#training
132d
91
The Year of Latency Debt (And How Big Tech Is Paying It Down) January 28, 2026
I typed a single sentence into one of the world's most advanced language models: "Write a function to parse JSON out of …
Cerebras BlogTutorial#inference#training
133d
92
Optimizing Communication for Mixture-of-Experts Training with Hybrid Expert Parallel
In LLM training, Expert Parallel (EP) communication for hyperscale mixture-of-experts (MoE) models is challenging. EP co…
NVIDIA Developer BlogModel#training#gpu
133d
93
Fast inference is going mainstream — the Cerebras ecosystem is scaling access January 28, 2026
Jan 28 2026 Fast inference is going mainstream — the Cerebras ecosystem is scaling access The broadband moment for AI in…
Cerebras BlogTutorial#inference#training
137d
94
Hear more about interactive world models in our latest podcast.
The latest episode of the Google AI: Release Notes podcast focuses on Genie 3, a real-time, interactive world model. Hos…
Google DeepMind BlogRelease#multimodal#training
137d
95
Speeding Up Variable-Length Training with Dynamic Context Parallelism and NVIDIA Megatron Core
This post introduces Dynamic Context Parallelism (Dynamic-CP), a scheduling approach in NVIDIA Megatron Core used for LL…
NVIDIA Developer BlogInfra#multimodal#training#gpu
138d
96
Unlocking Agentic RL Training for GPT-OSS: A Practical Retrospective
Unlocking Agentic RL Training for GPT-OSS: A Practical Retrospective LinkedIn is an AI-first company that's built agents…
Hugging Face BlogAgents#agents#training
139d
97
This new model is smarter than Sonnet 4.5…and 20X faster? January 08, 2026
So, you need speed, intelligence, and great economics… introducing GLM 4.7, the first open model that delivers all three…
Cerebras BlogTutorial#inference#training
146d
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ParaRNN: Large-Scale Nonlinear RNNs, Trainable in Parallel
ParaRNN: Large-Scale Nonlinear RNNs, Trainable in Parallel Recurrent Neural Networks (RNNs) are naturally suited to effi…
Apple Machine Learning ResearchResearch#inference#training
150d1 view
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OpenAI Partners with Cerebras to Bring High-Speed Inference to the Mainstream January 14, 2026
Jan 14 2026 OpenAI Partners with Cerebras to Bring High-Speed Inference to the Mainstream OpenAI and Cerebras have signe…
Cerebras BlogTutorial#inference#training
151d
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Import AI 439: AI kernels; decentralized training; and universal representations
Import AI 439: AI kernels; decentralized training; and universal representations How might a hypothetical superintellige…
Import AI (Jack Clark)Research#llama#claude#inference
161d