Blog
AI engineering insights, practical advice, and things I'm learning.
AI Engineering
gr.Workflow Turns AI Pipelines Into Deployable APIs
Learn how to model, debug, expose, and deploy multi-step AI pipelines with Gradio Workflow and daggr.
Gradio · Ai Pipelines · Workflow Automation · Api Deployment
AI Engineering
How to Run Late Interaction Models in Sentence Transformers 6.0
Learn how to load ColBERT and ColPali multi-vector models using the new MultiVectorEncoder in Sentence Transformers v6.0 for fine-grained document retrieval.
Sentence Transformers · Vector Search · Late Interaction
AI Engineering
How to Export Custom Geospatial Embeddings via OlmoEarth Studio
Learn how to extract custom Earth observation embedding vectors as Cloud-Optimized GeoTIFFs using the new export workflow in OlmoEarth Studio.
Geospatial Ai · Embedding Extraction · Earth Observation
AI Engineering
How to Run Gemma 4 E2B on Raspberry Pi 5 with LiteRT
Deploy the Gemma 4 E2B model locally on a Raspberry Pi 5 using the LiteRT-LM runtime for real-time edge workflows and robotics.
Edge Ai · Raspberry Pi · Litert
AI Engineering
How to Distill Large Models With CompactifAI Top-K Logits
Learn how to use Multiverse Computing's CompactifAI to distill large language models locally using offline Top-K logits and Fused Chunked KL loss.
Knowledge Distillation · Large Language Models · Model Compression
AI Engineering
Why Local AI Belongs in Your Personal Tech Stack
Cloud AI access is conditional. A local model gives you a private, offline capability that remains available when networks and providers fail.
Local Ai · On Device Ai · Offline Ai
AI Engineering
How to Audit a Local AI App's Privacy
A practical audit for local AI inference, storage, network requests, optional tools, encryption, deletion, and offline behavior.
Local Ai · Privacy · On Device Ai
AI Engineering
How to Profile Cloud TPUs With Google's Microbenchmark Suite
Learn how to measure interconnect latency, compute throughput, and memory bandwidth on Cloud TPUs to establish a Roofline model for your workloads.
Cloud Tpu · Performance Profiling · Benchmarking
AI Engineering
How to Run TPU Workloads on Google Cloud with Ray 2.55
Learn how to provision Google Cloud TPUs, handle slice topologies, and deploy machine learning models using Ray 2.55 and the KubeRay Operator.
Google Cloud Tpu · Ray Framework · Machine Learning Infrastructure
AI Engineering
How to Scale Diffusers Training With NeMo Automodel
Learn how to fine-tune large diffusion models like FLUX.1-dev and Wan 2.1 across multiple GPUs using the NVIDIA NeMo Automodel library.
Diffusion Models · Gpu Acceleration · Model Fine Tuning
AI Engineering
How to Profile PyTorch Attention Kernels on A100 GPUs
Learn how to use the PyTorch profiler to identify memory and compute bottlenecks in attention mechanisms using Hugging Face's tracing methodology.
Pytorch Profiler · Attention Mechanism · Gpu Optimization
AI Engineering
How to Cut CPU Costs with Cloudflare Workers Cache
You will learn how to configure Cloudflare Workers Cache to serve responses directly from entrypoints, handle invalidations, and partition cache keys.
Cloudflare Workers · Edge Computing · Serverless Optimization
AI Engineering
How to launch Hugging Face models in SageMaker Studio
You will learn how to use the new Hugging Face integration to automatically provision and deploy open-source models directly into Amazon SageMaker Studio.
Hugging Face · Amazon Sagemaker · Model Deployment
AI Engineering
SkyPilot Drops Cross-Cloud Egress Fees With Hugging Face Storage
Configure SkyPilot to mount Hugging Face Storage natively and eliminate cross-cloud egress fees for multi-cloud AI workloads.
Multi Cloud · Skypilot · Hugging Face
AI Engineering
How to Configure Elastic Training in MaxText on TPUs
Learn how to enable elastic training in MaxText to survive hardware failures and resume distributed AI workloads in seconds.
Tpu Acceleration · Distributed Training · Fault Tolerance
AI Engineering
How to Expose Ephemeral vLLM Endpoints on Hugging Face Jobs
Learn how to spin up temporary, OpenAI-compatible vLLM inference endpoints on Hugging Face serverless infrastructure using a single CLI command.
Vllm · Hugging Face · Serverless Inference
AI Engineering
How to Implement Saga Rollbacks in Cloudflare Workflows
Learn how to manage distributed transactions and write compensating actions using the saga rollback feature in Cloudflare Workflows.
Distributed Transactions · Cloudflare Workflows · State Management
AI Engineering
How to Speed Up MoE Fine-Tuning With NeMo AutoModel
Learn how to configure NVIDIA NeMo AutoModel in Transformers v5 to increase MoE training throughput and reduce GPU memory usage.
Mixture Of Experts · Nvidia Nemo · Model Fine Tuning
AI Engineering
How to Secure Claude API Workloads With Identity Federation
You will learn how to configure Workload Identity Federation to authenticate non-human Claude API requests and eliminate static access keys.
Claude Api · Workload Identity Federation · Cloud Security
AI Engineering
How to Configure Sparse-LoRA and DoRA With Hugging Face PEFT
Learn how to use PEFT 0.18.0 to configure Sparse-LoRA, DoRA, LoRA-XS, and rsLoRA for more efficient fine-tuning on single-GPU hardware.
Parameter Efficient Fine Tuning · Hugging Face Peft · Large Language Models