Amazon launches Alexa for Shopping as Rufus moves behind the scenes
Amazon has introduced Alexa for Shopping, combining its Rufus shopping chatbot with Alexa+ across its app, website, and Echo Show devices. The assistant can answer product questions, compare items, track prices, and support shopping reminders. It can also handle scheduled shopping actions and eligible automated purchases. The company said Alexa for Shopping combines Rufus’ product […]
NVIDIA Introduces a 4-Bit Pretraining Methodology Using NVFP4, Validated on a 12B Hybrid Mamba-Transformer at 10T Token Horizon
Pretraining frontier-scale LLMs in FP8 is now standard practice, but moving to 4-bit floating point has remained an open research problem because narrower formats compress dynamic range and amplify quantization error at long token horizons. A new research from NVIDIA describes a pretraining methodology built around NVFP4, a 4-bit microscaling format supported natively by Blackwell […]
A Coding Implementation to Compress and Benchmark Instruction-Tuned LLMs with FP8, GPTQ, and SmoothQuant Quantization using llmcompressor
import subprocess, sys def pip(*pkgs): subprocess.check_call([sys.executable, “-m”, “pip”, “install”, “-q”, *pkgs]) pip(“llmcompressor”, “compressed-tensors”, “transformers>=4.45”, “accelerate”, “datasets”) import os, gc, time, json, math from pathlib import Path import torch from transformers import AutoModelForCausalLM, AutoTokenizer from datasets import load_dataset assert torch.cuda.is_available(), \ “Enable a GPU: Runtime > Change runtime type > T4 GPU” print(“GPU:”, torch.cuda.get_device_name(0), “| CUDA:”, […]
Pandas Isn’t Going Anywhere: Why It’s Still My Go-To for Data Wrangling
learning data science in 2020, Pandas was one of the most popular tools. Although new tools focus on improving Pandas’ weaknesses in handling very large datasets, I still use Pandas for many data cleaning, processing, and analysis tasks. Yes, Pandas gives me a hard time when working with billions of rows, but it is definitely […]
LLM Evals Are Based on Vibes — I Built the Missing Layer That Decides What Ships
TL;DR a full working implementation in pure Python, with real benchmark numbers. Most teams evaluate LLM responses by reading them and guessing. That breaks the moment you scale. The real problem is not that models hallucinate. It is that nothing catches the confident ones, the responses that score 0.525, pass your threshold, and are quietly […]
Vercel Labs Introduces Zero, a Systems Programming Language Designed So AI Agents Can Read, Repair, and Ship Native Programs
Vercel Labs 01 / 09 · Overview ZeroThe Programming Languagefor Agents An experimental systems language that gives AI agents structured diagnostics,typed repair metadata, and machine-readable docs — alongside sub-10 KiB native binaries. Systems Language Agent-Native v0.1.1 Apache-2.0 Experimental Context 02 / 09 · Why Zero Exists The Agent Repair Loop Problem Most programming languages produce […]
A Coding Guide Implementing SHAP Explainability Workflows with Explainer Comparisons, Maskers, Interactions, Drift, and Black-Box Models
print(“\n” + “=”*72) print(“PART 3: Interaction decomposition”) print(“=”*72) inter = tree_expl.shap_interaction_values(X_te.iloc[:500]) inter_abs = np.abs(inter).mean(0) diag = np.diagonal(inter_abs).copy() off = inter_abs.copy(); np.fill_diagonal(off, 0) main_share = diag.sum() / (diag.sum() + off.sum()) print(f”Total attribution mass: {main_share*100:.1f}% main effects, ” f”{(1-main_share)*100:.1f}% interactions”) pairs = [(X.columns[i], X.columns[j], off[i, j]) for i in range(X.shape[1]) for j in range(i+1, X.shape[1])] pairs.sort(key=lambda t: […]
Nous Research Proposes Lighthouse Attention: A Training-Only Selection-Based Hierarchical Attention That Delivers 1.4–1.7× Pretraining Speedup at Long Context
Training large language models on long sequences has a well-known problem: attention is expensive. The scaled dot-product attention (SDPA) at the core of every transformer scales quadratically Θ(N²) in both compute and memory with sequence length N. FlashAttention addressed this through IO-aware tiling that avoids materializing the full N×N attention matrix in high-bandwidth memory, reducing […]
Meet LiteLLM Agent Platform: A Kubernetes-Based, Self-Hosted Infrastructure Layer for Isolated Agent Sandboxes and Persistent Session Management in Production
Running AI agents in a local script is straightforward. Running them reliably in production across teams, across restarts, with isolated environments per context is a different problem entirely. BerriAI, the company behind the LiteLLM AI Gateway, is now open-sourcing a purpose-built answer to that problem: the LiteLLM Agent Platform. The platform is described as a […]
From Data Analyst to Data Engineer: My 12-Month Self-Study Roadmap
. A part of me started this journey because data engineering is one of the hottest and highest-paying careers right now. I’m not going to pretend that wasn’t a factor. But there’s more to it than that. I’ve been learning data analytics for a while now. SQL, Power BI, Python (Pandas, NumPy, a little Polars), […]