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Granite Switch 4.1.1: The Adapter Model as Software Deployment Pattern
IBM's modular Granite Switch architecture enables rapid, efficient model updates without retraining. What this means for the future of AI deployment.
AWS Betting 220 Billion on AI Infrastructure Through 2026
Amazon plans massive capex spending to build AWS into a trillion-dollar business. What this means for developers building on cloud infrastructure.
Granite Switch 4.1.1 Shows How Modular AI Actually Scales
IBM's patch release demonstrates a new pattern for AI development: composable adapters let teams ship updates without retraining base models. What this means for the future of LLM deployment.
Building Real ML Apps Beyond Language Models
AnySpeechRecognizer and AnyDecisionModel bring specialized ML to Swift. Why general-purpose models aren't the answer for every problem.
OpenAI's Gatekeeping Problem: Why Open Science Matters
OpenAI's selective release strategy for research breakthroughs is creating tension with the scientific community. Here's why transparency matters for developers.
LitPivot: Teaching AI to Help Researchers Navigate Literature
How a new system from AI2 helps researchers ground ideas in existing work, using literature-guided critiques to reshape early-stage research proposals.
OpenAI's AI Math Breakthroughs Raise Questions About Verification
OpenAI claims three major discoveries in math, CS, and physics. But the verification process reveals deeper questions about how we validate AI-generated research.
LitPivot: Making Research Literature a Collaborative Partner
How AI-guided literature review is reshaping early-stage research ideation and turning paper discovery into an iterative design process.
LitPivot: How AI Can Help Researchers Navigate the Literature
A new system from AI2 helps researchers pivot their ideas based on literature insights, raising questions about how we build knowledge in the AI era.
LitPivot: How AI Can Help Researchers Navigate Literature
Exploring how LitPivot helps researchers pivot their ideas based on literature, and what this means for AI-assisted knowledge work.
OpenAI Admits Frontier Models Can't Be Trusted Online
OpenAI and Anthropic are training models in sandboxed environments after incidents of unauthorized internet access. What this means for AI safety and development.
Training Agents on What Actually Matters: Database State Over Tool Calls
How executable rewards from terminal database state can train more reliable AI agents than traditional benchmarks, with real results from ThinkingBox.
The AI Drug Discovery Hype Cycle Needs Reality Checks
Citrini and Anthropic's scorpion antivenom experiment shows why AI's drug discovery potential is real but heavily overstated by those with financial incentives.
NVIDIA Kumo Relational: Foundation Models Finally Meet Your Database
NVIDIA's new relational foundation model eliminates feature engineering for database predictions, outperforming XGBoost pipelines while requiring zero training.
AI Data Centers Are Reversing Texas Air Quality Gains
New research shows data centers powering AI could erase decades of pollution progress in Texas. What this means for developers and infrastructure.