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News

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techstrong.ai > articles > deepseek-unveils-v4-1-flash-model-with-architectural-upgrades-price-cuts-ahead-of-shanghai-ipo

DeepSeek Unveils V4.1-Flash Model with Architectural Upgrades, Price Cuts Ahead of Shanghai IPO

3+ day, 10+ hour ago   (538+ words) DeepSeek announced on Thursday the launch of DeepSeek-V4.1-Flash, an artificial intelligence (AI) lightweight model that outperforms its own flagship on coding and software agent tasks at a fraction of the operating cost. The open-weights release comes as the lab…...

Techstrong.ai
techstrong.ai > agentic-ai-guide

Agentic AI Guide

5+ day, 2+ hour ago   (27+ words) By Shankar Krishnan | By Joab Jackson | By Tom Smith | By Mike Vizard | By Frank Vizard | By Steven Vaughan-Nichols | By Alan Shimel | By Jaime Hampton | By Jon Swartz |...

Techstrong.ai
techstrong.ai > articles > perplexity-open-sources-lily-a-metal-driven-local-runtime-for-apple-silicon

Perplexity Open-Sources Lily, a Metal-Driven Local Runtime for Apple Silicon

5+ day, 6+ hour ago   (657+ words) TL;DR — Key Takeaways AI search company Perplexity has released a runtime engine, called Lily, that allows macOS users to run foundational models against their own files and processes much more quickly–while using fewer cloud tokens and better guarding…...

Techstrong.ai
techstrong.ai > articles > pinnacle-measures-the-work-not-the-model

PINNACLE Measures the Work, Not the Model

1+ week, 5+ day ago   (971+ words) TL;DR — Key Takeaways Signal65’s PINNACLE benchmark moves the argument from abstract intelligence and token speed to a harder enterprise measure: whether the entire job came out right, how much capacity the platform sustained and what each correct result cost....

Techstrong.ai
techstrong.ai > articles > quantum-computers-may-need-ai-before-ai-needs-quantum-computers

Quantum Computers May Need AI Before AI Needs Quantum Computers

2+ week, 5+ day ago   (526+ words) TL;DR — Key Takeaways The story about artificial intelligence and quantum computing is usually told in one direction. Build a powerful enough quantum computer, give it a machine-learning problem, and the quantum machine may eventually outperform conventional AI. That possibility…...

Techstrong.ai
techstrong.ai > features > why-most-ai-agent-deployments-fail-and-what-actually-works

Why Most AI Agent Deployments Fail, and What Actually Works

2+ week, 6+ day ago   (586+ words) TL;DR — Key Takeaways Most AI agent deployments don’t fail because of the model. They fail because of everything around it: The wrong workflow chosen first, the metrics that never got defined, the governance nobody built. I’ve watched this play…...