Science & Research

Exploring how AI practitioners can lower memory expenses through building, renting, or quantizing models, with a focus on recent advancements and practical strategies.

• My Intuition Team
• July 7, 2026

Apple Silicon chips offer a unique, cost-effective way to run large AI models locally by sharing memory between CPU and GPU, bypassing traditional VRAM limits.

• My Intuition Team
• July 7, 2026

Anthropic’s Claude now autonomously creates and orchestrates its own team of sub-agents for complex tasks, enhancing performance in high-value workflows.

• My Intuition Team
• July 7, 2026

Anthropic reveals that Skills are folders containing instructions, scripts, and assets, transforming ad-hoc prompts into durable organizational assets for AI teams.

• My Intuition Team
• July 6, 2026

Memory prices are expected to remain high through 2028 or beyond, with relief delayed until at least 2028–2029 due to industry capacity limits and demand trends.

• My Intuition Team
• July 6, 2026

Exploring how building, renting, and quantizing AI models can lower memory expenses without sacrificing capability amid the 2026 memory crunch.

• My Intuition Team
• July 6, 2026

Analyzing the hardware costs and limitations of running large language models locally in 2026, including VRAM constraints and value strategies.

• My Intuition Team
• July 6, 2026

Apple Silicon’s unified memory architecture offers a significant advantage for large AI models, enabling capacity surpassing discrete GPUs at lower cost and power.

• My Intuition Team
• July 6, 2026

Cloud providers face a memory shortage driving up costs, with AWS raising prices for the first time in 20 years. Many firms consider on-premises or hybrid solutions.

• My Intuition Team
• July 6, 2026

A detailed analysis of the four agentic loops in AI design, explaining what each allows you to stop doing and its significance for AI workflows.

• My Intuition Team
• July 6, 2026