FDM vs Resin for prototypes boils down to a key question—discover which method best suits your needs to achieve optimal results.
FDM vs Resin for Prototypes: The Answer Depends on One Question
The Mental Shift That Helps Teams Spot Weak Signals Early
Inevitably, adopting a mental shift toward curiosity and vigilance unlocks early detection of weak signals, helping teams stay ahead—and the key lies in understanding how to do it.
The Skills Marketplace, Six Months Later: Predicted vs Actual
An analysis of the emerging skills marketplace six months after predictions, highlighting confirmed developments, structural challenges, and future outlooks.
The 90-Day Window Closed. Nobody Sent a Notice.
After the Linux kernel patch on April 1, 2026, no security notices or disclosures were sent within the 90-day window, raising concerns about vulnerability exploitation.
732 Bytes to Root. One Hour of Scan Time.
A 732-byte Python script exploits a Linux kernel vulnerability, gaining root access in seconds after just an hour of automated scanning, collapsing security costs.
The Co-Founder’s Black Hole — A Structural Read on Jack Clark’s Automated AI R&D Essay
Anthropic co-founder Jack Clark predicts over 60% chance of fully automated AI research by 2028, raising concerns about institutional capacity and future risks.
Every Benchmark Launched 2023-2024 Has Fallen — The METR / SWE-Bench / CORE-Bench / MLE-Bench / PostTrainBench Sequence
Every major AI research benchmark launched in 2023-2024 has reached saturation or is nearing it within months, indicating rapid AI capability advancement.
Jack Clark Says It Out Loud — Reading the Co-Founder’s 60%/2028 Estimate on Automated AI R&D
Anthropic’s co-founder Jack Clark states there is a 60%+ probability that AI systems will autonomously develop their own successors by 2028, signaling a significant policy stance.
The Compute Concentration Audit: When Sovereign Wealth Funds Notice Three Companies Own the Frontier
Global regulators are investigating the dominance of AWS, Microsoft Azure, and Google Cloud in AI infrastructure, highlighting rising dependency concerns.
The Power Bottleneck: AI Data Centers and the Grid Cliff Approaching 2027-2028
AI data centers face a power bottleneck as grid expansion delays threaten to limit hyperscaler growth by 2027-2028, impacting AI deployment and costs.
