In 2026, choosing the right AI comes down to matching capability profiles to specific tasks, risk levels and business outcomes, rather than chasing benchmark winners.
The explosion in data quantity has kept the marriage of computing and statistics thriving through successive hype cycles: “big data,” “data science,” and now “AI.”
Serendipity innovation is not something that can be engineered – though many organizations try.
The FDA’s approval process was designed for medical devices that stay largely the same after launch. Clinical AI does not operate this way; it is built to evolve.
With AI, the best we can do for now is to paint likely scenarios that may unfold.
Italy is modernizing its rail transportation infrastructure. Key in this strategy is a transformation of station mapping with GIS and digital twins.
Anthropic co-founder issues warning about the rapidly increasing and encroaching power of AI, and what we need to do about it.
In this week’s edition of The Prototype, we look at how a new discovery could lead to unsinkable ships, the billions invested in AI “neolabs” and more.
There is a growing gap between belief in AI’s potential and the willingness to commit capital and change how organizations actually operate. That gap will define the next two years, making this a recalibrating year for tech services and AI-led transfor…
Open source powers critical systems, yet is undervalued and exposed. The 2026 State of the Software Supply Chain report reveals why this disconnect is risky.