2025-11-09
Companies hate to admit it, but the road to production-level AI deployment is littered with proof of concepts (PoCs) that go nowhere, or failed projects that never deliver on their goals. In certain domains, there’s little tolerance for iteration, especially in something like life sciences, when the AI application is facilitating new treatments to markets or diagnosing diseases. Even slightly inaccurate analyses and assumptions early on can create sizable downstream drift in ways that can be concerning.
In analyzing dozens of AI PoCs that sailed on through to full production use — or didn’t — six common pitfalls emerge. Interestingly, it’s not usually the qua [...]
2025-02-28
The keyword for the iPhone 16e seems to be "compromise." In this episode, Devindra chats with Cherlynn about her iPhone 16e review and try to figure out who this phone is actually for. Also, [...]
2025-11-13
Artificial intelligence agents powered by the world's most advanced language models routinely fail to complete even straightforward professional tasks on their own, according to groundbreaking re [...]
2025-11-13
Alembic Technologies has raised $145 million in Series B and growth funding at a valuation 13 times higher than its previous round, betting that the next competitive advantage in artificial intelligen [...]
2025-10-12
Imagine you do two things on a Monday morning.First, you ask a chatbot to summarize your new emails. Next, you ask an AI tool to figure out why your top competitor grew so fast last quarter. The AI si [...]
2025-11-13
LinkedIn is launching its new AI-powered people search this week, after what seems like a very long wait for what should have been a natural offering for generative AI.It comes a full three years afte [...]
2025-10-21
Presented by Apptio, an IBM companyWhen a technology with revolutionary potential comes on the scene, it’s easy for companies to let enthusiasm outpace fiscal discipline. Bean counting can seem shor [...]