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Posts published in “Technology”

Counterpoint: The Inevitable Bursting of the FDE Bubble

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Counterpoint: The Inevitable Bursting of the FDE Bubble

By Shay Levi on February 24, 2026

An opinion piece by the CEO and co-founder of Unframe

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CES 2026: Lenovo Rollable PCs, Uber Robotaxi – and a Sony Car

Lenovo laptop

CES 2026: Lenovo Rollable PCs, Uber Robotaxi – and a Sony Car

By Deborah Yao on January 7, 2026

The latest gadgets and innovations announced at CES 2026 in Las Vegas

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Cursor’s Snafu and the AI Pricing Trap: Why Usage Does Not Equal Value

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Cursor’s Snafu and the AI Pricing Trap: Why Usage Does Not Equal Value

By Ariela Bitran on September 5, 2025

An op-ed by the monetization strategy director of Chargebee

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A Nigerian Startup Aims to Democratize Access to Legal Services

startup drawing

A Nigerian Startup Aims to Democratize Access to Legal Services

By Divine-Favour Ukoh on May 15, 2025

Agbo Obinnaya, cofounder of Case Radar AI, seeks to provide all-in-one legal services powered by AI.

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Experian EVP: Lenders See AI as Critical but Struggle to Prove ROI
Experian EVP: Lenders See AI as Critical but Struggle to Prove ROI
By Deborah Yao
Vijay Mehta says lenders are still learning how to measure success.
FICO’s CAO on Why Focused AI Beats Generic LLMs in Finance
FICO’s CAO on Why Focused AI Beats Generic LLMs in Finance
By Deborah Yao
Chief Analytics Officer Scott Zoldi said general AI models and RAG are not enough to deliver the accuracy needed in finance.
Deloitte US AI Leader: Bringing AI Closer to the Business with FDE
Deloitte US AI Leader: Bringing AI Closer to the Business with FDE
By Deborah Yao
Kavitha Prabhakar is a big believer in Forward Deployed Engineering (FDE).
AI in Team Dynamics: Who Gets Replaced and Why?
AI in Team Dynamics: Who Gets Replaced and Why?
By Xienan Cheng, Pinar Yildirim and Mustafa Dogan
A paper by researchers from Peking University, the Wharton School and the University of East Anglia (U.K.)

AI in Team Dynamics: Who Gets Replaced and Why?
By Xienan Cheng, Pinar Yildirim and Mustafa Dogan on February 18, 2026
A paper by researchers from Peking University, the Wharton School and the University of East Anglia (U.K.)
Training LLMs Not to Lie
By OpenAI researchers on January 23, 2026
Large language models might be dishonest about their covert actions. OpenAI researchers propose a self-confession approach as a solution.
DeepSeek Proposes New Method to Improve Stability in LLMs
By DeepSeek researchers on January 6, 2026
MHC lets large language models train more reliably at scale without major increases in compute cost.