Nov 20, 2019
Why AI Projects Fail, Part 5: Change Management
My last two letters explored robustness and small data as common reasons why AI projects fail. In the final letter of this three-part series, I’d like to discuss change management.
Nov 20, 2019
14 Posts
Nov 20, 2019
The Batch: Artificial Noses, Surveillance on Wheels, Unwelcome Researchers, Privacy Problems, Beyond Bounding Boxes
My last two letters explored robustness and small data as common reasons why AI projects fail. In the final letter of this three-part series, I’d like to discuss change management. Change management isn’t an issue specific to AI, but given the technology’s disruptive nature...
Nov 20, 2019
Researchers Blocked at the Border: Some African AI researchers blocked from attending NeurIPS
Foreign researchers hoping to attend one of AI’s largest conferences were denied entry into Canada, where the event will be held. Most of those blocked were from developing nations.
Nov 20, 2019
What the Watchbot Sees: How Knightscope security robots use AI for surveillance
Knightscope’s security robots look cute. But these cone-headed automatons, which serve U.S. police departments and businesses, are serious surveillance machines.
Nov 20, 2019
When Private Data is Not Private: Google trained Project Nightingale on private patient data.
Google spent the past year training an AI-powered health care program using personal information from one of the largest hospital systems in the U.S. Patients had no idea — until last week.
Nov 20, 2019
Nose Job: AI predicts smell by analyzing a molecule's structure.
Predicting a molecule’s aroma is hard because slight changes in structure lead to huge shifts in perception. Good thing deep learning is developing a sense of smell.
Nov 20, 2019
Beyond the Bounding Box: RPDet and RepPoints for object detection, explained
Computer vision models typically draw bounding boxes around objects they spot, but those rectangles are a crude approximation of an object’s outline. A new method finds keypoints on an object’s perimeter to produce state-of-the-art object classification.
Nov 20, 2019
When Private Data is Not Private: Google trained Project Nightingale on private patient data.
Google spent the past year training an AI-powered health care program using personal information from one of the largest hospital systems in the U.S. Patients had no idea — until last week.
Nov 20, 2019
Why AI Projects Fail, Part 5: Change Management
My last two letters explored robustness and small data as common reasons why AI projects fail. In the final letter of this three-part series, I’d like to discuss change management.
Nov 20, 2019
What the Watchbot Sees: How Knightscope security robots use AI for surveillance
Knightscope’s security robots look cute. But these cone-headed automatons, which serve U.S. police departments and businesses, are serious surveillance machines.
Nov 20, 2019
Beyond the Bounding Box: RPDet and RepPoints for object detection, explained
Computer vision models typically draw bounding boxes around objects they spot, but those rectangles are a crude approximation of an object’s outline. A new method finds keypoints on an object’s perimeter to produce state-of-the-art object classification.
Nov 20, 2019
Researchers Blocked at the Border: Some African AI researchers blocked from attending NeurIPS
Foreign researchers hoping to attend one of AI’s largest conferences were denied entry into Canada, where the event will be held. Most of those blocked were from developing nations.
Nov 20, 2019
Nose Job: AI predicts smell by analyzing a molecule's structure.
Predicting a molecule’s aroma is hard because slight changes in structure lead to huge shifts in perception. Good thing deep learning is developing a sense of smell.
Nov 20, 2019
The Batch: Artificial Noses, Surveillance on Wheels, Unwelcome Researchers, Privacy Problems, Beyond Bounding Boxes
My last two letters explored robustness and small data as common reasons why AI projects fail. In the final letter of this three-part series, I’d like to discuss change management. Change management isn’t an issue specific to AI, but given the technology’s disruptive nature...
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